Diagnostic Tests For Diabetes Mellitus

ABSTRACT

In this chapter, indications for screening for diabetes mellitus are reviewed. Criteria for diagnosis are fasting plasmaglucose ≥ 126 mg/dl (7.0 mmol/l) or random glucose ≥200 mg/dl (11.1 mmol/l) with hyperglycemic symptoms, hemoglobin A1c (HbA1c) ≥6.5%, and oral glucose tolerance testing (OGTT) 2-h glucose ≥200 mg/dl (11.1 mmol/l) after 75 g of glucose. One-step and two-step strategies for diagnosing gestational diabetes using pregnancy-specific criteria as well as use of the 2-h 75-g OGTT for the postpartum testing of women with gestational diabetes (4-12 weeks after delivery) are described. Testing for other forms of diabetes with unique features are reviewed, including the recommendation to use the 2-h 75 g OGTT to screen for cystic fibrosis-related diabetes and post-transplantationdiabetes, fasting glucose test for HIV positive individuals, and genetic testing for monogenic diabetes syndromes including neonatal diabetes and maturity-onset diabetes of the young (MODY). Elevated measurements of pancreatic islet autoantibodies (e.g., to the 65-KDa isoform of glutamic acid decarboxylase (GAD65), tyrosine phosphatase related islet antigen 2 (IA-2), insulin (IAA), and zinc transporter (ZnT8)) suggest autoimmune type 1 diabetes (vs type 2 diabetes). IAA is primarily measured in youth. The use of autoantibody testing in diabetes screening programs is recommended in first degree relatives of an individual with type 1 diabetes or in research protocols. C-peptidemeasurements can be helpful in identifying those who have type 1 diabetes (low or undetectable c-peptide) from those who may have type 2 or monogenic diabetes.

SCREENING FOR DIABETES MELLITUS AND PREDIABETES

Early detection and treatment of diabetes mellitus is important in preventing acute and chronic complications of this disease. Individuals with symptoms suggestive of hyperglycemia, such as polyuria, polyphagia, polydipsia, unexplainedweight loss, blurred vision, excessive fatigue, or infections or wounds that heal poorly should be promptly tested. The American Diabetes Association (ADA) recommends routinely screening for type 2 diabetes in adults every three years beginning at age 45. In asymptomatic people, testing for type 2 diabetes should be considered in adults of any age if they are overweight or obese (BMI ≥ 25 kg/m², or ≥ 23 kg/m² if Asian background), planning pregnancy, and/or if theyhave additional risk factors as listed below in Table 1. Repeat screening should be performed at least every three years. Patients with prediabetes should be screened yearly (1). The US Preventive Services Task Force recommends glucose screening for all asymptomatic overweight or obese adults ages 40-70 (2); the American Association of Clinical Endocrinologists recommends screening at risk individuals at any age (3).

Table 1. Risk Factors for the Development of Type 2 Diabetes
Physical inactivity
First-degree relative with diabetes
High-risk race/ethnicity (e.g., African American, Latino, Native American, Asian American, PacificIslander)
Women who delivered a baby weighing >9 lb. or were diagnosed with Gestational Diabetes
Hypertension (≥130/80 mm Hg or on therapy for hypertension)
HDL cholesterol level <35 mg/dL (0.90 mmol/L) and/or a triglyceride level >250 mg/dL (2.8 mmol/L)
Individuals with polycystic ovary syndrome
People with prediabetes (HbA1C ≥5.7%, Impaired Glucose Tolerance (IGT), or Impaired FastingGlucose (IFG))
Other clinical conditions associated with insulin resistance (e.g., severe obesity, acanthosis nigricans. Metabolic dysfunction-associated steatotic liver disease)
History of cardiovascular disease
Individuals in other high-risk groups (HIV, exposure to high-risk medicines, evidence of periodontal disease, history of pancreatitis

Type 2 diabetes is becoming a growing problem in children and adolescents in high-risk populations. To address this issue, the ADA recommends screening overweight [body mass index (BMI) ≥85th percentile] or obese (BMI ≥95^thpercentile) youth at least every 3 years, beginning at age 10 or at the onset of puberty, if they have 1 or more additional risk factors listed below in Table 2. Repeat testing should be done more frequently if BMI increases (1).

Table 2. Risk Factors for Type 2 Diabetes in Children and Adolescents
Family history of type 2 diabetes in first and second-degree relatives
Race and ethnicity (Native American, African American, Latino, Asian American, Pacific Islander)
Signs of insulin resistance or conditions associated with insulin resistance (acanthosis nigricans,hypertension, dyslipidemia, small-for- gestational-age birth weight, or polycystic ovary syndrome)
Maternal history of diabetes or gestational diabetes during child's gestation

DIAGNOSING DIABETES AND PREDIABETES

The diagnosis of diabetes can be made using the fasting plasma glucose, random plasma glucose, oral glucose tolerance test, or hemoglobin A1c (HbA1c) (1). Testing should be performed on 2 separate days using one or more ofthe above tests, unless unequivocal hyperglycemia is present. Alternatively, in the absence of symptoms of hyperglycemia, diabetes can be diagnosed if there are two different abnormal test results from the same sample (1). An overview of the ADA criteria is shown in Table 3.

Table 3. ADA Criteria for the Diagnosis of Diabetes
HbA1C ≥6.5%. The test should be performed in a laboratory using a method that is NationalGlycohemoglobin Standardization Program certified and standardized to the Diabetes Control and Complications Trial (DCCT) assay.
FPG ≥126 mg/dL (7.0 mmol/L). Fasting is defined as no caloric intake for at least 8 h.
2-h plasma glucose ≥200 mg/dL (11.1 mmol/L) during an Oral Glucose Tolerance Test (OGTT). The test should be performed as described by the WHO, using a glucose load containing the equivalent of 75 g anhydrous glucose dissolved in water.
In an individual with classic symptoms of hyperglycemia or hyperglycemic crisis, a random plasma glucose ≥200 mg/dL (11.1 mmol/L). Random is any time of day without regard to time since previous meal.

HbA1c

The use of the HbA1c assay was recommended for the diagnosis of diabetes in 2009 by an International Expert Committee (4). HbA1c levels reflect overall glycemic control and correlate with the development of microvascular complications. An HbA1c ≥ 6.5% on two separate occasions can be used to diagnose diabetes. An HbA1c level of 6.0%to ≤ 6.5% identifies high risk of developing diabetes. The ADA considers individuals with a HbA1c of 5.7% to 6.4% at increased risk for developing diabetes (1). HbA1c should not be used to diagnose gestational diabetes, diabetes in HIV positive individuals, post-organ transplantation, or in people with cystic fibrosis.

Fasting and Random Plasma Glucose

Fasting plasma glucose is one method recommended by the ADA for the diagnosis of diabetes in children and non-pregnant adults (1). The interpretation of fasting glucose measures is shown in Table 4. The test should be performedafter an 8 hour fast. For routine clinical practice, fasting plasma glucose may be preferred over the oral glucosetolerance test because it is rapid, easier to administer, is more convenient for patients and providers, and has a lowercost (1). A random plasma glucose level, which is obtained at any time of the day regardless of the time of the last meal, can also be used in the diagnosis of diabetes in a patient with classic symptoms of hyperglycemia or hyperglycemic crisis.

Table 4. Fasting Plasma Glucose Criteria
	Fasting Plasma Glucose
Normal glucose tolerance	<100 mg/dl (5.6 mmol/l)
Impaired fasting glucose (pre-diabetes)	100-125 mg/dl (5.6-6.9mmol/l)
Diabetes mellitus	≥126 mg/dl (7.0 mmol/l)

For the diagnosis of diabetes, standard venous plasma glucose specimens should be obtained. Specimens should be processed promptly, since glucose is metabolized at room temperature. This process is influenced by storage temperature, storage time as well as other factors, and is accelerated in the presence of bacteria or leukocytosis.

Whole blood glucose specimens obtained with point-of- care devices should not be used for the diagnosis of diabetes because of the inaccuracies associated with these methods. Capillary and venous whole blood glucose concentrations are approximately 15% lower than plasma glucose levels in fasting specimens. However, most devices account for this difference in their calibration.

Oral Glucose Tolerance Test (OGTT)

OGTTS FOR THE DIAGNOSIS OF DIABETES AND IMPAIRED GLUCOSE TOLERANCE IN NON-PREGNANT INDIVIDUALS

A formal OGTT can be used to establish the diagnosis of diabetes mellitus (Table 5). OGTT is more cumbersome and costlier than the fasting plasma glucose test; however, the use of only the fasting plasma glucose may not identify a proportion of individuals with impaired glucose tolerance or diabetes (5). A plasma glucose level 2-hours after a glucose challenge may identify additional individuals with abnormal glucose tolerance who are at risk for microvascular and macrovascular complications, particularly in high-risk populations in which postprandial (versus fasting) hyperglycemia is evident early in the disease (6,7).

When using an OGTT, the criteria for the diagnosis of diabetes is a 2 h glucose >200 mg/dl (11.1 mmol/l) after a 75-gramoral glucose load (ADA and WHO criteria). The 75-gram glucose load should be administered when the patient has ingested at least 150 grams of carbohydrate for the 3 days preceding the test and after an overnight fast. Dilution of the75-gram oral glucose load (300-900 ml) may improve acceptability and palatability without compromising reproducibility(8). The patient should not be acutely ill or be taking drugs that affect glucose tolerance at the time of testing, and should abstain from tobacco, coffee, tea, food, alcohol and vigorous exercise during the test.

Table 5. Oral Glucose Tolerance Test Glucose Criteria
	2-h Plasma Glucose (after 75-gram Glucose Load)
Normal glucose tolerance	<140 mg/dl (7.8 mmol/l)
Impaired glucose tolerance(pre-diabetes)	140-199 mg/dl (7.8-11.1 mmol/l)
Diabetes mellitus	≥200 mg/dl (11.1 mmol/l)

OGTTS FOR THE DIAGNOSIS OF GESTATIONAL DIABETES

Please see the Endotext Chapter on Gestational Diabetes for additional details on the diagnosis of gestational diabetes. The prevalence of gestational diabetes (GDM) varies among racial and ethnic groups and between screening practices, testing methods, and diagnostic criteria. The overall frequency of GDM in the 15 centers participating in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study was 17.8% (9), and regional estimates may vary from 10% to 25 % depending on the population studied (10). The prevalence increases with increased number of risk factors (Tables 6 and 7), such that 33% of women with 4 or more risk factors have gestational diabetes (11). This condition is important to diagnose early because of the increased perinatal morbidity associated with poor glycemic control.

The US Preventive Task Force recommends screening for gestational diabetes in asymptomatic women after 24 weeks of gestation (12); the ADA recommends screening all pregnant women routinely between 24- and 28-weeks’ gestation (Table 8). If the woman has risk factors, however, screening should be performed at the initial prenatal visit using standard criteria (1).

Table 6. Risk Factors for the Development of Gestational Diabetes
Overweight or obese
Previous history of impaired glucose tolerance, gestational diabetes, or delivery of a babyweighing >9 lb.
Glycosuria or history of abnormal glucose tolerance
Family history of diabetes (especially first degree relative)
Polycystic ovarian syndrome, hypertension, glucocorticoid use
History of poor obstetric outcome
Age (>25 years)
High risk ethnicity
Multiple gestation

Table 7. Low Risk for the Development of Gestational Diabetes
Age (< 25 years)
Normal weight pre-pregnancy
Low risk ethnicity
No first-degree relatives with diabetes
No history of abnormal glucose tolerance
No history of poor obstetric outcome

Table 8. Time of Initial Testing for Gestational Diabetes
Risk of Development of Gestational Diabetes	Time of Initial Testing for Gestational Diabetes
Low risk	24-28 weeks gestation
Average risk	24-28 weeks gestation
High risk	As soon as feasible; repeat at 24-28 weeks if earliertesting normal

More than one method has been recommended for the screening and diagnosis of gestational diabetes. The criteria for the diagnosis of this condition remain controversial because the glucose thresholds for the development of complicationsin pregnancies with diabetes remain poorly defined. Currently, the ADA suggests screening for GDM with either the “one-step” or “two-step” approach (1). Long term outcome studies evaluating pregnancies complicated by GDM are currently underway and hopefully a uniform approach will be adopted.

One-Step Strategy

The International Association of Diabetes and Pregnancy Study Group (IADPSG), an international consensus group with representatives from multiple obstetrical and diabetes organizations including the ADA recommend that all women not previously known to have diabetes undergo a 75-gram 2-hour OGTT at 24-28 weeks of gestation (Table 9). This approach, which has been adopted internationally, is expected to increase the prevalence of GDM as only one abnormal value is sufficient to make the diagnosis (1,13). In 2017, the American College of Obstetricians and Gynecologists(ACOG) stated that clinicians may make the diagnosis of gestational diabetes based on only one elevated blood glucose value if warranted, based on their population, although this organization still supports the “two step” approach for diagnosis of GDM (14). These glucose thresholds were based on outcome data of the HAPO study that conveyed an odds ratio for adverse maternal, fetal, and neonatal outcomes of at least 1.75 based on fully adjusted logistic regression models (15).

Table 9. Oral Glucose Tolerance Test Glucose Criteria for the Diagnosis of GDM
75-gram 2- hour OGTT: Performed at 24-28 weeks gestation in the morning after an overnight fast of atleast 8 hours. GDM is diagnosed when any of the following values are exceeded:
Fasting	≥ 92 mg/dL (5.1 mmol/L)
One Hour	≥ 180 mg/dL (10.0 mmol/L)
Two Hour	≥ 153 mg/dL (8.5 mmol/L)

Two-Step Strategy

The American College of Obstetricians and Gynecologists (ACOG) as well as the National Institutes of Health (NIH) have been in support of the "two step" approach which consists of universal screening of all pregnant women at 24-28 weeks gestation with a 50-gram glucose challenge regardless of timing of previous meals (Table 10), followed by a 100- gram three-hour OGTT in screen positive patients (14, 16).

In the two-step approach, first a 50-gram oral glucose load is administered regardless of the timing of previous meals. The following thresholds have been defined as a positive screen: ≥130 mg/dL, ≥135 mg/dL, or ≥140 mg/dL (7.2 mmol/L, 7.5 mmol/L, or 7.8 mmol/L); the lower threshold has an estimated sensitivity and specificity of 88-99% and 66-77% compared to 70-88% and 69-89% respectively for the higher cutoff values of ≥135 mg/dL or ≥140 mg/dL (1).

Table 10. Abnormal Glucose Level on Screening Test
50-gram Glucose Load
1-h Plasma Glucose	≥130 mg/dl (7.8 mmol/l)

If the screening test is abnormal, the diagnosis of gestational diabetes should be confirmed using a formal 100-gram OGTT (Table 11). This test should be performed after an overnight (8-14 h) fast. It is generally recommended that the woman ingest at least 150 grams of carbohydrate/day for the 3 days prior to testing to prevent false positive results; however, the necessity of this preparatory diet in normally nourished women has been challenged (17). The ADArecommends using the Carpenter/Coustan criteria (1). At least 2 of the following 4 venous plasma glucose levels mustbe attained or exceeded to make the diagnosis of GDM (1).

Table 11. Oral Glucose Tolerance Test Glucose Criteria for the Diagnosis of GDM
	Carpenter/Coustan	National Diabetes Data Group
Fasting	≥95 mg/dl (5.3 mmol/l)	≥105 mg/dl (5.8 mmol/l)
One Hour	≥180 mg/dl (10.0 mmol/l)	≥190 mg/dl (10.6 mmol/l)
Two Hours	≥155 mg/dl (8.6 mmol/l)	≥165 mg/dl (9.2 mmol/l)
Three Hours	≥140 mg/dl (7.8 mmol/l)	≥145 mg/dl (8.1 mmol/l)

OGTTS FOR POSTPARTUM TESTING OF WOMEN WITH GESTATIONAL DIABETES

Women with a history of GDM are at a higher risk of developing type 2 diabetes than women without GDM (18,19). Women at the highest risk are those with multiple risk factors, those who had more severe gestational diabetes, andthose with poorer beta cell function (11). The ADA recommends testing women 4-12 weeks after delivery using a two-hour 75-gram OGTT. Women with normal results should be retested at least every 3 years. It is recommended thatwomen with impaired fasting glucose or impaired glucose tolerance be retested on a yearly basis (1).

Special Populations

Diabetes is common in patients with cystic fibrosis and is associated with adverse effects on nutritional status as well aspulmonary function. Annual screening for diabetes is recommended for individuals over age 10 with cystic fibrosis (1). HbA1c and fructosamine can be inaccurate in this population. In a retrospective analysis of the Toronto cystic fibrosis database, screening for diabetes using a HbA1c cutoff of 5.5% had a sensitivity of 91.8% and specificity of only 34.1% (20) but more studies need to be performed before the use of HbA1c is generally recommended for the diagnosis of diabetes in these individuals.

The use of the 2-hour 75 gm OGTT is recommended for the screening of healthy outpatients with cystic fibrosis. For patients receiving continuous drip feedings, laboratory glucose levels at the midpoint or immediately after feedings should be obtained. The diagnosis of diabetes is based on glucose levels ≥200 mg/dL on 2 separate occasions. If the patient is acutely ill or ingesting glucocorticoids, a FPG ≥126 mg/dL or 2-hour postprandial glucose ≥200 mg/dL thatpersists for >48 hours is sufficient to diagnose diabetes (21, 22).

FASTING GLUCOSE FOR DIAGNOSIS OF PREDIABETES AND DIABETES IN PEOPLE LIVING WITH HIV

Screening for prediabetes and diabetes by measuring fasting glucose before and 3-6 months after starting or changing antiretroviral therapy is recommended for everyone living with HIV (1). If normal, a fasting glucose test should be performed yearly. Screening using a HbA1c test is not recommended for diagnosis due to risk of inaccuracies (1, 23).

OGTTS FOR DIAGNOSIS OF POST- TRANSPLANTATION DIABETES

After an individual has had an organ transplant and is on stable immunosuppressive therapy, routine screening for diabetes is recommended. The recommended screening test is an OGTT post- transplantation (1).

TESTS USED FOR CLASSIFICATION OF DIABETES

General Approach

Other tests are used for the purpose of classifying diabetes. For details see individual chapters in Endotext:

· Diagnosis and Clinical Management of Monogenic Diabetes

· Atypical Forms of Diabetes

· Lipodystrophy Syndromes: Presentation and Treatment

· Fibrocalculous Pancreatic Diabetes

· Diabetes Mellitus After Solid Organ Transplantation

· Diabetes in People Living with HIV

· Autoimmune Polyglandular Syndromes

· Etiology and Pathogenesis of Diabetes Mellitus in Children and Adolescents

In brief, most patients with diabetes can be classified as either type 1 or type 2 diabetes using clinical judgement and simple tests if needed. However, the pathophysiology of diabetes is complex and significant overlap can exist, potentially leading to misclassification. While youth with type 1 diabetes typically present with rapid onset symptoms, adults with type 1 diabetes may have a much slower, more indolent course. While the incidence rate of type 1 diabetes is higher in youth, over half of individuals diagnosed with type 1 diabetes are adults (24). This is why ~40% of adults with new onset type 1 diabetes are initially misclassified as having type 2 diabetes (25). Another term for slowly progressing type 1 diabetes is latent autoimmune diabetes in the adult (LADA). However, the American Diabetes Association classifies LADA as type 1 diabetes. It is important to recognize these individuals because they require insulin sooner than individuals with type 2 diabetes (26) and they have a higher long-term risk of complications (27). On the other hand, type 2 diabetes can present in some populations (particularly those with Black or Latinx background) with diabetic ketoacidosis (DKA) and this is termed ketosis prone diabetes (28). The importance of this is that about half of individuals initially presenting with DKA who have normal c-peptide and negative autoantibodies may be able to come discontinue insulin therapy (1,29).

The most discriminating features of type 1 diabetes are younger age (<35 years), lower body mass index (<25 kg/m²), unintentional weight loss, ketoacidosis, and severe hyperglycemia (>360 mg/dl) at presentation (1, 25). A helpful pneumonic is AABBCC which stands for age, autoimmunity (personal or family history of other autoimmune disorders), body habitus, background (family history of type 1 diabetes), control (glucose), and comorbidity (such as treatment with a checkpoint inhibitor for cancer). However, these features are not absolute, and the correct classification may only become apparent over time.

An overview of the classification for suspected type 1 diabetes is shown in the Figure. For anyone with possible type 1 diabetes, testing for autoantibodies such as glutamate decarboxylase isoform 65 (GAD65A), insulin, insulinoma antigen 2, and zinc transporter isoform 8 (Znt8A) should be performed. The GAD antibody is the most prevalent autoantibody, but false positives can occur and the presence of multiple positive autoantibodies, and/or higher titers increases specificity.

The c-peptide is often normal at the time of diagnosis. Among individuals who have had diabetes for many years, it is important to note that autoantibodies may become undetectable. On the other hand, while the c-peptide is often normal at the time of diagnosis, it typically declines over time (and glucose fluctuations become more difficult to manage) making the clinical diagnosis clearer. The c-peptide should be obtained from a random (nonfasting) sample and interpreted within the context of a concomitant serum glucose level (ideally >144 mg/dl) (30). If normal, it should be measured periodically where the diagnosis is unclear.

Figure. Classification of suspected type 1 diabetes (T1D). Ab=antibody, MODY=maturity onset diabetes of youth, T2D=type 2 diabetes, Rx=treatment, Dx=diagnosis.

While type 2 diabetes is considered polygenic, several forms of monogenic diabetes are well known. These are often non-syndromic and include neonatal diabetes and older onset forms that collectively were formerly known as maturity onset diabetes of youth (MODY). Monogenic diabetes is typically inherited in an autosomal dominant manner and should be suspected in individuals diagnosed as children or young adults (<25 years) with a strong family history and without other clinical features of type 1 or type 2 diabetes such as obesity or type 1 diabetes autoantibodies (1). Individuals commonly have an intact c-peptide and HbA1c <7.5% at diagnosis. When these forms are suspected, patients should be referred for genetic testing. Some mutations leading to diabetes involve multiple organ systems and can be categorized as syndromic diabetes. Syndromic features include maternally inherited deafness, renal cysts, partial lipodystrophy, or severe insulin resistance in the absence of obesity. Such individuals should also be referred for genetic testing.

A comparison of features of types of diabetes is shown in Table 12.

Table 12. Characterization of Common Types of Diabetes (1)
	T1D	“LADA”	T2D	MODY
Age	Often young	>age 25	Often adult	<age 25
Family history	Occasional	Occasional	Usually	Yes
C-peptide	Low, often undetectable	Varies	Normal or high	normal
Auto-ab	+	+	-	-
Weight	Tend to be lean	Tend to be lean	Usually overweight	Tend to be lean
Metabolic syndrome	No	Varies	Usually	No
Insulin requirement	Yes	Varies, rapid progression	Varies	Varies

C-peptide

During the processing of proinsulin to insulin in the beta cell of the pancreas, the 31 amino acid connecting peptide which connects the A and B chains, called c-peptide, is enzymatically removed and secreted into the portal vein. C-peptide circulates independently from insulin and is mainly excreted by the kidneys. Levels are elevated in renal failure. Standardization of different c-peptide assays is still suboptimal. C-peptide testing is used to examine insulin secretory reserve in people with diabetes.

At the time of type 1 diabetes diagnosis, c-peptide levels commonly overlap with those observed in type 2 diabetes and cannot reliably distinguish between these diabetes types. With longer duration, there is progressive loss of c-peptide, and although c-peptide levels in many individuals with long-standing type 1 diabetes are extremely low or undetectable, there is heterogeneity in residual beta cell function with detectable c-peptide being more common in adult-onset type 1 diabetes (33). In type 1 diabetes, detectable c-peptide is associated with better glycemic control, less hypoglycemia, and decreased microvascular disease (34-35).

Type 2 diabetes is heterogeneous, with many individuals having progressive loss of beta cell function over many years evidenced by decreasing c-peptide levels. Fasting and glucose-stimulated c-peptide levels have been used in the past to distinguish type 1 (severe insulin deficiency) from type 2 diabetes with limited success. However, targeted testing may be more discriminatory. When random c-peptide testing was performed >3 years after clinical diagnosis of type 1 diabetes,13% had a c-peptide ≥200 pmol/L, and after islet autoantibody and genetic testing, 6.8% of these were reclassified: 5.1% as having type 2 diabetes and 1.6% as having monogenic diabetes (36).

C-peptide stimulation using glucagon or a mixed meal such as Sustacal, has also been used to help differentiate between type 1 and type 2 diabetes, and to determine the need for insulin therapy in type 2 diabetes. In the glucagon stimulation test, glucose, insulin and c-peptide levels are measured 6 and 10 min after the intravenous injection of 1 mg of glucagon. Normal stimulation of c-peptide is a 150- 300% elevation over basal levels. In the mixed meal tolerance test, Sustacal (6 mg/kg up to a maximum or 360 ml) is ingested over 5 minutes, and glucose and c-peptide are measured 90 min after oral ingestion. These tests have had limited general clinical utility since they do not reliably discriminate between patients who require insulin therapy. They have been used in research studies and in the evaluation of patients after pancreatectomy and pancreatic transplantation. In the Diabetes Control and Complications Trial, a basal c- peptide value of <0.2 pmol/ml and stimulated level of <0.5 pmol/ml were used to confirm the presence of type 1 diabetes at entry (37). According to the ADA guidelines, a random c-peptide and concomitant glucose level obtained within 5 hours of eating is sufficient for classification.

Pancreatic Autoantibodies

Islet autoantibodies can be detected early in the development of type 1 diabetes and are considered markers of autoimmune beta cell destruction. They predict progressive beta cell destruction and ultimately beta cell failure. The autoantibodies for which specific immunoassays are available include the 65-KDa isoform of glutamic acid decarboxylase (GAD65), insulin autoantibodies (IAA), zinc transporter antibodies (ZnT8), islet cell antigen 512 autoantibodies (ICA512), and autoantibodies to the tyrosine phosphatase related antigens islet antigen 2 (IA-2) and IA-2b. Measurements of ICA512, which are autoantibodies to parts of the IA-2 antigen, are no longer recommended. The presence of high levels of 2 or more antibodies is strongly predictive of type 1 diabetes mellitus. These antibodies may be detected before the onset of type 1 diabetes, at the time of diagnosis, and for variable amounts of time after diagnosis. They have been used in screening for type 1 diabetes in first-degree relatives of an individual with type 1 diabetes or in research studies related to the early detection, treatment, and prevention of type 1 diabetes (www.diabetestrialnet.org). These measurements are not recommended for use in general screening programs in low-risk individuals. The American Diabetes Association recommends offering screening via autoantibodies in persons with a strong family history of type 1 diabetes or otherwise known risk (1). Additional information on screening for type 1 diabetes may be found in the Endotext Chapter “Changing the Course of Disease in Type 1 Diabetes”.

Commercially available assays for autoantibodies are often useful in distinguishing type 1 diabetes from type 2 diabetes. The absence of detection of these antibodies, however, does not exclude the diagnosis of type 1 diabetes. Since IAA can form in response to insulin therapy, detection can be the result of insulin injections or autoimmune insulin antibody formation. GAD65 antibodies are frequently observed early in the course of type 1 diabetes. They are also present in the rare neurological disorder, stiff-man syndrome, and in some patients with polyendocrine autoimmune disease.

In adults with newly diagnosed diabetes for whom type 1 diabetes is a possible diagnosis, GAD65 is commonly measured first, along with or followed by IA2 and ZnT8. IAA are more commonly detected in young children who developtype 1 diabetes.

Lynam and coworkers (38) developed a clinical multivariable model to help differentiate between type 1 and type 2 diabetes in adults ages 18-50 years. The model includes age at diagnosis, BMI, islet autoantibodies (GAD, IA-2), and atype 1 diabetes genetic risk score. The authors define type 1 diabetes by a non-fasting c-peptide <200 pmol/L andrapid insulin requirement within the first 3 years of diagnosis. The definition of type 2 diabetes was not requiring insulin treatment within the first 3 years after diagnosis or, if insulin was used, having a c-peptide measurement of >600 pmol/Lat ≥5 years post-diagnosis. Since the measures of the genetic variants in the type 1 diabetes genetic risk score are not widely available, this model is not used clinically in the United States.

Monogenic Diabetes Syndromes

Monogenic diabetes syndromes account for 1%-5% of all individuals with diabetes and have been primarily classified as neonatal diabetes or Maturity-Onset Diabetes of the Young (MODY) based on clinical characteristics. More than 50 affected genes have been described. A Diabetes Care Expert Forum was assembled in 2019 to re- consider the classification of monogenic diabetes syndromes. They recommend a classification system based upon molecular genetics, listing the affected gene, inheritance/phenotype, disease mechanism/special features, and the treatment implications (39).

The ADA recommends immediate genetic testing for all infants diagnosed with diabetes within the first 6 months of life (Table 13) (1). MODY most commonly manifests before age 25 years but can be diagnosed in older individuals. The inheritance is typically autosomal dominant. Individuals who have positive islet autoantibody test results and/or low c-peptide concentrations should not be tested for monogenic diabetes syndromes (40). A MODY risk calculator is availableat: https://www.diabetesgenes.org/exeter-diabetes-app/

Table 13. When to Consider Genetic Testing for Monogenic Diabetes Syndromes
Diabetes diagnosed younger than 6 months of age
Diabetes in children and young adults not characteristic of type 1 or type 2 (negative pancreatic auto-antibodies, non- obese, no features of metabolic syndrome) and with a strong family history (diabetes in successive generations suggesting dominant inheritance)
Fasting glucose 100-150 mg/dL, stable A1c (5.6-7.6%), especially if in a non-obese child or youngadult

ACKNOWLEDGEMENTS

The authors would like to acknowledge the authors of a previous version of this chapter entitled “Pancreatic Islet Function Tests”: Sai Katta MBBS, Marisa E Desimone MD, and Ruth S Weinstock, MD, PhD.

REFERENCES

American Diabetes Association Professional Practice Committee; 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2025. Diabetes Care1 January 2025; 48 (Supplement_1): S27–S49. https://doi.org/10.2337/dc25-S002.
Siu AL; US Preventive Services Task Force. Screening for abnormal blood glucose and type 2 diabetes mellitus: U.S. Preventive Services Task Force Recommendation Statement. Ann Intern Med. 2015;163(11):861-8.
American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for Developing a Diabetes Mellitus Comprehensive Care Plan. Endocr Pract 2015;21(Suppl.2):1-87.
The International Expert Committee. International Expert Committee Report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care 2009;32:1327-1334.
Shaw JE, Zimmet PZ, McCarty D, de Courten Type 2 diabetes worldwide according to the new classification and criteria. Diabetes Care 2000;23 (Suppl 2):B5.
The DECODE Study Group, the European Diabetes Epidemiology Group. Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria. Arch Intern Med 2001;161:397-405.
Harris TJ, Cook DG, Wicks PD, Cappuccio FP. Impact of the new American Diabetes Association and World Health Organization diagnostic criteria for diabetes on subjects from three ethnic groups living in the UK. Nutr Metab Cardiovasc Dis 2000;10:305-309.
Sievenpiper JL, Jenkins DJA, Josse RG, Vuksan V. Dilution of the 75-g oral glucose tolerance test improves overall tolerability but not reproducibility in subjects with different body compositions. Diab Res Clin Pract 2001;51:87-95.
Sacks DA, Hadden DR, Maresh M, et al. Frequency of gestational diabetes mellitus at collaborating centers based on IADPSG consensus panel-recommended criteria: the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. Diabetes Care. 2012;35:526–528.
Guariguata L, Linnenkamp U Beagley J et al. Global estimates of the prevalence of hyperglycaemia in pregnancy. Diabetes Res Clin Pract. 2014;103(2):176.
Metzger BE, Buchanan TA, Coustan DR, et al. Summary and recommendations of the Fifth International Workshop-Conference on Gestational Diabetes Mellitus. Diabetes Care 2007; 30 (Suppl 2):S251-S260.
Moyer VA; US Preventive Services Task Force. Screening for gestational diabetes mellitus; U.S Preventive Services Task Force recommendation. Ann Intern Med. 2014; 160(6):414-20.
International Association of Diabetes and Pregnancy Study Groups Consensus Panel, Metzger BE, Gabbe SG, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care 2010; 33:676.
American College of Obstetricians and Gynecologists Practice Bulletin 180:Gestational Diabetes Mellitus. Obstet Gynecol. 2017;130:e17-37.
HAPO Study Cooperative Research Group, Metzger BE, Lowe LP, et al. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 2008; 358:1991-2002.
Vandorsten JP, Dodson WC, Espeland MA et al. NIH consensus development conference: diagnosing gestational diabetes mellitus. NIH Consens State Sci Statements 2013;29:1-
Crowe SM, Mastrobattista JM, Monga M. Oral glucose tolerance test and the preparatory diet. Am J Obstet Gynecol 2000;182:1052-1054.
Bellamy L, Casas JP, Hingorani AD, Williams D. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet 2009; 373:1773.
Noctor E, Crowe C, Carmody LA et al. ATLANTIC-DIP Investigators. Abnormal glucose tolerance post-gestational diabetes mellitus as defined by the International Association of Diabetes and Pregnancy Study Groups criteria. Eur J Endocrinol 2016;175:287-97.
Gilmour JA, Sykes J, Etchells E, Tullis E. Cystic fibrosis-related diabetes screening in adults: a gap analysis and evaluation of accuracy of glycated hemoglobin levels. Can J Diabetes 2019;43:13-18.
Moran A, Brunzell C, Cohen RC, Katz M, Marshall BC, et al. Clinical care guidelines for cystic fibrosis-related diabetes. A position statement of the American Diabetes Association and a clinical practice guideline of the Cystic Fibrosis Foundation, endorsed by the Pediatric Endocrine Society. Diabetes Care 2010;33:2697-2708.
Moran A, Pillay K, Becker DJ, Acerini CL; International Society for Pediatric and Adolescent Diabetes. ISPAD Clinical Practice Consensus Guidelines 2014. Management of cystic – fibrosis related diabetes in children and adolescents. Pediatr Diabetes 2014;15(S20):65-76.
Kim PS, Woods C, Georgoff P et al. A1c underestimates glycemia in HIV infection. Diabetes Care 2009;32:1591-1593.
Leslie RD, Evans-Molina C, Freund-Brown J, Buzzetti R, Dabelea D, Gillespie KM, Goland R, Jones AG, Kacher M, Phillips LS, Rolandsson O, Wardian JL, Dunne JL. Adult-Onset Type 1 Diabetes: Current Understanding and Challenges. Diabetes Care. 2021 Nov;44(11):2449-2456. doi: 10.2337/dc21-0770.
Holt RIG, DeVries JH, Hess-Fischl A, Hirsch IB, Kirkman MS, Klupa T, Ludwig B, Nørgaard K, Pettus J, Renard E, Skyler JS, Snoek FJ, Weinstock RS, Peters AL. The Management of Type 1 Diabetes in Adults. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2021 Nov;44(11):2589-2625. doi: 10.2337/dci21-0043.
Davis TM, Wright AD, Mehta ZM, Cull CA, Stratton IM, Bottazzo GF, Bosi E, Mackay IR, Holman RR. Islet autoantibodies in clinically diagnosed type 2 diabetes: prevalence and relationship with metabolic control (UKPDS 70). Diabetologia. 2005 Apr;48(4):695-702. doi: 10.1007/s00125-005-1690-x
Maddaloni E, Coleman RL, Agbaje O, Buzzetti R, Holman RR. Time-varying risk of microvascular complications in latent autoimmune diabetes of adulthood compared with type 2 diabetes in adults: a post-hoc analysis of the UK Prospective Diabetes Study 30-year follow-up data (UKPDS 86). Lancet Diabetes Endocrinol. 2020 Mar;8(3):206-215. doi: 10.1016/S2213-8587(20)30003-6.
Redondo MJ, Balasubramanyam A. Toward an Improved Classification of Type 2 Diabetes: Lessons From Research into the Heterogeneity of a Complex Disease. J Clin Endocrinol Metab. 2021 Nov 19;106(12):e4822-e4833. doi: 10.1210/clinem/dgab545.
Maldonado M, Hampe CS, Gaur LK, D'Amico S, Iyer D, Hammerle LP, Bolgiano D, Rodriguez L, Rajan A, Lernmark A, Balasubramanyam A. Ketosis-prone diabetes: dissection of a heterogeneous syndrome using an immunogenetic and beta-cell functional classification, prospective analysis, and clinical outcomes. J Clin Endocrinol Metab. 2003 Nov;88(11):5090-8. doi: 10.1210/jc.2003-030180.
Hope SV, Knight BA, Shields BM, Hattersley AT, McDonald TJ, Jones AG. Random non-fasting C-peptide: bringing robust assessment of endogenous insulin secretion to the clinic. Diabet Med. 2016 Nov;33(11):1554-1558. doi: 10.1111/dme.13142.
Fiorentino TV, Marini MA, Succurro E, Andreozzi F, Sesti G. Relationships of surrogate indexes of insulin resistance with insulin sensitivity assessed by euglycemic hyperinsulinemic clamp and subclinical vascular damage. BMJ Open Diabetes Res Care 2019;7:e000911.
Chase HP, Cuthbertson DD, Dolan LM, Kaufman F, Krischer JP, Schatz DA, White NH, Wilson DM, Wolfsdorf J. The Diabetes Prevention Trial-Type 1 Study Group. First-phase insulin release during the intravenous glucose tolerance test as a risk factor for type 1 diabetes. J Pediatr 2001;138:2244-249.
Davis AK, DuBose SN, Haller MJ, Miller KM, DiMeglio LA, Bethin KE, Goland RS et al. Prevalence of detectable c- peptide according to age at diagnosis of type 1 .Diabetes Care 2015;38:476-481.
Rickels MR, Evans-Molina C, Bahnson HT, Ylescupidez A, Nadeau KJ, Hao W, Clements MA, Sherr JL, Pratley RE, Hannon TS, Shah VN, Miller KM, Greenbaum CJ; T1D Exchange β-Cell Function Study Group. High residual C-peptide likely contributes to glycemic control in type 1 diabetes. J Clin Invest. 2020;130(4):1850-1862.
Gubitosi-Klug RA, Braffett BH, Hitt S, Arends V, Uschner D, Jones K, Diminick L, Karger AB, Paterson AD, Roshandel D, Marcovina S, Lachin JM, Steffes M, Palmer JP; DCCT/EDIC Research Group. Residual β cell function in long- term type 1 diabetes associates with reduced incidence of hypoglycemia. J Clin Invest. 2021 Feb 1;131(3):e143011.
Foteinopoulou E, Clarke CAL, Pattenden RJ, Ritchie SA, McMurray EM, Reynolds RM et al. Impact of routine clinic measurement of serum c-peptide in people with a clinician- diagnosis of type 1 diabetes. Diabet Med 2020 Nov 1,e14449.
Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes N Engl J Med1993;329:977- 986.
Lynam A, McDonald T, Hill A et al. Development and validation of multivariable clinical diagnosis models to identify type 1 diabetes requiring rapid insulin therapy in adults aged 18-50 years. BMJ Open 2019;9:e031586.
Riddle MC, Philipson LH, Rich SS, Carlsson A, Franks PW, Greeley SAW et al. Monogenic diabetes: from genetic insights to population-based precision in care: reflections from a Diabetes Care editors’ expert forum. Diabetes Care 2020; 43:3117-3128.
Shields BM, Shepherd M, Hudson M, McDonald TJ, Colclough K, Peters J, Knight B, Hyde C, Ellard S, Pearson ER, Hattersley AT; UNITED study team. Population-Based Assessment of a Biomarker-Based Screening Pathway to Aid Diagnosis of Monogenic Diabetes in Young-Onset Patients. Diabetes Care. 2017 Aug;40(8):1017-1025.

Surgical Prevention and Treatment of Diabetes

ABSTRACT

The effective treatment of obesity is challenging. This in part reflects the complexity of the underlying disease process. However, there are a growing number of effective surgical, endoscopic, and pharmacologic treatments which are available. Although there has long been a preference on lifestyle modification such as diet and exercise, there is a relative paucity of evidence to support these interventions as effective long-term treatments for obesity, in producing sustained weight loss and resultant improvements in obesity related disease and mortality. Conversely, bariatric procedures which include sleeve gastrectomy, roux en Y gastric bypass, single anastomosis gastric bypass, biliopancreatic diversion, and several less frequently performed operations have been shown to produce substantial and durable weight loss with significant improvements in obesity related disease, quality of life, and mortality. The mechanisms by which these operations work vary depending on the procedure however they primarily act via alterations in the gut-brain axis and alterations in neurohormonal signaling. These changes produce sustained changes in appetite and hunger and unlike weight loss mediated by diet are not followed by a rebound weight regain in the long term. In addition, there appear to be modifications in bile acid metabolism and the gut microbiome which also play a contributory role in weight loss following bariatric surgery.

The criteria for consideration of bariatric surgery have recently been updated to reflect advances in knowledge, surgical technique, and safety. According to the 2022 guidelines produced by the International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO), people with a BMI >35kg/m² should be recommended surgery and those with BMI 30-34.9kg/m² with metabolic disease should be considered. It is important to involve the multidisciplinary team in determining suitability for surgery as well as for long-term follow up (1). The multidisciplinary team typically includes a dietician, psychologist, physician, and surgeon. The decision on which procedure should be used is based on patient or surgeon preference, availability of appropriate aftercare and the patient’s tolerance of risk and permanent anatomical change.

BACKGROUND

The hallmark of an effective treatment of obesity is not one which can produce clinically weight loss, rather one which can produce weight loss which is sustained in the long term such that there is an improvement in obesity related disease and mortality. Although diet and lifestyle modification has long been the cornerstone of many obesity treatment programs, the primary concern with such approaches including very low energy diets (VLED) is the durability of weight loss. Randomized controlled trials have shown that weight loss of up to 15% is possible in people living with obesity however less than 10% will maintain this over one year and the majority will return to their pre-diet weight within 3-5 years (2). Conversely, bariatric surgery has been demonstrated to produce weight loss of 20-30% which critically is not only sustained in the long-term but has the effect of modifying the underlying disease process and resetting of the homeostatic weight ‘set point’, primarily through neurohormonal changes (3, 4).

The concept of the set point suggests that in the majority of adults, there is a pre-determined inherent weight around which each individual will maintain their weight over the long-term with a gradual increase seen over time. Following a period of volitional weight loss with dietary changes, there is a decrease in the overall weight followed by several homeostatic adaptations which see a return to the original baseline weight. Following bariatric surgery, irrespective of the procedure performed, there tends to be an initial period of rapid weight loss for the first 18 months followed by a period of weight stability and a subsequent very gradual weight regain. In spite of the recognized weight regain, what is critical is that overall, following surgery, there is a new, lower set point with a similar weight gain trajectory as to what is seen in the general population.

It was initially felt that bariatric procedures could be classified according to the mechanism by which they were thought to act, resulting in the description of ‘restrictive’ and ‘malabsorptive’ procedures however subsequent mechanistic studies have demonstrated this to be incorrect as they were recognized to act via alterations in neurohormonal signaling, bile acid metabolism, and changes in the microbiome (5).

The longest-term data establishing the role of bariatric surgery as a treatment for obesity compared to traditional lifestyle interventions comes from the landmark Swedish Obese Subjects (SOS) study (3). With more than 25 years of follow up, this case-control series demonstrated that irrespective of the procedure performed, bariatric surgery produces sustained weight loss which is maintained long term and supports a reduction in all-cause mortality due to cardiovascular causes and cancer compared to matched controls receiving standard care at the time (6). Critically, in addition to producing sustained weight loss, evidence from randomized controlled trials (RCTs) have consistently supported the efficacy of bariatric surgery in the treatment of obesity related disease, specifically type 2 diabetes mellitus (T2DM) compared to medical treatment (7-18).

In light of improvements in glycemic control and even remission of diabetes in a subset of people with obesity, bariatric surgery forms a central element in the treatment algorithm as endorsed by the American Diabetes Association (ADA) and International Diabetes Federation (IDF) for those with obesity and T2DM. Early views of gastrointestinal surgery as a means of permanently curing diabetes have been replaced by a more realistic view that it is more likely a means of inducing remission and improving long term glycemic control. Longer-term data from studies has now demonstrated that one in four people who initially go into remission will experience a relapse of T2DM (7). Despite this, it is essential to recognize that although some of the metabolic improvements associated with surgery dissipate with time, glycemic control is still very good compared to those treated with medication alone. As demonstrated by the UK Prospective Diabetes Study (UKPDS), there is a legacy effect of even a short period of improved glycemic control on the development of diabetes-related complications, cardiovascular endpoints and mortality (19). Thus, even individuals who do not meet the ADA criteria for diabetes remission, these improvements in glycemic control should not be dismissed as they may have important implications for morbidity and mortality.

A HISTORICAL PERSPECTIVE OF BARIATRIC SURGERY

Surgical procedures involving the upper gastrointestinal tract have long been recognized to result in substantial and sustained reductions in weight, albeit most often to the detriment of the patient. Although the mechanisms producing this weight loss were at the time very poorly understood, it became apparent that this effect could be used within the context of obesity to potentially produce surgically mediated weight loss with an improvement in metabolic disease.

Small Bowel Bypass Procedures (1950-1970)

Surgical management of obesity began with the introduction of the jejunoileal bypass (JIB) in 1954 (20). In this procedure, the proximal jejunum was diverted to distal part of the gut, leaving a long segment of excluded small intestine and a marked reduction in absorptive capacity. Although the JIB offered substantial and sustained weight loss with improvements in lipid metabolism, it was associated with serious side-effects including diarrhea, electrolyte imbalances, oxalate calculi in the kidneys, and progressive hepatic fibrosis with eventual liver failure (21-25). Given the seriousness of these complications, these procedures were generally abandoned by the 1970s in favor of so-called stomach stapling procedures

Stomach Stapling Procedures (1970-1990)

The Roux-en-Y gastric bypass (RYGB) operation was introduced by Edward Mason in 1960 (26) and gastroplasty in 1973 (27). Numerous variations of this procedure have followed, the most significant variant being the vertical banded gastroplasty (VBG) which was first described by Dr Mason in 1982 (28) . It was hoped that this group of operations would provide greater short- and long-term safety and yet retain the power of gastric bypass. Unfortunately, both randomized controlled trials and observational studies have consistently shown that it failed in both aspirations (29-32).

In the meantime, there was a resurgence of hypoabsorptive surgery with Italian surgeon, Nicola Scopinaro, introducing the biliopancreatic diversion procedure (BPD) in 1976 (33). The basic procedure involves distal gastrectomy leaving a proximal gastric pouch of 200 – 500 ml, a 200 cm length of terminal ileum anastomosed to the gastric pouch, and the biliopancreatic limb entering at 50 cm from the ileocecal valve (34). The most notable remodeling of the procedure has been the so-called duodenal switch variant (BPD-DS) proposed by Picard Marceau’s group in 1993 (35, 36) in which a longitudinal gastrectomy (sleeve gastrectomy) enabled retention of the gastric antrum for controlled gastric emptying, and the ileal limb was anastomosed to the proximal duodenum.

Adoption of the Laparoscopic Approach

One of the most remarkable advances in bariatric surgery came with the near universal adoption of a laparoscopic approach. The reduced invasiveness resulted in major improvements in safety with regard to morbidity and mortality, irrespective of the procedure performed. This contributed to a major rise in the use of bariatric surgery for obesity across the world. According to the most recent IFSO Global Registry Report, 99.7% of all primary bariatric procedures undertaken worldwide are done laparoscopically (37).

One of the first laparoscopic procedures to gain widespread acceptance was the laparoscopic adjustable gastric band (LAGB) which had been specifically designed as a standalone laparoscopic procedure in 1993. Proponents of the LAGB felt the procedure offered two primary benefits; there was an improved safety profile as it did not require the formation of any gastrointestinal anastomoses while also providing the option of a procedure which could be specifically tailored to individual needs; and allowing for band filling and deflation without requiring further surgery. LAGB became the most commonly performed bariatric procedure worldwide throughout the 1990s with only the United States not seeing widespread adoption due to regulatory restrictions which were only resolved in 2001. The adoption of laparoscopic RYGB started within a similar timeframe as LAGB however, the technical challenge associated with the formation of two gastrointestinal anastomoses contributed to a slower uptake. As surgical techniques advanced, in part due to the development of more advanced stapling devices, RYGB became the most commonly performed bariatric procedure worldwide. The adoption of sleeve gastrectomy (SG) has steadily risen in recent years, now accounting for approximately 60% of procedures world-wide, therefore overtaking RYGB which accounted for 29.5% as of 2023 (37).This increase is in part driven by the perception that it is less technically challenging than procedures such as RYGB as no anastomosis is formed.

Although RYGB and SG continue to account for the majority of procedures, the adoption of laparoscopic surgery has not only increased safety associated with bariatric surgery but has also contributed to the development of several new operations. One anastomosis gastric bypass (OAGB) is particularly noteworthy with regard to its increasing popularity and growing evidence base to support it as both safe and effective in terms of weight loss and resolution of metabolic co-morbidity. OAGB currently accounts for approximately 4% of procedures world-wide although the number has steadily risen in recent years (37).

Overall, the availability of several safe and effective laparoscopic bariatric procedures allows for greater ability to choose an operation that meets both the expectations and need of the individual while matching this with the skill set of the surgeon and moving the field closer to an era of precision medicine.

CURRENT METHODS IN BARIATRIC SURGERY

Sleeve Gastrectomy

The sleeve gastrectomy (SG) has become the most commonly performed bariatric procedure worldwide. Although initially conceived as part of the two-stage duodenal switch procedure SG has become a standalone operation having recognized the substantial weight loss it produces as well as improvement in obesity associated disease. SG involves excision of approximately 80% of the stomach by using multiple firings of a linear stapler/cutter to separate a narrow tube or sleeve of the lesser curve of the stomach from the greater curve. The initial firing starts approximately 4-7cm proximal to the pylorus which is preserved to maintain gastric emptying. A bougie (usually >32Fr) is placed in the lesser curve segment during the resection to maintain adequate lumen size. Although there is variability in the precise size, a 2012 consensus statement recommended the use of a bougie between 32-40Fr (38).

SG is relatively contraindicated in those with significant gastro-esophageal reflux disease (GERD) due to the high risk of worsening of pre-existing reflux and which can be difficult to manage symptomatically and may also play a role in the development of Barrett’s esophagus. Due to this potential risk, it is advised by the International Federation for the Surgery of Obesity (IFSO) that any person undergoing SG have surveillance endoscopy one year postoperatively and then every 2-3 years thereafter (39). Other recognized complications of SG include staple line leak and bleeding in the early postoperative period as well as de novo or worsening of GERD and stricture. As the gastric remnant is removed, SG is not a reversible procedure.

Although initially and incorrectly classified as a procedure that acted via mechanical restriction, mechanistic studies have demonstrated that SG acts by modifying key neurohormones including GLP-1 and PYY which regulate hunger, appetite, and satiety via the gut-brain axis (40). SG is also thought to reduce hunger through resection of the gastric fundus which is the site of ghrelin production (41).

Figure 1. Sleeve gastrectomy.

Laparoscopic Adjustable Gastric Banding (LAGB)

At one time LAGB was one of the most commonly performed bariatric procedures, however, it is now infrequently performed due to the perceived high complication and re-operation rate as well as the mounting evidence to support that that it does not produce equivalent weight loss to procedures such as SG and RYGB. Although previous studies have demonstrated nearly 50% excess weight loss that can be maintained with >15 year follow up, the major caveat was the requirement for very close follow up with regular band adjustments which was not sustainable in real world practice (42).

In spite of the apparent limitations of the LAGB, the less invasive nature of the operation and potential reversibility of the procedure make it a potential consideration for those who are considered higher risk. Recognized complications of LAGB include port site infection, GERD, pouch dilatation, band slippage and erosion. Studies have suggested that up to 50% of those who have a LAGB will require reoperation or band removal (43).

The exact mechanisms of action of the LAGB are unclear however they are thought to act beyond the pure mechanical effect by involving vagal afferents (44). Vagal stimulation may help regulate food intake by promoting satiety.

Figure 2. The band consists of a ring of silicone with an inner balloon. The balloon is connected to an access port.

Figure 3. The LAGB is placed over the cardia of the stomach within 1cm of the esophago-gastric junction.

Roux en Y Gastric Bypass (RYGB)

Roux en Y gastric bypass is now less commonly performed than SG due in part to the technical challenge of forming two anastomoses and previous lack of level one evidence demonstrating its superiority in terms of weight loss or resolution of obesity related disease. The emergence of recent data from several RCTs appears to support that RYGB may produce significantly higher weight loss than SG with greater improvements in obesity related disease including dyslipidemia and gastro-esophageal reflux disease (GERD). Overall, there is good long-term evidence to support the efficacy of RYGB as a safe procedure which provides significant and durable weight loss with a significant improvement in metabolic complications such as T2DM (7, 45). It is also the procedure of choice in those with significant pre-existing GERD and obesity rather than SG (46).

Similar to SG, studies have shown that RYGB produces weight loss through changes in gut hormones, namely GLP-1 and PYY, an effect which is believed to be in part the result of early delivery of nutrient in the terminal ileum and passage of undiluted bile in the bypass and the proximal jejunum (4, 5). These changes appear within days of surgery and as well as producing long-term reductions in weight are also responsible for the weight-loss independent improvements in glucose homeostasis which occur in the immediate postoperative period.

RYGB involves the formation of a small gastric pouch with an excluded gastric remnant. A loop of jejunum is then brought up and anastomosed to the gastric pouch to form the gastro-jejunostomy with the alimentary limb distal to this. Within the alimentary limb, ingested food is excluded from mixing with any digestive enzymes as the proximal jejunum has been bypassed. Approximately 100-120cm distal to the gastro-jejunostomy, a second anastomosis is formed between the biliary limb and the alimentary limb to form the jejuno-jejunostomy. It is only distal to this anastomosis that there is mixing of food and bile.

Although this is overall a very safe procedure, the most potentially serious complication which may arise is bowel obstruction or ischemia secondary to an internal hernia as two mesenteric defects are created during the procedure. Both mesenteric defects are typically closed intraoperatively, however, they may increase in size over time following weight loss and as the fat content of the mesentery decreases. Studies would support the routine closure of mesenteric defects but doing so is associated with an increased risk of complications associated with small bowel obstruction at the jejunojejunostomy (47). Additional complications include the possibility of anastomotic leaks or stricture and staple line bleeding. A small minority of people may also develop chronic abdominal pain which may be challenging to treat. It is also worth noting that due to the anatomical changes produced by RYGB, future procedures such as ERCP may require alternative approaches to accessing the excluded proximal duodenum via the remnant stomach. This may also be of concern in populations where there is concern about gastric cancer as the remnant stomach cannot be assessed by standard esophagogastroduodenoscopy.

Figure 4. RYGB showing a small gastric pouch, a narrow gastrojejunostomy and exclusion of foods from the duodenum and proximal jejunum.

One Anastomosis Gastric Bypass (OAGB)

The one gastric bypass is increasingly popular as an alternative to the RYGB owing in part to the fact that it produces significant weight loss but requires the formation of only one anastomosis. OAGB involves the formation of a small gastric pouch to which a loop of jejunum is anastomosed to form a gastro-jejunostomy. Unlike the RYGB, there is only one anastomosis and the length of duodenum and proximal jejunum which is bypassed is much longer, typically up to 150cm (48, 49). (figure 5).

The mechanism of action is thought to be very similar to that of RYGB in that it results in changes in gut hormone signaling via bypass of the proximal duodenum and studies to date would suggest that weight loss outcomes as a result are comparable (48). These changes are also responsible for the improvements in glucose homeostasis and resolution or improvement of T2DM.

Given the relative lack of long-term follow up on OAGB, there are concerns regarding the potential implications of chronic bile acid reflux and the possibility of inducing gastric and esophageal malignancy, however, there is no high-quality evidence at present to support these concerns.

Figure 5. OAGB showing the gastric pouch as a sleeve of lesser curve of stomach and the loop gastrojejunostomy.

Biliopancreatic Diversion / Duodenal Switch (BPD/DS)

Although BPD/DS is not amongst the most commonly performed bariatric procedures, accounting for only ~1% of operations worldwide, it is noteworthy for the amount of weight loss it induces as well as the resultant improvements in metabolic dysfunction. The operation is a two-stage procedure with the initial operation involving the formation of a sleeve gastrectomy with preservation of the pylorus. In the second stage, the duodenum is mobilized and divided at D1 and subsequently anastomosed to the distal ileum. The duoden-ileal anastomosis forms the alimentary limb through which ingested food will pass, without mixing with digestive enzymes. A second anastomosis is then formed between the biliary limb and the distal ileum, approximately 80-100cm proximal to the ileocecal valve. The second anastomosis creates a short common channel for mixing of ingested food and digestive enzymes.

The weight loss and metabolic improvements following BPD/DS are significantly greater than RYGB/OAGB and SG, however, it remains an infrequently performed procedure not only due to the technical challenges but primarily owing to significant long-term complications. As a result of the very short common channel, micronutrient and fat-soluble vitamin deficiencies are expected and long-term supplementation and monitoring is essential. The potential complications resulting from nutrient deficiency can be severe and in cases irreversible, including night blindness and Wernicke’s encephalopathy. Up to 10% will remain deficient despite adherence to dietary and nutritional guidelines and supplementation and will require re-operation (50).

Figure 6. The DS variant of BPD with a sleeve gastrectomy, retention of the gastric antrum, diversion of food into the mid small gut and diversion of pancreatic and biliary secretions to the distal small gut. Note both limbs are passing behind the transverse colon and a color difference is added to help follow the respective pathways. The common channel is the normal ileum terminating at the ileo-cecal junction.

Single Anastomosis Duodenal-Ileal Bypass with Sleeve (SADI-S)

The SADI-S procedure is seen as a potentially simplified version of the BPD-DS procedure. Similar to BPD-DS, the procedure involves the mobilization of the duodenum followed by sleeve gastrectomy with division of the duodenum. A duodenojejunal anastomosis is subsequently formed between the duodenal stump and a loop of ileum 250-300cm proximal to the ileocecal junction which is brought up in an antecolic fashion (51). Weight loss and metabolic outcomes following SADI-S have been shown to be very good at five years with 40% total weight loss with 60-80% of individuals in T2DM remission (52-54). As there is a longer common channel, the risk of nutritional deficiencies is lower than seen with BPD-DS and were similar to RYGB (55).

Experimental Bariatric Procedures

In recent years, there has been growing interest in non-surgical treatments for obesity including endoscopic approaches. Although long-term data is more limited, the ability to offer less invasive procedures may further broaden the population to which effective obesity treatment is available. EndoBarrier is an endoscopically placed 60cm duodenal-jejunal bypass liner which aims to replicate the effects of RYGB. Once placed within the duodenal bulb, the liner allows the flow of gastric content to the jejunum via the lumen while pancreatic content flows along the outside, preventing any mixing until the end of the liner is reached. The device can be left in situ for a maximum of 12 months with studies demonstrating a significant improvement in weight and HbA1c, however results >1 year are limited and the device does not at present have approval for use (56).

MECHANISMS OF ACTION IN BARIATRIC SURGERY

Although the development of the set point theory would support that for the majority of adults, there appears to be a pre-determined inherent weight around which most will not significantly deviate from in the long term, there appear to be profound changes following bariatric surgery which contribute to weight loss which is maintained. Irrespective of the procedure performed, people tend to demonstrate a similar weight loss pattern following surgery with an initial period of rapid weight loss for the first 18 months followed by a period of weight stability and a subsequent very gradual weight regain. In spite of the recognized weight regain, what is key is that overall, following surgery, there seems to be a new, lower set point and the adoption of a similar weight gain trajectory as to what is seen in the general population.

Early views of bariatric surgery saw procedures characterized according to the mechanism by which they were thought to act with sleeve gastrectomy (SG) described as a volume reducing surgery, biliopancreatic diversion (BPD) seen as a hypoabsorptive procedure and Roux en Y gastric bypass (RYGB) as both. Subsequent mechanistic and behavioral studies have since produced greater insights in to the mechanisms of weight regulation, alterations in appetite and satiety and neurohormonal changes as well as bile acid metabolism which are now recognized as key regulators resulting in weight loss an improvement in metabolic dysfunction (41, 57, 58).

Neurohormonal Changes

The key to understanding many of the effects of bariatric surgery is an appreciation of the complex interaction between gut hormones and higher cortical centers which regulate appetite and satiety. Mechanistic studies following bariatric surgery have provided important insights on how these neurohormones mediate their effects as well as how these pathways may be modulated surgically and pharmacologically to produce sustained weight loss as well as improvements in metabolic dysfunction associated with obesity.

Central regulation of appetite and hunger occurs primarily within several nuclei located within the hypothalamus including the arcuate nucleus (ARC) which is one of the most well defined and characterized. Within the ARC, there are distinct neuronal subtypes which respond to signals from the brain stem as well as from within the circulation to potentiate their effects on appetite and hunger. Hunger stimulating neurons found within the medial ARC express neuropeptide Y (NPY) and agouti-related peptide (AgRP) which are recognized as the primary orexigenic neurons. Animal studies have contributed to characterizing the effects of these neurons with pharmacological activation of the NPY/AgRP neurons producing a rapid increase in food intake and fat stores while decreasing energy expenditure (59). The orexigenic effects of these neurons are counterbalanced by those within the lateral ARC, including pro-opiomelanocortin (POMC) and cocaine-and-amphetamine-related transcript (CART) neurons which decrease hunger and appetite a-melanocyte stimulating hormone (a-MSH) as it is one of the primary agonists of the anorectic melanocortin-4 receptor (MCR4) (60). The importance of the melanocortin pathway has been clearly illustrated by the effects of MCR4 deficiency in humans which has been identified as the most common cause of monogenic obesity. In these individuals, there is dysregulation of eating behaviors resulting in hyperphagia and obesity (61).

In addition, further peripheral feedback via gastrointestinal neurohormones plays an important role in modulating appetite and satiety. Although gut hormones have long been recognized to have essential roles within the gastrointestinal tract, regulating the release of insulin and exocrine secretions as well as altering motility, their central effects in regulating metabolism and energy balance via the gut brain axis are becoming increasingly well recognized and characterized.

The adipocyte derived hormone, leptin, has been identified as an important mediator in the regulation of body weight, serving as a marker of nutritional status and overall fat mass. Although leptin has a bidirectional effect and may affect both anorectic and orexigenic pathways, it appears to be predominantly related to the preservation of body weight. Falling leptin levels secondary to decreased fat mass appear to stimulate orexigenic NPY neurons in the ARC of the hypothalamus, mediating increased appetite and food intake (62, 63). Although initially considered as a potential therapeutic target for those with obesity given its effects on appetite and food intake, studies have demonstrated that those with obesity have high circulating levels of leptin and may be resistant to its effects (64). Studies have shown that in people with obesity, the administration of exogenous leptin does not significantly impact food intake, nor does it result in a reduction in body weight aside from very rare cases of congenital leptin deficiency (65).

Ghrelin is the only characterized peripherally derived orexigenic neuropeptide, mediating its effects on appetite centrally within the ARC of the hypothalamus by activating NPY/AgRP neurons (66). Ghrelin is primarily produced peripherally by the stomach and centrally within the pituitary gland and the two sources have been seen to have differing means of signaling. Pituitary derived ghrelin mediates its effect directly via the hypothalamus whereas ghrelin produced from within the stomach is believed to act via vagal afferents as its effects have been shown to be diminished following vagotomy (67). In addition to mediating central changes in appetite, ghrelin also produces important changes in glucose homeostasis with ghrelin being shown to inhibit glucose-stimulated insulin secretion and impairs glucose tolerance (68). The primary regulator of plasma ghrelin levels appears to be overall caloric intake with levels rising and falling in line with food intake and fasting although the exact mechanisms by which ghrelin secretion is controlled have still not been elucidated. The importance of ghrelin in long-term weight regulation in those with obesity has been supported by studies which have demonstrated increased levels of ghrelin following diet induced weight loss, a change which was not seen in those with surgically mediated weight loss following bariatric surgery (69). Furthermore in people living with obesity, the normal physiological reduction in ghrelin levels in the post-prandial period is attenuated which suggests a potential role for ghrelin in the development of obesity (70).

Glucagon-like peptide-1 (GLP-1) is one of the best characterized neurohormones involved in the physiological and metabolic changes mediated by bariatric surgery, acting both through central and peripheral receptors to mediate its effects. GLP-1 is an incretin hormone which is secreted by the enteroendocrine L cells primarily located within the terminal ileum and colon in response to luminal nutrient exposure, particularly fats and carbohydrates (71). Within the gastrointestinal tract, GLP-1 has an important role in regulating gastric emptying and has been demonstrated to decrease the rate of gastric emptying and increasing post prandial satiety and fullness, an effect which is thought to be mediated via the vagus nerve (72). Studies in rodent models following vagotomy have demonstrated a lack of GLP-1 secretion following ingestion of high fat test meals, supporting the importance of the vagus nerve as a mediator of this response (73). The delay in gastric emptying has also been demonstrated to have an effect on glucose absorption rates and glycemia. In those given the GLP-1 antagonist there was an increased glycemic response following a carbohydrate test meal (72). The predominant effects of GLP-1 on altering glucose metabolism occur via its action as an incretin hormone. Within the pancreas, GLP-1 binds to b-cells stimulating insulin secretion in a glucose dependent manner. In addition, GLP-1 improves glucose sensitivity in glucose resistant b-cells, allowing previously resistant b-cells to sense and respond to glucose and hyperglycemia (74). The use of GLP-1 receptor agonists have also been shown in rodents to increase b-cell proliferation while inhibiting apoptosis to increase overall b-cell mass (75). Further augmenting its effect on improving post prandial glycemia, GLP-1 also stimulates somatostatin by binding to GLP-1 receptors on pancreatic b-cells while inhibiting pancreatic glucagon secretion in a glucose dependent manner (76). Within the liver, GLP-1 inhibits hepatic glucose production while stimulating glucose uptake by muscle and adipose tissue. Centrally, GLP-1 is also produced within the nucleus of the solitary tract in the brainstem which projects to the hypothalamic paraventricular nucleus which expresses GLP-1 receptors (77). The small molecular size of GLP-1 allows it to cross the blood-brain-barrier thus GLP-1 receptor agonists given peripherally are thought to mediate central effects via receptors in the hypothalamus to promote satiety and reduce energy intake, contributing to weight loss.

Similar to GLP-1, peptide YY (PYY) is primarily secreted by the endocrine L cells within the terminal ileum in the postprandial period and has overlapping effects to GLP-1. Following its release, PYY results in delayed gastric emptying and decreased gastric secretion. Centrally, PYY acts within the arcuate nucleus of the hypothalamus by binding to the anorectic POMC neurons to inhibit feeding (78). Vagotomy results in an attenuated anorectic response to PYY, suggesting the potential role of the vagus in this pathway (79). In addition to its anorectic effects, PYY plays a role in weight maintenance via its effects on energy expenditure. In humans, peripheral infusion of PYY has been shown to increase energy expenditure as well as raising fat oxidation rates (80). Further establishing the role of PYY in body weight regulation was a study that demonstrated a negative correlation between fasting PYY levels and levels of adiposity and resting metabolic rate (81). In people living with obesity, there is a lower postprandial PYY level compared to normal body weight individuals in response to a test meal, which was associated with decreased satiety and relatively increased food intake (82). Peripheral administration of PYY produces a similar reduction in food intake in those with obesity as in those of a normal body weight, suggesting that PYY resistance is not likely contributing to the development of obesity (83).

Bile Acid Metabolism

In addition to the critical role neurohormones are thought to play in long-term weight regulation, changes in bile acid (BA) metabolism have been recognized as a potential key mediator, which may contribute to long term weight loss following bariatric surgery. Studies in both human and rodent models have demonstrated increased plasma bile acids following Roux en Y gastric bypass (RYGB), sleeve gastrectomy (SG), and biliopancreatic diversion (BPD) in both human and rodent models. The farnesoid X receptor (FXR) is a nuclear BA receptor and is an important regulator of genes which are involved in BA synthesis and transport in addition to its role in lipid and glucose metabolism (84). There is growing interest that changes in BA metabolism via FXR are a key link between the alterations in BA composition following bariatric surgery and the improvements in glucose homeostasis and remission of T2DM. Studies in rodent models have supported the potential relationship between alterations in BA metabolism mediated by the FXR with weight loss and improvements in glycemic control. In mice with diet induced obesity undergoing SG and FXR receptor genetic disruption, there was a clear decrease in weight loss and improvements in glycemia compared to wild type littermates also undergoing SG, establishing the importance of a functional FXR to mediate some of the metabolic improvements following surgery (85). It is thought that the increase in plasma bile acids results in FXR activation which in turn produces an increase in FGF19 which has effects mimicking the actions of insulin, increasing glycogen synthesis while decreasing gluconeogenesis (86).

Increased plasma BA are also thought to induce metabolic changes following bariatric surgery by binding to the G protein coupled receptor, TRG5, which is expressed in the distal ileum. Found within the enteroendocrine L cells, BA are thought to activate TGR5, which is a key element in the signaling pathway responsible for increasing GLP-1 production (86). In addition to the changes in glucose metabolism mediated by TGR5 activation, it is thought that this receptor may play a role in contributing to an overall shift towards a negative energy balance in the postoperative period, resulting in increased oxygen consumption and energy expenditure.

Table 1. Possible Mechanisms of Bariatric Surgical Effect.
Induce satiety, reduce appetite, control hunger
Change of taste preference - less sweet foods; lower fat content
Reduce caloric Intake
Diversion from proximal duodenum
Malabsorption of macronutrients
Increased energy expenditure; Increased diet-induced thermogenesis
Changes in the normal homeostatic adaptations to weight loss
Changes in the gut microbiome
Changes in plasma bile acid levels
Changes in gut hormones: candidates include the incretins (GLP-1; GIP), ghrelin, CCK, Peptide YY
Central mechanisms: Modify hedonics; central appetite control; altered food preferences

OUTCOMES AFTER BARIATRIC SURGERY

Mortality And Adverse Events

PERIOPERATIVE MORTALITY

Although there is often a perception that bariatric surgery should be reserved as treatment of last resort when all other approaches have not been effective, this is not supported by current data. Early data on morbidity following bariatric surgery was significantly higher but has remarkably decreased in part owing to the near universal adoption of the minimally invasive approach and advances in surgical techniques.

UK registry data looking at all primary bariatric operations from 2009-2016 demonstrated a 30-day mortality rate of 0.08% after discharge with an overall downward trend in mortality over the study period. Similarly, a population based study comparing 30 day, 90 day, and 1 year mortality rates demonstrated that bariatric surgery had the lowest mortality rate over all time periods compared to other common elective procedures including cholecystectomy, hysterectomy, and hip and knee arthroplasty (87, 88).

Early Adverse Events (<30 days)

Overall, the incidence of adverse events in the early postoperative period is low, with similar rates seen in randomized controlled trials comparing different procedures. In a review of more than 100,000 cases, the most common early adverse events were not directly related to the procedure, rather they were myocardial infarction and pulmonary embolus which were seen in 1.15 and 1.17% of cases respectively (89). These two complications were also associated with the highest mortality rate amongst those experiencing early postoperative complications (89). Bleeding in the early postoperative period although potentially serious and requiring a return to operation room is uncommon with rates cited between 0.5% for SG and 1% following RYGB (90).

Looking specifically at procedure related complications, staple line leak following SG although uncommon remains a concern as it can be challenging to treat. A systematic review of 148 studies including more than 40,000 individuals found an overall leak rate of 1.5% (91). Several techniques have been identified to help reduce the risk of leaks including reinforcement and buttressing, however, no consensus exists as to the ideal approach. Although RYGB is seen as a technically challenging procedure due to the formation of two anastomoses, the risk of anastomotic leak is approximately 1% and an overall complication rate of 4.4% (92, 93). Similar rates of anastomotic leak have been reported following OAGB (94).

Late Adverse Events

Depending on the specific procedure several long-term medical problems can occur and include micronutrient deficiencies, dumping syndrome, hypoglycemia, cholelithiasis, nephrolithiasis, and osteoporosis and fractures. These medical problems are discussed in detail in the Endotext chapter entitled Medical Management of the Postoperative Bariatric Surgery Patient (95).

RYBG is the procedure with the greatest amount of data to support its long-term safety and efficacy. However, there are several well characterized long-term complications which may arise. Internal herniation, although rare, occurs in approximately 2-3% following RYGB, presenting with symptoms of small bowel obstruction, most commonly severe abdominal pain (96). It is important to have a high index of suspicion with these symptoms as definitive diagnosis based on imaging alone is unreliable and diagnostic laparoscopy should be considered (97). It is also worth noting that studies have found that up to 10% of individuals report chronic abdominal pain following RYGB which can be difficult to treat and may impact negatively on quality of life (98, 99).

One of the primary concerns in the long-term for patients undergoing SG is the possibility of developing de novo reflux or the worsening of pre-existing symptoms which can be difficult to treat (100). A RCT with 5-year follow-up demonstrated that 16% of patients following SG developed de novo reflux vs 4% undergoing RYGB (46). The SM-BOSS study also found a reflux remission rate of 60.4% compared to 25.0% following SG (101). In patients with severe reflux following SG, conversion to RYGB has been found to be effective in improving or treating symptoms (102). Given the concerns regarding the long-term risk of reflux and the development of Barrett’s esophagus, IFSO has issued guidance to recommend surveillance endoscopy one year postoperatively and then every 2-3 years thereafter (39).

Although there is more limited long-term data for patients undergoing OAGB, studies have shown that up to 41% of patients at 5 years reported gastro-esophageal reflux compared to 18% of those undergoing RYGB (103). Given the anatomical configuration, bile acid reflux and esophagitis has also been found endoscopically and although the long-term implications are unknown, it does raise concerns regarding future cancer risk (104).

Considering the nature of bariatric surgery, a commitment to long-term follow up, particularly focusing on nutritional supplementation and monitoring, is an essential element in the decision to proceed with an operation. However, the specific requirements are largely procedure specific and determined by the anatomical changes involved. Although relatively rarely performed DS is noteworthy not only for the weight loss and improvement in metabolic dysfunction it can result in relatively high-risk nutritional deficiencies compared to other procedures.

Weight Loss Outcomes

The ability to produce not only profound weight loss but weight loss which is sustained in the long term is essential to the success of bariatric as a treatment for obesity, which is recognized as a chronic and progressive disease. As such, the importance of studies can in some ways be categorized according to the length of their follow-up period when considering their clinical relevance or impact although clearly the soundness of the overall methodology is the primary determinant. Short-term studies (1 - 3 years) are plentiful but simply suggest potential effectiveness. Medium term studies (3 -10 years) are far fewer but are more assuring of real effectiveness. There is also now mounting longer term data emerging which further adds to the more than 25-year follow up of the landmark Swedish Obese Subjects (SOS) study.

SHORT AND MEDIUM-TERM OUTCOMES

In recent years, there have been a number of RCTs with 5-year follow up periods which have emerged comparing weight loss between different procedures. The SM-BOSS study was a multi-center RCT comparing SG to RYGB with a primary end point comparing weight loss (101). At 5 years, the study did not show a statistically significant difference in excess BMI loss with -61.1% seen following SG compared to -68.3% following RYGB. Similarly, the SLEEVEPASS study also sought to compare SG to RYGB with the primary end point of weight loss measured as % excess weight loss (EWL) (105). The %EWL at 5 years was 49% after SG and 57% following RYGB, however, this difference was not statistically significant. The individual participant data of both studies were merged with the results supporting a greater percentage BMI loss and resolution of hypertension with RYGB compared to SG but no difference in T2DM remission or quality of life at 5 years (106).

While none of the published data at present clearly supports the superiority of one procedure over another, there are two ongoing RCTs, ByBandSleeve and Bypass Sleeve Equipoise Trial (BEST) which may change this (107, 108).

LONG-TERM (>10 YEAR) OUTCOMES

The prospective Swedish Obese Subjects (SOS) study was a key step in establishing the effect of bariatric surgery in people with obesity compared to usual care and now has more than 25 years of follow-up data. Follow-up data which was measured at 2, 10, 15, and 20 years demonstrated -23%, -17%, -16% and -18% mean changes in body weight in the surgery group compared to between 1% and -1% in the standard care group at these same time points (6). It is worth noting that this study included several procedures such as gastric banding and vertical banded gastroplasty which are no longer commonly performed.

Looking specifically at RYGB, there is mounting data to support the long-term weight loss produced by the procedure. A prospective study looking at 1156 participants undergoing RYGB over a 12 year follow up period found a -26.9% mean percent weight loss (45). The mean percent weight loss at 6 years was similar at -28% suggesting that weight remained relatively stable after the initial period of weight loss in the first year. These results were similar to a retrospective cohort analysis of 10-year weight loss outcomes following RYGB which showed a mean weight change of -28.6% (109).

Data looking at >10-year outcomes for SG is more limited, however, the 10-year observational follow up study of the SLEEVEPASS study showed a mean excess weight loss (EWL) of 43.5% (110). Similarly, high quality studies evaluating the >10-year weight loss outcomes are limited for OAGB given the relative recent adoption of the procedure. However, a retrospective single-center analysis of 385 participants showed a mean % total weight loss (TWL) of 33.4% (111). Although infrequently performed due to the high complication and reoperation rate, BPD/DS remains the procedure which produces the most substantial weight loss with studies showing a 10 year TWL of 40.7% (50).

Overall, it would appear that the effect of bariatric surgery, irrespective of the procedure performed, is a period of rapid weight loss followed by prolonged weight stability which is essential to improving long-term morbidity and mortality.

Type 2 Diabetes and Bariatric Surgery

Type 2 diabetes and obesity are inherently linked diseases and improvements in glycemic control has become one of the earliest indicators that surgical modification of the gastrointestinal tract could result in profound metabolic changes and indeed could help modify the underlying disease process. Early studies looking at jejuno-ileal bypass demonstrated a rapid normalization of blood glucose in the early postoperative period, prior to any weight loss, which first raised the possibility that these operations could produce changes in a weight loss independent manner. The 1995 observational study which showed a normalization of glycemia in more than 600 people with obesity and T2DM undergoing RYGB was one of the first to create widespread interest in the possibility of employing surgery as a treatment for T2DM (112). Having recognized this effect, the metabolic effects of bariatric surgery and its implications for T2DM have become one of the main focuses of research. RCTs comparing bariatric surgery to medical management alone have consistently demonstrated that it is more effective in improving glycemia and cardiovascular risk factors, irrespective of the procedure performed. As such, it is now endorsed by governing bodies world-wide as a central element of the treatment algorithm for people with T2DM and obesity (113).

The STAMPEDE trial was a RCT comparing the use of bariatric surgery, either SG or RYGB in conjunction to intensive medical therapy (IMT) compared to IMT alone (8). Over a 5 year follow up period, only 5% of the participants in the IMT group reached an HbA1c of <6% vs 23% undergoing SG and 29% following RYGB. A further study involving three arms compared RYGB to BPD and medication. Over a ten year follow up period, T2DM remission rates were 25% for RYGB, 50% for BPD, and 5.5% for those treated with medication, however, that includes one participant who crossed over from the medical therapy group to surgery (7). Although the study showed that the remission rates decreased in both surgical groups between the 5 and 10-year follow up period and was lower particularly within the RYGB group, even in those who did relapse, glycemic control remained very good (HbA1c<7% or <53mmol/mol). The ARMSS-T2DM study a pooled analysis of four RCTs is currently the largest analysis with the longest follow up comparing bariatric surgery with medical treatment/lifestyle modification for T2DM (114). At 12 years, the between group difference in HbA1c levels was -1.1% with none of the patients in the medical group in remission compared to 12.7% in remission in the bariatric surgery group. The patients in the bariatric surgery group were also using fewer anti-diabetes medications.

REMISSION RATES IN RCTs

As of April 2024, there were 12 randomized controlled trials which irrespective of the type of surgery have consistently demonstrated the greater improvements in glycemic control and disease remission with bariatric surgery compared to medical therapy (8, 10-16, 18, 115-117) All studies have compared one or more bariatric procedures with a group having non-surgical treatment (NST). The difficulty in drawing firm conclusions is in part due to the studies not being directly comparable due to extensive heterogeneity, including different criteria for patient selection, treatment durations, and the use of various definitions of remission of diabetes, particularly the cut-off values for HbA1c. Nevertheless, they serve to provide key comparisons with NST, the current offering to more than 99% of people with diabetes.

The first of the studies was performed the Centre for Obesity Research and Education (CORE) in Melbourne (115). 60 patients were randomized to LAGB or NST. They were required to have a BMI between 30-40kg/m² and to have been known to have T2DM duration < 2 years. At 2-year follow up, 73% of patients were in remission (defined as a HbA1c < 6.2%) following LAGB vs 13% in the NST group.

The STAMPEDE study randomized 150 patients to either intensive medical therapy (IMT) alone or IMT plus SG or RYGB. Remission was defined as an HbA1c <6.0%. At 5 years, remission rates were 5% in the IMT group vs 23% following SG and 29% following RYGB.

Mingrone et al report the longest follow up having completed a 10 year follow up of 60 patients to NST, BPD, or RYGB (7). They used criteria of HbA1c <6.5% and fasting glycemia <5.55mmol/L without medication for one year to define remission. Of all the patients who initially went into remission in the surgical group, 37.5% remained in remission at 10 years with 25% for RYGB and 50% for BPD. 20 of the 34 patients in the surgical group who were in remission at 2 years subsequently relapsed by 10 years, however, all maintained good glycemic control with a mean HbA1c of 6.7%. There were two patients within the medical group at 10 years who were in remission included in the intention to treat analysis. However, these were both patients who had surgery during the follow up period.

Ikamuddin et al (118), carried out a multicenter RCT with 120 patients undergoing either RYGB or having NST. The defined remission as HbA1c <6% at consecutive annual visits without the use of medications. None of the participants in the medical therapy group were in remission at any point during the study while 16% of the participants who underwent RYGB were in remission at year two and 7% at year five.

Courcoulas et al randomized 69 patients into 3 groups – NST, RYGB, and LAGB (13). They defined remission as HbA1c< 6.5% and FBG <125mg/dL. At five years, the reported remission rates were 30% for the RYGB group and 19% for LAGB while none of the patients in the medical group were considered to be in remission.

A Summary of the RCTs to date comparing the long-term efficacy of metabolic surgery compared to medication or lifestyle modification for T2DM can be seen in Table 2 (Adapted from Courcoulas et al (114)).

Table 2. RCTs Comparing Long-Term Efficacy of Metabolic Surgery vs. Medication or Lifestyle
Study	No of participants	Follow-up (months)	Study design	Remission criteria	Remission^* (%)	P value
Parikh (8)	57	6	RYGB/LAGB/SG vcontrol	HbA_1c<6.5%	65 v 0	0.001
Liang (9)	101	12	RYGB v control	HbA_1c<6.5%	90 v 0	<0.001
Halperin (10)	38	12	RYGB v control	HbA_1c<6.5%	58 v 16	0.03
Ding (11)	45	12	LAGB v control	HbA_1c<6.5%	33 v 23	0.46
Cummings (12)	43	12	RYGB v control	HbA_1c<6.0%	60 v 5.9	0.002
Dixon (13)	60	24	LAGB v control	HbA_1c<6.2%	73 v 13	<0.001
Wentworth (14)	51	24	LAGB v control	FBG <7.0 mmol/L	52 v 8	0.001
Simonson (15)	45	36	LAGB v control	HbA_1c<6.5% and FBG <126 mg/dL	13 v 5	0.60
Kirwan (16)	316	36	RYGB/LAGB/SG vcontrol	HbA_1c≤6.5%	37.5 v 2.6	<0.001
Schauer (17)	150	60	RYGB v SG v control	HbA_1c≤6.0%	22 v 15 v 0	<0.05
Ikramuddin (18)	120	60	RYGB v control	HbA_1c<6.0%	7 v 0	0.01
Courcoulas (19)	69	60	RYGB v LAGB vcontrol	HbA_1c<6.5% and FBG <125 mg/dL	30 v 19 v 0	0.02
Mingrone (20)	60	120	RYGB v BPD vcontrol	HbA_1c<6.5% and FBG <100 mg/dL	25 v 50 v 5.5	0.008

V= versus

DURABILITY OF REMISSION

As long-term evidence from RCTs has emerged, it would support that some of the metabolic effects appear to diminish over time, which perhaps in part reflects the underlying nature of diabetes, which is understood as both chronic and progressive. The SAMPEDE study found a three-year remission rate following RYGB of 38% which fell to 22% at five-years (8, 119). The suggestion that the metabolic effects of RYGB are attenuated with time were supported by the RCT with the longest follow up which found the remission rate fell from 75% at 2 years to 37% at 5 years and 25% at 10 years (7).

The effects of SG were examined in the STAMPEDE study which showed a reduction in remission rates from 37% to 24% between years 1-3 and 15% at 5 years (8). The initial remission rates as well as long-term remission have been demonstrated to be highest following BPD with 63% in remission at 5 years and 50% at 10 years (7).

MACROVASCULAR AND MICROVASCULAR COMPLICATIONS

The durability of remission and the reduction of complications has been demonstrated at a fifteen year follow up in the SOS study, a prospective matched cohort study (120). They reported that the remission rate for the surgical group, predominantly gastroplasty, at two years was 72% and at 15 years was 31%. This remission rate, though reduced with time, was significantly better than the 6.5% in the control group, indicating an important long-term benefit. Furthermore, and arguably more important than the remission rate, they found the number macrovascular and microvascular complications of diabetes were fewer at 15 years in the surgical group than in the controls.

OTHER HEALTH OUTCOMES AFTER BARIATRIC SURGERY

Cancer

Obesity has been demonstrated to not only be a risk factor for the development of certain types of cancer but may also increase the risk of mortality associated with cancer. The SOS study was the first interventional trial which demonstrated a decreased incidence of cancer, amongst patients undergoing bariatric surgery compared to matched controls (121). Since then, there has been increased recognition of the possibility that weight loss mediated by bariatric surgery may reduce both the incidence of cancers as well as improving long term outcomes. A subsequent matched cohort study, the SPLENDID study demonstrated reduced cumulative incidence of mortality related to 13 types of cancer in patients undergoing bariatric surgery compared to the non-surgical group with an adjusted HR of 0.52 (122). Further studies examining the effect of bariatric surgery specifically on the incidence of non-hormonal cancers demonstrated a nearly 50% reduction in patients undergoing bariatric surgery compared to matched controls (123).

Cardiovascular Disease

Obesity is one of the most important modifiable risk factors in the prevention of cardiovascular disease. However, until the publication of several critical studies, what was not clear was whether or not weight loss achieved through surgical means could modify individual cardiovascular risk factors and produce a resultant improvement in mortality. There are now more than 30 observational studies which have examined primary prevention of cardiovascular disease, demonstrating reduced morbidity and mortality in patients with obesity undergoing surgery compared to usual care. The SOS study which has more than 30 years of follow up data has demonstrated the long-term benefits of bariatric surgery on reducing cardiovascular risk, demonstrating a 30% reduction in death from cardiovascular disease (6). One of the largest observational studies to date including nearly 14,000 patients found a 62% reduction in new onset heart failure, 31% reduction in myocardial infarction rates, 33% reduction in stroke, and a 22% reduction in atrial fibrillation (124).

Liver

The term metabolic dysfunction-associated steatotic liver disease (MASLD) is a broad categorization of a spectrum of liver diseases ranging from hepatic steatosis to metabolic dysfunction-associated steatohepatitis (MASH, which can progress to cirrhosis and end-stage liver disease. MASLD is now the most common cause of chronic liver disease globally; however, its implications have up until recently been largely underappreciated due to the fact that many patients are asymptomatic. In patients with obesity, the incidence of disease is far higher, and the entire spectrum of disease is seen, with up to 80% having steatosis, 37% MASH, 23% fibrosis, and 5.8% cirrhosis (125).

The majority of patients with MASLD are asymptomatic and a significant proportion will also be biochemically normal; thus, a diagnosis of MASLD can only be made on the basis of imaging studies. It is difficult to monitor the progression of MASLD, particularly in those with normal liver enzymes; however, one-third of patients with early-stage MASH will progress to fibrosis within five to ten years of diagnosis (126). Given the growing number of individuals affected by obesity and MASLD, it is anticipated that MASH will become the leading indication for liver transplantation (127). An increasing body of evidence supports the consideration of MASH and fibrosis as a significant obesity-related complication and recommend its inclusion as an indication for bariatric/metabolic surgery, given their potential reversibility with substantial weight loss mediated by surgery.

A meta-analysis of 21 studies, including over 2000 patients undergoing bariatric/metabolic procedures, found a resolution of steatosis or steatohepatitis and biochemical normalization in most patients (128). The critical finding was that in those with severe disease and established fibrosis there was a reversal of these changes in 30% of patients.

Dyslipidemia of Obesity

Increased fasting triglyceride and decreased high-density lipoprotein (HDL)-cholesterol concentrations characterize the dyslipidemia of obesity and insulin resistance (129). This dyslipidemia pattern is highly atherogenic and a common pattern associated with coronary artery disease (130). Bariatric surgery produces substantial decreases in fasting triglyceride levels, a normalization of HDL, and an improved total cholesterol–to–HDL-cholesterol ratio (131-133). Although elevation of total cholesterol is not purely obesity-driven, evidence would support that procedures such as OAGB and RYGB (134) can produce significant improvements in total cholesterol levels(135).

Hypertension

There is evidence of a reduction in both systolic and diastolic blood pressure (BP) following weight loss in association with bariatric surgery (136). The GATEWAY study examined the long-term effects of bariatric surgery on hypertension (HTN) control and remission. The RCT involved 100 participants comparing 5-year outcomes in people with HTN on medical therapy alone vs RYBG and medical therapy. RYBG was associated with HTN remission in 46.9% of participants compared to 2.4% of those in the medical therapy group. The number of medications required to maintain BP<140/90mmHg was reduced by 80.7% following RYGB (137).

Asthma

There is a positive relationship between asthma and obesity with a possible dose-response effect (138, 139). The Nurses' Health study identified a five-fold increase in the relative risk of asthma with a weight gain of 25kg from age 18 when compared to a weight stable group (140). In patients with obesity, outcomes from asthma are worse with more patients with poor control despite maximal therapy, more frequent exacerbations, and poorer quality of life (141). Given the link between sustained weight loss and improvements in asthma, there has been significant interest in the possible role of surgery in the management of patients with obesity and asthma. A systematic review of studies involving SG, LAGB, RYGB and BPD described a consistent improvement in pulmonary function tests following bariatric surgery as well as quality of life (142).

Obstructive Sleep Apnea

Obstructive sleep apnea is characterized by recurrent episodes of upper airway obstruction and hypoxia during sleep due to abnormal airway collapsibility. Excess weight is the strongest independent risk factor in the development of obstructive sleep apnea, with a 10% change in body weight associated with a 30% worsening in the apnea-hypopnea index (AHI), one of the primary indexes for measuring severity (143). A systematic review of 69 studies found that irrespective of the procedure performed, bariatric surgery resulted in a significant improvement in most patients. These findings were supported by a further meta-analysis which found 83.6% of patients reporting resolution or improvement of symptoms (144). Although there is evidence demonstrating significant improvements with regard to the AHI, it is essential to note that despite this, most patients following treatment remain within the moderate to severe range. Bariatric surgery should not be undertaken with the goal of cure in mind, but rather to control or reduce disease severity.

IMPROVEMENT IN QUALITY OF LIFE (QOL)

Several studies clearly demonstrate major QOL improvements following bariatric procedures (145-149). A large prospective study of QOL after bariatric surgery employed the Medical Outcomes Trust Short Form-36 (SF-36). The SF-36 is a reliable, broadly used instrument that has been validated in people living with obesity. In this study, 459 participants with complex obesity were found to have lower scores compared with a control population for all 8 aspects of QOL measured, particularly the physical health scores. Weight loss provided a dramatic and sustained improvement in all measures of the SF-36. Improvement was greater in those with more preoperative disability, however, the extent of weight loss was not a good predictor of improved QOL. Even for patients who required revisional surgery during the follow-up period, they found a similar improvement in measures of QOL. Similar improvements in QOL have been demonstrated in patients having LAGB for previously failed gastric stapling (150).

IMPROVEMENT IN SURVIVAL

The ultimate test of effectiveness of a treatment is the reduction of mortality. There is a growing body of evidence on long-term mortality of people who have undergone bariatric surgery compared to people with obesity who have not had surgery which shows improved survival. The SOS study demonstrated that over a median follow up period of 24 years that there was a lower risk of mortality in the people who had undergone surgery compared to the matched controls which resulted in a median increase in life expectancy by 2.4 years (6). The risk of death from both cardiovascular risk but also cancer was lower in the patients who had undergone surgery. In spite of these improvements, the group of patients who had undergone surgery still had an 8-year shorter life expectancy relative to the general population with the leading cause of death being cardiovascular disease.

A systematic review and meta-analysis of 16 matched cohort studies and one prospective controlled trial found that there is a median improvement in life expectancy of 6.1 years in patients who had undergone bariatric surgery compared to usual care. Although both participants with and without T2DM demonstrated an increased overall survival, the treatment effect was considerably larger for those with T2DM with an increased life expectancy of 9.3 years compared to the non-surgical group. The number needed to treat to prevent one additional death in 10 years was 8.4 for people with T2DM compared to 29.8 for those without (151).

FUTURE DIRECTIONS COMBINING MEDICATIONS WITH SURGERY

There has long been a focus on comparing outcomes for the treatments of obesity and related diseases, particularly T2DM looking at the use of either surgery or medical therapy. Although studies have consistently demonstrated the efficacy of surgery in achieving long-term reductions in weight and improvements in diabetes, it is clear from our understanding of the disease process itself that obesity is a chronic and progressive disease which will over time require treatment intensification. Looking to the management of other diseases, including cancer, surgery is often viewed as a means of establishing disease control with adjunctive medical therapies to sustain this effect in the long-term (152, 153).

The concept of utilizing medication with bariatric surgery has been demonstrated to be both safe and effective as demonstrated by the STAMPEDE trial in which both RYGB and SG were combined with IMT. Impressive advances in pharmacotherapy initially developed as anti-diabetes medications but equally recognized for its efficacy in producing weight loss in people without diabetes has made the potential for employing multi-modal care even more promising, improving long term disease control and remission.

WHO SHOULD BE CONSIDERED FOR BARIATRIC SURGERY?

For many years, the criteria for bariatric surgery were largely based on the National Institutes of Health (NIH) guidelines issued more than 30 years ago in 1991 (154). These guidelines were highly constrained by BMI cut offs and based on surgical outcomes from the era of open surgery. Having recognized the significant advances in surgery, safety outcomes as well as our greater understanding of the disease process, related disease, and mechanisms of action of surgery, IFSO and ASMBS jointly released updated guidelines in 2022 (1).

Major changes to the previous guidelines include:

Metabolic and bariatric surgery (MBS) is recommended for individuals with BMI>35kg/m²regardless of the presence of obesity related disease.
MBS should be considered for individuals with a BMI 30-34.9kg/m² with metabolic disease.
BMI thresholds should be adjusted in the Asian population such that a BMI>25kg/m² suggests clinical obesity and individuals with a BMI>27.5kg/m² are offered MBS.
Appropriately selected children and adolescents should be considered for MBS.

NEEDS AND CHALLENGES

Bariatric surgery should be viewed as a process of care that begins with a careful initial clinical evaluation and detailed patient education, continuing beyond the operative procedure through a permanent follow-up. The increasing number of safe and effective bariatric procedures should be seen as part of a growing number of treatments for obesity which may need to be combined in a stepwise and progressive approach to achieve long-term disease control. Improving care for people with obesity undergoing bariatric surgery is an evolving process as our understanding of the disease itself and its implications for people living with obesity deepens. Future areas which remain to be improved include

A better understanding of the mechanisms of action of each procedure is required to enable optimum surgery and follow up.
Accurate and comprehensive data management. Bariatric surgical procedures should be incorporated into national clinical registries to enable objective assessment of the risks and benefits across the community.
More randomized controlled trials to improve our understanding of the long-term outcomes of different procedures and their implications for control of obesity related co-morbidity
Improved evidence-based decision-making pathways to help determine who would benefit most from bariatric surgery.
High quality clinical trials looking at the use of multimodal care, combining bariatric surgery with pharmacotherapy to improve long-term disease remission and control.
Definition of safe and efficient pathways for assessment, surgery. and post-surgery care.
Greater focus on understanding the implications of obesity stigma, how it affects patient care and what clinicians can do to address these inequalities.

Bariatric surgery has the potential to be one of the most important and powerful treatment approaches in medicine. High quality clinical care, good science, and comprehensive data management will allow optimal application of this approach to be realized.

REFERENCES

Eisenberg D, Shikora SA, Aarts E, Aminian A, Angrisani L, Cohen RV, et al. 2022 American Society of Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) Indications for Metabolic and Bariatric Surgery. Obes Surg. 2023;33(1):3-14.
Lean MEJ, Leslie WS, Barnes AC, Brosnahan N, Thom G, McCombie L, et al. Durability of a primary care-led weight-management intervention for remission of type 2 diabetes: 2-year results of the DiRECT open-label, cluster-randomised trial. Lancet Diabetes Endocrinol. 2019;7(5):344-55.
Sjöström L, Narbro K, Sjöström CD, Karason K, Larsson B, Wedel H, et al. Effects of bariatric surgery on mortality in Swedish obese subjects. N Engl J Med. 2007;357(8):741-52.
Pournaras DJ, Aasheim ET, Bueter M, Ahmed AR, Welbourn R, Olbers T, et al. Effect of bypassing the proximal gut on gut hormones involved with glycemic control and weight loss. Surg Obes Relat Dis. 2012;8(4):371-4.
Pournaras DJ, le Roux CW. Obesity, gut hormones, and bariatric surgery. World J Surg. 2009;33(10):1983-8.
Carlsson LMS, Sjöholm K, Jacobson P, Andersson-Assarsson JC, Svensson PA, Taube M, et al. Life Expectancy after Bariatric Surgery in the Swedish Obese Subjects Study. N Engl J Med. 2020;383(16):1535-43.
Mingrone G, Panunzi S, De Gaetano A, Guidone C, Iaconelli A, Capristo E, et al. Metabolic surgery versus conventional medical therapy in patients with type 2 diabetes: 10-year follow-up of an open-label, single-centre, randomised controlled trial. Lancet. 2021;397(10271):293-304.
Schauer PR, Bhatt DL, Kirwan JP, Wolski K, Aminian A, Brethauer SA, et al. Bariatric Surgery versus Intensive Medical Therapy for Diabetes - 5-Year Outcomes. N Engl J Med. 2017;376(7):641-51.
Kashyap SR, Bhatt DL, Wolski K, Watanabe RM, Abdul-Ghani M, Abood B, et al. Metabolic effects of bariatric surgery in patients with moderate obesity and type 2 diabetes: analysis of a randomized control trial comparing surgery with intensive medical treatment. Diabetes Care. 2013;36(8):2175-82.
Ding SA, Simonson DC, Wewalka M, Halperin F, Foster K, Goebel-Fabbri A, et al. Adjustable Gastric Band Surgery or Medical Management in Patients With Type 2 Diabetes: A Randomized Clinical Trial. J Clin Endocrinol Metab. 2015;100(7):2546-56.
Halperin F, Ding SA, Simonson DC, Panosian J, Goebel-Fabbri A, Wewalka M, et al. Roux-en-Y gastric bypass surgery or lifestyle with intensive medical management in patients with type 2 diabetes: feasibility and 1-year results of a randomized clinical trial. JAMA Surg. 2014;149(7):716-26.
Ikramuddin S, Billington CJ, Lee WJ, Bantle JP, Thomas AJ, Connett JE, et al. Roux-en-Y gastric bypass for diabetes (the Diabetes Surgery Study): 2-year outcomes of a 5-year, randomised, controlled trial. The lancet Diabetes & endocrinology. 2015;3(6):413-22.
Courcoulas AP, Goodpaster BH, Eagleton JK, Belle SH, Kalarchian MA, Lang W, et al. Surgical vs medical treatments for type 2 diabetes mellitus: a randomized clinical trial. JAMA surgery. 2014;149(7):707-15.
Simonson DC, Halperin F, Foster K, Vernon A, Goldfine AB. Clinical and Patient-Centered Outcomes in Obese Patients With Type 2 Diabetes 3 Years After Randomization to Roux-en-Y Gastric Bypass Surgery Versus Intensive Lifestyle Management: The SLIMM-T2D Study. Diabetes Care. 2018;41(4):670-9.
Cummings DE, Arterburn DE, Westbrook EO, Kuzma JN, Stewart SD, Chan CP, et al. Gastric bypass surgery vs intensive lifestyle and medical intervention for type 2 diabetes: the CROSSROADS randomised controlled trial. Diabetologia. 2016;59(5):945-53.
Wentworth JM, Playfair J, Laurie C, Ritchie ME, Brown WA, Burton P, et al. Multidisciplinary diabetes care with and without bariatric surgery in overweight people: a randomised controlled trial. Lancet Diabetes Endocrinol. 2014;2(7):545-52.
Dixon JB, O'Brien PE, Playfair J, Chapman L, Schachter LM, Skinner S, et al. Adjustable gastric banding and conventional therapy for type 2 diabetes: a randomized controlled trial. JAMA. 2008;299(3):316-23.
Liang Z, Wu Q, Chen B, Yu P, Zhao H, Ouyang X. Effect of laparoscopic Roux-en-Y gastric bypass surgery on type 2 diabetes mellitus with hypertension: a randomized controlled trial. Diabetes Res Clin Pract. 2013;101(1):50-6.
Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med. 2008;359(15):1577-89.
Kremen A, Linner JH, Nelson CH. An experimental evaluation of the nutritional importance of proximal and distal small intestine. Annals of Surgery. 1954;140:439-44.
Jorizzo JL, Apisarnthanarax P, Subrt P, Hebert AA, Henry JC, Raimer SS, et al. Bowel-bypass syndrome without bowel bypass. Bowel-associated dermatosis-arthritis syndrome. Archives of Internal Medicine. 1983;143(3):457-61.
O'Leary JP. Hepatic complications of jejunoileal bypass. Seminars in Liver Disease. 1983;3(3):203-15.
Corrodi P. Jejunoileal bypass: change in the flora of the small intestine and its clinical impact. Reviews of Infectious Diseases. 1984;6 (Suppl 1):S80-4.
Parfitt AM, Podenphant J, Villanueva AR, Frame B. Metabolic bone disease with and without osteomalacia after intestinal bypass surgery: a bone histomorphometric study. Bone. 1985;6(4):211-20.
DeWind LT, Payne JH. Intestinal bypass surgery for morbid obesity. Long-term results. Journal of the American Medical Association. 1976;236(20):2298-301.
Mason EE, Ito C. Gastric bypass in obesity. Surgical Clinics of North America. 1967;47(6):1345-51.
Printen KJ, Mason EE. Gastric surgery for relief of morbid obesity. Archices of Surgery. 1973;106(4):428-31.
Mason EE. Vertical banded gastroplasty for obesity. Archices of Surgery. 1982;117(5):701-6.
Hall JC, Watts JM, O'Brien PE, Dunstan RE, Walsh JF, Slavotinek AH, et al. Gastric surgery for morbid obesity. The Adelaide Study. Annals of Surgery. 1990;211(4):419-27.
Pories WJ, Flickinger EG, Meelheim D, Van Rij AM, Thomas FT. The effectiveness of gastric bypass over gastric partition in morbid obesity: consequence of distal gastric and duodenal exclusion. Annals of Surgery. 1982;196(4):389-99.
Sugerman HJ, Starkey JV, Birkenhauer R. A randomized prospective trial of gastric bypass versus vertical banded gastroplasty for morbid obesity and their effects on sweets versus non- sweets eaters. Annals of Surgery. 1987;205(6):613-24.
Sugerman HJ, Londrey GL, Kellum JM, Wolf L, Liszka T, Engle KM, et al. Weight loss with vertical banded gastroplasty and Roux-Y gastric bypass for morbid obesity with selective versus random assignment. American Journal of Surgery. 1989;157(1):93-102.
Scopinaro N, Gianetta E, Civalleri D, Bonalumi U, Bachi V. Bilio-pancreatic bypass for obesity: II. Initial experience in man. British Journal of Surgery. 1979;66(9):618-20.
Scopinaro N, Gianetta E, Adami GF, Friedman D, Traverso E, Marinari GM, et al. Biliopancreatic diversion for obesity at eighteen years. Surgery. 1996;119(3):261-8.
Marceau P, Biron S, Bourque RA, Potvin M, Hould FS, Simard S. Biliopancreatic diversion with a new type of gastrectomy. Obesity Surgery. 1993;3(1):29-35.
Marceau P, Hould FS, Simard S, Lebel S, Bourque RA, Potvin M, et al. Biliopancreatic diversion with duodenal switch. World Journal of Surgery. 1998;22(9):947-54.
Brown WA, Liem R, Al-Sabah S, Anvari M, Boza C, Cohen RV, et al. Metabolic Bariatric Surgery Across the IFSO Chapters: Key Insights on the Baseline Patient Demographics, Procedure Types, and Mortality from the Eighth IFSO Global Registry Report. Obes Surg. 2024;34(5):1764-77.
Bhandari M, Fobi MAL, Buchwald JN, Group: BMSSBW. Standardization of Bariatric Metabolic Procedures: World Consensus Meeting Statement. Obes Surg. 2019;29(Suppl 4):309-45.
Brown WA, Johari Halim Shah Y, Balalis G, Bashir A, Ramos A, Kow L, et al. IFSO Position Statement on the Role of Esophago-Gastro-Duodenal Endoscopy Prior to and after Bariatric and Metabolic Surgery Procedures. Obes Surg. 2020;30(8):3135-53.
Zakeri R, Batterham RL. Potential mechanisms underlying the effect of bariatric surgery on eating behaviour. Curr Opin Endocrinol Diabetes Obes. 2018;25(1):3-11.
Kalinowski P, Paluszkiewicz R, Wróblewski T, Remiszewski P, Grodzicki M, Bartoszewicz Z, et al. Ghrelin, leptin, and glycemic control after sleeve gastrectomy versus Roux-en-Y gastric bypass-results of a randomized clinical trial. Surg Obes Relat Dis. 2017;13(2):181-8.
O'Brien PE, MacDonald L, Anderson M, Brennan L, Brown WA. Long-term outcomes after bariatric surgery: fifteen-year follow-up of adjustable gastric banding and a systematic review of the bariatric surgical literature. Ann Surg. 2013;257(1):87-94.
Himpens J, Cadière GB, Bazi M, Vouche M, Cadière B, Dapri G. Long-term outcomes of laparoscopic adjustable gastric banding. Arch Surg. 2011;146(7):802-7.
Stefanidis A, Forrest N, Brown WA, Dixon JB, O'Brien PB, Juliane Kampe, et al. An investigation of the neural mechanisms underlying the efficacy of the adjustable gastric band. Surg Obes Relat Dis. 2016;12(4):828-38.
Adams TD, Davidson LE, Litwin SE, Kim J, Kolotkin RL, Nanjee MN, et al. Weight and Metabolic Outcomes 12 Years after Gastric Bypass. N Engl J Med. 2017;377(12):1143-55.
Biter LU, 't Hart JW, Noordman BJ, Smulders JF, Nienhuijs S, Dunkelgrün M, et al. Long-term effect of sleeve gastrectomy vs Roux-en-Y gastric bypass in people living with severe obesity: a phase III multicentre randomised controlled trial (SleeveBypass). Lancet Reg Health Eur. 2024;38:100836.
Stenberg E, Szabo E, Ågren G, Ottosson J, Marsk R, Lönroth H, et al. Closure of mesenteric defects in laparoscopic gastric bypass: a multicentre, randomised, parallel, open-label trial. Lancet. 2016;387(10026):1397-404.
Robert M, Espalieu P, Pelascini E, Caiazzo R, Sterkers A, Khamphommala L, et al. Efficacy and safety of one anastomosis gastric bypass versus Roux-en-Y gastric bypass for obesity (YOMEGA): a multicentre, randomised, open-label, non-inferiority trial. Lancet. 2019;393(10178):1299-309.
Mahawar KK, Parmar C, Graham Y. One anastomosis gastric bypass: key technical features, and prevention and management of procedure-specific complications. Minerva Chir. 2019;74(2):126-36.
Bolckmans R, Himpens J. Long-term (>10 Yrs) Outcome of the Laparoscopic Biliopancreatic Diversion With Duodenal Switch. Ann Surg. 2016;264(6):1029-37.
Sánchez-Pernaute A, Rubio Herrera MA, Pérez-Aguirre E, García Pérez JC, Cabrerizo L, Díez Valladares L, et al. Proximal duodenal-ileal end-to-side bypass with sleeve gastrectomy: proposed technique. Obes Surg. 2007;17(12):1614-8.
Torres A, Rubio MA, Ramos-Leví AM, Sánchez-Pernaute A. Cardiovascular Risk Factors After Single Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy (SADI-S): a New Effective Therapeutic Approach? Curr Atheroscler Rep. 2017;19(12):58.
Surve A, Cottam D, Medlin W, Richards C, Belnap L, Horsley B, et al. Long-term outcomes of primary single-anastomosis duodeno-ileal bypass with sleeve gastrectomy (SADI-S). Surg Obes Relat Dis. 2020;16(11):1638-46.
Sánchez-Pernaute A, Herrera MA, Pérez-Aguirre ME, Talavera P, Cabrerizo L, Matía P, et al. Single anastomosis duodeno-ileal bypass with sleeve gastrectomy (SADI-S). One to three-year follow-up. Obes Surg. 2010;20(12):1720-6.
Dijkhorst PJ, Boerboom AB, Janssen IMC, Swank DJ, Wiezer RMJ, Hazebroek EJ, et al. Failed Sleeve Gastrectomy: Single Anastomosis Duodenoileal Bypass or Roux-en-Y Gastric Bypass? A Multicenter Cohort Study. Obes Surg. 2018;28(12):3834-42.
Ryder REJ, Yadagiri M, Burbridge W, Irwin SP, Gandhi H, Bashir T, et al. Duodenal-jejunal bypass liner for the treatment of type 2 diabetes and obesity: 3-year outcomes in the First National Health Service (NHS) EndoBarrier Service. Diabet Med. 2022;39(7):e14827.
Pournaras DJ, le Roux CW. Are bile acids the new gut hormones? Lessons from weight loss surgery models. Endocrinology. 2013;154(7):2255-6.
Karamanakos SN, Vagenas K, Kalfarentzos F, Alexandrides TK. Weight loss, appetite suppression, and changes in fasting and postprandial ghrelin and peptide-YY levels after Roux-en-Y gastric bypass and sleeve gastrectomy: a prospective, double blind study. Ann Surg. 2008;247(3):401-7.
Krashes MJ, Koda S, Ye C, Rogan SC, Adams AC, Cusher DS, et al. Rapid, reversible activation of AgRP neurons drives feeding behavior in mice. J Clin Invest. 2011;121(4):1424-8.
Sohn JW. Network of hypothalamic neurons that control appetite. BMB Rep. 2015;48(4):229-33.
Farooqi IS, Keogh JM, Yeo GS, Lank EJ, Cheetham T, O'Rahilly S. Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med. 2003;348(12):1085-95.
Sahu A. Leptin signaling in the hypothalamus: emphasis on energy homeostasis and leptin resistance. Front Neuroendocrinol. 2003;24(4):225-53.
Flier JS. Clinical review 94: What's in a name? In search of leptin's physiologic role. J Clin Endocrinol Metab. 1998;83(5):1407-13.
Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR, et al. Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med. 1996;334(5):292-5.
Blüher S, Mantzoros CS. Leptin in humans: lessons from translational research. Am J Clin Nutr. 2009;89(3):991S-7S.
Nakazato M, Murakami N, Date Y, Kojima M, Matsuo H, Kangawa K, et al. A role for ghrelin in the central regulation of feeding. Nature. 2001;409(6817):194-8.
le Roux CW, Neary NM, Halsey TJ, Small CJ, Martinez-Isla AM, Ghatei MA, et al. Ghrelin does not stimulate food intake in patients with surgical procedures involving vagotomy. J Clin Endocrinol Metab. 2005;90(8):4521-4.
Tong J, Prigeon RL, Davis HW, Bidlingmaier M, Kahn SE, Cummings DE, et al. Ghrelin suppresses glucose-stimulated insulin secretion and deteriorates glucose tolerance in healthy humans. Diabetes. 2010;59(9):2145-51.
Cummings DE, Weigle DS, Frayo RS, Breen PA, Ma MK, Dellinger EP, et al. Plasma ghrelin levels after diet-induced weight loss or gastric bypass surgery. N Engl J Med. 2002;346(21):1623-30.
le Roux CW, Patterson M, Vincent RP, Hunt C, Ghatei MA, Bloom SR. Postprandial plasma ghrelin is suppressed proportional to meal calorie content in normal-weight but not obese subjects. J Clin Endocrinol Metab. 2005;90(2):1068-71.
Baggio LL, Drucker DJ. Biology of incretins: GLP-1 and GIP. Gastroenterology. 2007;132(6):2131-57.
Deane AM, Nguyen NQ, Stevens JE, Fraser RJ, Holloway RH, Besanko LK, et al. Endogenous glucagon-like peptide-1 slows gastric emptying in healthy subjects, attenuating postprandial glycemia. J Clin Endocrinol Metab. 2010;95(1):215-21.
Rocca AS, Brubaker PL. Role of the vagus nerve in mediating proximal nutrient-induced glucagon-like peptide-1 secretion. Endocrinology. 1999;140(4):1687-94.
Holz GG, Kühtreiber WM, Habener JF. Pancreatic beta-cells are rendered glucose-competent by the insulinotropic hormone glucagon-like peptide-1(7-37). Nature. 1993;361(6410):362-5.
Vilsbøll T. The effects of glucagon-like peptide-1 on the beta cell. Diabetes Obes Metab. 2009;11 Suppl 3:11-8.
Ørgaard A, Holst JJ. The role of somatostatin in GLP-1-induced inhibition of glucagon secretion in mice. Diabetologia. 2017;60(9):1731-9.
Tang-Christensen M, Vrang N, Larsen PJ. Glucagon-like peptide containing pathways in the regulation of feeding behaviour. Int J Obes Relat Metab Disord. 2001;25 Suppl 5:S42-7.
Batterham RL, Cowley MA, Small CJ, Herzog H, Cohen MA, Dakin CL, et al. Gut hormone PYY(3-36) physiologically inhibits food intake. Nature. 2002;418(6898):650-4.
Abbott CR, Monteiro M, Small CJ, Sajedi A, Smith KL, Parkinson JR, et al. The inhibitory effects of peripheral administration of peptide YY(3-36) and glucagon-like peptide-1 on food intake are attenuated by ablation of the vagal-brainstem-hypothalamic pathway. Brain Res. 2005;1044(1):127-31.
Sloth B, Holst JJ, Flint A, Gregersen NT, Astrup A. Effects of PYY1-36 and PYY3-36 on appetite, energy intake, energy expenditure, glucose and fat metabolism in obese and lean subjects. Am J Physiol Endocrinol Metab. 2007;292(4):E1062-8.
Guo Y, Ma L, Enriori PJ, Koska J, Franks PW, Brookshire T, et al. Physiological evidence for the involvement of peptide YY in the regulation of energy homeostasis in humans. Obesity (Silver Spring). 2006;14(9):1562-70.
le Roux CW, Batterham RL, Aylwin SJ, Patterson M, Borg CM, Wynne KJ, et al. Attenuated peptide YY release in obese subjects is associated with reduced satiety. Endocrinology. 2006;147(1):3-8.
Batterham RL, Cohen MA, Ellis SM, Le Roux CW, Withers DJ, Frost GS, et al. Inhibition of food intake in obese subjects by peptide YY3-36. N Engl J Med. 2003;349(10):941-8.
Claudel T, Staels B, Kuipers F. The Farnesoid X receptor: a molecular link between bile acid and lipid and glucose metabolism. Arterioscler Thromb Vasc Biol. 2005;25(10):2020-30.
Ryan KK, Tremaroli V, Clemmensen C, Kovatcheva-Datchary P, Myronovych A, Karns R, et al. FXR is a molecular target for the effects of vertical sleeve gastrectomy. Nature. 2014;509(7499):183-8.
Bozadjieva N, Heppner KM, Seeley RJ. Targeting FXR and FGF19 to Treat Metabolic Diseases-Lessons Learned From Bariatric Surgery. Diabetes. 2018;67(9):1720-8.
Alam M, Bhanderi S, Matthews JH, McNulty D, Pagano D, Small P, et al. Mortality related to primary bariatric surgery in England. BJS Open. 2017;1(4):122-7.
Böckelman C, Hahl T, Victorzon M. Mortality Following Bariatric Surgery Compared to Other Common Operations in Finland During a 5-Year Period (2009-2013). A Nationwide Registry Study. Obes Surg. 2017;27(9):2444-51.
Chang SH, Freeman NLB, Lee JA, Stoll CRT, Calhoun AJ, Eagon JC, et al. Early major complications after bariatric surgery in the USA, 2003-2014: a systematic review and meta-analysis. Obes Rev. 2018;19(4):529-37.
Heneghan HM, Meron-Eldar S, Yenumula P, Rogula T, Brethauer SA, Schauer PR. Incidence and management of bleeding complications after gastric bypass surgery in the morbidly obese. Surg Obes Relat Dis. 2012;8(6):729-35.
Gagner M, Kemmeter P. Comparison of laparoscopic sleeve gastrectomy leak rates in five staple-line reinforcement options: a systematic review. Surg Endosc. 2020;34(1):396-407.
Jacobsen HJ, Nergard BJ, Leifsson BG, Frederiksen SG, Agajahni E, Ekelund M, et al. Management of suspected anastomotic leak after bariatric laparoscopic Roux-en-y gastric bypass. Br J Surg. 2014;101(4):417-23.
Robertson AGN, Wiggins T, Robertson FP, Huppler L, Doleman B, Harrison EM, et al. Perioperative mortality in bariatric surgery: meta-analysis. Br J Surg. 2021;108(8):892-7.
Kermansaravi M, Kassir R, Valizadeh R, Parmar C, Davarpanah Jazi AH, Shahmiri SS, et al. Management of leaks following one-anastomosis gastric bypass: an updated systematic review and meta-analysis of 44 318 patients. Int J Surg. 2023;109(5):1497-508.
Kim TY, Kim S, Schafer AL, Medical Management of the Postoperative Bariatric Surgery Patient.In Feingold KR, Anawalt B, Blackman MR, Boyce A, Chrousos G, Corpas E, et al. Endotext. 2020.
Ekelund M. Systematic review and meta-analysis of internal herniation after gastric bypass surgery (Br J Surg 2015; 102: 451-460). Br J Surg. 2015;102(5):460-1.
Farukhi MA, Mattingly MS, Clapp B, Tyroch AH. CT Scan Reliability in Detecting Internal Hernia after Gastric Bypass. JSLS. 2017;21(4).
Gormsen J, Burcharth J, Gögenur I, Helgstrand F. Prevalence and Risk Factors for Chronic Abdominal Pain After Roux-en-Y Gastric Bypass Surgery: A Cohort Study. Ann Surg. 2021;273(2):306-14.
Høgestøl IK, Chahal-Kummen M, Eribe I, Brunborg C, Stubhaug A, Hewitt S, et al. Chronic Abdominal Pain and Symptoms 5 Years After Gastric Bypass for Morbid Obesity. Obes Surg. 2017;27(6):1438-45.
DuPree CE, Blair K, Steele SR, Martin MJ. Laparoscopic sleeve gastrectomy in patients with preexisting gastroesophageal reflux disease : a national analysis. JAMA Surg. 2014;149(4):328-34.
Peterli R, Wölnerhanssen BK, Peters T, Vetter D, Kröll D, Borbély Y, et al. Effect of Laparoscopic Sleeve Gastrectomy vs Laparoscopic Roux-en-Y Gastric Bypass on Weight Loss in Patients With Morbid Obesity: The SM-BOSS Randomized Clinical Trial. JAMA. 2018;319(3):255-65.
Parmar CD, Mahawar KK, Boyle M, Schroeder N, Balupuri S, Small PK. Conversion of Sleeve Gastrectomy to Roux-en-Y Gastric Bypass is Effective for Gastro-Oesophageal Reflux Disease but not for Further Weight Loss. Obes Surg. 2017;27(7):1651-8.
Robert M, Poghosyan T, Maucort-Boulch D, Filippello A, Caiazzo R, Sterkers A, et al. Efficacy and safety of one anastomosis gastric bypass versus Roux-en-Y gastric bypass at 5 years (YOMEGA): a prospective, open-label, non-inferiority, randomised extension study. Lancet Diabetes Endocrinol. 2024;12(4):267-76.
Saarinen T, Pietiläinen KH, Loimaala A, Ihalainen T, Sammalkorpi H, Penttilä A, et al. Bile Reflux is a Common Finding in the Gastric Pouch After One Anastomosis Gastric Bypass. Obes Surg. 2020;30(3):875-81.
Salminen P, Helmiö M, Ovaska J, Juuti A, Leivonen M, Peromaa-Haavisto P, et al. Effect of Laparoscopic Sleeve Gastrectomy vs Laparoscopic Roux-en-Y Gastric Bypass on Weight Loss at 5 Years Among Patients With Morbid Obesity: The SLEEVEPASS Randomized Clinical Trial. JAMA. 2018;319(3):241-54.
Wölnerhanssen BK, Peterli R, Hurme S, Bueter M, Helmiö M, Juuti A, et al. Laparoscopic Roux-en-Y gastric bypass versus laparoscopic sleeve gastrectomy: 5-year outcomes of merged data from two randomized clinical trials (SLEEVEPASS and SM-BOSS). Br J Surg. 2021;108(1):49-57.
Group B-B-SC. Roux-en-Y gastric bypass, gastric banding, or sleeve gastrectomy for severe obesity: Baseline data from the By-Band-Sleeve randomized controlled trial. Obesity (Silver Spring). 2023;31(5):1290-9.
Hedberg S, Olbers T, Peltonen M, Österberg J, Wirén M, Ottosson J, et al. BEST: Bypass equipoise sleeve trial; rationale and design of a randomized, registry-based, multicenter trial comparing Roux-en-Y gastric bypass with sleeve gastrectomy. Contemp Clin Trials. 2019;84:105809.
Maciejewski ML, Arterburn DE, Van Scoyoc L, Smith VA, Yancy WS, Weidenbacher HJ, et al. Bariatric Surgery and Long-term Durability of Weight Loss. JAMA Surg. 2016;151(11):1046-55.
Salminen P, Grönroos S, Helmiö M, Hurme S, Juuti A, Juusela R, et al. Effect of Laparoscopic Sleeve Gastrectomy vs Roux-en-Y Gastric Bypass on Weight Loss, Comorbidities, and Reflux at 10 Years in Adult Patients With Obesity: The SLEEVEPASS Randomized Clinical Trial. JAMA Surg. 2022;157(8):656-66.
Carandina S, Soprani A, Zulian V, Cady J. Long-Term Results of One Anastomosis Gastric Bypass: a Single Center Experience with a Minimum Follow-Up of 10 Years. Obes Surg. 2021;31(8):3468-75.
Pories WJ, Swanson MS, MacDonald KG, Long SB, Morris PG, Brown BM, et al. Who would have thought it? An operation proves to be the most effective therapy for adult-onset diabetes mellitus. Ann Surg. 1995;222(3):339-50; discussion 50-2.
Rubino F, Nathan DM, Eckel RH, Schauer PR, Alberti KG, Zimmet PZ, et al. Metabolic Surgery in the Treatment Algorithm for Type 2 Diabetes: A Joint Statement by International Diabetes Organizations. Diabetes Care. 2016;39(6):861-77.
Courcoulas AP, Patti ME, Hu B, Arterburn DE, Simonson DC, Gourash WF, et al. Long-Term Outcomes of Medical Management vs Bariatric Surgery in Type 2 Diabetes. JAMA. 2024;331(8):654-64.
Dixon JB, O'Brien PE, Playfair J, Chapman L, Schachter LM, Skinner S, et al. Adjustable gastric banding and conventional therapy for Type 2 Diabetes: A randomized controlled trial. Journal of the American Medical Association. 2008;299(3):316-23.
Mingrone G, Panunzi S, De Gaetano A, Guidone C, Iaconelli A, Nanni G, et al. Bariatric-metabolic surgery versus conventional medical treatment in obese patients with type 2 diabetes: 5 year follow-up of an open-label, single-centre, randomised controlled trial. Lancet. 2015;386(9997):964-73.
Kirwan JP, Courcoulas AP, Cummings DE, Goldfine AB, Kashyap SR, Simonson DC, et al. Diabetes Remission in the Alliance of Randomized Trials of Medicine Versus Metabolic Surgery in Type 2 Diabetes (ARMMS-T2D). Diabetes Care. 2022;45(7):1574-83.
Ikramuddin S, Korner J, Lee WJ, Connett JE, Inabnet WB, Billington CJ, et al. Roux-en-Y gastric bypass vs intensive medical management for the control of type 2 diabetes, hypertension, and hyperlipidemia: the Diabetes Surgery Study randomized clinical trial. JAMA. 2013;309(21):2240-9.
Schauer PR, Bhatt DL, Kirwan JP, Wolski K, Brethauer SA, Navaneethan SD, et al. Bariatric surgery versus intensive medical therapy for diabetes--3-year outcomes. N Engl J Med. 2014;370(21):2002-13.
Sjostrom L, Peltonen M, Jacobson P, Ahlin S, Andersson-Assarsson J, Anveden A, et al. Association of Bariatric Surgery With Long-term Remission of Type 2 Diabetes and With Microvascular and Macrovascular Complications. JAMA. 2014;311(22):2297-304.
Sjöström L, Gummesson A, Sjöström CD, Narbro K, Peltonen M, Wedel H, et al. Effects of bariatric surgery on cancer incidence in obese patients in Sweden (Swedish Obese Subjects Study): a prospective, controlled intervention trial. Lancet Oncol. 2009;10(7):653-62.
Aminian A, Wilson R, Al-Kurd A, Tu C, Milinovich A, Kroh M, et al. Association of Bariatric Surgery With Cancer Risk and Mortality in Adults With Obesity. JAMA. 2022;327(24):2423-33.
Clapp B, Portela R, Sharma I, Nakanishi H, Marrero K, Schauer P, et al. Risk of non-hormonal cancer after bariatric surgery: meta-analysis of retrospective observational studies. Br J Surg. 2022;110(1):24-33.
Aminian A, Zajichek A, Arterburn DE, Wolski KE, Brethauer SA, Schauer PR, et al. Association of Metabolic Surgery With Major Adverse Cardiovascular Outcomes in Patients With Type 2 Diabetes and Obesity. JAMA. 2019.
Lazo M, Clark JM. The epidemiology of nonalcoholic fatty liver disease: a global perspective. Semin Liver Dis. 2008;28(4):339-50.
Caldwell S, Argo C. The natural history of non-alcoholic fatty liver disease. Dig Dis. 2010;28(1):162-8.
Bzowej NH. Nonalcoholic steatohepatitis: the new frontier for liver transplantation. Curr Opin Organ Transplant. 2018;23(2):169-74.
Fakhry TK, Mhaskar R, Schwitalla T, Muradova E, Gonzalvo JP, Murr MM. Bariatric surgery improves nonalcoholic fatty liver disease: a contemporary systematic review and meta-analysis. Surg Obes Relat Dis. 2019;15(3):502-11.
Despres J. The insulin resistance-dyslipidemia syndrome: The most prevalent cause of coronary artery disease. Canadian Medical Association Journal. 1993;148(8):1339-40.
Koba S, Hirano T, Sakaue T, Sakai K, Kondo T, Yorozuya M, et al. Role of small dense low-density lipoprotein in coronary artery disease patients with normal plasma cholesterol levels. Journal of Cardiology. 2000;36(6):371-8.
Busetto L, Pisent C, Rinaldi D, Longhin PL, Segato G, De Marchi F, et al. Variation in lipid levels in morbidly obese patients operated with the LAP-BAND adjustable gastric banding system: effects of different levels of weight loss. Obesity Surgery. 2000;10(6):569-77.
Bacci V, Basso MS, Greco F, Lamberti R, Elmore U, Restuccia A, et al. Modifications of metabolic and cardiovascular risk factors after weight loss induced by laparoscopic gastric banding. Obesity Surgery. 2002;12(1):77-82.
Dixon J, O'Brien P. Ovarian dysfunction, androgen excess and neck circumference in obese women: Changes with weight loss (abstract). Obesity Surgery. 2002;12(2):193.
Brolin RE, Bradley LJ, Wilson AC, Cody RP. Lipid risk profile and weight stability after gastric restrictive operations for morbid obesity. Journal of Gastrointestinal Surgery. 2000;4(5):464-9.
Carbajo MA, Fong-Hirales A, Luque-de-León E, Molina-Lopez JF, Ortiz-de-Solórzano J. Weight loss and improvement of lipid profiles in morbidly obese patients after laparoscopic one-anastomosis gastric bypass: 2-year follow-up. Surg Endosc. 2017;31(1):416-21.
Sjostrom CD, Lissner L, Wedel H, Sjostrom L. Reduction in incidence of diabetes, hypertension and lipid disturbances after intentional weight loss induced by bariatric surgery: the SOS Intervention Study. Obesity Research. 1999;7(5):477-84.
Schiavon CA, Cavalcanti AB, Oliveira JD, Machado RHV, Santucci EV, Santos RN, et al. Randomized Trial of Effect of Bariatric Surgery on Blood Pressure After 5 Years. J Am Coll Cardiol. 2024;83(6):637-48.
Beuther DA, Sutherland ER. Overweight, obesity, and incident asthma: a meta-analysis of prospective epidemiologic studies. American Journal of Respiratory and Critical Care Medicine. 2007;175(7):661-6.
Young SY, Gunzenhauser JD, Malone KE, McTiernan A. Body mass index and asthma in the military population of the northwestern United States. Archives of Internal Medicine. 2001;161(13):1605-11.
Camargo C, Weiss S, Zhang S, Willett W, Speizer F. Prospective study of body mass index, weight change, and risk of adult-onset asthma in women. Arch Intern Med. 1999;159(Nov):2582-88.
Diaz J, Farzan S. Clinical implications of the obese-asthma phenotypes. Immunol Allergy Clin North Am. 2014;34(4):739-51.
Khalooeifard R, Adebayo R, Rahmani J, Clark C, Shadnoush M, Mohammadi Farsani G. Health Effect of Bariatric Surgery on Patients with Asthma: A Systematic Review and Meta-Analysis. Bariatric Surgical Practice and Patient Care. 2021;16(1):2-9.
Peppard PE, Young T, Palta M, Dempsey J, Skatrud J. Longitudinal study of moderate weight change and sleep-disordered breathing. JAMA. 2000;284(23):3015-21.
Camargo CA, Weiss ST, Zhang S, Willett WC, Speizer FE. Prospective study of body mass index, weight change, and risk of adult-onset asthma in women. Arch Intern Med. 1999;159(21):2582-8.
Dixon JB. Elevated homocysteine with weight loss. Obesity Surgery. 2001;11(5):537-8.
Weiner R, Datz M, Wagner D, Bockhorn H. Quality-of-life outcome after laparoscopic adjustable gastric banding for morbid obesity. Obesity Surgery. 1999;9(6):539-45.
Schok M, Geenen R, van Antwerpen T, de Wit P, Brand N, van Ramshorst B. Quality of life after laparoscopic adjustable gastric banding for severe obesity: postoperative and retrospective preoperative evaluations. Obesity Surgery. 2000;10(6):502-8.
Balsiger BM, Kennedy FP, Abu-Lebdeh HS, Collazo-Clavell M, Jensen MD, O'Brien T, et al. Prospective evaluation of Roux-en-Y gastric bypass as primary operation for medically complicated obesity [see comments]. Mayo Clinic Proceedings. 2000;75(7):673-80.
Horchner R, Tuinebreijer MW, Kelder PH. Quality-of-life assessment of morbidly obese patients who have undergone a Lap-Band operation: 2-year follow-up study. Is the MOS SF- 36 a useful instrument to measure quality of life in morbidly obese patients? Obesity Surgery. 2001;11(2):212-8; discussion 9.
O'Brien P, Brown W, Dixon J. Revisional Surgery for Morbid Obesity- Conversion to the Lap-Band System. Obesity Surgery. 2000;10(6):557-63.
Syn NL, Cummings DE, Wang LZ, Lin DJ, Zhao JJ, Loh M, et al. Association of metabolic-bariatric surgery with long-term survival in adults with and without diabetes: a one-stage meta-analysis of matched cohort and prospective controlled studies with 174 772 participants. Lancet. 2021;397(10287):1830-41.
Pournaras DJ, Hardwick RH, le Roux CW. Gastrointestinal surgery for obesity and cancer: 2 sides of the same coin. Surg Obes Relat Dis. 2017;13(4):720-1.
Sudlow A, le Roux CW, Pournaras DJ. Review of multimodal treatment for type 2 diabetes: combining metabolic surgery and pharmacotherapy. Ther Adv Endocrinol Metab. 2019;10:2042018819875407.
NIH conference. Gastrointestinal surgery for severe obesity. Consensus Development Conference Panel. Ann Intern Med. 1991;115(12):956-61.

Normal Physiology of ACTH and GH Release in the Hypothalamus and Anterior Pituitary in Man

ABSTRACT

This chapter summarizes the intimate relationship between the hypothalamus and the anterior pituitary with respect to the secretion of ACTH and GH from the physiological viewpoint. Other chapters in Endotext cover the hormones prolactin, LH, FSH, TSH and the posterior pituitary. Adrenocorticotropic hormone (ACTH) and growth hormone (GH) are both peptide hormones secreted from the anterior pituitary. ACTH is derived from cleavage of the precursor hormone pro-opiomelanocortin (POMC) by prohormone convertase enzymes. Classically, it activates the production and release of cortisol from the zona fasciculata of the adrenal cortex via the melanocortin receptor MC2R. The major hypophysiotropic factor controlling ACTH expression and secretion is corticotropin-releasing hormone (CRH), in conjunction with arginine vasopressin (AVP). Key physiological features of the hypothalamo-pituitary-adrenal (HPA) axis are discussed, including the ultradian pulsatility of CRH, AVP and ACTH secretion, the circadian pattern of secretion, the negative feedback of cortisol on the HPA axis, the stress response, and the effects of aging and gender. GH is secreted mainly by somatotrophs in the anterior pituitary, but it is also expressed in other parts of the brain. Similarly, to ACTH, the release of GH is pulsatile with diurnal variation, under a negative feedback auto-regulatory loop, and can be affected by various factors. Activities that affect secretion of GH include sleep and exercise, and physical stresses such as fasting and hypoglycemia, hyperglycemia, hypovolemic shock, and surgery. GH secretion demonstrates differences between the sexes, with male ‘pulsatile’ secretion versus female ‘continuous’ secretion. In addition, the level of secretion also declines with age, a phenomenon termed the ‘somatopause’. All these are discussed in detail in this chapter.

THE HYPOTHALAMO-PITUITARY INTERFACE

The hypothalamus and pituitary serve as the body’s primary interface between the nervous system and the endocrine system. This interface takes the form of:

Amplification from femto (10^-15) and pico (10^-12)-molar concentrations of hypophysiotropic hormones to nano (10^-9) molar concentrations of pituitary hormones.
Temporal smoothing from ultradian pulsed secretion of hypophysiotropic hormones to circadian rhythms of pituitary hormone secretion (1).

The function of this interface is modified by feedback, usually negative, via the nervous system and via the endocrine system.

REGULATION OF ACTH

Cells of Origin

ACTH is released from corticotrophs in the human pituitary, constituting 15-20% of the cells of the anterior pituitary (see Endotext chapter- Development and Microscopic Anatomy of the Pituitary Gland). They are distributed in the median wedge, anteriorly and laterally, and posteriorly adjacent to the pars nervosa. These cells are characteristically identified from their basophil staining and PAS-positivity due to the high glycoprotein content of the N-terminal glycopeptide of pro-opiomelanocortin (vide infra), as well as ACTH immunopositivity. Scattered ACTH-positive cells are also present in the human homologue of the intermediate lobe. Some of these appear to extend into the posterior pituitary, the so-called “basophilic invasion” (2).

ACTH/POMC

POMC GENE STRUCTURE

ACTH is derived from a 266 amino acid precursor, pro-opiomelanocortin (POMC: Figure 1). POMC is encoded by a single-copy gene on chromosome 2p23.3 over 8 kb (3). It contains a 5′ promoter and three exons. Apart from the hydrophobic signal peptide and 18 amino acids of the N-terminal glycopeptide, the rest of POMC is encoded by the 833 bp exon 3.

Figure 1. POMC and its derivatives.

POMC PROMOTER

The promoter of POMC has most extensively been studied in rodents (4). Common transcription elements such as a TATA box, a CCAAT box, and an AP-1 site are found within the promoter (5,6). Corticotroph and melanotroph-specific transcription of POMC appears to be dependent on a CANNTG element motif synergistically binding corticotroph upstream transcription element-binding (CUTE) proteins (7). These include neurogenic differentiation 1 factor (NeuroD1) (8), pituitary homeobox 1 (Pitx1 or Ptx1) (9), and Tpit (10,11). NeuroD1 is a member of the NeuroD family and forms heterodimers with other basic-helix-loop-helix (bHLH) proteins, activating transcription of genes that contain an E-box, in this case POMC. This highly restricted pattern of expression in the nervous and endocrine systems is important during development. NeuroD1 is expressed in corticotrophs but not melanotrophs, thus indicating that there are some differences between the operations of the transcriptional mechanisms of these two POMC-expressing cell types (8). Tpit is a transcription factor of the T-box family and it plays an important role in late-stage cell determination of corticotrophs and melanotrophs (10). Pitx1 is a homeoprotein belonging to a class of transcription factors that are involved in organogenesis and cell differentiation. Both Tpit and Pitx1 bind to their respective responsive elements and are involved in controlling the late differentiation of POMC gene expression, maintaining a basal level of POMC transcription and participating in hormone-induced POMC expression (12). To summarize the respective roles of the CUTE proteins, Pitx1 confers pituitary specificity in the broadest sense, Tpit confers the POMC lineage identity common to corticotrophs and melanotrophs, whereas NeuroD1 expression confers corticotroph identity (4). However, CUTE proteins are not the only method by which POMC expression is differentiated between corticotrophs and melanotrophs. The Pax7 transcription factor has been shown to be a key determinant of melanotroph identity, and it works by remodeling chromatin prior to Tpit expression, opening key areas of chromatin to allow Tpit and other transcription factors access to enhancers, resulting in melanotroph specification (13).

Ikaros transcription factors, which had previously been characterized as being essential for B and T cell development, have been demonstrated to bind and regulate the POMC gene in mice. Moreover, Ikaros knockout mice demonstrate impaired corticotroph development in their pituitaries, as well as reduced circulating ACTH, MSH, and corticosterone levels (14), suggesting a role in corticotroph development.

POMC transcription is positively regulated by corticotrophin releasing hormone (CRH). CRH acts via its G-protein coupled receptor to activate adenylate cyclase, increase intracellular cAMP and stimulate protein kinase-A (15). Transcription stimulation is mediated by an upstream element (PCRH-RE) binding a novel transcription factor (PCRH-REB) containing protein kinase-A phosphorylation sites (16). CRH also stimulates the transcription of c-Fos, FosB and JunB, as well as binding to the POMC AP-1 site (17). Another secondary messenger pathway that controls POMC expression involves intracellular Ca²⁺ ions (18). Both cAMP and intracellular Ca²⁺ pathways cross-talk with each other(19). These findings further support the importance of cAMP and Ca²⁺ in the intracellular signaling of corticotrophs and melanotrophs. Interestingly, there is a remarkable absence of cAMP-responsive elements (CRE) and Ca²⁺ responsive elements (CaRE) in the promoter region of POMC despite the demonstrated importance of cAMP and Ca²⁺ in the intracellular signaling of corticotrophs and melanotrophs. Other, more indirect strategies have evolved to translate cAMP signals into changes in POMC gene expression involving a CREB/c-Fos/AP-1 signaling cascade activating POMC transcription via an activator protein-1 (AP-1) site in exon 1. Similarly, intracellular Ca²⁺ may signal via the Ca²⁺ binding repressor DREAM (downstream response element-antagonist modulator) and modulation of c-Fos expression (20).

CRH also activates POMC expression through a Nur response element which binds the related orphan nuclear receptors Nur77, Nurr1, and NOR1 (21). The pituitary adenylate cyclase-activating peptide (PACAP) also stimulates cAMP synthesis and POMC transcription, presumably through a common pathway with CRH (22).

The effect of Nuclear transcription factor kappa B (NF-κB) on POMC expression is unclear. Although NF-κB is mostly associated with an activation of gene expression, it has been shown to inhibit POMC gene expression by binding to the promoter region (23). In keeping with this finding, CRH treatment blocks this binding, leading to an increase in POMC expression. On the contrary, it has also been shown that more pertinent high glucose (metabolic stress condition) elevates POMC transcription in AtT-20 cells through, or at least in part, the NF-κB responsive element and AP-1 sites (24).

POMC mRNA transcription in corticotrophs is negatively regulated by glucocorticoids (25), although glucocorticoids increase expression of POMC in the hypothalamus (26). The inhibitory effect of glucocorticoids on corticotroph POMC expression appears, in the rat POMC promoter, to be dependent on a glucocorticoid response element partially overlapping the CCAAT box (27). The element binds the glucocorticoid receptor as a homodimer plus a monomer on the other side of the DNA helix (28). Glucocorticoid regulation of corticotroph POMC transcription is also indirectly mediated via other mechanisms such as down-regulation of c-jun expression and direct protein-protein mediated inhibition of CRH-induced AP-1 binding (29), inhibition of CRH receptor transcription (30), inhibition of CRH/cAMP induced activation of Tpit/Pitx1, inhibition of CRH action via the Nur response element (12), and suppression of NeuroD1 expression which in turn inhibits the positive NeuroD1/E-box interaction in the POMC promoter (31).

There are also some other nuclear receptors and respective ligands that show potential roles in POMC regulation. All-trans retinoic acid (ATRA), a stereoisomeric form of retinoic acid, has been shown to inhibit POMC transactivation and ACTH secretion in murine corticotroph tumor AtT20 cells via inhibition of AP-1 and Nur transcriptional activities (32). Mutations in the retinoic acid receptor-related orphan receptors (ROR) also result in enhanced corticosterone secretion and ACTH response as well as a lack of diurnal variation compared to wild-type mice (33). As for the thyroid hormone and its receptor, there appears to be no reported direct interaction with the POMC promoter, although POMC^-/- animals are known to display primary hyperthyroidism (34). More studies are needed to elucidate the potential roles of different nuclear receptors and ligands in POMC regulation. It is also important to note that most of these studies were conducted using tumor cells or in vitro models, as some of the global knockout models can be lethal or difficult.

Leukemia Inhibitory Factor (LIF), a pro-inflammatory cytokine expressed in corticotrophs, has also been shown to stimulate POMC transcription via activation of the Jak-STAT pathway (35,36). This stimulation is synergistic with CRH. Deletional analysis of the POMC promoter has identified a LIF-responsive region from –407 to –301. A STAT binding site that stimulates POMC transcription and which partly overlaps with the Nur response element has been identified within the POMC promoter (37). This pathway might form an interface between the immune system and regulation of the pituitary-adrenal axis, particularly during chronic inflammation, where pro-inflammatory cytokines such as LIF might stimulate STAT3 expression and therefore POMC transcription (38). Another interface between the immune system and POMC expression involves Toll-like receptor (most likely TLR4) recognition of lipopolysaccharide, which is a component of the bacterial cell wall. This appears to act via activation of c-Fos and AP-1 expression (39).

The POMC promoter sits within a CpG island, defined as the regions in the genome which the G and C content exceed 50%. These genomic regions are important controllers of gene expression as hypermethylation of the cytosine leads to silencing of gene expression via remodeling of the chromatin structure to favor heterochromatinization (40). Hypermethylation of the POMC promoter leads to repression of POMC expression in non-expressing tissues. In contrast, hypomethylation leads to de-repression of the POMC promoter in POMC expressing tissues (e.g. corticotrophs). Notably, a small cell lung carcinoma cell line, which expresses POMC and ACTH, possesses a hypomethylated POMC promoter, suggesting that ectopic ACTH secretion by tumors may be due to hypomethylation at a relatively early stage in carcinogenesis (41).

BIOGENESIS OF ACTH

Prohormone convertase enzymes PC1 and PC2 process POMC at pairs of basic residues (Lys-Lys or Lys-Arg). This generates ACTH, the N-terminal glycopeptide, joining peptide, and beta-lipotropin (beta-LPH) (Figure 1). ACTH can be further processed to generate alpha-melanocyte stimulating hormone (alpha-MSH) and corticotropin-like intermediate lobe peptide (CLIP), whereas beta-LPH can be processed to generate gamma-LPH and beta-endorphin (42). In corticotrophs, POMC is mainly processed to the N-terminal glycopeptide, joining peptide, ACTH, and beta-LPH; smaller amounts of the other peptides are present (43). Other post-translational modifications include glycosylation of the N-terminal glycopeptide (44), C-terminal amidation of N-terminal glycopeptide, joining peptide and alpha-MSH (45,46), and N-terminal acetylation of ACTH, alpha-MSH and beta-endorphin (47,48).

HYPOPHYSIOTROPIC HORMONES AFFECTING ACTH RELEASE

Corticotropin Releasing Hormone (CRH)

This 41 amino acid neuropeptide (49) is derived from a 196-amino acid prohormone (50). CRH is likely to be involved in all the three types of stress responses: behavioral, autonomic and hormonal. CRH immunoreactivity is mainly found in the paraventricular nuclei (PVN) of the hypothalamus, often co-localized with AVP (51). CRH is part of a family of neuropeptides together with the urocortins 1, 2 and 3 (52).

CRH binds to G-protein coupled seven-transmembrane domain receptors (53,54), which are classically coupled to adenylate cyclase via Gs, stimulating cAMP synthesis and PK-A activity. However, it is increasingly clear that CRH receptors also couple to Gi (inhibiting adenylate cyclase) and Gq (stimulating phospholipase C, the processing of phosphatidylinositol 4,5-bisphosphate into inositol trisphosphate and diacylglycerol and intracellular Ca²⁺ release), as well as the recruitment of beta-arrestins which counter-regulate CRH-R function via G-protein decoupling and receptor internalization/desensitization (52).

To date, two CRH receptor genes have been identified in humans. CRH-R1 mediates the action of CRH at corticotrophs by binding to CRH; it also binds urocortin 1. CRH-R1 is most extensively expressed in the CNS. CRH-R2 binds to all three urocortins, while binding CRH at a far lower affinity (52). CRH-R2 is predominantly expressed in the heart and has profound effects on the regulation of the cardiovascular system and blood pressure (55,56).

Besides stimulating POMC transcription and ACTH biogenesis, CRH stimulates the release of ACTH from corticortophs via CRH-R1 leading to a biphasic response with the fast release of a pre-synthesized pool of ACTH, and the slower and sustained release of newly-synthesized ACTH (57). Figure 2 describes the stimulation of ACTH release by CRH (58). It is clear that CRH and CRH-R1 is the ‘main line’ of the HPA axis with major defects in this axis with CRH (59) and CRH-R1 knockout (60). Although urocortin 1 can also activate CRH-R1, urocortin 1 knockout mice appear to have normal HPA axis function, suggesting that urocortin 1 does not have a significant regulatory role on the axis (61). Indeed, knocking out all three urocortins does not have any major effect on basal corticosterone levels (62) although female urocortin 2 knockout mice exhibit a more subtle dysregulation with elevated basal ACTH and corticosterone secretion which is modulated by their estrogen status (63).

Figure 2. Diagram showing the release of ACTH from corticotroph cells. CRH binds to a particular receptor that leads to activation of cAMP. The rise in cAMP inhibits TREK-1, thus leading to the depolarization of the cell and subsequently influx of calcium via VGCC. The rise in intracellular calcium leads to the exocytosis and release of ACTH.

CRH secretion is also regulated by other neurotransmitters and cytokines. These include acetylcholine, norepinephrine/noradrenaline, histamine, serotonin, gamma-aminobutyric acid (GABA), interleukin-1beta, and tumor necrosis factor. All of these factors increase hypothalamic CRH expression, except for GABA which is inhibitory.

Arginine Vasopressin (AVP)

In the anterior pituitary, AVP principally binds to the seven-transmembrane domain V1b receptor, also known as the V3 receptor (64). The receptor is coupled to phospholipase C, phosphatidyl inositol generation, and activation of protein kinase-C (65,66) and not via adenylate cyclase and cAMP (15). AVP stimulates ACTH release weakly by itself, but synergizes with the effects of CRH on ACTH release (67). Downregulation of protein kinase C by phorbol ester treatment abolishes the synergistic effect of AVP on ACTH release by CRH (68). AVP does not stimulate POMC transcription either by itself or in synergism with CRH (69). Between the two neuropeptide effects on ACTH release, CRH is the more dominant effect although there is some residual HPA axis activation in female CRH knockout mice (59).

The association between AVP and ACTH release suggests that measurement of AVP levels might be useful for assessing anterior pituitary function. However, direct measurement of plasma AVP is technically difficult due to its small molecular size and binding to platelets. Copeptin is a 39-amino acid glycosylated peptide which is derived from the C-terminal part of the AVP precursor at an equimolar amount to AVP. It remains stable for several days at room temperature in serum or plasma, and its measurement is reliable and reproducible, making it a biomarker of AVP release (70). The copeptin increment during glucagon stimulation testing correlates well with the ACTH increment in healthy controls, but not in patients with pituitary disease (71). Interestingly, there appears to be a sexual dimorphism in terms of the correlation between copeptin and ACTH/cortisol release under the conditions of insulin tolerance testing, with a positive correlation observed in women but no significant correlation in men, i.e. copeptin cannot be used as a universal marker of HPA axis stimulation (72).

Other Influences on ACTH Release

Glucocorticoids rapidly travel through circulation to inhibit the HPA axis at the level of the hypothalamus (release of CRH) (73-76) and anterior pituitary (release of ACTH) (77,78) when synthesized. There is an inherent short delay in this dynamic relationship between the hypothalamus-pituitary-adrenal system but nevertheless it is one of the main influences on ACTH release.

The mineralocorticoid system has always been closely linked to the glucocorticoid system. The endogenous glucocorticoids bind to the mineralocorticoid receptors with a 10-fold greater affinity than to the glucocorticoid receptors (79-81). The mineralocorticoid receptors have a more restricted expression profile throughout the body, with notably high levels of expression in the kidney and adipose tissue, although it is also expressed in certain parts of the brain (82). Administration of mineralocorticoid antagonists intracerebroventricularly or intrahippocampal infusion have been shown to increase the basal HPA axis activity as well as potentiate the initial rise of ACTH in response to stress (83,84).

Oxytocin and AVP have been co-localized to the PVN and supraoptic nuclei of the hypothalamus (85). Oxytocin controversially inhibits ACTH release in man (86-88) by competing for AVP receptor binding (89), but its more dominant effect seems to be a potentiation of the effects of CRH on ACTH release (90,91).

Vasoactive intestinal peptide (VIP) and its relative, peptide histidine isoleucine (PHI), have been shown to activate ACTH secretion (92). This is most probably mediated indirectly via CRH (93).

Atrial natriuretic peptide (ANP) 1-28 has been localized to the PVN and supraoptic nuclei (94). In healthy males, infusion of ANP 1-28 was reported to attenuate the ACTH release induced by CRH (95,96), but this only occurs under highly specific conditions and is not readily reproducible. In physiological doses, ANP 1-28 does not appear to affect CRH-stimulated ACTH release (97).

Opiates and opioid peptides inhibit ACTH release (98). There does not seem to be a direct action at the pituitary level. It is likely that these act by modifying release of CRH at the hypothalamic level (99). Opiate receptor antagonists such as naloxone or naltrexone cause ACTH release by blocking tonic inhibition by endogenous opioid peptides (100).

The endocannabinoid system has recently appeared as a key player in regulating the baseline tone and stimulated peaks of ACTH release. The seven-transmembrane cannabinoid receptor type 1 (CB1) is found on corticotrophs, and the endocannabinoids anandamide and 2-arachidonoylglycerol can be detected in normal pituitaries (101). Antagonism of CB1 causes a dose-dependent rise in corticosterone levels in mice (102). CB1^-/- knockout mice demonstrate higher corticosterone levels compared to wild-type CB1^+/+ littermates, although the circadian rhythm is preserved. Treatment of the CB1^-/- mice with low-dose dexamethasone did not significantly suppress their corticosterone levels and surprisingly caused a paradoxical rise in ACTH levels when compared to the wild-type, although high-dose dexamethasone suppressed corticosterone and ACTH to the same degree in both CB1^-/- and CB1^+/+ mice. These CB1^-/- mice have: (1) higher CRH mRNA expression in the PVN; (2) lower glucocorticoid receptor mRNA expression in the CA1 hippocampal region, but not in the dentate gyrus or the PVN; (3) significantly higher baseline ACTH secretion from primary pituitary cell cultures as well as augmented ACTH responses to stimulation with CRH or forskolin (103). It has also been known for some time that the administration of the cannabinoid agonist delta-9-tetrahydrocannabinol (THC) for 14 days suppresses the cortisol response to hypoglycemia in normal humans (104). Thus, the endocannabinoids appear to negatively regulate basal and stimulated ACTH release at multiple levels of the hypothalamo-pituitary-adrenal axis.

Catecholamines act centrally via alpha₁-adrenergic receptors to stimulate CRH release. Peripheral catecholamines do not affect ACTH release at the level of the pituitary in humans (105).

Nitric oxide (NO) and carbon monoxide negatively modulate the HPA axis by reducing CRH release, at least in vitro(106,107). Endotoxin administered into isolated rat hypothalamus led to generation of NO and CO, which subsequently led to significant decrease in CRH and vasopressin secretion (107).

GH secretagogues such as ghrelin and the synthetic GH secretagogue hexarelin stimulate ACTH release, probably via stimulating AVP release with a much lesser effect on CRH (108-111). GH-releasing peptide-2 (GHRP-2) has also been shown to cause ACTH release in humans (112,113). GH releasing hormone (GHRH) has been shown to potentiate the ACTH and cortisol response to insulin-induced hypoglycemia, but not to potentiate the ACTH and cortisol response after administration of CRH/AVP (114).

Obestatin, a 23 amino acid amidated peptide, is derived from preproghrelin, which is the same precursor as ghrelin (Figure 3). Obestatin is found to suppress food intake and have opposing metabolic effects to ghrelin when administered intraperitoneally in mice (115). An early study showed that intravenous or intracerebroventricular obestatin had no effects on pituitary hormone release (GH, prolactin, ACTH and TSH) in male rats (116), consistent with the fact that the obestatin receptor GPR39 is not expressed in the pituitary (115,117,118). A study in mice and non-human primates (baboon) again showed no effects of obestatin on prolactin, LH, FSH and TSH expression and release. However, obestatin was shown to stimulate POMC expression and ACTH release in vitro and in vivo, and in this study the authors found GPR39 expression in pituitary tissue and primary pituitary cell cultures, contrary to the above-mentioned studies. This effect was mediated by the adenylyl cyclase and MAPK pathways. The increase in ACTH release was also associated with an increase in pituitary CRH receptor expression. Interestingly, obestatin did not inhibit the stimulatory effect of ghrelin on ACTH release (119). Therefore, the effects of obestatin on pituitary hormone secretions remain controversial.

Figure 3. Schematic diagram showing the synthesis of ghrelin and obestatin from the same precursor, preproghrelin. Preproghrelin is a 117 amino acid precursor encoded at chromosome 3. Cleavage of this protein leads to the production of ghrelin, a 28 amino acid peptide, and obestatin, a 23 amino acid protein. Ghrelin can be present as both des-acyl- and acyl-ghrelin (figure modified from (291)).

Angiotensin II (Ang II) is able to stimulate ACTH release in vitro from pituitary cells (120). Central Ang II is likely to stimulate CRH release via its receptors in the median eminence, as passive immunization with anti-CRH can abolish the effect of Ang II (121). Intracerebroventricular Ang II can stimulate ACTH release in rats (122) and is able to stimulate the synthesis of CRH and POMC mRNA (123). Conversely, blockade of Ang II subtype 1 (AT1) receptors with candesartan is able to decrease the CRH, ACTH, and cortisol response to isolation stress in rats (124,125). There is some controversy as to whether peripheral Ang II can modulate ACTH secretion. It is likely that the ACTH rise seen after Ang II infusion into rats is mediated via circumventricular organ stimulation, as blockade of Ang II effects on the circumventricular organs with simultaneous infusion of saralasin blocks this rise (122).

In vitro studies have shown an inhibitory effect of somatostatin on ACTH release in AtT-20 pituitary cell lines from rats, which is mediated via somatostatin receptor (SSTR) subtypes 2 and 5 (126). This inhibitory effect is dependent on the absence of glucocorticoids in the culture medium, but is more prominent when somatostatin analogues targeting SSTR 5 are used (127,128). In rodents, pasireotide, a somatostatin analogue capable of activating SSTRs 1, 2, 3, and 5, is capable of inhibiting CRH-stimulated ACTH release in contrast to octreotide (selective for SSTRs 2 and 5), which was less efficacious (129). Early in vivo studies in humans showed no effect of somatostatin on basal or CRH-stimulated ACTH release (130), although somatostatin does decrease basal secretion in the context of Addison’s disease (131). It is unlikely, therefore, that somatostatin itself is an inhibitor of ACTH release in normal human physiology. Corticotroph adenomas express the somatostatin receptor (SSTR) subtype 5 (132) and ACTH secretion from cultured corticotroph adenomas is inhibited by pasireotide (133). This is the basis for the use of pasireotide to treat Cushing’s disease (134). Octreotide is clinically ineffective in this context (135), but may be effective if glucocorticoids are lowered.

The role of TRH in ACTH release is in dispute. Although there is evidence that prepro-TRH 178-199 can inhibit both basal and CRH-stimulated ACTH release in AtT-20 cell lines and rat anterior pituitary cells (136,137), other investigators have not been able to confirm this (138). There has also been another study showing that TRH is able to induce ACTH release from AtT-20/NYU-1 cells (139), but no in vivo studies exist to substantiate a physiological role.

Tumor necrosis factor-alpha (TNFalpha) is a macrophage-derived pleiotropic cytokine that has been shown to stimulate plasma ACTH and corticosterone secretion in a dose-dependent manner (140). The primary site of action of TNFalpha effect on the HPA axis is likely to be on hypothalamic CRH-secreting neurons. The effects are abolished with CRH antiserum treatment, thus suggesting that CRH is a major mediator of the HPA axis response to TNFalpha.

Interleukins IL-1, IL-6 and possibly IL-2 appear to stimulate ACTH release (141-143). There seem to be multiple mechanisms for interleukins to stimulate ACTH release, but most of the acute effects of these agents are almost certainly via the hypothalamus (144).

Leukemia Inhibitory Factor is able to stimulate POMC synthesis, as noted above.

Endothelial Growth Factor (EGF) is a pituitary cell growth factor that is previously known to induce production of prolactin (145). Both EGF and its receptor (EGFR) are expressed in normal pituitary tissue (146). More recently, EGF has been found to regulate the transcription of POMC and production of ACTH (147-149). The mechanism behind this is still unclear, although mutations in ubiquitin-specific protease 8 (USP8), a deubiquitinase enzyme with various targets including EGFR, leading to hyperactivation of this enzyme and subsequent increased EGFR deubiquitination and recirculation to the cell surface, enhance the release of ACTH (147,150). A significant percentage of corticotroph adenomas harbor somatic mutations in USP8, and a germline mutation case have also been described and can develop Cushing’s disease (147,150,151). These findings further provide evidence that EGF and EGFR can regulate production of ACTH.

PHYSIOLOGY OF ACTH RELEASE

Pulsatility of ACTH Release

Frequent sampling of ACTH with deconvolution analysis reveals that it is secreted in pulses from the corticotroph with 40 pulses ± 1.5 measured per 24 hours, on analysis of 10-minute sampling data. These pulses temporally correlate with the pulsed secretion of cortisol, allowing for a 15 minute delay in secretion, and correlate in amplitude (152). Pulse concordance has been measured at 47% (ACTH to cortisol) and 60% (cortisol to ACTH) in one study (153), and 90% (ACTH to cortisol) in another (154). Although the pulsatility of ACTH secretion may result from pulsatile CRH release, there is evidence that isolated human pituitaries intrinsically release ACTH in a pulsatile fashion (155). In addition, studies in rats have shown that constant CRH infusion still resulted in oscillations of ACTH and glucocorticoid release (156). However, the pulsatile activities of ACTH and glucocorticoid are entirely dependent on the level, rather than the pattern, of CRH secretion (156).

The pulsatile release of ACTH induces pulses of glucocorticoid secretion. In rats with HPA axis suppression, constant infusion of ACTH did not induce pulsatile glucocorticoid secretion (157). It was shown in vitro using ZF cell lines that constant ACTH treatment led to larger increase in pCREB and steroidogenic gene transcription at the start of treatment but the cells became unresponsive to the stimuli over time (158). The responsiveness of cells to the ACTH treatment could only be maintained with pulsatile ACTH treatment, further supporting the importance of pulsatile release of ACTH physiologically.

Recent developments in automated sampling of blood (159) and tissue interstitial fluid via microdialysis (160) have also uncovered the ultradian rhythms in plasma ACTH which correlate well with plasma and tissue steroid (cortisol and cortisone) concentrations, indicating that the ultradian rhythms in blood ACTH and cortisol/cortisone translate well to tissue exposure to these steroids.

Circadian Rhythm

In parallel with cortisol, ACTH levels vary in an endogenous circadian rhythm, reaching a peak between 06.00-09.00h, declining through the day to a nadir between 23.00h-02.00h, and beginning to rise again at about 02.00-03.00h. An increase in ACTH pulse amplitude rather than frequency is responsible for this rhythm (152). The circadian rhythm in glucocorticoid secretion is a key mechanism for re-entraining behavior in the face of external perturbations such as an abrupt phase shift of light conditions, i.e. a model of ‘jet lag’ (161).

The circadian rhythm is mediated via a master oscillator in the supra-chiasmatic nucleus (SCN). A lesion in the SCN eliminates the glucocorticoid circadian rhythm (162). An autoregulatory negative transcription-translation loop feedback system involving cyclical synthesis of the period proteins Per1-3, Clock/BMAL1, and Cry1/2 acts as the basic molecular oscillator, where the Clock/BMAL1 heterodimer acts to activate the transcription of Per and Cry proteins (the so-called ‘positive limb’). In turn, the Per and Cry proteins complex together, translocate back into the nucleus and inhibit Clock/BMAL1-mediated transcription (the so-called ‘negative limb’). The system is reset by phosphorylation, ubiquitination and proteasomal degradation of the Per/Cry repressor complexes (163,164). Entrainment of the oscillator is achieved by light input from the retina, mediated via the retino-hypothalamic tract. Light-activated transcription of immediate-early genes such as c-fos and JunB (165,166) causes activation of PER1 gene transcription as well as modification of the acetylation pattern of histone tails. The latter are implicated in the control of chromatin structure and accessibility of genes to transcription (167). The impact of a period protein gene deletion on circulating glucocorticoids depends on which side of the clock feedback loop is affected (164). Knockout mice with mutations in the components of positive limb of the oscillator (Clock or BMAL1) suffer from hypocortisolism and lose circadian cyclicity (168,169). The deletion of Per2, which affects the negative limb of the oscillator, also results in hypocortisolism (170). However, Cry1 knockout (also affecting the negative limb) leads to hypercortisolism (171,172).

Is a circadian rhythm in CRH secretion responsible for the ACTH rhythm? Although there is a report of a circadian rhythm in CRH secretion (173), and in situ hybridization studies show that there is a circadian rhythm in CRH expression in the suprachiasmatic nucleus (174), other reports do not confirm this (175). Moreover, the circadian rhythm persists despite a continuous infusion of CRH, suggesting that other factors are responsible for the modulation of ACTH pulses (176). The most likely alternative candidate is AVP: immunocytochemical studies show a circadian rhythm in AVP expression (177) and Clock knockout mice show a loss of the circadian rhythm in AVP RNA expression in the SCN (178). In addition, metyrapone and CRH infusion in normal individuals showed a persistence of the HPA circadian rhythm, thus further supporting the role of AVP in regulating ACTH rhythm (176).

However, rhythmic HPA axis activity is not the be-all and end-all of the circadian rhythm of glucocorticoid release. For example, the adrenal rhythm of cortisol secretion persists after hypophysectomy (179). Indeed, light pulses can induce glucocorticoid secretion independent of ACTH secretion. This HPA axis-independent pathway is mediated by the sympathetic nervous system innervation of the adrenals (180). The adrenal glands also possess an independent circadian oscillator: oscillatory Clock/BMAL1, Per1-3 and Cry1 expression is seen in the outer adrenal cortex (zona glomerulosa and zona fasciculata). This adrenal circadian clock appears to ‘gate’ the response to ACTH, i.e. it defines a time window during which ACTH is most able to stimulate glucocorticoid secretion (181). Exogenous ACTH is capable of phase-dependently resetting glucocorticoid rhythms (182), suggesting that the adrenal circadian clock can be entrained by the ACTH rhythm. This illustrates a general principle of circadian system organization, namely that there is a hierarchical system with the SCN master clock entraining and coordinating peripheral and non-SCN tissue clocks via endocrine and neuronal signals.

Stress

Stress, both physical and psychological, induces the release of ACTH and cortisol, particularly via CRH and AVP (183,184), and increases the turnover of these neurohypophysiotropic factors by increasing the transcription of CRH and AVP (185).

During acute stress, an immediate activation of the autonomic nervous system takes place, followed by a delayed response via the HPA axis-mediated release of glucocorticoids (164). During the initial stage, there is an immediate increase of catecholamines via activation of the sympathetic preganglionic neurons in the spinal cord, which in turn stimulates adrenal medulla production of catecholamines via splanchnic nerve innervation. The catecholamines released will also collectively affect peripheral effector organs where they are translated into the classical fight-or-flight response. The delayed response of stress involves activation of the HPA axis, leading to an increase in glucocorticoid level, which in turn can terminate the effects of the sympathetic response together with the reflex parasympathetic activation. It is important to note that this neurohormonal stress response has an additional endocrine leg in the form of glucagon: together, one of the important effects of this trio is to enhance the release of glucose, amino acids and fatty acids, a coordinated catabolic response to stress (186).

Stress paradigms studied in humans include hypoglycemia during the insulin tolerance test (Figure 4), and venipuncture (187). Elective surgery has also long been used as a paradigm of the stress response in humans (188-190): the magnitude of cortisol rise correlates positively with the severity of surgery (191). Experimentally, other stress paradigms such as hemorrhage, oxidative stress, intraperitoneal hypertonic saline, restraint/immobilization, foot shock, forced swimming, or shaking are used to study the stress responses in animals. Importantly, different stress paradigms can have differential effects on CRH and AVP. In situ hybridization with intronic and exonic probes can be used to study the transcription of heterogenous nuclear RNA (hnRNA), followed by its processing (including splicing, capping and polyadenylation) to messenger RNA (mRNA) within 1-2 hours. CRH and AVP hnRNA levels in rats subjected to restraint show significant increases at 1 and 2 hours after the induction of stress, followed by significant increases in mRNA levels at 4 hours (192). In contrast, intraperitoneal hypertonic saline causes a rapid 8.6-fold increase in CRH hnRNA and mRNA within 15 minutes, returning to basal levels by 1 hour. AVP hnRNA responses are slower, peaking at 11.5-fold increase by 2 hours, followed by a prolonged elevation of AVP mRNA levels from 4 hours onwards (193). As previously noted, serum copeptin can be used as a more stable biomarker of AVP secretion and copeptin increments correlate well with cortisol secretion in a glucagon stimulation test paradigm (71), but exhibit a sexual dimorphism in the context of the insulin tolerance test (72).

Figure 4. Typical response to hypoglycemia (≤2.2 mmol/l) induced by 0.15 U/kg Actrapid i.v. in a normal subject. Peak cortisol is ≥550 nmol/l.

Various stressors are known to stimulate oxytocin release which in turn, at least acutely, appears to potentiate CRH-induced ACTH secretion and therefore cortisol release (90). There are also roles for endogenous nitric oxide (NO) and carbon monoxide (CO) in modulating the ACTH response to stress (194). Neuronal NO synthase co-localizes with AVP and to some extent CRH in paraventricular neurons (195,196). Knockout mice lacking wild-type and neuronal NO synthase have much reduced quantities of POMC immunoreactivity in their arcuate nuclei and pituitaries compared to wild-type mice (195,197). In general, inflammatory stressors appear to activate an endogenous inhibitory pathway, whereby NO and CO attenuate the stimulated secretion of CRH and AVP. These effects can also be seen in terms of circulating AVP. However, the regulation of the pituitary-adrenal axis by other stressors may involve an activating role for these gaseous neurotransmitters. CRH-R2, as noted above, binds the urocortins 1, 2 and 3, and appears to mediate a down-regulatory role in the HPA response to stress: knockout mice exhibit a ‘hypersensitive’ acute ACTH and corticosterone response (198) and a defective recovery from stress with a slower drop in corticosterone (199).

Repetitive stress causes variable effects, enhancement or desensitization, on ACTH responses, depending on the stress paradigm involved. This appears to be positively correlated with changes in AVP binding to V1b receptors, reflecting changes in the number of binding sites and not their affinities. It is at present unclear whether this is due to changes in transcription of the V1b gene, alterations in mRNA stability, translational control or recruitment of receptors from intercellular pools (200). With chronic stress, oxytocin is thought to have a longer term stress-antagonistic function, partially via cortisol-mediated negative feedback on CRH, partially via GABAergic inhibition of CRH neuron function and partially via a direct inhibitory effect of oxytocin on CRH expression (90).

As noted above, circadian rhythms in adrenal ACTH responsiveness, controlled by local oscillator circuits, gate’ the glucocorticoid output in response to a certain level of ACTH. In the case of stress, this leads to markedly different glucocorticoid responses depending on when (during the active or inactive phase) the experimental stress is applied to experimental animals. Moreover, the timing of repetitive stress application can lead to differences in the behavioral and metabolic responses to repetitive/chronic stress. Lastly, it is also known that stress can influence clock function at the level of the SCN and also at the level of the adrenal circadian oscillator leading to phase shifts (164). In humans, stressors such as illness leads to abolition of the diurnal variation of cortisol, which appears to be ACTH independent (201,202). This change in the diurnal regulation of cortisol secretion is linked to regulation of immune responses which is likely to be adaptive in the acute context, but which may be maladaptive with chronic stress (203).

FEEDBACK REGULATION OF THE HPA AXIS

Glucocorticoid feedback occurs at multiple levels: at the pituitary, at the hypothalamus, and most importantly, centrally at the level of the hippocampus, which contains the highest concentration of glucocorticoid receptors in the central nervous system. Multiple effects mediate this feedback (Figure 5), including:

inhibition of CRH and AVP synthesis and release in the PVN (204,205).
inhibition of POMC transcription (as outlined above).
inhibition of ACTH release induced by CRH and AVP (206).

Figure 5. Regulation of ACTH. Green arrows denote stimulatory influences, red arrows denote inhibitory influences.

Fast feedback occurs within seconds to minutes and involves inhibition of ACTH release by the corticosteroids, mediated through the glucocorticoid receptor (GR). For example, an injection of prednisolone inhibits ovine CRH-stimulated ACTH release within 20 minutes (207). In vitro this appears to involve inhibition of CRH-stimulated ACTH release, and CRH release, but basal secretion is not affected. Protein synthesis is not required, implying that the glucocorticoid effect is non-genomic (208,209). Cell membrane-associated GR has recently been shown to directly mediate fast feedback inhibition by inhibition of Src phosphorylation in corticotrophs (210), but other work implicates the GC-induced secretion of annexin 1/lipocortin1 from folliculostellate cells as a paracrine mechanism for inhibition of ACTH release (211). In addition, receptors for ACTH (MC2R) are present in normal corticotrophs, allowing ‘ultra-fast’ feedback regulation of the HPA axis (212). The receptor expression is lost in the corticotroph adenomas of patients with Cushing’s disease, which could be the potential mechanism of resistance to feedback of the HPA axis seen in these patients (212).

Intermediate feedback occurs within 4 hours’ time frame and involves inhibition of CRH synthesis and release from CRH neurons, not affecting ACTH synthesis (209). However, it is thought that this is a relatively minor contributor to negative feedback (73). Slow feedback occurs over longer timeframes and involves inhibition of POMC transcription (209), via GR antagonism of Nur response element activation of POMC transcription by CRH. The molecular mechanism involves a GR-dependent recruitment of the histone deacetylase HDAC2 to a trans-repressor complex with Brg1, histone H4 deacetylation, and chromatin remodeling (213,214).

There is evidence that ACTH can inhibit CRH synthesis in the context of elevated CRH levels due to Addison’s disease or hypopituitarism, although not in the context of normal human subjects (215). Immunohistochemical studies of the paraventricular nuclei in adrenalectomized or hypophysectomized rats show a reduction of CRH and AVP positive cells when these rats are given ACTH infusions (216).

Glucocorticoids have also been shown to control the cell cycle in corticotrophs. This occurs via feedback repression of the positive cell-cycle regulators L-Myc, N-Myc, and E2F2, plus activation of the negative cell-cycle regulators Gadd45b, GADD45g, and Cables1. In this way, glucocorticoids negatively regulate corticotroph proliferation, a key influence which appears to be lost in corticotroph adenomas (217).

Eating

Cortisol is well known to rise after eating (218,219). This rise is provoked by two mechanisms: (i) by direct stimulation of the HPA axis; and (ii) via regeneration of cortisone to cortisol by stimulation of 11β-hydroxysteroid dehydrogenase type 1 (11βHSD1) (220). The postprandial rise in cortisol has been shown to be mediated via increased pituitary ACTH secretion, which is in turn is modulated by central stimulant alpha-1 adrenoreceptors (221). The cortisol response to food is also enhanced in obese subjects compared to normal BMI individuals (222).

There also appear to be key differences between the effects of individual macronutrients, where carbohydrates lead to equal stimulation of the HPA axis and 11βHSD1, and where fat and protein led to greater stimulation of the HPA axis compared to 11βHSD1. Direct intravenous infusion of macronutrients such as Intralipid and amino acids does not stimulate cortisol secretion (223,224). The most likely candidates for the factors that mediate stimulation of the HPA axis after eating are the gut hormones which are released in response to enteral nutrients. For example, glucagon-like peptide-1_7-36 (GLP-1_7-36) has been shown to stimulate cortisol and ACTH secretion, suggesting a direct effect on the hypothalamus/pituitary (225-227). Gastric inhibitory peptide (GIP), however, has not been shown to stimulate cortisol secretion except in the special case of ectopic GIP receptors in bilateral adrenal hyperplasia, causing food-stimulated Cushing’s syndrome (228). 11HSD1 activity appears to be inhibited by GIP (229), therefore suggesting the GIP is not a key player in mediating the post-prandial rise in cortisol. Although ghrelin has been shown to increase cortisol secretion when given in infusion (108-110), ghrelin is suppressed after eating, making it an unlikely mediator of the post-prandial cortisol response.

AGING OF THE HPA AXIS

Studies in humans and experimental animals have shown evidence that hyperactivity of the HPA axis contributes to neuronal and peripheral deterioration associated with aging (230,231). Hyperactivity of the HPA axis can be caused by stress and is necessary as part of physiological adaptation. However, there must be mechanisms to limit the response to stress, especially during chronic stress, in order to avoid the damaging effects of prolonged exposure to stress hormones such as CRH and corticosterone.

High basal levels of glucocorticoids and loss of circadian rhythm have been associated with greater cognitive decline at a given age (232). Aging is associated with high basal levels of circulating corticosteroids, although there is not always a correlation between plasma ACTH and corticosteroids (233-235). In addition, there is also an alteration to the circadian rhythm of the HPA axis, as demonstrated by studies using a feeding-associated circadian rhythm paradigm. It was found that it took 1 week for young rats and 3 weeks for older rats to entrain the secretion of corticosterone in response to a restricted feeding schedule where they were fed for 2 hours per day. After the rats were shifted to a different pattern of feeding, the entrained circadian rhythm of corticosterone secretion persisted much longer in young rats than in older rats. This suggests that the aged HPA axis appears to take longer to adjust to changes in circadian rhythm, but such adjustments do not ‘stick’ as well as compared to the younger HPA axis (236,237).

When the expression of CRH in the SCN was examined using in situ hybridization, younger 3-4-month-old Sprague-Dawley rats exposed to light from 04.00h to 18.00h have a clear diurnal rhythm with higher expression seen in samples taken at 03.00h versus 23.00h. This rhythm was lost in older 17-20 month old rats with equal expression seen in samples from 03.00h and 23.00h (174). Fetal grafts containing the SCN have been shown to restore the circadian rhythm in old Sprague-Dawley rats, thereby suggesting that the altered diurnal variation of HPA axis probably involves alterations in the function of the suprachiasmatic nuclei (238).

Aging is also associated with an increase in expression of 11HSD1 both in brain and peripheral tissues (239,240). Such changes could conceivably expose tissues to elevated levels of glucocorticoids and contribute to the aging process.

The effects of aging on CRH regulation and whether CRH influences the course of aging are still unclear. Studies have reported increased, unchanged, or reduced hypothalamic CRH release and expression during aging (232).

GENDER DIFFERENCES IN HPA AXIS REGULATION

Endogenous glucocorticoid responses to stress are significantly elevated (in an estrogen-dependent fashion) in females as compared with males (241-244). This estrogen dependence is likely mediated through estrogen-response elements within the promoter regions of CRH (245). As previously noted, there is also a sexual differential in the relationship between AVP release and the ACTH/cortisol response during insulin tolerance testing where the serum levels of copeptin (as a marker of AVP release) positively correlate with ACTH/cortisol release in women but not men (72). However, the sexual dimorphism of the stress response is not seen with exercise-induced stress (246) nor acute psychological stress (247).

PSYCHONEUROENDOCRINOLOGY OF HPA

The link between the HPA axis and psychophysiopathology has long been speculated (248). Neuropsychological disturbances are well observed in humans and study models with abnormal or aberrant HPA axis.

Depression is associated with increased inflammation and given that HPA axis is strictly implicated in inflammation, it is hypothesized that alteration in HPA axis is associated with increase in pro-inflammatory cytokines causing depression, at least with a subgroup of individuals with depression (249). In depression, it is hypothesized that the regulation of ACTH and cortisol secretory activity are altered, along with impaired corticosteroid receptor signaling (250,251). Dysregulation of the HPA axis contributes to suppression of transcription of the brain-derived neurotrophic factor (BDNF) gene, thereby reducing the synthesis and secretion of BDNF protein, a nerve growth factor family (252). This leads to neurodegenerative changes, most prominently in hippocampus, observed in depression. Chronic excess of cortisol in the brain may also lead to serotonin deficiency due to decreased availability of tryptophan, the substrate for serotonin production, and reduction of density and reactivity of serotonin receptors (252). The use of antidepressants targeting this aspect of neurotransmission has shown to normalize the activity of HPA axis, decreasing the levels of CRH and consequently also ACTH and cortisol (252).

Some depressed patients were also reported to have enlarged adrenal glands (253,254) and impaired negative feedback with the hypercortisolemia, thereby suggesting that the level of impairment is at the glucocorticoid receptor-dependent negative feedback, either centrally or at the level of pituitary (255,256). However, when a study looking at 24-hour automated blood cortisol sampling study in depressed premenopausal women was conducted, it found only 6 patients (24%) of a cohort of 25 to have hypercortisolemia (257). This suggests that not all depressed patients will have hypercortisolemia as the main feature of dysregulation of HPA axis. The impairment of the negative feedback was hypothesized to be due to the diminished sensitivity of the glucocorticoid receptors (the ‘glucocorticoid resistance’ theory) secondary to reduced receptor function and expression, shown in large number of experimental, biological and molecular studies (258).

In bipolar disorder, an increase in cortisol secretion may be seen in the manic phase (259). Interestingly, a weaker cortisol awakening response is observed in patients with depression, mania and partial remission against those of healthy control subjects (260), thereby indicating dysregulation of HPA axis in bipolar disorder subjects.

In schizophrenia, individuals who developed or at risk of developing psychosis have been observed to have elevated levels of cortisol measured upon waking up (261,262). The disturbance is more pronounced in individuals not treated with antipsychotic medications. Elevated cortisol levels appear to be correlated with the risk of a first psychotic episode (263), but symptom severity is only correlated with cortisol levels during the initial phase of psychosis (264-266).

REGULATION OF GH RELEASE

Somatotroph Development and Differentiation

Somatotrophs make up approximately 50% of the cell population of the anterior pituitary and generally are concentrated in the lateral wings of the pituitary gland. These cells are characteristically acidophilic, polyhedral and immunopositive for GH and Pit-1. A smaller number of such cells are mammo-somatotrophs, i.e. immunopositive for GH and prolactin (267).

During the process of cell differentiation in the Rathke’s pouch primordium, a cascade of transcription factors is activated to specify anterior pituitary cell types. The two factors particularly involved in differentiation of the lactotroph, somatotroph, and thyrotroph lineages are Prop-1 (Prophet of Pit-1) and Pit-1, also known as GHF-1 and Pou1f1. Prop-1 is a paired-like homeodomain transcription factor; mutations in this gene cause combined GH, prolactin, and TSH deficiency. Mutations of Prop-1 will also give abnormalities of gonadotroph function and, occasionally, corticotroph reserve. Interestingly, these deficiencies are often progressive over time. Pit-1 is part of the POU homeodomain family of transcription factors that includes unc-86, Oct-1, and Oct-2 (268). Pit-1 is a key transcription factor that activates GH gene transcription in the somatotroph (vide infra).

The transcription factor Foxo1 (forkhead box transcription factor) is expressed in 40% of somatotrophs. Foxo1 is involved in the development of various other tissues slow-twitch muscle fibers, bone and pancreas, and a global knockout is lethal. A pituitary-specific knockout of Foxo1 causes a delay in the terminal differentiation of somatotrophs but does not affect commitment of pituitary progenitor cells to the somatotroph lineage (269). Foxo1 exerts its effect via stimulation of NeuroD4 expression which is also important to the terminal differentiation of somatotrophs (270).

Growth Hormone (GH)

GH GENOMIC LOCUS

Human GH was first isolated in 1956 (271) and the structure of the peptide was elucidated fifteen years later (272). Human GH is a 191 amino acids single chain peptide with two disulphide bonds and molecular weight of 22,000 daltons. The GH locus, a 66 kb region of DNA, is located on chromosome 17q22-q24 and consists of 5 homologous genes, which appear to have been duplicated from an ancestral GH-like gene (Table 1) (273,274).

Table 1. The Five Genes in the GH Locus
Gene	Product	Variant(s)	Expressed in	References
hGH-N or GH1	Normal GH	2 alternatively spliced variants (97): 22 kDa (full-length 191 aa). 20 kDa (lacking residues 32-46)	Anterior pituitary	(275)
hGH-V or GH2	Variant GH detectable in pregnancy from mid-term to delivery (276,277)	20 kDa	Placental syncytiotrophoblast cells	(278)
CSH-1, CSH-2	Chorionic somatotropin/human placental lactogen	22 kDa	Placental syncytiotrophoblast cells	(279,280)
CSH-like gene CSHL-1	Non-functional proteins	Many alternatively spliced variants		(281)

STRUCTURE OF THE GH PROMOTER

Because of their origin from an ancestral GH-like gene, all five genes in the GH genomic locus share 95% sequence identity including their promoters (282): proximal elements in the promoter bind Pit-1/GHF-1 (283-286). Pit-1 plays a central role in controlling the expression of hGH-NN gene. Inactivation or lack of functional Pit-1 expression in both mice and human inhibits the differentiation and proliferation of the pituitary cells (287). Although Pit-1 is necessary for transcription of transfected GH1 genes in rat pituitary cells, it is not sufficient (288). Other transcription factors such as Sp1, CREB, and the thyroid hormone receptor are involved (285,289,290).

A placenta-specific enhancer found downstream of the CSH genes (291) as well as pituitary-specific repressor sequences found upstream of GH2, CSH-1 and -2, and CSHL-1 may serve to limit transcription of these particular genes to the placenta (292).

A locus control region consisting of two DNase-I hypersensitive regions (HS), specifically HG-I site, 14.5 and 30 kb upstream of GH1 appears to be required for pituitary-specific GH1 expression (293). This region, which also binds Pit-1 (294), activates histone acetyltransferase, which controls chromatin structure and the accessibility of the GH locus to transcription factors (295,296). The acetylated histone domain potentiates GH transcription and, more recently, HS-I was also shown to be crucial for establishing a domain of non-coding polymerase II transcription necessary for gene activation (297).

Pit-1 is mainly expressed in the pituitary somatotrophs, but it has also notably been demonstrated to be expressed in extrapituitary tissues. Pit-1 regulates local GH expression in the mammary gland and may be involved in mammary development and possibly the pathogenesis of breast carcinoma (298).

GROWTH HORMONE STRUCTURE

This is a 191 amino acid single chain polypeptide hormone that occurs in various modified forms in the circulation. During spontaneous pulses of secretion, the majority full-length isoform of 22 kDa makes up 73%, the alternatively spliced 20 kDa isoform contributes 16%, while the ‘acidic’ desamido and N-alpha acylated isoforms make up 10%. During basal secretion between pulses other forms (30 kDa, 16 kDa and 12 kDa) can also be identified which consist of immunoreactive fragments of GH (299-301).

Higher molecular weight forms of GH exist in the circulation, representing GH bound to growth hormone binding proteins (GHBP) (302). The high-affinity GHBP consists of the extracellular domain of the hepatic GH receptor, and this binds the 22 kDa GH isoform preferentially (303). This high-affinity GHBP is released into circulation by proteolytic processing of the GH receptor by the metalloprotease TACE/ADAM-17 (304). The low-affinity GHBP binds the 20 kDa isoform preferentially (305). Binding of GH to GHBP prolongs the circulation time of GH as the complex is not filtered by the glomeruli (300). GH/GHBP interactions may also compete for GH binding to its surface receptors (306).

GH is also expressed in other areas of the brain, such as the cortex, hippocampus, cortex, caudate nucleus, and retinal areas (307), as is the GH receptor, IGF-1, and the IGF-1 receptor, where it is thought that these mediate neuroprotective and regenerative functions (308).

HYPOPHYSIOTROPIC HORMONES AFFECTING GH RELEASE

GHRH

GHRH was originally isolated from a pancreatic tumor taken from a patient that presented with acromegaly and somatotroph hyperplasia (309). GHRH is derived from a 108 amino acid prepro-hormone to give GHRH (1-40) and (1-44) (Figure 6), which are both found in the human hypothalamus (310,311). The C-terminal 30-44 residues appear to be dispensable, as residues 1-29 show full bioactivity. GHRH binds to a seven-transmembrane domain G-protein coupled receptor that activates adenylate cyclase (312), which stimulates transcription of the GH gene as well as release of GH from intracellular pools (313,314). No other hormone is released by GHRH, although GHRH has homology to other neuropeptides such as PHI, glucagon, secretin and GIP (315).

Figure 6. Hypophysiotrophic hormones influencing GH release. The pathway of GPR101 leading to GH release is currently unclear therefore not shown on this figure.

Somatostatin

Somatostatin (a.k.a. somatotropin release inhibitory factor or SRIF) is derived from a 116 amino acid prohormone to give rise to two principal forms, somatostatin-28 and -14 (316). Both of these are cyclic peptides due to an intramolecular disulphide bond (Figure 6). Somatostatin has multiple effects on anterior pituitary as well as pancreatic, liver and gastrointestinal function:

It inhibits GH secretion directly from somatotrophs (317,318) and antagonizes the GH secretagogue activity of ghrelin (319).
It inhibits GH secretion indirectly via antagonizing GHRH secretion.
It inhibits GH secretion indirectly via inhibiting the secretion of ghrelin from the stomach (320-322).
It inhibits secretion of TSH and TRH stimulation of TSH secretion from the pituitary (323,324).
It inhibits the secretion of CCK, glucagon, gastrin, secretin, GIP, insulin and VIP from the pancreas (325).

Somatostatin binds to specific seven-transmembrane domain G-protein coupled receptors (SSTRs), of which there are at least 5 subtypes. SSTRs 2 and 5 are the most abundant in the pituitary (326). An immunohistochemical study on fetal pituitaries has shown that SSTR 2 is present from 13 weeks gestation, mainly on thyrotrophs and gonadotrophs. SSTR 5 is mainly found on somatotrophs and develops relatively late in gestation at 35-38 weeks of gestation, suggesting that SSTR 2 regulates TSH, LH and FSH whereas SSTR 5 regulates GH (327). The somatostatin receptors couple to various 2^nd messenger systems such as adenylate cyclase, protein phosphatases, phospholipase C, cGMP dependent protein kinases, potassium, and calcium ion channels (328).

Ghrelin

Ghrelin is an orexigenic (appetite-stimulatory) peptide that was isolated from stomach and can stimulate the release of GH. It is derived from preproghrelin, a 117 amino acid peptide, by cleavage and n-octanoylation at the third residue to give a 28 amino acid active peptide (Figure 3 and Figure 6). Ghrelin is the endogenous ligand of the GH secretagogue receptor (GHS-R) 1a, another member of the seven-transmembrane receptor family G-protein coupled to the phospholipase C-phosphoinositide pathway (329,330). This variant of GHS-R has been shown to transduce the GH-releasing effect of synthetic growth hormone secretagogues (GHSs) as well as ghrelin and also plays a role in neuroendocrine and appetite-stimulating activities centrally. Both ghrelin and GHS-R1a have corresponding widespread tissue expression (331). The other GHS-R variant, GHS-R1b, is a 289 amino acid G-protein coupled receptor with five transmembrane domains. The biological function of GHS-R1b is unclear. It has widespread expression throughout the body (331) but does not bind to ghrelin or other GHSs. However, it was shown to have counter-regulatory attenuating role on GHS-R1a signaling, possibly via the formation of heterodimers with GHS-R1a (332).

The majority of circulating ghrelin exists as the des-octanoylated (des-acyl) form: octanoylated ghrelin constitutes approximately 1.8% of the total amount of circulating ghrelin (333). Octanoylation appears to be essential for GH secretagogue activity, as des-acyl ghrelin is inactive for GH release (329). The enzyme that octanoylates ghrelin has recently been identified as ghrelin O-acyltransferase (GOAT) (334). GOAT is a porcupine-like enzyme belonging to the super-family of membrane-bound O-acyltransferase 4 (MBOAT4) and has widespread tissue expression corresponding to ghrelin (335). Historically, the earliest GH secretagogues discovered such as GHRP-1, GHRP-2, GHRP-6, and hexarelin were synthetic and derived from the enkephalins (336).

In the circulation, ghrelin appears to be bound to a subfraction of HDL particles containing clusterin and the A-esterase paraoxonase. It has been suggested that paraoxonase may be responsible for catalyzing the conversion of ghrelin to des-acyl ghrelin (337). However, inhibition of paraoxonase in human serum does not inhibit the de-acylation of ghrelin, and there is a negative correlation in these sera between the paraoxonase activity and ghrelin degradation. Instead, it is more likely that butyrylcholinesterase and other B-esterases are responsible for this activity (338).

Ghrelin is present in the arcuate nucleus of the hypothalamus and in the anterior pituitary (339). Immunofluorescence studies show that ghrelin is localized in somatotrophs, thyrotrophs, and lactotrophs, but not in corticotrophs or gonadotrophs, suggesting that ghrelin may be acting in a paracrine fashion in the anterior pituitary (340). It stimulates GH release in vitro directly from somatotrophs (329) and also when infused in vivo, although the latter action appears to require the participation of an intact GHRH system (319). Ghrelin stimulates GH secretion in a synergistic fashion when co-infused with GHRH (110). Both GHS and ghrelin have been shown to stimulate the release of GH in a dose-related pattern which is more marked in humans than in animals (341,342).

Besides its GH releasing activity, ghrelin has orexigenic activity (343,344), and stimulates insulin secretion (345), ACTH and prolactin release (346). Knocking out the preproghrelin gene in mice does not seem to affect their size, growth rate, food intake, body composition, and reproduction, indicating that proghrelin products (acyl- or desacyl-ghrelin, obestatin) are not dominantly and critically involved in mouse viability, appetite regulation, and fertility (347), although subtle reductions in the amplitude of secretory GH peaks can be detected in these knockout mice during their youth: these differences recede with aging (348). Ghrelin null mice show an increased utilization of fat as an energy substrate when placed on a high-fat diet, which may indicate that ghrelin is involved in modulating the use of metabolic substrates (349). GHS-R knockout mice have the same food intake and body composition as their wild-type littermates, although their body weight is decreased in comparison. However, treatment of GHS-R null mice with ghrelin does not stimulate GH release or food intake, confirming that these properties of ghrelin are mediated through the GHS-R (350).

Although it is clear that acyl-ghrelin activates GH secretion when injected into mice and men, the specific contribution of acyl-ghrelin to physiological pulsatile GH release is less clear. This question has been studied by knocking out GOAT: these mice showed an overall decline in the amount of GH release compared to age matched wild-type mice. The alteration of the GH release observed did not coincide with alterations in the pituitary GH content and GHRH, somatostatin, neuropeptide Y, or GHS-R mRNA expression. However, an increase in pulse number and greater irregularity of GH pulses was observed in these mice. Although other mutations that cause derangement of GH secretion have been previously associated with the ‘feminization’ of the expression of GH-dependent sexually divergent liver genes in male animals, there was no evidence of this in the Goat^-/- mice. An increase in IGF-1 in the circulation, in the liver and also in the muscle was observed in the Goat^-/- mice, either as a result of the disordered GH pulse pattern, or because there was a failure of the elevated IGF-1 levels to feedback on GH release. Overall, the data suggest that acyl-ghrelin has a regulatory role in the patterning of GH secretion, but the absence of acyl-ghrelin does not fatally knock out GH production (351).

To complicate things further, des-acyl ghrelin may have biological effects of its own. It has been shown to inhibit apoptosis and cell death in primary cardiomyocyte and endothelial cell cultures (352), to have varying effects on the proliferation of various prostate carcinoma cell lines (353), to inhibit isoproterenol-induced lipolysis in rat adipocyte cultures (354), and to induce hypotension and bradycardia when injected into the nucleus tractus solitarii of rats (355). More controversially, intracerebroventricular or peripherally administered des-acyl ghrelin causes a decrease in food consumption in fasted mice and inhibits gastric emptying. Des-acyl ghrelin overexpression in transgenic mice causes a decrease in body weight, food intake, fat pad mass weight, and decreased linear growth compared to normal littermates (356). These observations were not replicated by other researchers, who found no effect of des-acyl ghrelin on feeding (357). The effects of des-acyl ghrelin appear not to be mediated via the type 1a or 1b GHS-R (352-354). The effects of peripherally administered des-acyl ghrelin on stomach motility can be inhibited by intracerebrovascular CRH receptor type 2 antagonists, suggesting that CRH receptor type 2 is involved, but there is no direct evidence that des-acyl ghrelin binds this receptor (358)

As noted above, the GH-stimulatory actions of ghrelin in vivo seem to require an intact GHRH system, as immunoneutralization of GHRH blocks ghrelin-induced GH secretion (319). The actions of GH secretagogues are blocked by hypothalamo-pituitary disconnection, which suggests that in vivo ghrelin’s stimulatory actions are indirect and mediated by GHRH (359). However, GHRH cannot be the sole mediator of ghrelin’s actions as the GH response to ghrelin is greater than that to GHRH (360), and, as noted above, ghrelin synergistically potentiates GH release by a maximal dose of GHRH (110). There is no evidence to suggest that ghrelin decreases somatostatinergic tone as immunoneutralization of somatostatin does not block ghrelin’s ability to release GH (319). There may therefore be another mediator, the so-called ‘U’ factor, released by ghrelin, which causes GH secretion (361).

Macimorelin (also known as Ghryelin) is an orally available ghrelin receptor (GHSR) agonist which is now validated for stimulation testing for GH reserve (362).

LEAP2

Liver-expressed antimicrobial peptide 2 (LEAP2) has recently been discovered as an endogenous antagonist to GHSR(363). It is produced in the small intestines, mainly in the jejunum (363). Level of LEAP2 declines with fasting, as opposed to the level of ghrelin which goes up (363,364). In addition, the expression of LEAP2 is significantly upregulated following bariatric surgery, which is currently the most effective treatment for obesity (363). In vivo studies have shown that LEAP2 is capable of inhibiting the effects of ghrelin on GH secretion and food intake (363). LEAP2 is also shown to bind to GHSR in a non-competitive manner to ghrelin, thereby suggesting the presence of an allosteric site on the receptor (363).

Obestatin

As mentioned earlier, the effects of obestatin on pituitary hormones release remain controversial. Initial study has shown that intravenous or intracerebrovascular treatment of obestatin did not affect the release of growth hormone in male rats (116). However, a more recent study has shown that obestatin treatment inhibits both basal and ghrelin-induced GH release and expression, both in vitro and in vivo in non-human primates and in mice (119). This inhibitory effect is mediated by the adenylyl-cyclase and MAPK pathways. Obestatin treatment causes a reduction in Pit-1 and GHRH-R mRNA levels in the pituitary as well as a decrease in hypothalamic GHRH and ghrelin expression. Obestatin also reduces the expression of pituitary somatostatin receptors, namely SSTR subtypes 1 and 2 (119).

OTHER INFLUENCES ON GROWTH HORMONE RELEASE

Glucocorticoids and Sex Hormones

Glucocorticoid treatment has a biphasic effect on GH secretion: an initial acute stimulation in 3 hours, followed by suppression within 12 hours (365,366). The latter is the clinically important effect, as excess endogenous and exogenous glucocorticoids are well known to suppress growth in children (367). The inhibitory effect of glucocorticoids on GH release is possibly mediated by increase in expression of somatostatin (368).

Sex hormones are also involved in regulating GH release particularly during puberty and also later in life. They affect GH release by acting at hypothalamic, pituitary, and peripheral levels. Both estrogen and testosterone increase GH secretion in humans by amplifying secretory burst mass and reduce the orderliness of GH secretion (369). Estrogen affects GH secretion mainly by interacting with the estrogen receptor-alpha expressed in the GHRH neurons and in the GH-secreting pituitary cells. The stimulatory effects of estrogen on GH secretion are possibly mediated by the release of GHRH and/or by enhancing the sensitivity to ghrelin released from the hypothalamus (370). Estrogen increases the irregularity in pulsatility and lowers total and free IGF-1. Although estrogen increases the secretion of GH, it is also known to counter-regulate itself by reducing GH sensitivity in the liver and other peripheral organs, hence decreasing the secretion of IGF-1. The mechanism of this effect is via upregulating the SOCS-2 protein which in turn inhibits the JAK1-STAT5 signal transduction pathway of the GHR (371). GH deficient patients started on estrogen therapy therefore require a higher dose of GH replacement therapy to achieve a particular target IGF-1 level (372). The route of estrogen replacement is an important influence on GH requirement and those on oral estrogen are clearly more GH resistant than women using transdermal preparations (373,374). Testosterone, on the other hand, increases basal GH secretion and IGF-1 concentrations, thus relieving the negative feedback on GH secretion (369).

Leptin

Leptin is a 167 amino acid anorexigenic peptide primarily produced by white adipose tissue (375), regulates body fat mass (376) by feedback inhibition of the appetite centers of the hypothalamus (377). Leptin and its receptor have been detected both by RT-PCR and immunohistochemistry in surgical pituitary adenoma specimens and in normal pituitary tissue (378,379). However, pituitary adenoma cells in culture do not secrete GH in response to leptin treatment (379,380).

Leptin increases GH secretion in the short term, mainly via an increase in GHRH secretion and decrease in somatostatin expression. In the long term, it leads to a decrease in GH secretion, probably reducing GHRH sensitivity (381). In obese subjects, in whom which plasma leptin levels are persistently elevated, GH secretion and responsiveness are reduced in both animals and humans (382). However, if leptin-deficient obese subjects are studied in parallel with sex and BMI-matched leptin-replete obese subjects, it is found that their GH responses to GHRH and GHRP-6 are equally blunted suggesting that the leptin is not influential in mediating the hyposomatotropinism of obesity (383).

IGSF1

IGSF1 (X-linked immunoglobulin superfamily, member 1) gene encodes a transmembrane immunoglobulin superfamily glycoprotein that is highly expressed in the Rathke’s pouch, adult anterior pituitary cells, and the hypothalamus. Loss of function mutations in IGSF1 result in a variable spectrum of anterior pituitary dysfunction, including central hypothyroidism and hypoprolactinemia (384,385). More recently, effects of IGSF1 deficiency on somatroph function were characterized in adult males harboring hemizygous IGSF1 loss-of-function mutations and Igsf1-deficient mice (386). It was shown that IGFS1-deficient patients develop acromegaloid facial features accompanied by elevated IGF-1 concentrations and GH profile. Similar biochemical profiles were also observed in the male Igsf1-deficient mice. The exact mechanism of how IGSF1 regulates or influence GH secretion has not been elucidated.

Kisspeptin

Kisspeptin is a peptide hormone that binds to the G-protein coupled receptor GPR54. Although it was originally characterized as a ‘metastasis suppressor’ gene, its most well-characterized role is in stimulating the secretion of GnRH from GnRH neurons, in turn leading to gonadotrophin production from pituitary gonadotrophs. In addition to this, kisspeptin stimulates GH release from somatotrophs (387,388). These positive effects of kisspeptin are seen when given in vivo to cows or sheep (389), but so far have not been seen when given intravenously in small studies in human volunteers (390), although this may be because the GH stimulatory effects are only observed with central administration.

Catecholamines

In general, alpha-adrenergic pathways stimulate GH secretion, by stimulation of GHRH release and inhibition of somatostatinergic tone, while beta-adrenergic pathways inhibit secretion by increasing somatostatin release (391,392). The alpha₂-adrenoceptor agonist clonidine can therefore be used as a provocative test of GH secretion (393,394)although clinical experience suggests that this is an unreliable stimulatory test for GH secretion in practice. L-dopa stimulates GH secretion; however, this action does not appear to be mediated via dopamine receptors as specific blockade of these receptors with pimozide does not alter the GH response to L-dopa (395). Instead, L-dopa’s effects appear to depend on conversion to noradrenaline or adrenaline, as alpha-adrenoceptor blockade with phentolamine disrupts the GH response to L-dopa (396).

Acetylcholine

Muscarinic pathways are known to stimulate GH secretion, probably by modulating somatostatinergic tone (397). Pyridostigmine, an indirect agonist which blocks acetylcholinesterase, increases the 24 hour secretion of GH by selectively increasing GH pulse mass (398). On the other hand, the muscarinic antagonist atropine is able to blunt the GH release associated with slow wave sleep (399) and that associated with GHRH administration (400). Passive immunization with anti-somatostatin antibodies abolishes the pyridostigmine induced rise in GH in rats, but not immunization with anti-GHRH antibodies, supporting the central role of somatostatinergic tone in mediating this response (401).

Dopamine

Continuous infusion of dopamine into normal healthy men leads to an increase in mean GH secretion comparable to that observed with GHRH. When given together, dopamine and GHRH have additive effects on GH secretion, and similarly the dopamine agonist bromocriptine augments the effects of GHRH (402).

Endogenous Opioids

Endorphins and enkephalins are able to stimulate GH secretion in man (403), and blockade with opiate antagonists can attenuate the GH response to exercise (404). Passive immunization against GHRH in rats inhibits GH release in response to an enkephalin analogue, which argues for stimulation of GHRH in response to these compounds (405). In keeping with this, a recent study demonstrated close juxtapositions between the enkephalinergic/ endorphinergic/ dynorphinergic axonal varicosities and GHRH-immunoreactive perikarya in the human hypothalamus (406). Morphologically, the majority of contacts between the GHRH perikarya and endogenous opiates were enkephalinergic while only few dynorphin- and endorphin-GHRH interactions were detected. Enkephalinergic-GHRH interactions and fibers are known to be densely populated in the infundibular nucleus and anterior periventricular area, thereby suggesting that enkephalin regulates not only the activity of GHRH- but also somatostatin-synthesizing neurons (407). The balance between the activation of GHRH and somatostatin neuronal systems may determine if enkephalin stimulates or inhibits or has no effect on pituitary GH secretion. Unfortunately, the study was unable to detect the presence of synapses between the enkephalinergic/ endorphinergic/ dynorphinergic and GHRH neurons because the immunocytochemistry was carried out under light microscope. Electron microscopy was not applied in the study due to the long post-mortem period. Nevertheless, these findings demonstrated the presence of intimate associations between the endogenous opioid and GHRH systems in the human hypothalamus, as well as indicated the significant differences between the regulatory roles of endogenous opioids on growth in humans.

Stimulation of GHRH by endorphins and enkephalins cannot be the only mechanism increasing GH release, however, as the met-enkephalin analogue DAMME is able to increase GH release over and above the levels released during maximal stimulation by a GHRH analogue (408). It is possible that the actions of endogenous opioids occur via an interaction with the GHS-R, as the original GH secretagogues characterized were derived from the enkephalins (336).

Endocannabinoids

As with ACTH/cortisol, the endocannabinoids may also influence the release of GH. Somatotroph cells bear the CB1 receptor (101). The administration of THC for 14 days suppresses GH secretion in response to hypoglycemia in healthy human subjects (104). Oddly enough, THC and anandamide appear to have opposing effects on GH levels in ovariectomized rats: THC increases and anandamide decreases GH secretion in this context (409). However, the treatment of anterior pituitary cells in primary culture with THC does not seem to influence the release of GH and prolactin to GHRH and TRH, suggesting that the effects of THC are mediated via the hypothalamus and not directly on the anterior pituitary (410), perhaps by stimulating somatostatin release (411).

Ghrelin and the Endocannabinoid System

Ghrelin and the endocannabinoid system interact in a bidirectional fashion. The intraperitoneal administration of cannabinoids results in increased plasma ghrelin levels and stomach ghrelin expression in rats (412) and CB1 receptor antagonism with rimonabant reduces ghrelin levels (413), suggesting that the orexigenic effects of cannabinoids may also be connected to an increase in ghrelin secretion from the gastric X/A-like cells. The effects of ghrelin on appetite were also abolished in CB1 knockout or in the presence of the CB1 antagonist rimonabant (414-416). In addition, the effects of cannabinoids are also abolished in the absence of the ghrelin receptor GHS-R1a (417). These findings confirm that both ghrelin and cannabinoid signaling pathways have to intact to mediate the effects of these two systems on appetite. Interestingly, in vivo and in vitro GH release is intact in response to ghrelin in CB1-knockout animals (415). These findings are intriguing because they suggest that the effects of ghrelin on GH release are somehow modulated differently at the receptor-binding stage of the pathway compared to its orexigenic and metabolic effects. Moreover, it has also been proposed that the bidirectional relationship of the ghrelin and endocannabinoid system might be potentially mediated by the interaction (e.g. heterodimerization) between GHS-R1a and CB1 receptors (417). However, further molecular and functional studies are needed to elucidate the exact mechanism of interaction between these two systems.

Free Fatty Acids

The negative feedback regulation of plasma free fatty acids on growth hormone secretion has long been studied (418). Low free fatty acids have been shown to stimulate GH release, although there is a lag period between these two phenomena. Similarly, high plasma levels of free fatty acids have been shown to stimulate splanchnic somatostatin, thereby affecting GH secretion (419). Studies on both hypothalamic and cortical cell cultures have shown marked decrease in somatostatin mRNA levels when both the neuronal cells are treated with free fatty acids, thereby indicating the possible role for free fatty acids in the regulation of the GH secretion centrally (420).

Other Neuropeptides and Factors Affecting GH Secretion

Many neuropeptides, including the ones in the following paragraphs, have been shown to influence GH secretion in various contexts. For the most part, however, their physiological role in man is not well characterized.

Infusion of galanin, a 29 amino acid peptide originally isolated from the small intestine, causes stimulation of GH secretion when infused alone and also enhances GHRH-stimulated GH secretion (421).

Calcitonin, the 32 amino acid peptide secreted from the C cells of the thyroid gland, appears to inhibit the stimulated secretion of GH by GHRH, arginine, and insulin-induced hypoglycemia (422,423).

Neuropeptide Y (NPY) is an orexigenic peptide that has been shown to inhibit GH secretion in rats (424-426), from human somatotroph tumor cells in culture (427), and from rat hypothalamic explants (428). When infused into patients with prolactin-secreting pituitary adenomas, 9 out of 15 patients showed a paradoxical rise in GH levels (429). However, when infused into healthy young men overnight, NPY did not have any significant effect on GH secretion (430).

Pituitary adenylate cyclase-activating polypeptide (PACAP) is a hypothalamic C-terminally amidated 38 residue peptide hormone originally characterized on the basis of its ability to stimulate cAMP accumulation from anterior pituitary cells (431). In rats, PACAP stimulates GH release from pituitary cell lines and also when infused in vivo (432-434). When infused into human volunteers, however, GH levels do not appear to be affected (435).

Klotho, a transmembrane protein that is classically known for its ‘co-receptor’ activity with fibroblast growth hormone receptors, has recently been characterized as a possible secretagogue for GH. Although it is usually attached to membranes, the extracellular region can be shed from the cell surface, and there is some evidence for endocrine activity. Klotho knockout mice exhibit reduced growth in the context of a ‘early aging’ phenotype, and histopathological examination of their somatotrophs demonstrate reduced numbers of secretory granules. Klotho treatment of somatotrophs in vitro has been demonstrated to increase GH secretion, but at present its physiological role is yet to be fully elucidated (436).

GPR101, an orphan GPCR that is constitutively coupled to G_s, has been shown to induce GH secretion through the activation of protein kinase A and protein kinase C in the G_s and G_q/11 pathways (437). Transgenic mice with overexpression of pituitary-specific Gpr101 develops gigantism phenotype and has hypersecretion of GH, in the absence of pituitary hyperplasia or tumorigenesis, thereby indicating that the role of Gpr101 in the pituitary enhances secretion rather than enhancing proliferation (437). In humans, duplication of the GPR101 gene and thus, overexpression of GPR101, leads to a severe form of pituitary gigantism known as X-linked acrogigantism (X-LAG) (438-441). X-LAG is characterized by infant-onset somatotroph tumors or hyperplasia with high levels of GH and in most cases prolactin as well.

Nesfatins, and nesfatin-like-peptides, are hypothalamic and brainstem peptides speculated to be involved in energy homeostasis (442). They have been shown to inhibit GH release in mammalian somatotroph cell lines (443). Both of these peptides bind to the membrane of the GH3 cells, thereby indicating the possibility of a GPCR-mediated action (443). Interestingly, their effects on GH synthesis seem to be concentration-dependent, as low and high concentrations of nesfatins downregulate the expression of GH mRNA, while medium concentrations of nesfatins does not produce this effect (443). Their physiological significance in humans has not yet been established.

FEEDBACK LOOPS OF GH SECRETION

Multiple negative feedback loops exist to autoregulate the GH axis (Figure 7).

Somatostatin auto-inhibits its own secretion (444).
GHRH auto-inhibits its own secretion by stimulating somatostatin release (445).
GH auto-regulates its own secretion in short term by stimulating somatostatin release and inhibiting GHRH-stimulated GH release (446-448). There is also a negative feedback on stomach ghrelin release by GH (449). More recently, it is demonstrated that in long-term feedback situation, the inhibition of GH release is most likely due to feedback inhibition by IGF-1 (450).
IGF-1, whose production is stimulated by GH, inhibits GH release in a biphasic manner: (1) by stimulating hypothalamic somatostatin release early, and (2) by inhibiting GH release after 24 hours, probably by inhibiting GH mRNA transcription (451,452). Interestingly, IGF-1 infusion suppresses GHRH-induced GH release in males but not in females, suggesting a sexually dimorphic effect (450).

Figure 7. Regulation of GH. Green arrows denote stimulatory influences, red arrows denote inhibitory influences.

PHYSIOLOGY OF GH SECRETION

Pulsatility of GH Secretion

The secretory pattern of GH was first elucidated in rats (453). Circulating GH levels are pulsatile, with high peaks separated by valleys where the GH is undetectable by conventional RIAs or IRMAs (Figure 8). The recent development of sensitive chemiluminescent assays for GH with high frequency sampling and deconvolution analysis has allowed the detailed study of GH secretion. This shows that there are detectable levels of basal GH secretion in the ‘valleys’ (454). On average, there are 10 pulses of GH secretion per day lasting a mean of 96.4 mins with 128 mins between each pulse (455). The diurnal secretory pattern of GH in human is fully developed after puberty, demonstrating a major peak at late night/early morning which is associated with NREM (slow wave)-sleep, and a number of peaks during the light hours of the day, but with quite large individual difference (456).

Figure 8. Pulsatility of circulating GH levels in adult men and women.

There is a dynamic interplay of pulsatile GHRH and somatostatin secretion:

Via crosstalk: GHRH neurons receive inhibitory inputs from somatostatin neurons, whilst somatostatin neurons receive direct stimulatory inputs from GHRH neurons
Via synergistic actions on somatotrophs: Pre-exposure to somatostatin enhances GHRH-stimulated secretion of GH (457).

Further studies in animals have revealed that somatotropin releasing inhibiting factor regulates the magnitude of the troughs of GH as well as the amplitude of the peaks, whereas GHRH functions as the main regulator of the pulsatile pattern (450,458,459). Interestingly, continuous GHRH administration in human volunteers does not affect the pulsatility of GH secretion (460). Moreover, patients with an inactivating mutation of the GHRH receptor continue to show pulsatile GH secretion, suggesting that somatostatin pulsatility is sufficient to determine GH pulsatility (461). These observations suggest that the mechanisms involved in humans may differ from the animal models.

GH and Sexual Dimorphism

The technical developments in sensitive detection of GH and deconvolution analysis referred to above have elucidated differences in secretion between men and women. Women have higher mean GH levels throughout the day than men due to higher incremental and maximal GH peak amplitudes (Figure 8), but show no significant difference in GH half-life, interpulse times, or pulse frequency (462). The higher basal GH levels may underlie the higher nadir GH levels seen in normal women after GH suppression with oral glucose (463). Recent evidence suggests that there are sexual differences in the expression of somatostatin and somatostatin receptor subtypes in the rat pituitary, which would clearly cause differences in the physiological regulation of GH release (464).

Differences in GH secretion patterns between the sexes, with male ‘pulsatile’ secretion versus female ‘continuous’ secretion, can cause different patterns of gene activation in target tissues, e.g. induction of linear growth patterns, gain of body weight, induction of liver enzymes and STAT 5b signaling pathway activity (465).

GH and Aging

GH and IGF-1 levels are known to decline continuously with age and to very low levels in those aged ≥60 years (466). This phenomenon, known as the ‘somatopause’, is also seen in other mammals and has led to the speculation that GH treatment can be a potent anti-aging therapy (467). Conversely, decreased GH/IGF-1 signaling has also been shown to extend longevity in a wide variety of species such as worms, fruit flies, mice, and yeast (468), thus raising the question of whether decreased activity of the GH/IGF-1 axis might be beneficial for human longevity. Somatopause might therefore be nature’s way of sustaining the aging individual (469).

It is also suggested that the anorexia associated with aging is due to the decline in the level of acylated ghrelin in older adults. This is supported by a recent study that showed an age-dependent decline in both circulating acyl-ghrelin and growth hormone levels in older adults (aged 62-74 years, BMI range 20.9-29 kg/m²) compared to young adults (aged 18-28 years, BMI range 20.6-26.2 kg/m²) (470). By estimating the correlations between amplitudes of individual GH secretory events and the average acyl-ghrelin concentration in the 60-minute interval preceding each GH burst, the ghrelin/GH association was more than 3-fold lower in the older group compared with the young adults, thus suggesting that with normal aging, endogenous acyl-ghrelin levels are less tightly linked to GH regulation. In addition, ghrelin mimetics have also been shown to be a potential treatment for the musculoskeletal impairment associated with aging (471).

Sleep

The secretion rate of GH shows a circadian pattern, with peak rates measured during sleep. These are approximately triple the daytime rate (472). GH secretion is especially associated with slow wave sleep (SWS – stages 3 and 4) (473). Deep sleep is also shown to enhance the activity of GH axis and has an inhibitory effect on cortisol levels (474). The decline in GH secretion during aging is paralleled by the decreasing proportion of time spent in SWS, although it is unclear which is cause and which is effect (475). In early data from a clinical trial, GH deficient patients have increased sleep fragmentation and decreased total sleep time, and it is conjectured that such alterations in sleep patterns may be responsible for excessive daytime sleepiness in such patients (476).

Sleep deprivation, in the laboratory or due to travel causing ‘jet lag’, causes two alterations in the GH secretory pattern: the magnitude of secretory spikes is augmented: the return to pre-travel levels takes at least 11 days and is slower to recover after westward travel. The major pulse of GH secretion occurring in early sleep is also shifted to late sleep (477). It is also noted that the GH pulses are more equally distributed throughout 24 hours of sleep deprivation compared to a night-time sleep condition, with large individual pulses occurring during the day (478).

Administration of a GHRH antagonist reduces nocturnal GH pulsatility by 75% (479). Normal subjects remain sensitive to GHRH boluses during the night, however, and the lowering of somatostatinergic tone during the night may be responsible for the increase in GH secretion rate (480). Recent work, however, has also demonstrated that ghrelin levels rise through the night in lean men (481). It is likely, therefore, that a combination of increased GHRH, decreased somatostatin and increased ghrelin levels underlie the circadian variation in GH secretion.

Administration of GHRH augments increased nocturnal GH release and promotes SWS. Somatostatin does not change nocturnal GH release, and does not affect the proportion of SWS, but may increase rapid eye movement (REM) sleep density (482). Ghrelin has been shown to promote slow wave sleep at the expense of REM sleep, accompanied by an increase in GH and prolactin release when administered exogenously (483).

Exercise

Exercise is a powerful stimulus to secretion of GH (484), which occurs by about 15 min from the start of exercise (485). The kinetics may vary between subjects, an effect which is likely to be related to differences in age, sex and body composition (486). Ten minutes of high-intensity exercise is required to stimulate a significant rise in GH (487). Anaerobic exercise causes a larger release of GH than aerobic exercise of the same duration (488).

Acetylcholine, adrenaline, noradrenaline, and endogenous opioids have been implicated in exercise-induced GH release (397). However, ghrelin levels do not rise in acute exercise, indicating that ghrelin may not have a role to play in exercise-induced GH release (489).

Recent evidence also indicates that exercise enhances SWS and thus leads to increase in GH release as well as brain-derived neutrotrophic factors (BDNF) and IGF-1 gene expression and protein levels (490,491). This is thought to improve learning and memory performance, especially in the elderly (490,491). Sleep-deprived individuals seem to have a larger exercise-induced GH response, although the reason behind this is still unclear (492).

Hypoglycemia

Insulin-induced hypoglycemia is another powerful stimulus to GH secretion (Figure 9) (493,494). The peak GH levels achieved during insulin stress testing correlate well with those achieved during slow wave sleep (495). The hypoglycemic response is mediated by alpha₂-adrenergic receptors (496) to cause inhibition of somatostatin release (397), although other evidence argues for a role of stimulated GHRH release, as a GHRH receptor antagonist significantly suppressed hypoglycemic GH release (497). Ghrelin is unlikely to be involved in the GH response to insulin-induced hypoglycemia as circulating ghrelin levels are suppressed by the insulin bolus (498).

Figure 9. Normal response of GH to insulin-induced hypoglycemia (≤2.2 mmol/l). Peak GH secreted is ≥6.66 µg/L.

Other Stressors

Other physical stresses such as hypovolemic shock (499) and elective surgery (500) cause increased GH release; alpha-adrenergic dependent mechanisms are thought to underly this, as blockade with phentolamine inhibits the response (500).

Hyperglycemia

In contrast to hypoglycemia, ingestion of an oral glucose load causes an initial suppression of plasma GH levels for 1-3 hours (Figure 10), followed by a rise in GH concentrations at 3-5 hours (501). The initial suppression could be mediated by increased somatostatin release as pyridostigmine, a postulated inhibitor of somatostatin release, blocks this suppression (502). Circulating ghrelin levels also fall following ingestion of glucose (503). The GH response to ghrelin and GHRH infusions is blunted by oral glucose, an effect that is probably mediated by somatostatin (504). The later rise in GH levels is postulated to be due to a decline in somatostatinergic tone plus a reciprocal increase in GHRH, leading to a ‘rebound’ rise (397).

Figure 10. GH response to 75g oral glucose in 8 non-acromegalic, non-diabetic women, given at time 0. Error bars denote SD. Note the high variability of the baseline GH level due to the pulsatile nature of GH secretion. GH levels fall to <0.4 µg/L at 120 minutes.

In type I diabetes mellitus, GH dynamics are disordered, with elevated 24 hour release of GH (505). Deconvolution analysis shows that GH pulse frequencies and maximal amplitudes are increased. The latter is accounted for by higher ‘valley’ levels (506). Better glycemic control appears to normalize these disordered dynamics (507). The pathophysiological mechanism appears to involve reduced somatostatinergic tone (397).

There is conflicting evidence for increased, decreased, or normal GH dynamics in type II diabetics. It is likely that this reflects two factors acting in opposite directions: (1) the confounding factor of obesity in these patients, which leads to hyposecretion of GH; and (2) the hyperglycemia, which leads to hypersecretion (397).

Dietary Restriction and Fasting

Dietary restriction and fasting lead to a significant increase in pituitary secretion of GH (508). A 5-day fast in normal healthy men resulted in a significant increase in the pulse frequency as well as pulse amplitude of GH release. This was coupled with a decrease in expression and secretion of IGF-1, which could explain the lack of feedback inhibitory effect on pituitary GH secretion in the fasting state.

Obesity and Malnutrition

Chronic malnutrition states such as marasmus and kwashiorkor cause a rise in GH levels (509). On the other hand, obesity is known to be associated with lower GH levels, partially due to decreased levels of GH binding protein and partially due to decreased frequency of GH pulses (510). Visceral adiposity, as assessed by CT scanning and dual energy X-ray absorptiometry, seems to be especially important, and correlates negatively with mean 24 hour GH concentrations (511). The mechanism of decreased GH release in obesity has been ascribed to increased somatostatinergic tone, as pyridostigmine is able to reverse this, to some extent, by suppressing somatostatin release (512-514). However, this cannot be the full explanation, as pyridostigmine is not able to fully reverse the hyposomatotropinism of obesity, even when combined with GHRH and the GH secretagogue GHRP-6 (515).

The fasting induced elevation in secretion of GH is blunted in obesity (516,517). Nevertheless, fasting in obese volunteers still induces an appreciable increase in GH secretion, with accompanying increase in lipolysis and insulin resistance. Co-administration of pegvisomant (a GH receptor antagonist) abrogated this phenomenon, suggesting that the elevation in GH during fasting is responsible for the insulin resistance induced by fasting (518).

Although leptin has been shown to be influential on GH secretion in rats (519), this may not be so in humans. Leptin-deficient subjects have been compared with obese non-deficient control subjects in their GH responses when stimulated with GHRH plus GHRP-6. Both these groups have decreased GH peaks compared to non-obese control subjects, as expected. There was no significant difference in mean GH peaks between leptin-deficient and leptin-replete controls, suggesting that leptin does not play a significant role in the GH suppression seen in obese humans, and that the decreased GH secretion of obesity is mediated via other mechanisms (383).

Another candidate for the mechanism linking obesity to GH secretion is ghrelin. Its levels correlate negatively with body fat content (520). A comparative study between 5 lean and 5 obese men employed rapid sampling and pulse analysis of ghrelin levels over 24 hours. Ghrelin levels increased at night in the lean controls but did not in the obese group (481). Weight loss caused circulating ghrelin levels to rise in two studies (521,522). Contradicting this, however, Lindeman and colleagues found that ghrelin levels paradoxically correlated positively with visceral fat area, in contrast with 24-hour GH secretion, which correlated negatively. Moreover, in their study, weight loss increased GH secretion but did not affect ghrelin levels (523). More recently, a study comparing subjects with central obesity only with subjects suffering from the metabolic syndrome showed changes in ghrelin levels not to be associated with central obesity per se but with other components of the metabolic syndrome (524). The response of GH secretion to exogenous ghrelin is significantly blunted in obese patients and this response is restored early on after Roux-en-Y gastric bypass (prior to any major weight loss), suggesting that there is an intrinsic resistance to ghrelin in obesity which is reversed with gastric bypass, and which is not linked to weight loss (525). Therefore, there does not appear to be a simple relationship where obesity-induced reduction in ghrelin levels leads to the reduced secretion of GH.

Amino Acids

GH release is stimulated by a protein meal (526). L-arginine, an essential amino acid, can be used as a provocative test for GH secretion (527). Evidence that L-arginine acts through inhibition of somatostatin release includes the observation that L-arginine can still enhance the GH response to GHRH despite the use of maximal doses of GHRH (528). However, a specific GHRH antagonist blunted the GH response to L-arginine, an observation that supports the notion that L-arginine also acts through stimulation of GHRH secretion (497). Unlike oral glucose, L-arginine does not modify the GH response to ghrelin infusion (504).

REFERENCES

Marshall J. Control of Pituitary Hormone Secretion – Role of Pulsatility. In: Besser G, Thorner M, eds. Comprehensive Clinical Endocrinology. Edinburgh, UK: Mosby; 2002:19-34.
Doniach I. Histopathology of the pituitary. Clin Endocrinol Metab. 1985;14(4):765-789.
McKusick V, Phillips JI, Hamosh A, Tiller G, O'Neill M. Pro-opiomelanocortin. In: McKusick V, ed. Online Mendelian Inheritance in Man. Baltimore, MD, USA: Johns Hopkins University; 2007: http://www.ncbi.nlm.nih.gov:80/entrez/dispomim.cgi?id=176830. Accessed 20 Jan 2007
Drouin J. 60 YEARS OF POMC: Transcriptional and epigenetic regulation of POMC gene expression. J Mol Endocrinol. 2016;56(4):T99-T112.
Drouin J, Chamberland M, Charron J, Jeannotte L, Nemer M. Structure of the rat pro-opiomelanocortin (POMC) gene. FEBS Lett. 1985;193(1):54-58.
Therrien M, Drouin J. Pituitary pro-opiomelanocortin gene expression requires synergistic interactions of several regulatory elements. Mol Cell Biol. 1991;11(7):3492-3503.
Therrien M, Drouin J. Cell-specific helix-loop-helix factor required for pituitary expression of the pro-opiomelanocortin gene. Mol Cell Biol. 1993;13(4):2342-2353.
Poulin G, Turgeon B, Drouin J. NeuroD1/beta2 contributes to cell-specific transcription of the proopiomelanocortin gene. Mol Cell Biol. 1997;17(11):6673-6682.
Lamonerie T, Tremblay JJ, Lanctot C, Therrien M, Gauthier Y, Drouin J. Ptx1, a bicoid-related homeo box transcription factor involved in transcription of the pro-opiomelanocortin gene. Genes Dev. 1996;10(10):1284-1295.
Lamolet B, Pulichino AM, Lamonerie T, Gauthier Y, Brue T, Enjalbert A, Drouin J. A pituitary cell-restricted T box factor, Tpit, activates POMC transcription in cooperation with Pitx homeoproteins. Cell. 2001;104(6):849-859.
Langlais D, Couture C, Sylvain-Drolet G, Drouin J. A Pituitary-Specific Enhancer of the POMC Gene with Preferential Activity in Corticotrope Cells. Mol Endocrinol. 2011;25(2):348-359.
Murakami I, Takeuchi S, Kudo T, Sutou S, Takahashi S. Corticotropin-releasing hormone or dexamethasone regulates rat proopiomelanocortin transcription through Tpit/Pitx-responsive element in its promoter. J Endocrinol.2007;193(2):279-290.
Budry L, Balsalobre A, Gauthier Y, Khetchoumian K, L'Honore A, Vallette S, Brue T, Figarella-Branger D, Meij B, Drouin J. The selector gene Pax7 dictates alternate pituitary cell fates through its pioneer action on chromatin remodeling. Genes Dev. 2012;26(20):2299-2310.
Ezzat S, Mader R, Yu S, Ning T, Poussier P, Asa SL. Ikaros integrates endocrine and immune system development. J Clin Invest. 2005;115(4):1021-1029.
Aguilera G, Harwood JP, Wilson JX, Morell J, Brown JH, Catt KJ. Mechanisms of action of corticotropin-releasing factor and other regulators of corticotropin release in rat pituitary cells. J Biol Chem. 1983;258(13):8039-8045.
Jin WD, Boutillier AL, Glucksman MJ, Salton SR, Loeffler JP, Roberts JL. Characterization of a corticotropin-releasing hormone-responsive element in the rat proopiomelanocortin gene promoter and molecular cloning of its binding protein. Mol Endocrinol. 1994;8(10):1377-1388.
Autelitano DJ, Cohen DR. CRF stimulates expression of multiple fos and jun related genes in the AtT-20 corticotroph cell. Mol Cell Endocrinol. 1996;119(1):25-35.
Loeffler JP, Kley N, Pittius CW, Hollt V. Calcium ion and cyclic adenosine 3',5'-monophosphate regulate proopiomelanocortin messenger ribonucleic acid levels in rat intermediate and anterior pituitary lobes. Endocrinology. 1986;119(6):2840-2847.
Antoni FA. Interactions between intracellular free Ca2+ and cyclic AMP in neuroendocrine cells. Cell Calcium.2012;51(3-4):260-266.
Jenks BG. Regulation of proopiomelanocortin gene expression: an overview of the signaling cascades, transcription factors, and responsive elements involved. Ann N Y Acad Sci. 2009;1163:17-30.
Martens C, Bilodeau S, Maira M, Gauthier Y, Drouin J. Protein-protein interactions and transcriptional antagonism between the subfamily of NGFI-B/Nur77 orphan nuclear receptors and glucocorticoid receptor. Mol Endocrinol.2005;19(4):885-897.
Boutillier AL, Monnier D, Koch B, Loeffler JP. Pituitary adenyl cyclase-activating peptide: a hypophysiotropic factor that stimulates proopiomelanocortin gene transcription, and proopiomelanocortin-derived peptide secretion in corticotropic cells. Neuroendocrinology. 1994;60(5):493-502.
Karalis KP, Venihaki M, Zhao J, van Vlerken LE, Chandras C. NF-kappaB participates in the corticotropin-releasing, hormone-induced regulation of the pituitary proopiomelanocortin gene. J Biol Chem.2004;279(12):10837-10840.
Asaba K, Iwasaki Y, Asai M, Yoshida M, Nigawara T, Kambayashi M, Hashimoto K. High glucose activates pituitary proopiomelanocortin gene expression: possible role of free radical-sensitive transcription factors. Diabetes Metab Res Rev. 2007;23(4):317-323.
Suda T, Tozawa F, Yamada M, Ushiyama T, Tomori N, Sumitomo T, Nakagami Y, Demura H, Shizume K. Effects of corticotropin-releasing hormone and dexamethasone on proopiomelanocortin messenger RNA level in human corticotroph adenoma cells in vitro. J Clin Invest. 1988;82(1):110-114.
Wardlaw SL, McCarthy KC, Conwell IM. Glucocorticoid regulation of hypothalamic proopiomelanocortin. Neuroendocrinology. 1998;67(1):51-57.
Drouin J, Charron J, Gagner JP, Jeannotte L, Nemer M, Plante RK, Wrange O. Pro-opiomelanocortin gene: a model for negative regulation of transcription by glucocorticoids. J Cell Biochem. 1987;35(4):293-304.
Drouin J, Sun YL, Chamberland M, Gauthier Y, De Lean A, Nemer M, Schmidt TJ. Novel glucocorticoid receptor complex with DNA element of the hormone-repressed POMC gene. Embo J. 1993;12(1):145-156.
Autelitano DJ, Lundblad JR, Blum M, Roberts JL. Hormonal regulation of POMC gene expression. Annu Rev Physiol. 1989;51:715-726.
Pozzoli G, Bilezikjian LM, Perrin MH, Blount AL, Vale WW. Corticotropin-releasing factor (CRF) and glucocorticoids modulate the expression of type 1 CRF receptor messenger ribonucleic acid in rat anterior pituitary cell cultures. Endocrinology. 1996;137(1):65-71.
Parvin R, Saito-Hakoda A, Shimada H, Shimizu K, Noro E, Iwasaki Y, Fujiwara K, Yokoyama A, Sugawara A. Role of NeuroD1 on the negative regulation of Pomc expression by glucocorticoid. PLoS One. 2017;12(4):e0175435.
Paez-Pereda M, Kovalovsky D, Hopfner U, Theodoropoulou M, Pagotto U, Uhl E, Losa M, Stalla J, Grubler Y, Missale C, Arzt E, Stalla GK. Retinoic acid prevents experimental Cushing syndrome. The Journal of clinical investigation. 2001;108(8):1123-1131.
Frederic F, Chianale C, Oliver C, Mariani J. Enhanced endocrine response to novel environment stress and lack of corticosterone circadian rhythm in staggerer (Rora sg/sg) mutant mice. J Neurosci Res. 2006;83(8):1525-1532.
Martin NM, Small CJ, Sajedi A, Liao XH, Weiss RE, Gardiner JV, Ghatei MA, Bloom SR. Abnormalities of the hypothalamo-pituitary-thyroid axis in the pro-opiomelanocortin deficient mouse. Regul Pept. 2004;122(3):169-172.
Ray DW, Ren SG, Melmed S. Leukemia inhibitory factor (LIF) stimulates proopiomelanocortin (POMC) expression in a corticotroph cell line. Role of STAT pathway. J Clin Invest. 1996;97(8):1852-1859.
Ray DW, Ren SG, Melmed S. Leukemia inhibitory factor regulates proopiomelanocortin transcription. Ann N Y Acad Sci. 1998;840:162-173.
Mynard V, Guignat L, Devin-Leclerc J, Bertagna X, Catelli MG. Different mechanisms for leukemia inhibitory factor-dependent activation of two proopiomelanocortin promoter regions. Endocrinology. 2002;143(10):3916-3924.
Bousquet C, Zatelli MC, Melmed S. Direct regulation of pituitary proopiomelanocortin by STAT3 provides a novel mechanism for immuno-neuroendocrine interfacing. J Clin Invest. 2000;106(11):1417-1425.
Iwasaki Y, Taguchi T, Nishiyama M, Asai M, Yoshida M, Kambayashi M, Takao T, Hashimoto K. Lipopolysaccharide stimulates proopiomelanocortin gene expression in AtT20 corticotroph cells. Endocr J. 2008;55(2):285-290.
Smith ZD, Meissner A. DNA methylation: roles in mammalian development. Nat Rev Genet. 2013;14(3):204-220.
Newell-Price J, King P, Clark AJ. The CpG island promoter of the human proopiomelanocortin gene is methylated in nonexpressing normal tissue and tumors and represses expression. Mol Endocrinol. 2001;15(2):338-348.
Benjannet S, Rondeau N, Day R, Chretien M, Seidah NG. PC1 and PC2 are proprotein convertases capable of cleaving proopiomelanocortin at distinct pairs of basic residues. Proc Natl Acad Sci U S A. 1991;88(9):3564-3568.
Chretien M, Seidah NG. Chemistry and biosynthesis of pro-opiomelanocortin. ACTH, MSH's, endorphins and their related peptides. Mol Cell Biochem. 1981;34(2):101-127.
Seidah NG, Chretien M. Complete amino acid sequence of a human pituitary glycopeptide: an important maturation product of pro-opiomelanocortin. Proc Natl Acad Sci U S A. 1981;78(7):4236-4240.
Seidah NG, Rochemont J, Hamelin J, Benjannet S, Chretien M. The missing fragment of the pro-sequence of human pro-opiomelanocortin: sequence and evidence for C-terminal amidation. Biochem Biophys Res Commun.1981;102(2):710-716.
Eipper BA, Mains RE. Structure and biosynthesis of pro-adrenocorticotropin/endorphin and related peptides. Endocr Rev. 1980;1(1):1-27.
Bradbury AF, Smyth DG, Snell CR. Prohormones of beta-melanotropin (beta-melanocyte-stimulating hormone, beta-MSH) and corticotropin (adrenocorticotropic hormone, ACTH): structure and activation. Ciba Found Symp.1976;41:61-75.
Barnea A, Cho G. Acetylation of adrenocorticotropin and beta-endorphin by hypothalamic and pituitary acetyltransferases. Neuroendocrinology. 1983;37(6):434-439.
Vale W, Spiess J, Rivier C, Rivier J. Characterization of a 41-residue ovine hypothalamic peptide that stimulates secretion of corticotropin and beta-endorphin. Science. 1981;213(4514):1394-1397.
Shibahara S, Morimoto Y, Furutani Y, Notake M, Takahashi H, Shimizu S, Horikawa S, Numa S. Isolation and sequence analysis of the human corticotropin-releasing factor precursor gene. Embo J. 1983;2(5):775-779.
Sawchenko PE, Swanson LW. Localization, colocalization, and plasticity of corticotropin-releasing factor immunoreactivity in rat brain. Fed Proc. 1985;44(1 Pt 2):221-227.
Deussing JM, Chen A. The Corticotropin-Releasing Factor Family: Physiology of the Stress Response. Physiol Rev. 2018;98(4):2225-2286.
Perrin M, Donaldson C, Chen R, Blount A, Berggren T, Bilezikjian L, Sawchenko P, Vale W. Identification of a second corticotropin-releasing factor receptor gene and characterization of a cDNA expressed in heart. Proc Natl Acad Sci U S A. 1995;92(7):2969-2973.
Chen R, Lewis KA, Perrin MH, Vale WW. Expression cloning of a human corticotropin-releasing-factor receptor. Proc Natl Acad Sci U S A. 1993;90(19):8967-8971.
Takefuji M, Murohara T. Corticotropin-Releasing Hormone Family and Their Receptors in the Cardiovascular System. Circ J. 2019;83(2):261-266.
Bale TL, Vale WW. CRF and CRF receptors: role in stress responsivity and other behaviors. Annu Rev Pharmacol Toxicol. 2004;44:525-557.
DeBold CR, DeCherney GS, Jackson RV, Sheldon WR, Alexander AN, Island DP, Rivier J, Vale W, Orth DN. Effect of synthetic ovine corticotropin-releasing factor: prolonged duration of action and biphasic response of plasma adrenocorticotropin and cortisol. J Clin Endocrinol Metab. 1983;57(2):294-298.
Tse A, Lee AK, Tse FW. Ca2+ signaling and exocytosis in pituitary corticotropes. Cell Calcium. 2012;51(3-4):253-259.
Muglia L, Jacobson L, Dikkes P, Majzoub JA. Corticotropin-releasing hormone deficiency reveals major fetal but not adult glucocorticoid need. Nature. 1995;373(6513):427-432.
Timpl P, Spanagel R, Sillaber I, Kresse A, Reul JM, Stalla GK, Blanquet V, Steckler T, Holsboer F, Wurst W. Impaired stress response and reduced anxiety in mice lacking a functional corticotropin-releasing hormone receptor 1. Nat Genet. 1998;19(2):162-166.
Wang X, Su H, Copenhagen LD, Vaishnav S, Pieri F, Shope CD, Brownell WE, De Biasi M, Paylor R, Bradley A. Urocortin-deficient mice display normal stress-induced anxiety behavior and autonomic control but an impaired acoustic startle response. Mol Cell Biol. 2002;22(18):6605-6610.
Neufeld-Cohen A, Tsoory MM, Evans AK, Getselter D, Gil S, Lowry CA, Vale WW, Chen A. A triple urocortin knockout mouse model reveals an essential role for urocortins in stress recovery. Proc Natl Acad Sci U S A.2010;107(44):19020-19025.
Chen A, Zorrilla E, Smith S, Rousso D, Levy C, Vaughan J, Donaldson C, Roberts A, Lee KF, Vale W. Urocortin 2-deficient mice exhibit gender-specific alterations in circadian hypothalamus-pituitary-adrenal axis and depressive-like behavior. J Neurosci. 2006;26(20):5500-5510.
Sugimoto T, Saito M, Mochizuki S, Watanabe Y, Hashimoto S, Kawashima H. Molecular cloning and functional expression of a cDNA encoding the human V1b vasopressin receptor. J Biol Chem. 1994;269(43):27088-27092.
Raymond V, Leung PC, Veilleux R, Labrie F. Vasopressin rapidly stimulates phosphatidic acid-phosphatidylinositol turnover in rat anterior pituitary cells. FEBS Lett. 1985;182(1):196-200.
Abou-Samra AB, Catt KJ, Aguilera G. Involvement of protein kinase C in the regulation of adrenocorticotropin release from rat anterior pituitary cells. Endocrinology. 1986;118(1):212-217.
Plotsky PM. Hypophysiotropic regulation of stress-induced ACTH secretion. Adv Exp Med Biol. 1988;245:65-81.
Bilezikjian LM, Woodgett JR, Hunter T, Vale WW. Phorbol ester-induced down-regulation of protein kinase C abolishes vasopressin-mediated responses in rat anterior pituitary cells. Mol Endocrinol. 1987;1(8):555-560.
Levin N, Blum M, Roberts JL. Modulation of basal and corticotropin-releasing factor-stimulated proopiomelanocortin gene expression by vasopressin in rat anterior pituitary. Endocrinology. 1989;125(6):2957-2966.
Morgenthaler NG, Struck J, Alonso C, Bergmann A. Assay for the measurement of copeptin, a stable peptide derived from the precursor of vasopressin. Clin Chem. 2006;52(1):112-119.
Lewandowski KC, Lewinski A, Skowronska-Jozwiak E, Stasiak M, Horzelski W, Brabant G. Copeptin under glucagon stimulation. Endocrine. 2016;52(2):344-351.
Kacheva S, Kolk K, Morgenthaler NG, Brabant G, Karges W. Gender-specific co-activation of arginine vasopressin and the hypothalamic-pituitary-adrenal axis during stress. Clin Endocrinol (Oxf). 2015;82(4):570-576.
Evans AN, Liu Y, Macgregor R, Huang V, Aguilera G. Regulation of hypothalamic corticotropin-releasing hormone transcription by elevated glucocorticoids. Mol Endocrinol. 2013;27(11):1796-1807.
Guardiola-Diaz HM, Kolinske JS, Gates LH, Seasholtz AF. Negative glucorticoid regulation of cyclic adenosine 3', 5'-monophosphate-stimulated corticotropin-releasing hormone-reporter expression in AtT-20 cells. Mol Endocrinol.1996;10(3):317-329.
Malkoski SP, Dorin RI. Composite glucocorticoid regulation at a functionally defined negative glucocorticoid response element of the human corticotropin-releasing hormone gene. Mol Endocrinol. 1999;13(10):1629-1644.
Malkoski SP, Handanos CM, Dorin RI. Localization of a negative glucocorticoid response element of the human corticotropin releasing hormone gene. Mol Cell Endocrinol. 1997;127(2):189-199.
Drouin J, Sun YL, Nemer M. Glucocorticoid repression of pro-opiomelanocortin gene transcription. J Steroid Biochem. 1989;34(1-6):63-69.
Drouin J, Trifiro MA, Plante RK, Nemer M, Eriksson P, Wrange O. Glucocorticoid receptor binding to a specific DNA sequence is required for hormone-dependent repression of pro-opiomelanocortin gene transcription. Mol Cell Biol. 1989;9(12):5305-5314.
Reul JM, de Kloet ER. Two receptor systems for corticosterone in rat brain: microdistribution and differential occupation. Endocrinology. 1985;117(6):2505-2511.
Reul JM, de Kloet ER. Anatomical resolution of two types of corticosterone receptor sites in rat brain with in vitro autoradiography and computerized image analysis. J Steroid Biochem. 1986;24(1):269-272.
Reul JM, van den Bosch FR, de Kloet ER. Relative occupation of type-I and type-II corticosteroid receptors in rat brain following stress and dexamethasone treatment: functional implications. The Journal of endocrinology.1987;115(3):459-467.
Edwards CR, Stewart PM, Burt D, Brett L, McIntyre MA, Sutanto WS, de Kloet ER, Monder C. Localisation of 11 beta-hydroxysteroid dehydrogenase--tissue specific protector of the mineralocorticoid receptor. Lancet.1988;2(8618):986-989.
Ratka A, Sutanto W, Bloemers M, de Kloet ER. On the role of brain mineralocorticoid (type I) and glucocorticoid (type II) receptors in neuroendocrine regulation. Neuroendocrinology. 1989;50(2):117-123.
van Haarst AD, Oitzl MS, de Kloet ER. Facilitation of feedback inhibition through blockade of glucocorticoid receptors in the hippocampus. Neurochem Res. 1997;22(11):1323-1328.
Brownstein MJ, Russell JT, Gainer H. Synthesis, transport, and release of posterior pituitary hormones. Science.1980;207(4429):373-378.
Legros JJ, Chiodera P, Demey-Ponsart E. Inhibitory influence of exogenous oxytocin on adrenocorticotropin secretion in normal human subjects. J Clin Endocrinol Metab. 1982;55(6):1035-1039.
Legros JJ, Chiodera P, Geenen V, von Frenckell R. Confirmation of the inhibitory influence of exogenous oxytocin on cortisol and ACTH in man: evidence of reproducibility. Acta Endocrinol (Copenh). 1987;114(3):345-349.
Lewis DA, Sherman BM. Oxytocin does not influence adrenocorticotropin secretion in man. J Clin Endocrinol Metab. 1985;60(1):53-56.
Antoni FA, Holmes MC, Kiss JZ. Pituitary binding of vasopressin is altered by experimental manipulations of the hypothalamo-pituitary-adrenocortical axis in normal as well as homozygous (di/di) Brattleboro rats. Endocrinology.1985;117(4):1293-1299.
Winter J, Jurek B. The interplay between oxytocin and the CRF system: regulation of the stress response. Cell Tissue Res. 2019;375(1):85-91.
Gibbs DM, Vale W, Rivier J, Yen SS. Oxytocin potentiates the ACTH-releasing activity of CRF(41) but not vasopressin. Life Sci. 1984;34(23):2245-2249.
Alexander LD, Evans K, Sander LD. A possible involvement of VIP in feeding-induced secretion of ACTH and corticosterone in the rat. Physiol Behav. 1995;58(2):409-413.
Alexander LD, Sander LD. Involvement of vasopressin and corticotropin-releasing hormone in VIP- and PHI-induced secretion of ACTH and corticosterone. Neuropeptides. 1995;28(3):167-173.
Jirikowski GF, Back H, Forssmann WG, Stumpf WE. Coexistence of atrial natriuretic factor (ANF) and oxytocin in neurons of the rat hypothalamus. Neuropeptides. 1986;8(3):243-249.
King MS, Baertschi AJ. Physiological concentrations of atrial natriuretic factors with intact N-terminal sequences inhibit corticotropin-releasing factor-stimulated adrenocorticotropin secretion from cultured anterior pituitary cells. Endocrinology. 1989;124(1):286-292.
Kellner M, Wiedemann K, Holsboer F. Atrial natriuretic factor inhibits the CRH-stimulated secretion of ACTH and cortisol in man. Life Sci. 1992;50(24):1835-1842.
Ur E, Faria M, Tsagarakis S, Anderson JV, Besser GM, Grossman A. Atrial natriuretic peptide in physiological doses does not inhibit the ACTH or cortisol response to corticotrophin-releasing hormone-41 in normal human subjects. J Endocrinol. 1991;131(1):163-167.
Taylor T, Dluhy RG, Williams GH. beta-endorphin suppresses adrenocorticotropin and cortisol levels in normal human subjects. J Clin Endocrinol Metab. 1983;57(3):592-596.
Tsagarakis S, Navarra P, Rees LH, Besser M, Grossman A, Navara P. Morphine directly modulates the release of stimulated corticotrophin-releasing factor-41 from rat hypothalamus in vitro [published erratum appears in Endocrinology 1989 Dec;125(6):3095]. Endocrinology. 1989;124(5):2330-2335.
Jackson RV, Grice JE, Hockings GI, Torpy DJ. Naloxone-induced ACTH release: mechanism of action in humans. Clin Endocrinol (Oxf). 1995;43(4):423-424.
Pagotto U, Marsicano G, Fezza F, Theodoropoulou M, Grubler Y, Stalla J, Arzberger T, Milone A, Losa M, Di Marzo V, Lutz B, Stalla GK. Normal human pituitary gland and pituitary adenomas express cannabinoid receptor type 1 and synthesize endogenous cannabinoids: first evidence for a direct role of cannabinoids on hormone modulation at the human pituitary level. J Clin Endocrinol Metab. 2001;86(6):2687-2696.
Wade MR, Degroot A, Nomikos GG. Cannabinoid CB1 receptor antagonism modulates plasma corticosterone in rodents. Eur J Pharmacol. 2006;551(1-3):162-167.
Cota D, Steiner MA, Marsicano G, Cervino C, Herman JP, Grubler Y, Stalla J, Pasquali R, Lutz B, Stalla GK, Pagotto U. Requirement of Cannabinoid Receptor Type 1 for the Basal Modulation of Hypothalamic-Pituitary-Adrenal Axis Function. Endocrinology. 2006.
Benowitz NL, Jones RT, Lerner CB. Depression of growth hormone and cortisol response to insulin-induced hypoglycemia after prolonged oral delta-9-tetrahydrocannabinol administration in man. J Clin Endocrinol Metab.1976;42(5):938-941.
al-Damluji S. Adrenergic control of the secretion of anterior pituitary hormones. Baillieres Clin Endocrinol Metab.1993;7(2):355-392.
Kostoglou-Athanassiou I, Costa A, Navarra P, Nappi G, Forsling ML, Grossman AB. Endotoxin stimulates an endogenous pathway regulating corticotropin-releasing hormone and vasopressin release involving the generation of nitric oxide and carbon monoxide. J Neuroimmunol. 1998;86(1):104-109.
Pozzoli G, Mancuso C, Mirtella A, Preziosi P, Grossman AB, Navarra P. Carbon monoxide as a novel neuroendocrine modulator: inhibition of stimulated corticotropin-releasing hormone release from acute rat hypothalamic explants. Endocrinology. 1994;135(6):2314-2317.
Korbonits M, Kaltsas G, Perry LA, Grossman AB, Monson JP, Besser GM, Trainer PJ. Hexarelin as a test of pituitary reserve in patients with pituitary disease. Clin Endocrinol (Oxf). 1999;51(3):369-375.
Korbonits M, Kaltsas G, Perry LA, Putignano P, Grossman AB, Besser GM, Trainer PJ. The growth hormone secretagogue hexarelin stimulates the hypothalamo-pituitary-adrenal axis via arginine vasopressin. J Clin Endocrinol Metab. 1999;84(7):2489-2495.
Arvat E, Maccario M, Di Vito L, Broglio F, Benso A, Gottero C, Papotti M, Muccioli G, Dieguez C, Casanueva FF, Deghenghi R, Camanni F, Ghigo E. Endocrine activities of ghrelin, a natural growth hormone secretagogue (GHS), in humans: comparison and interactions with hexarelin, a nonnatural peptidyl GHS, and GH-releasing hormone. J Clin Endocrinol Metab. 2001;86(3):1169-1174.
Mozid AM, Tringali G, Forsling ML, Hendricks MS, Ajodha S, Edwards R, Navarra P, Grossman AB, Korbonits M. Ghrelin is released from rat hypothalamic explants and stimulates corticotrophin-releasing hormone and arginine-vasopressin. Horm Metab Res. 2003;35(8):455-459.
Arvat E, di Vito L, Maccagno B, Broglio F, Boghen MF, Deghenghi R, Camanni F, Ghigo E. Effects of GHRP-2 and hexarelin, two synthetic GH-releasing peptides, on GH, prolactin, ACTH and cortisol levels in man. Comparison with the effects of GHRH, TRH and hCRH. Peptides. 1997;18(6):885-891.
Kimura T, Shimatsu A, Arimura H, Mori H, Tokitou A, Fukudome M, Nakazaki M, Tei C. Concordant and discordant adrenocorticotropin (ACTH) responses induced by growth hormone-releasing peptide-2 (GHRP-2), corticotropin-releasing hormone (CRH) and insulin-induced hypoglycemia in patients with hypothalamopituitary disorders: evidence for direct ACTH releasing activity of GHRP-2. Endocr J. 2010;57(7):639-644.
Perras B, Schultes B, Schwaiger R, Metz C, Wesseler W, Born J, Fehm HL. Growth hormone-releasing hormone facilitates hypoglycemia-induced release of cortisol. Regul Pept. 2002;110(1):85-91.
Zhang JV, Ren PG, Avsian-Kretchmer O, Luo CW, Rauch R, Klein C, Hsueh AJ. Obestatin, a peptide encoded by the ghrelin gene, opposes ghrelin's effects on food intake. Science. 2005;310(5750):996-999.
Yamamoto D, Ikeshita N, Daito R, Herningtyas EH, Toda K, Takahashi K, Iida K, Takahashi Y, Kaji H, Chihara K, Okimura Y. Neither intravenous nor intracerebroventricular administration of obestatin affects the secretion of GH, PRL, TSH and ACTH in rats. Regul Pept. 2007;138(2-3):141-144.
McKee KK, Tan CP, Palyha OC, Liu J, Feighner SD, Hreniuk DL, Smith RG, Howard AD, Van der Ploeg LH. Cloning and characterization of two human G protein-coupled receptor genes (GPR38 and GPR39) related to the growth hormone secretagogue and neurotensin receptors. Genomics. 1997;46(3):426-434.
Holst B, Egerod KL, Schild E, Vickers SP, Cheetham S, Gerlach LO, Storjohann L, Stidsen CE, Jones R, Beck-Sickinger AG, Schwartz TW. GPR39 signaling is stimulated by zinc ions but not by obestatin. Endocrinology.2007;148(1):13-20.
Luque RM, Cordoba-Chacon J, Ibanez-Costa A, Gesmundo I, Grande C, Gracia-Navarro F, Tena-Sempere M, Ghigo E, Gahete MD, Granata R, Kineman RD, Castano JP. Obestatin plays an opposite role in the regulation of pituitary somatotrope and corticotrope function in female primates and male/female mice. Endocrinology.2014:en20131728.
Gaillard RC, Favrod-Coune CA, Capponi AM, Muller AF. Corticotropin-releasing activity of the renin-angiotensin system peptides in rat and in man. Neuroendocrinology. 1985;41(6):511-517.
Rivier C, Vale W. Effect of angiotensin II on ACTH release in vivo: role of corticotropin-releasing factor. Regul Pept.1983;7(3):253-258.
Murakami K, Ganong WF. Site at which angiotensin II acts to stimulate ACTH secretion in vivo. Neuroendocrinology. 1987;46(3):231-235.
Sumitomo T, Suda T, Nakano Y, Tozawa F, Yamada M, Demura H. Angiotensin II increases the corticotropin-releasing factor messenger ribonucleic acid level in the rat hypothalamus. Endocrinology. 1991;128(5):2248-2252.
Armando I, Volpi S, Aguilera G, Saavedra JM. Angiotensin II AT1 receptor blockade prevents the hypothalamic corticotropin-releasing factor response to isolation stress. Brain Res. 2007;1142:92-99.
Armando I, Carranza A, Nishimura Y, Hoe KL, Barontini M, Terron JA, Falcon-Neri A, Ito T, Juorio AV, Saavedra JM. Peripheral administration of an angiotensin II AT(1) receptor antagonist decreases the hypothalamic-pituitary-adrenal response to isolation Stress. Endocrinology. 2001;142(9):3880-3889.
Strowski MZ, Dashkevicz MP, Parmar RM, Wilkinson H, Kohler M, Schaeffer JM, Blake AD. Somatostatin receptor subtypes 2 and 5 inhibit corticotropin-releasing hormone-stimulated adrenocorticotropin secretion from AtT-20 cells. Neuroendocrinology. 2002;75(6):339-346.
Lamberts SW, Zuyderwijk J, den Holder F, van Koetsveld P, Hofland L. Studies on the conditions determining the inhibitory effect of somatostatin on adrenocorticotropin, prolactin and thyrotropin release by cultured rat pituitary cells. Neuroendocrinology. 1989;50(1):44-50.
van der Hoek J, Waaijers M, van Koetsveld PM, Sprij-Mooij D, Feelders RA, Schmid HA, Schoeffter P, Hoyer D, Cervia D, Taylor JE, Culler MD, Lamberts SW, Hofland LJ. Distinct functional properties of native somatostatin receptor subtype 5 compared with subtype 2 in the regulation of ACTH release by corticotroph tumor cells. Am J Physiol Endocrinol Metab. 2005;289(2):E278-287.
Silva AP, Schoeffter P, Weckbecker G, Bruns C, Schmid HA. Regulation of CRH-induced secretion of ACTH and corticosterone by SOM230 in rats. Eur J Endocrinol. 2005;153(3):R7-R10.
Stafford PJ, Kopelman PG, Davidson K, McLoughlin L, White A, Rees LH, Besser GM, Coy DH, Grossman A. The pituitary-adrenal response to CRF-41 is unaltered by intravenous somatostatin in normal subjects. Clin Endocrinol (Oxf). 1989;30(6):661-666.
Fehm HL, Voigt KH, Lang R, Beinert KE, Raptis S, Pfeiffer EF. Somatostatin: a potent inhibitor of ACTH-hypersecretion in adrenal insufficiency. Klin Wochenschr. 1976;54(4):173-175.
de Bruin C, Pereira AM, Feelders RA, Romijn JA, Roelfsema F, Sprij-Mooij DM, van Aken MO, van der Lelij AJ, de Herder WW, Lamberts SW, Hofland LJ. Coexpression of dopamine and somatostatin receptor subtypes in corticotroph adenomas. J Clin Endocrinol Metab. 2009;94(4):1118-1124.
Hofland LJ, van der Hoek J, Feelders R, van Aken MO, van Koetsveld PM, Waaijers M, Sprij-Mooij D, Bruns C, Weckbecker G, de Herder WW, Beckers A, Lamberts SW. The multi-ligand somatostatin analogue SOM230 inhibits ACTH secretion by cultured human corticotroph adenomas via somatostatin receptor type 5. Eur J Endocrinol. 2005;152(4):645-654.
Feelders RA, de Bruin C, Pereira AM, Romijn JA, Netea-Maier RT, Hermus AR, Zelissen PM, van Heerebeek R, de Jong FH, van der Lely AJ, de Herder WW, Hofland LJ, Lamberts SW. Pasireotide alone or with cabergoline and ketoconazole in Cushing's disease. N Engl J Med. 2010;362(19):1846-1848.
de Herder WW, Lamberts SW. Is there a role for somatostatin and its analogs in Cushing's syndrome? Metabolism. 1996;45(8 Suppl 1):83-85.
Redei E, Hilderbrand H, Aird F. Corticotropin release inhibiting factor is encoded within prepro-TRH. Endocrinology. 1995;136(4):1813-1816.
Redei E, Hilderbrand H, Aird F. Corticotropin release-inhibiting factor is preprothyrotropin-releasing hormone-(178-199). Endocrinology. 1995;136(8):3557-3563.
Nicholson WE, Orth DN. Preprothyrotropin-releasing hormone-(178-199) does not inhibit corticotropin release. Endocrinology. 1996;137(5):2171-2174.
Gershengorn MC, Arevalo CO, Geras E, Rebecchi MJ. Thyrotropin-releasing hormone stimulation of adrenocorticotropin production by mouse pituitary tumor cells in culture: possible model for anomalous release of adrenocorticotropin by thyrotropin-releasing hormone in some patients with Cushing's disease and Nelson's syndrome. J Clin Invest. 1980;65(6):1294-1300.
Bernardini R, Kamilaris TC, Calogero AE, Johnson EO, Gomez MT, Gold PW, Chrousos GP. Interactions between tumor necrosis factor-alpha, hypothalamic corticotropin-releasing hormone, and adrenocorticotropin secretion in the rat. Endocrinology. 1990;126(6):2876-2881.
Perlstein RS, Mougey EH, Jackson WE, Neta R. Interleukin-1 and interleukin-6 act synergistically to stimulate the release of adrenocorticotropic hormone in vivo. Lymphokine Cytokine Res. 1991;10(1-2):141-146.
Uehara A, Gottschall PE, Dahl RR, Arimura A. Stimulation of ACTH release by human interleukin-1 beta, but not by interleukin-1 alpha, in conscious, freely-moving rats. Biochem Biophys Res Commun. 1987;146(3):1286-1290.
Uehara A, Gottschall PE, Dahl RR, Arimura A. Interleukin-1 stimulates ACTH release by an indirect action which requires endogenous corticotropin releasing factor. Endocrinology. 1987;121(4):1580-1582.
Besedovsky HO, del Rey A. Immune-neuro-endocrine interactions: facts and hypotheses. Endocr Rev.1996;17(1):64-102.
Murdoch GH, Potter E, Nicolaisen AK, Evans RM, Rosenfeld MG. Epidermal growth factor rapidly stimulates prolactin gene transcription. Nature. 1982;300(5888):192-194.
Kontogeorgos G, Stefaneanu L, Kovacs K, Cheng Z. Localization of Epidermal Growth Factor (EGF) and Epidermal Growth Factor Receptor (EGFr) in Human Pituitary Adenomas and Nontumorous Pituitaries: An Immunocytochemical Study. Endocr Pathol. 1996;7(1):63-70.
Reincke M, Sbiera S, Hayakawa A, Theodoropoulou M, Osswald A, Beuschlein F, Meitinger T, Mizuno-Yamasaki E, Kawaguchi K, Saeki Y, Tanaka K, Wieland T, Graf E, Saeger W, Ronchi CL, Allolio B, Buchfelder M, Strom TM, Fassnacht M, Komada M. Mutations in the deubiquitinase gene USP8 cause Cushing's disease. Nat Genet.2015;47(1):31-38.
Araki T, Liu X, Kameda H, Tone Y, Fukuoka H, Tone M, Melmed S. EGFR Induces E2F1-Mediated Corticotroph Tumorigenesis. J Endocr Soc. 2017;1(2):127-143.
Fukuoka H, Cooper O, Ben-Shlomo A, Mamelak A, Ren SG, Bruyette D, Melmed S. EGFR as a therapeutic target for human, canine, and mouse ACTH-secreting pituitary adenomas. The Journal of clinical investigation.2011;121(12):4712-4721.
Perez-Rivas LG, Theodoropoulou M, Ferrau F, Nusser C, Kawaguchi K, Stratakis CA, Faucz FR, Wildemberg LE, Assie G, Beschorner R, Dimopoulou C, Buchfelder M, Popovic V, Berr CM, Toth M, Ardisasmita AI, Honegger J, Bertherat J, Gadelha MR, Beuschlein F, Stalla G, Komada M, Korbonits M, Reincke M. The Gene of the Ubiquitin-Specific Protease 8 Is Frequently Mutated in Adenomas Causing Cushing's Disease. J Clin Endocrinol Metab.2015;100(7):E997-1004.
Perez-Rivas LG, Osswald A, Knosel T, Lucia K, Schaaf C, Hristov M, Fazel J, Kirchner T, Beuschlein F, Reincke M, Theodoropoulou M. Expression and mutational status of USP8 in tumors causing ectopic ACTH secretion syndrome. Endocr Relat Cancer. 2017;24(9):L73-L77.
Veldhuis JD, Iranmanesh A, Johnson ML, Lizarralde G. Amplitude, but not frequency, modulation of adrenocorticotropin secretory bursts gives rise to the nyctohemeral rhythm of the corticotropic axis in man. J Clin Endocrinol Metab. 1990;71(2):452-463.
Krishnan KR, Ritchie JC, Saunders W, Wilson W, Nemeroff CB, Carroll BJ. Nocturnal and early morning secretion of ACTH and cortisol in humans. Biol Psychiatry. 1990;28(1):47-57.
Desir D, Van Cauter E, Beyloos M, Bosson D, Golstein J, Copinschi G. Prolonged pulsatile administration of ovine corticotropin-releasing hormone in normal man. J Clin Endocrinol Metab. 1986;63(6):1292-1299.
Gambacciani M, Liu JH, Swartz WH, Tueros VS, Rasmussen DD, Yen SS. Intrinsic pulsatility of ACTH release from the human pituitary in vitro. Clin Endocrinol (Oxf). 1987;26(5):557-563.
Walker JJ, Spiga F, Waite E, Zhao Z, Kershaw Y, Terry JR, Lightman SL. The origin of glucocorticoid hormone oscillations. PLoS Biol. 2012;10(6):e1001341.
Spiga F, Waite EJ, Liu Y, Kershaw YM, Aguilera G, Lightman SL. ACTH-dependent ultradian rhythm of corticosterone secretion. Endocrinology. 2011;152(4):1448-1457.
Hazell G, Horn G, Lightman SL, Spiga F. Dynamics of ACTH-Mediated Regulation of Gene Transcription in ATC1 and ATC7 Adrenal Zona Fasciculata Cell Lines. Endocrinology. 2019;160(3):587-604.
Henley DE, Leendertz JA, Russell GM, Wood SA, Taheri S, Woltersdorf WW, Lightman SL. Development of an automated blood sampling system for use in humans. J Med Eng Technol. 2009;33(3):199-208.
Upton TJ, Zavala E, Methlie P, Kampe O, Tsagarakis S, Oksnes M, Bensing S, Vassiliadi DA, Grytaas MA, Botusan IR, Ueland G, Berinder K, Simunkova K, Balomenaki M, Margaritopoulos D, Henne N, Crossley R, Russell G, Husebye ES, Lightman SL. High-resolution daily profiles of tissue adrenal steroids by portable automated collection. Sci Transl Med. 2023;15(701):eadg8464.
Kiessling S, Eichele G, Oster H. Adrenal glucocorticoids have a key role in circadian resynchronization in a mouse model of jet lag. J Clin Invest. 2010;120(7):2600-2609.
Moore RY, Eichler VB. Loss of a circadian adrenal corticosterone rhythm following suprachiasmatic lesions in the rat. Brain Res. 1972;42(1):201-206.
Dunlap JC. Molecular bases for circadian clocks. Cell. 1999;96(2):271-290.
Koch CE, Leinweber B, Drengberg BC, Blaum C, Oster H. Interaction between circadian rhythms and stress. Neurobiol Stress. 2017;6:57-67.
Kornhauser JM, Nelson DE, Mayo KE, Takahashi JS. Photic and circadian regulation of c-fos gene expression in the hamster suprachiasmatic nucleus. Neuron. 1990;5(2):127-134.
Kornhauser JM, Nelson DE, Mayo KE, Takahashi JS. Regulation of jun-B messenger RNA and AP-1 activity by light and a circadian clock. Science. 1992;255(5051):1581-1584.
Crosio C, Cermakian N, Allis CD, Sassone-Corsi P. Light induces chromatin modification in cells of the mammalian circadian clock. Nat Neurosci. 2000;3(12):1241-1247.
Leliavski A, Shostak A, Husse J, Oster H. Impaired glucocorticoid production and response to stress in Arntl-deficient male mice. Endocrinology. 2014;155(1):133-142.
Turek FW, Joshu C, Kohsaka A, Lin E, Ivanova G, McDearmon E, Laposky A, Losee-Olson S, Easton A, Jensen DR, Eckel RH, Takahashi JS, Bass J. Obesity and metabolic syndrome in circadian Clock mutant mice. Science.2005;308(5724):1043-1045.
Yang S, Liu A, Weidenhammer A, Cooksey RC, McClain D, Kim MK, Aguilera G, Abel ED, Chung JH. The role of mPer2 clock gene in glucocorticoid and feeding rhythms. Endocrinology. 2009;150(5):2153-2160.
Barclay JL, Shostak A, Leliavski A, Tsang AH, Johren O, Muller-Fielitz H, Landgraf D, Naujokat N, van der Horst GT, Oster H. High-fat diet-induced hyperinsulinemia and tissue-specific insulin resistance in Cry-deficient mice. Am J Physiol Endocrinol Metab. 2013;304(10):E1053-1063.
Lamia KA, Papp SJ, Yu RT, Barish GD, Uhlenhaut NH, Jonker JW, Downes M, Evans RM. Cryptochromes mediate rhythmic repression of the glucocorticoid receptor. Nature. 2011;480(7378):552-556.
Watabe T, Tanaka K, Kumagae M, Itoh S, Hasegawa M, Horiuchi T, Miyabe S, Ohno H, Shimizu N. Diurnal rhythm of plasma immunoreactive corticotropin-releasing factor in normal subjects. Life Sci. 1987;40(17):1651-1655.
Cai A, Wise PM. Age-related changes in the diurnal rhythm of CRH gene expression in the paraventricular nuclei. Am J Physiol. 1996;270(2 Pt 1):E238-243.
Cunnah D, Jessop DS, Besser GM, Rees LH. Measurement of circulating corticotrophin-releasing factor in man. J Endocrinol. 1987;113(1):123-131.
Ur E, Capstick C, McLoughlin L, Checkley S, Besser GM, Grossman A. Continuous administration of human corticotropin-releasing hormone in the absence of glucocorticoid feedback in man. Neuroendocrinology.1995;61(2):191-197.
Yamase K, Takahashi S, Nomura K, Haruta K, Kawashima S. Circadian changes in arginine vasopressin level in the suprachiasmatic nuclei in the rat. Neurosci Lett. 1991;130(2):255-258.
Jin X, Shearman LP, Weaver DR, Zylka MJ, de Vries GJ, Reppert SM. A molecular mechanism regulating rhythmic output from the suprachiasmatic circadian clock. Cell. 1999;96(1):57-68.
Fahrenkrug J, Hannibal J, Georg B. Diurnal rhythmicity of the canonical clock genes Per1, Per2 and Bmal1 in the rat adrenal gland is unaltered after hypophysectomy. J Neuroendocrinol. 2008;20(3):323-329.
Ishida A, Mutoh T, Ueyama T, Bando H, Masubuchi S, Nakahara D, Tsujimoto G, Okamura H. Light activates the adrenal gland: timing of gene expression and glucocorticoid release. Cell Metab. 2005;2(5):297-307.
Oster H, Damerow S, Hut RA, Eichele G. Transcriptional profiling in the adrenal gland reveals circadian regulation of hormone biosynthesis genes and nucleosome assembly genes. J Biol Rhythms. 2006;21(5):350-361.
Yoder JM, Brandeland M, Engeland WC. Phase-dependent resetting of the adrenal clock by ACTH in vitro. Am J Physiol Regul Integr Comp Physiol. 2014;306(6):R387-393.
Plotsky PM, Bruhn TO, Vale W. Hypophysiotropic regulation of adrenocorticotropin secretion in response to insulin-induced hypoglycemia. Endocrinology. 1985;117(1):323-329.
Plotsky PM, Bruhn TO, Vale W. Evidence for multifactor regulation of the adrenocorticotropin secretory response to hemodynamic stimuli. Endocrinology. 1985;116(2):633-639.
Berkenbosch F, De Goeij DC, Tilders FJ. Hypoglycemia enhances turnover of corticotropin-releasing factor and of vasopressin in the zona externa of the rat median eminence. Endocrinology. 1989;125(1):28-34.
Jones BJ, Tan T, Bloom SR. Minireview: Glucagon in stress and energy homeostasis. Endocrinology.2012;153(3):1049-1054.
Meeran K, Hattersley A, Mould G, Bloom SR. Venepuncture causes rapid rise in plasma ACTH. Br J Clin Pract.1993;47(5):246-247.
Plumpton FS, Besser GM. The adrenocortical response to surgery and insulin-induced hypoglycaemia in corticosteroid-treated and normal subjects. Br J Surg. 1969;56(3):216-219.
Plumpton FS, Besser GM, Cole PV. Corticosteroid treatment and surgery. 1. An investigation of the indications for steroid cover. Anaesthesia. 1969;24(1):3-11.
Plumpton FS, Besser GM, Cole PV. Corticosteroid treatment and surgery. 2. The management of steroid cover. Anaesthesia. 1969;24(1):12-18.
Khoo B, Boshier PR, Freethy A, Tharakan G, Saeed S, Hill N, Williams EL, Moorthy K, Tolley N, Jiao LR, Spalding D, Palazzo F, Meeran K, Tan T. Redefining the stress cortisol response to surgery. Clin Endocrinol (Oxf). 2017.
Ma XM, Levy A, Lightman SL. Rapid changes in heteronuclear RNA for corticotrophin-releasing hormone and arginine vasopressin in response to acute stress. J Endocrinol. 1997;152(1):81-89.
Ma XM, Aguilera G. Transcriptional responses of the vasopressin and corticotropin-releasing hormone genes to acute and repeated intraperitoneal hypertonic saline injection in rats. Brain Res Mol Brain Res. 1999;68(1-2):129-140.
Kim CK, Rivier CL. Nitric oxide and carbon monoxide have a stimulatory role in the hypothalamic-pituitary-adrenal response to physico-emotional stressors in rats. Endocrinology. 2000;141(6):2244-2253.
Bernstein HG, Keilhoff G, Seidel B, Stanarius A, Huang PL, Fishman MC, Reiser M, Bogerts B, Wolf G. Expression of hypothalamic peptides in mice lacking neuronal nitric oxide synthase: reduced beta-END immunoreactivity in the arcuate nucleus. Neuroendocrinology. 1998;68(6):403-411.
Yamada K, Emson P, Hokfelt T. Immunohistochemical mapping of nitric oxide synthase in the rat hypothalamus and colocalization with neuropeptides. J Chem Neuroanat. 1996;10(3-4):295-316.
Keilhoff G, Seidel B, Reiser M, Stanarius A, Huang PL, Bogerts B, Wolf G, Bernstein HG. Lack of neuronal NOS has consequences for the expression of POMC and POMC-derived peptides in the mouse pituitary. Acta Histochem. 2001;103(4):397-412.
Bale TL, Contarino A, Smith GW, Chan R, Gold LH, Sawchenko PE, Koob GF, Vale WW, Lee KF. Mice deficient for corticotropin-releasing hormone receptor-2 display anxiety-like behaviour and are hypersensitive to stress. Nat Genet. 2000;24(4):410-414.
Coste SC, Kesterson RA, Heldwein KA, Stevens SL, Heard AD, Hollis JH, Murray SE, Hill JK, Pantely GA, Hohimer AR, Hatton DC, Phillips TJ, Finn DA, Low MJ, Rittenberg MB, Stenzel P, Stenzel-Poore MP. Abnormal adaptations to stress and impaired cardiovascular function in mice lacking corticotropin-releasing hormone receptor-2. Nat Genet. 2000;24(4):403-409.
Aguilera G, Rabadan-Diehl C. Vasopressinergic regulation of the hypothalamic-pituitary-adrenal axis: implications for stress adaptation. Regul Pept. 2000;96(1-2):23-29.
Michalaki M, Margeli T, Tsekouras A, Gogos CH, Vagenakis AG, Kyriazopoulou V. Hypothalamic-pituitary-adrenal axis response to the severity of illness in non-critically ill patients: does relative corticosteroid insufficiency exist? Eur J Endocrinol. 2010;162(2):341-347.
Tan T, Khoo B, Mills EG, Phylactou M, Patel B, Eng PC, Thurston L, Muzi B, Meeran K, Prevost AT, Comninos AN, Abbara A, Dhillo WS. Association between high serum total cortisol concentrations and mortality from COVID-19. Lancet Diabetes Endocrinol. 2020.
Dumbell R, Matveeva O, Oster H. Circadian Clocks, Stress, and Immunity. Front Endocrinol (Lausanne).2016;7:37.
Itoi K, Mouri T, Takahashi K, Murakami O, Imai Y, Sasaki S, Yoshinaga K, Sasano N. Suppression by glucocorticoid of the immunoreactivity of corticotropin-releasing factor and vasopressin in the paraventricular nucleus of rat hypothalamus. Neurosci Lett. 1987;73(3):231-236.
Davis LG, Arentzen R, Reid JM, Manning RW, Wolfson B, Lawrence KL, Baldino F, Jr. Glucocorticoid sensitivity of vasopressin mRNA levels in the paraventricular nucleus of the rat. Proc Natl Acad Sci U S A. 1986;83(4):1145-1149.
Abou-Samra AB, Catt KJ, Aguilera G. Biphasic inhibition of adrenocorticotropin release by corticosterone in cultured anterior pituitary cells. Endocrinology. 1986;119(3):972-977.
Russell GM, Henley DE, Leendertz J, Douthwaite JA, Wood SA, Stevens A, Woltersdorf WW, Peeters BW, Ruigt GS, White A, Veldhuis JD, Lightman SL. Rapid glucocorticoid receptor-mediated inhibition of hypothalamic-pituitary-adrenal ultradian activity in healthy males. J Neurosci. 2010;30(17):6106-6115.
Dallman MF, Akana SF, Cascio CS, Darlington DN, Jacobson L, Levin N. Regulation of ACTH secretion: variations on a theme of B. Recent Prog Horm Res. 1987;43:113-173.
Keller-Wood ME, Dallman MF. Corticosteroid inhibition of ACTH secretion. Endocr Rev. 1984;5(1):1-24.
Deng Q, Riquelme D, Trinh L, Low MJ, Tomic M, Stojilkovic S, Aguilera G. Rapid Glucocorticoid Feedback Inhibition of ACTH Secretion Involves Ligand-Dependent Membrane Association of Glucocorticoid Receptors. Endocrinology. 2015;156(9):3215-3227.
Taylor AD, Cowell AM, Flower J, Buckingham JC. Lipocortin 1 mediates an early inhibitory action of glucocorticoids on the secretion of ACTH by the rat anterior pituitary gland in vitro. Neuroendocrinology. 1993;58(4):430-439.
Morris DG, Kola B, Borboli N, Kaltsas GA, Gueorguiev M, McNicol AM, Ferrier R, Jones TH, Baldeweg S, Powell M, Czirjak S, Hanzely Z, Johansson JO, Korbonits M, Grossman AB. Identification of adrenocorticotropin receptor messenger ribonucleic acid in the human pituitary and its loss of expression in pituitary adenomas. J Clin Endocrinol Metab. 2003;88(12):6080-6087.
Drouin J, Bilodeau S, Vallette S. Of old and new diseases: genetics of pituitary ACTH excess (Cushing) and deficiency. Clin Genet. 2007;72(3):175-182.
Bilodeau S, Vallette-Kasic S, Gauthier Y, Figarella-Branger D, Brue T, Berthelet F, Lacroix A, Batista D, Stratakis C, Hanson J, Meij B, Drouin J. Role of Brg1 and HDAC2 in GR trans-repression of the pituitary POMC gene and misexpression in Cushing disease. Genes Dev. 2006;20(20):2871-2886.
Suda T, Tomori N, Yajima F, Ushiyama T, Sumitomo T, Nakagami Y, Demura H, Shizume K. A short negative feedback mechanism regulating corticotropin-releasing hormone release. J Clin Endocrinol Metab. 1987;64(5):909-913.
Sawchenko PE, Arias C. Evidence for short-loop feedback effects of ACTH on CRF and vasopressin expression in parvocellular neurosecretory neurons. J Neuroendocrinol. 1995;7(9):721-731.
Roussel-Gervais A, Couture C, Langlais D, Takayasu S, Balsalobre A, Rueda BR, Zukerberg LR, Figarella-Branger D, Brue T, Drouin J. The Cables1 Gene in Glucocorticoid Regulation of Pituitary Corticotrope Growth and Cushing Disease. J Clin Endocrinol Metab. 2016;101(2):513-522.
Quigley ME, Yen SS. A mid-day surge in cortisol levels. J Clin Endocrinol Metab. 1979;49(6):945-947.
Follenius M, Brandenberger G, Hietter B. Diurnal cortisol peaks and their relationships to meals. J Clin Endocrinol Metab. 1982;55(4):757-761.
Stimson RH, Mohd-Shukri NA, Bolton JL, Andrew R, Reynolds RM, Walker BR. The postprandial rise in plasma cortisol in men is mediated by macronutrient-specific stimulation of adrenal and extra-adrenal cortisol production. J Clin Endocrinol Metab. 2014;99(1):160-168.
Al-Damluji S, Iveson T, Thomas JM, Pendlebury DJ, Rees LH, Besser GM. Food-induced cortisol secretion is mediated by central alpha-1 adrenoceptor modulation of pituitary ACTH secretion. Clin Endocrinol (Oxf).1987;26(5):629-636.
Korbonits M, Trainer PJ, Nelson ML, Howse I, Kopelman PG, Besser GM, Grossman AB, Svec F. Differential stimulation of cortisol and dehydroepiandrosterone levels by food in obese and normal subjects: relation to body fat distribution. Clin Endocrinol (Oxf). 1996;45(6):699-706.
Wake DJ, Homer NZ, Andrew R, Walker BR. Acute in vivo regulation of 11beta-hydroxysteroid dehydrogenase type 1 activity by insulin and intralipid infusions in humans. J Clin Endocrinol Metab. 2006;91(11):4682-4688.
Benedict C, Hallschmid M, Scheibner J, Niemeyer D, Schultes B, Merl V, Fehm HL, Born J, Kern W. Gut protein uptake and mechanisms of meal-induced cortisol release. J Clin Endocrinol Metab. 2005;90(3):1692-1696.
Larsen PJ, Tang-Christensen M, Jessop DS. Central administration of glucagon-like peptide-1 activates hypothalamic neuroendocrine neurons in the rat. Endocrinology. 1997;138(10):4445-4455.
Ryan AS, Egan JM, Habener JF, Elahi D. Insulinotropic hormone glucagon-like peptide-1-(7-37) appears not to augment insulin-mediated glucose uptake in young men during euglycemia. J Clin Endocrinol Metab.1998;83(7):2399-2404.
Gil-Lozano M, Perez-Tilve D, Alvarez-Crespo M, Martis A, Fernandez AM, Catalina PA, Gonzalez-Matias LC, Mallo F. GLP-1(7-36)-amide and Exendin-4 stimulate the HPA axis in rodents and humans. Endocrinology.2010;151(6):2629-2640.
Lacroix A, Bolte E, Tremblay J, Dupre J, Poitras P, Fournier H, Garon J, Garrel D, Bayard F, Taillefer R, et al. Gastric inhibitory polypeptide-dependent cortisol hypersecretion--a new cause of Cushing's syndrome. N Engl J Med. 1992;327(14):974-980.
Gogebakan O, Andres J, Biedasek K, Mai K, Kuhnen P, Krude H, Isken F, Rudovich N, Osterhoff MA, Kintscher U, Nauck M, Pfeiffer AF, Spranger J. Glucose-dependent insulinotropic polypeptide reduces fat-specific expression and activity of 11beta-hydroxysteroid dehydrogenase type 1 and inhibits release of free fatty acids. Diabetes.2012;61(2):292-300.
Swaab DF, Bao AM, Lucassen PJ. The stress system in the human brain in depression and neurodegeneration. Ageing Res Rev. 2005;4(2):141-194.
Ferrari E, Magri F. Role of neuroendocrine pathways in cognitive decline during aging. Ageing Res Rev.2008;7(3):225-233.
Aguilera G. HPA axis responsiveness to stress: implications for healthy aging. Exp Gerontol. 2011;46(2-3):90-95.
Kasckow JW, Lupien SJ, Behan DP, Welge J, Hauger RJ. Circulating human corticotropin-releasing factor-binding protein levels following cortisol infusions. Life Sci. 2001;69(2):133-142.
Tizabi Y, Aguilera G, Gilad GM. Age-related reduction in pituitary corticotropin-releasing hormone receptors in two rat strains. Neurobiol Aging. 1992;13(2):227-230.
Lupien S, Lecours AR, Schwartz G, Sharma S, Hauger RL, Meaney MJ, Nair NP. Longitudinal study of basal cortisol levels in healthy elderly subjects: evidence for subgroups. Neurobiol Aging. 1996;17(1):95-105.
Linkowski P, Van Onderbergen A, Kerkhofs M, Bosson D, Mendlewicz J, Van Cauter E. Twin study of the 24-h cortisol profile: evidence for genetic control of the human circadian clock. Am J Physiol. 1993;264(2 Pt 1):E173-181.
Franz CE, York TP, Eaves LJ, Mendoza SP, Hauger RL, Hellhammer DH, Jacobson KC, Levine S, Lupien SJ, Lyons MJ, Prom-Wormley E, Xian H, Kremen WS. Genetic and environmental influences on cortisol regulation across days and contexts in middle-aged men. Behav Genet. 2010;40(4):467-479.
Cai A, Scarbrough K, Hinkle DA, Wise PM. Fetal grafts containing suprachiasmatic nuclei restore the diurnal rhythm of CRH and POMC mRNA in aging rats. Am J Physiol. 1997;273(5 Pt 2):R1764-1770.
Cooper MS. 11beta-Hydroxysteroid dehydrogenase: a regulator of glucocorticoid response in osteoporosis. J Endocrinol Invest. 2008;31(7 Suppl):16-21.
Holmes MC, Carter RN, Noble J, Chitnis S, Dutia A, Paterson JM, Mullins JJ, Seckl JR, Yau JL. 11beta-hydroxysteroid dehydrogenase type 1 expression is increased in the aged mouse hippocampus and parietal cortex and causes memory impairments. J Neurosci. 2010;30(20):6916-6920.
Lesniewska B, Miskowiak B, Nowak M, Malendowicz LK. Sex differences in adrenocortical structure and function. XXVII. The effect of ether stress on ACTH and corticosterone in intact, gonadectomized, and testosterone- or estradiol-replaced rats. Res Exp Med (Berl). 1990;190(2):95-103.
Lesniewska B, Nowak M, Malendowicz LK. Sex differences in adrenocortical structure and function. XXVIII. ACTH and corticosterone in intact, gonadectomised and gonadal hormone replaced rats. Horm Metab Res.1990;22(7):378-381.
Jezova D, Kvetnansky R, Vigas M. Sex differences in endocrine response to hyperthermia in sauna. Acta Physiol Scand. 1994;150(3):293-298.
Jezova D, Jurankova E, Mosnarova A, Kriska M, Skultetyova I. Neuroendocrine response during stress with relation to gender differences. Acta Neurobiol Exp (Wars). 1996;56(3):779-785.
Vamvakopoulos NC, Chrousos GP. Evidence of direct estrogenic regulation of human corticotropin-releasing hormone gene expression. Potential implications for the sexual dimophism of the stress response and immune/inflammatory reaction. J Clin Invest. 1993;92(4):1896-1902.
Kirschbaum C, Wust S, Faig HG, Hellhammer DH. Heritability of cortisol responses to human corticotropin-releasing hormone, ergometry, and psychological stress in humans. J Clin Endocrinol Metab. 1992;75(6):1526-1530.
Matthews KA, Gump BB, Owens JF. Chronic stress influences cardiovascular and neuroendocrine responses during acute stress and recovery, especially in men. Health Psychol. 2001;20(6):403-410.
Holsboer F. The corticosteroid receptor hypothesis of depression. Neuropsychopharmacology. 2000;23(5):477-501.
Pariante CM. Why are depressed patients inflamed? A reflection on 20 years of research on depression, glucocorticoid resistance and inflammation. Eur Neuropsychopharmacol. 2017;27(6):554-559.
Beck-Friis J, Ljunggren JG, Thoren M, von Rosen D, Kjellman BF, Wetterberg L. Melatonin, cortisol and ACTH in patients with major depressive disorder and healthy humans with special reference to the outcome of the dexamethasone suppression test. Psychoneuroendocrinology. 1985;10(2):173-186.
Reus VI, Joseph M, Dallman M. Regulation of ACTH and cortisol in depression. Peptides. 1983;4(5):785-788.
Dziurkowska E, Wesolowski M. Cortisol as a Biomarker of Mental Disorder Severity. J Clin Med. 2021;10(21).
Nemeroff CB, Krishnan KR, Reed D, Leder R, Beam C, Dunnick NR. Adrenal gland enlargement in major depression. A computed tomographic study. Arch Gen Psychiatry. 1992;49(5):384-387.
Rubin RT, Phillips JJ, Sadow TF, McCracken JT. Adrenal gland volume in major depression. Increase during the depressive episode and decrease with successful treatment. Arch Gen Psychiatry. 1995;52(3):213-218.
Holsboer F, von Bardeleben U, Wiedemann K, Muller OA, Stalla GK. Serial assessment of corticotropin-releasing hormone response after dexamethasone in depression. Implications for pathophysiology of DST nonsuppression. Biol Psychiatry. 1987;22(2):228-234.
Young EA, Haskett RF, Murphy-Weinberg V, Watson SJ, Akil H. Loss of glucocorticoid fast feedback in depression. Arch Gen Psychiatry. 1991;48(8):693-699.
Young EA, Carlson NE, Brown MB. Twenty-four-hour ACTH and cortisol pulsatility in depressed women. Neuropsychopharmacology. 2001;25(2):267-276.
Amasi-Hartoonian N, Sforzini L, Cattaneo A, Pariante CM. Cause or consequence? Understanding the role of cortisol in the increased inflammation observed in depression. Curr Opin Endocr Metab Res. 2022;24:100356.
Misiak B, Loniewski I, Marlicz W, Frydecka D, Szulc A, Rudzki L, Samochowiec J. The HPA axis dysregulation in severe mental illness: Can we shift the blame to gut microbiota? Prog Neuropsychopharmacol Biol Psychiatry.2020;102:109951.
Huang MC, Chuang SC, Tseng MM, Chien YL, Liao SC, Chen HC, Kuo PH. Cortisol awakening response in patients with bipolar disorder during acute episodes and partial remission: A pilot study. Psychiatry Res.2017;258:594-597.
Walker EF, Brennan PA, Esterberg M, Brasfield J, Pearce B, Compton MT. Longitudinal changes in cortisol secretion and conversion to psychosis in at-risk youth. J Abnorm Psychol. 2010;119(2):401-408.
Labad J, Stojanovic-Perez A, Montalvo I, Sole M, Cabezas A, Ortega L, Moreno I, Vilella E, Martorell L, Reynolds RM, Gutierrez-Zotes A. Stress biomarkers as predictors of transition to psychosis in at-risk mental states: roles for cortisol, prolactin and albumin. J Psychiatr Res. 2015;60:163-169.
Shah JL, Malla AK. Much ado about much: stress, dynamic biomarkers and HPA axis dysregulation along the trajectory to psychosis. Schizophr Res. 2015;162(1-3):253-260.
Chaumette B, Kebir O, Mam-Lam-Fook C, Morvan Y, Bourgin J, Godsil BP, Plaze M, Gaillard R, Jay TM, Krebs MO. Salivary cortisol in early psychosis: New findings and meta-analysis. Psychoneuroendocrinology.2016;63:262-270.
Nordholm D, Rostrup E, Mondelli V, Randers L, Nielsen MO, Wulff S, Norbak-Emig H, Broberg BV, Krakauer K, Dazzan P, Zunszain PA, Nordentoft M, Glenthoj B. Multiple measures of HPA axis function in ultra high risk and first-episode schizophrenia patients. Psychoneuroendocrinology. 2018;92:72-80.
Corcoran CM, Smith C, McLaughlin D, Auther A, Malaspina D, Cornblatt B. HPA axis function and symptoms in adolescents at clinical high risk for schizophrenia. Schizophr Res. 2012;135(1-3):170-174.
Horvath E, Kovacs K. Fine structural cytology of the adenohypophysis in rat and man. J Electron Microsc Tech.1988;8(4):401-432.
Cohen LE, Radovick S. Molecular basis of combined pituitary hormone deficiencies. Endocr Rev. 2002;23(4):431-442.
Kapali J, Kabat BE, Schmidt KL, Stallings CE, Tippy M, Jung DO, Edwards BS, Nantie LB, Raeztman LT, Navratil AM, Ellsworth BS. Foxo1 Is Required for Normal Somatotrope Differentiation. Endocrinology. 2016;157(11):4351-4363.
Zhu X, Zhang J, Tollkuhn J, Ohsawa R, Bresnick EH, Guillemot F, Kageyama R, Rosenfeld MG. Sustained Notch signaling in progenitors is required for sequential emergence of distinct cell lineages during organogenesis. Genes Dev. 2006;20(19):2739-2753.
Li CH, Papkoff H. Preparation and properties of growth hormone from human and monkey pituitary glands. Science. 1956;124(3235):1293-1294.
Li CH, Dixon JS. Human pituitary growth hormone. 32. The primary structure of the hormone: revision. Arch Biochem Biophys. 1971;146(1):233-236.
Niall HD, Hogan ML, Sauer R, Rosenblum IY, Greenwood FC. Sequences of pituitary and placental lactogenic and growth hormones: evolution from a primordial peptide by gene reduplication. Proc Natl Acad Sci U S A.1971;68(4):866-870.
Owerbach D, Rutter WJ, Martial JA, Baxter JD, Shows TB. Genes for growth hormone, chorionic somatommammotropin, and growth hormones-like gene on chromosome 17 in humans. Science.1980;209(4453):289-292.
McKusick V, Phillips JI, Bottani A, Antonarakis S, O'Neill M, Kniffin C, Hartz P, Gross M. GROWTH HORMONE 1; GH1. In: McKusick V, ed. Online Mendelian Inheritance in Man. Baltimore, MD, USA: Johns Hopkins University; 2007: http://www.ncbi.nlm.nih.gov:80/entrez/dispomim.cgi?id=139250. Accessed 20 Jan 2007
Frankenne F, Rentier-Delrue F, Scippo ML, Martial J, Hennen G. Expression of the growth hormone variant gene in human placenta. J Clin Endocrinol Metab. 1987;64(3):635-637.
Liebhaber SA, Urbanek M, Ray J, Tuan RS, Cooke NE. Characterization and histologic localization of human growth hormone-variant gene expression in the placenta. J Clin Invest. 1989;83(6):1985-1991.
McKusick V, Phillips JI. GROWTH HORMONE 2; GH2. In: McKusick V, ed. Online Mendelian Inheritance in Man. Baltimore, MD: Johns Hopkins University; 2007: http://www.ncbi.nlm.nih.gov:80/entrez/dispomim.cgi?id=139240. Accessed 20 Jan 2007
McKusick V, Phillips JI, Rasooly R. CHORIONIC SOMATOMAMMOTROPIN HORMONE 1; CSH1. In: McKusick V, ed. Online Mendelian Inheritance in Man. Baltimore, MD: Johns Hopkins University; 2007: http://www.ncbi.nlm.nih.gov:80/entrez/dispomim.cgi?id=150200. Accessed 20 Jan 2007
McKusick V, Rasooly R. CHORIONIC SOMATOMAMMOTROPIN HORMONE 2; CSH2. In: McKusick V, ed. Online Mendelian Inheritance in Man. Baltimore, MD: Johns Hopkins University; 2007: http://www.ncbi.nlm.nih.gov:80/entrez/dispomim.cgi?id=118820. Accessed 20 Jan 2007
Rasooly R. CHORIONIC SOMATOMAMMOTROPIN HORMONE-LIKE 1; CSHL1. In: McKusick V, ed. Online Mendelian Inheritance in Man. Baltimore, MD: Johns Hopkins University; 2007: http://www.ncbi.nlm.nih.gov:80/entrez/dispomim.cgi?id=603515. Accessed 20 Jan 2007
Chen EY, Liao YC, Smith DH, Barrera-Saldana HA, Gelinas RE, Seeburg PH. The human growth hormone locus: nucleotide sequence, biology, and evolution. Genomics. 1989;4(4):479-497.
Bodner M, Castrillo JL, Theill LE, Deerinck T, Ellisman M, Karin M. The pituitary-specific transcription factor GHF-1 is a homeobox-containing protein. Cell. 1988;55(3):505-518.
Lemaigre FP, Peers B, Lafontaine DA, Mathy-Hartert M, Rousseau GG, Belayew A, Martial JA. Pituitary-specific factor binding to the human prolactin, growth hormone, and placental lactogen genes. DNA. 1989;8(3):149-159.
Lemaigre FP, Courtois SJ, Durviaux SM, Egan CJ, LaFontaine DA, Rousseau GG. Analysis of cis- and trans-acting elements in the hormone-sensitive human somatotropin gene promoter. J Steroid Biochem. 1989;34(1-6):79-83.
Nachtigal MW, Nickel BE, Klassen ME, Zhang WG, Eberhardt NL, Cattini PA. Human chorionic somatomammotropin and growth hormone gene expression in rat pituitary tumour cells is dependent on proximal promoter sequences. Nucleic Acids Res. 1989;17(11):4327-4337.
Li S, Crenshaw EB, 3rd, Rawson EJ, Simmons DM, Swanson LW, Rosenfeld MG. Dwarf locus mutants lacking three pituitary cell types result from mutations in the POU-domain gene pit-1. Nature. 1990;347(6293):528-533.
Fox SR, Jong MT, Casanova J, Ye ZS, Stanley F, Samuels HH. The homeodomain protein, Pit-1/GHF-1, is capable of binding to and activating cell-specific elements of both the growth hormone and prolactin gene promoters. Mol Endocrinol. 1990;4(7):1069-1080.
Tansey WP, Catanzaro DF. Sp1 and thyroid hormone receptor differentially activate expression of human growth hormone and chorionic somatomammotropin genes. J Biol Chem. 1991;266(15):9805-9813.
Nickel BE, Nachtigal MW, Bock ME, Cattini PA. Differential binding of rat pituitary-specific nuclear factors to the 5'-flanking region of pituitary and placental members of the human growth hormone gene family. Mol Cell Biochem.1991;106(2):181-187.
Walker WH, Fitzpatrick SL, Saunders GF. Human placental lactogen transcriptional enhancer. Tissue specificity and binding with specific proteins. J Biol Chem. 1990;265(22):12940-12948.
Nachtigal MW, Nickel BE, Cattini PA. Pituitary-specific repression of placental members of the human growth hormone gene family. A possible mechanism for locus regulation. J Biol Chem. 1993;268(12):8473-8479.
Jones BK, Monks BR, Liebhaber SA, Cooke NE. The human growth hormone gene is regulated by a multicomponent locus control region. Mol Cell Biol. 1995;15(12):7010-7021.
Shewchuk BM, Liebhaber SA, Cooke NE. Specification of unique Pit-1 activity in the hGH locus control region. Proc Natl Acad Sci U S A. 2002;99(18):11784-11789.
Elefant F, Cooke NE, Liebhaber SA. Targeted recruitment of histone acetyltransferase activity to a locus control region. J Biol Chem. 2000;275(18):13827-13834.
Ho Y, Elefant F, Cooke N, Liebhaber S. A defined locus control region determinant links chromatin domain acetylation with long-range gene activation. Mol Cell. 2002;9(2):291-302.
Ho Y, Tadevosyan A, Liebhaber SA, Cooke NE. The juxtaposition of a promoter with a locus control region transcriptional domain activates gene expression. EMBO Rep. 2008;9(9):891-898.
Gil-Puig C, Seoane S, Blanco M, Macia M, Garcia-Caballero T, Segura C, Perez-Fernandez R. Pit-1 is expressed in normal and tumorous human breast and regulates GH secretion and cell proliferation. Eur J Endocrinol.2005;153(2):335-344.
Frohman LA, Burek L, Stachura MA. Characterization of growth hormone of different molecular weights in rat, dog and human pituitaries. Endocrinology. 1972;91(1):262-269.
Baumann G, Winter RJ, Shaw M. Circulating molecular variants of growth hormone in childhood. Pediatr Res.1987;22(1):21-22.
Baumann G, Stolar MW, Amburn K. Molecular forms of circulating growth hormone during spontaneous secretory episodes and in the basal state. J Clin Endocrinol Metab. 1985;60(6):1216-1220.
Herington AC, Ymer S, Stevenson J. Identification and characterization of specific binding proteins for growth hormone in normal human sera. J Clin Invest. 1986;77(6):1817-1823.
Leung DW, Spencer SA, Cachianes G, Hammonds RG, Collins C, Henzel WJ, Barnard R, Waters MJ, Wood WI. Growth hormone receptor and serum binding protein: purification, cloning and expression. Nature.1987;330(6148):537-543.
Zhang Y, Jiang J, Black RA, Baumann G, Frank SJ. Tumor necrosis factor-alpha converting enzyme (TACE) is a growth hormone binding protein (GHBP) sheddase: the metalloprotease TACE/ADAM-17 is critical for (PMA-induced) GH receptor proteolysis and GHBP generation. Endocrinology. 2000;141(12):4342-4348.
Baumann G, Shaw MA. Plasma transport of the 20,000-dalton variant of human growth hormone (20K): evidence for a 20K-specific binding site. J Clin Endocrinol Metab. 1990;71(5):1339-1343.
Ross RJ, Esposito N, Shen XY, Von Laue S, Chew SL, Dobson PR, Postel-Vinay MC, Finidori J. A short isoform of the human growth hormone receptor functions as a dominant negative inhibitor of the full-length receptor and generates large amounts of binding protein. Mol Endocrinol. 1997;11(3):265-273.
Gossard F, Dihl F, Pelletier G, Dubois PM, Morel G. In situ hybridization to rat brain and pituitary gland of growth hormone cDNA. Neurosci Lett. 1987;79(3):251-256.
Aberg ND, Brywe KG, Isgaard J. Aspects of growth hormone and insulin-like growth factor-I related to neuroprotection, regeneration, and functional plasticity in the adult brain. ScientificWorldJournal. 2006;6:53-80.
Thorner MO, Perryman RL, Cronin MJ, Rogol AD, Draznin M, Johanson A, Vale W, Horvath E, Kovacs K. Somatotroph hyperplasia. Successful treatment of acromegaly by removal of a pancreatic islet tumor secreting a growth hormone-releasing factor. J Clin Invest. 1982;70(5):965-977.
Mayo K, Vale W, Rivier J, Rosenfeld M, Evans R. Expression-cloning and sequence of a cDNA encoding human growth hormone-releasing factor. Nature. 1983;306(5938):86-88.
Gubler U, Monahan J, Lomedico P, Bhatt R, Collier K, Hoffman B, Bohlen P, Esch F, Ling N, Zeytin F, Brazeau P, Poonian M, Gage L. Cloning and sequence analysis of cDNA for the precursor of human growth hormone-releasing factor, somatocrinin. Proc Natl Acad Sci U S A. 1983;80(14):4311-4314.
Mayo K. Molecular cloning and expression of a pituitary-specific receptor for growth hormone-releasing hormone. Mol Endocrinol. 1992;6(10):1734-1744.
Barinaga M, Yamonoto G, Rivier C, Vale W, Evans R, Rosenfeld M. Transcriptional regulation of growth hormone gene expression by growth hormone-releasing factor. Nature. 1983;306(5938):84-85.
Fukata J, Diamond D, Martin J. Effects of rat growth hormone (rGH)-releasing factor and somatostatin on the release and synthesis of rGH in dispersed pituitary cells. Endocrinology. 1985;117(2):457-467.
Campbell R, Scanes C. Evolution of the growth hormone-releasing factor (GRF) family of peptides. Growth Regul.1992;2(4):175-191.
Shen L, Pictet R, Rutter W. Human somatostatin I: sequence of the cDNA. Proc Natl Acad Sci U S A.1982;79(15):4575-4579.
Siler T, VandenBerg G, Yen S, Brazeau P, Vale W, Guillemin R. Inhibition of growth hormone release in humans by somatostatin. J Clin Endocrinol Metab. 1973;37(4):632-634.
Brazeau P, Vale W, Burgus R, Ling N, Butcher M, Rivier J, Guillemin R. Hypothalamic polypeptide that inhibits the secretion of immunoreactive pituitary growth hormone. Science. 1973;179(68):77-79.
Tannenbaum GS, Epelbaum J, Bowers CY. Interrelationship between the Novel Peptide Ghrelin and Somatostatin/Growth Hormone-Releasing Hormone in Regulation of Pulsatile Growth Hormone Secretion. Endocrinology. 2003;144(3):967-974.
Broglio F, Koetsveld Pv P, Benso A, Gottero C, Prodam F, Papotti M, Muccioli G, Gauna C, Hofland L, Deghenghi R, Arvat E, Van Der Lely AJ, Ghigo E. Ghrelin secretion is inhibited by either somatostatin or cortistatin in humans. J Clin Endocrinol Metab. 2002;87(10):4829-4832.
Norrelund H, Hansen TK, Orskov H, Hosoda H, Kojima M, Kangawa K, Weeke J, Moller N, Christiansen JS, Jorgensen JO. Ghrelin immunoreactivity in human plasma is suppressed by somatostatin. Clin Endocrinol (Oxf).2002;57(4):539-546.
Shimada M, Date Y, Mondal MS, Toshinai K, Shimbara T, Fukunaga K, Murakami N, Miyazato M, Kangawa K, Yoshimatsu H, Matsuo H, Nakazato M. Somatostatin suppresses ghrelin secretion from the rat stomach. Biochem Biophys Res Commun. 2003;302(3):520-525.
Vale W, Rivier C, Brazeau P, Guillemin R. Effects of somatostatin on the secretion of thyrotropin and prolactin. Endocrinology. 1974;95(4):968-977.
Siler TM, Yen SC, Vale W, Guillemin R. Inhibition by somatostatin on the release of TSH induced in man by thyrotropin-releasing factor. J Clin Endocrinol Metab. 1974;38(5):742-745.
Liddle R. Physiology of somatostatin and its analogues. UpToDate version 14.3. Wellesley, MA, United States of America: UpToDate, Inc.; 2006.
Patel Y, Greenwood M, Panetta R, Hukovic N, Grigorakis S, Robertson L, Srikant C. Molecular biology of somatostatin receptor subtypes. Metabolism. 1996;45(8 Suppl 1):31-38.
Peineau S, Guimiot F, Csaba Z, Jacquier S, Fafouri A, Schwendimann L, de Roux N, Schulz S, Gressens P, Auvin S, Dournaud P. Somatostatin receptors type 2 and 5 expression and localization during human pituitary development. Endocrinology. 2014;155(1):33-39.
Reisine T, Bell GI. Molecular biology of somatostatin receptors. Endocr Rev. 1995;16(4):427-442.
Kojima M, Hosoda H, Date Y, Nakazato M, Matsuo H, Kangawa K. Ghrelin is a growth-hormone-releasing acylated peptide from stomach. Nature. 1999;402(6762):656-660.
Howard AD, Feighner SD, Cully DF, Arena JP, Liberator PA, Rosenblum CI, Hamelin M, Hreniuk DL, Palyha OC, Anderson J, Paress PS, Diaz C, Chou M, Liu KK, McKee KK, Pong SS, Chaung LY, Elbrecht A, Dashkevicz M, Heavens R, Rigby M, Sirinathsinghji DJ, Dean DC, Melillo DG, Van der Ploeg LH, et al. A receptor in pituitary and hypothalamus that functions in growth hormone release. Science. 1996;273(5277):974-977.
Gnanapavan S, Kola B, Bustin SA, Morris DG, McGee P, Fairclough P, Bhattacharya S, Carpenter R, Grossman AB, Korbonits M. The tissue distribution of the mRNA of ghrelin and subtypes of its receptor, GHS-R, in humans. J Clin Endocrinol Metab. 2002;87(6):2988.
Chan CB, Cheng CH. Identification and functional characterization of two alternatively spliced growth hormone secretagogue receptor transcripts from the pituitary of black seabream Acanthopagrus schlegeli. Mol Cell Endocrinol. 2004;214(1-2):81-95.
Hosoda H, Kojima M, Matsuo H, Kangawa K. Ghrelin and des-acyl ghrelin: two major forms of rat ghrelin peptide in gastrointestinal tissue. Biochem Biophys Res Commun. 2000;279(3):909-913.
Yang J, Brown MS, Liang G, Grishin NV, Goldstein JL. Identification of the acyltransferase that octanoylates ghrelin, an appetite-stimulating peptide hormone. Cell. 2008;132(3):387-396.
Lim CT, Kola B, Grossman A, Korbonits M. The expression of ghrelin O-acyltransferase (GOAT) in human tissues. Endocr J. 2011;58(8):707-710.
Momany FA, Bowers CY, Reynolds GA, Chang D, Hong A, Newlander K. Design, synthesis, and biological activity of peptides which release growth hormone in vitro. Endocrinology. 1981;108(1):31-39.
Beaumont NJ, Skinner VO, Tan TM, Ramesh BS, Byrne DJ, MacColl GS, Keen JN, Bouloux PM, Mikhailidis DP, Bruckdorfer KR, Vanderpump MP, Srai KS. Ghrelin Can Bind to a Species of High Density Lipoprotein Associated with Paraoxonase. J Biol Chem. 2003;278(11):8877-8880.
De Vriese C, Gregoire F, Lema-Kisoka R, Waelbroeck M, Robberecht P, Delporte C. Ghrelin degradation by serum and tissue homogenates: identification of the cleavage sites. Endocrinology. 2004;145(11):4997-5005.
Korbonits M, Bustin SA, Kojima M, Jordan S, Adams EF, Lowe DG, Kangawa K, Grossman AB. The expression of the growth hormone secretagogue receptor ligand ghrelin in normal and abnormal human pituitary and other neuroendocrine tumors. J Clin Endocrinol Metab. 2001;86(2):881-887.
Caminos JE, Nogueiras R, Blanco M, Seoane LM, Bravo S, Alvarez CV, Garcia-Caballero T, Casanueva FF, Dieguez C. Cellular distribution and regulation of ghrelin messenger ribonucleic acid in the rat pituitary gland. Endocrinology. 2003;144(11):5089-5097.
Kojima M, Hosoda H, Date Y, Nakazato M, Matsuo H, Kangawa K. Ghrelin is a growth-hormone-releasing acylated peptide from stomach. Nature. 1999;402(6762):656-660.
Muccioli G, Tschop M, Papotti M, Deghenghi R, Heiman M, Ghigo E. Neuroendocrine and peripheral activities of ghrelin: implications in metabolism and obesity. Eur J Pharmacol. 2002;440(2-3):235-254.
Wren A, Small C, Abbott C, Dhillo W, Seal L, Cohen M, Batterham R, Taheri S, Stanley S, Ghatei M, Bloom S. Ghrelin causes hyperphagia and obesity in rats. Diabetes. 2001;50(11):2540-2547.
Wren A, Seal L, Cohen M, Brynes A, Frost G, Murphy K, Dhillo W, Ghatei M, Bloom S. Ghrelin enhances appetite and increases food intake in humans. J Clin Endocrinol Metab. 2001;86(12):5992.
Date Y, Nakazato M, Hashiguchi S, Dezaki K, Mondal M, Hosoda H, Kojima M, Kangawa K, Arima T, Matsuo H, Yada T, Matsukura S. Ghrelin is present in pancreatic alpha-cells of humans and rats and stimulates insulin secretion. Diabetes. 2002;51(1):124-129.
Takaya K, Ariyasu H, Kanamoto N, Iwakura H, Yoshimoto A, Harada M, Mori K, Komatsu Y, Usui T, Shimatsu A, Ogawa Y, Hosoda K, Akamizu T, Kojima M, Kangawa K, Nakao K. Ghrelin strongly stimulates growth hormone release in humans. J Clin Endocrinol Metab. 2000;85(12):4908-4911.
Sun Y, Ahmed S, Smith RG. Deletion of ghrelin impairs neither growth nor appetite. Mol Cell Biol.2003;23(22):7973-7981.
Hassouna R, Zizzari P, Tomasetto C, Veldhuis JD, Fiquet O, Labarthe A, Cognet J, Steyn F, Chen C, Epelbaum J, Tolle V. An early reduction in GH peak amplitude in preproghrelin-deficient male mice has a minor impact on linear growth. Endocrinology. 2014;155(9):3561-3571.
Wortley KE, Anderson KD, Garcia K, Murray JD, Malinova L, Liu R, Moncrieffe M, Thabet K, Cox HJ, Yancopoulos GD, Wiegand SJ, Sleeman MW. Genetic deletion of ghrelin does not decrease food intake but influences metabolic fuel preference. Proc Natl Acad Sci U S A. 2004;101(21):8227-8232.
Sun Y, Wang P, Zheng H, Smith RG. Ghrelin stimulation of growth hormone release and appetite is mediated through the growth hormone secretagogue receptor. Proc Natl Acad Sci U S A. 2004;101(13):4679-4684.
Xie TY, Ngo ST, Veldhuis JD, Jeffery PL, Chopin LK, Tschop M, Waters MJ, Tolle V, Epelbaum J, Chen C, Steyn FJ. Effect of Deletion of Ghrelin-O-Acyltransferase on the Pulsatile Release of Growth Hormone in Mice. J Neuroendocrinol. 2015;27(12):872-886.
Baldanzi G, Filigheddu N, Cutrupi S, Catapano F, Bonissoni S, Fubini A, Malan D, Baj G, Granata R, Broglio F, Papotti M, Surico N, Bussolino F, Isgaard J, Deghenghi R, Sinigaglia F, Prat M, Muccioli G, Ghigo E, Graziani A. Ghrelin and des-acyl ghrelin inhibit cell death in cardiomyocytes and endothelial cells through ERK1/2 and PI 3-kinase/AKT. J Cell Biol. 2002;159(6):1029-1037.
Cassoni P, Ghe C, Marrocco T, Tarabra E, Allia E, Catapano F, Deghenghi R, Ghigo E, Papotti M, Muccioli G. Expression of ghrelin and biological activity of specific receptors for ghrelin and des-acyl ghrelin in human prostate neoplasms and related cell lines. Eur J Endocrinol. 2004;150(2):173-184.
Muccioli G, Pons N, Ghe C, Catapano F, Granata R, Ghigo E. Ghrelin and des-acyl ghrelin both inhibit isoproterenol-induced lipolysis in rat adipocytes via a non-type 1a growth hormone secretagogue receptor. Eur J Pharmacol. 2004;498(1-3):27-35.
Tsubota Y, Owada-Makabe K, Yukawa K, Maeda M. Hypotensive effect of des-acyl ghrelin at nucleus tractus solitarii of rat. Neuroreport. 2005;16(2):163-166.
Asakawa A, Inui A, Fujimiya M, Sakamaki R, Shinfuku N, Ueta Y, Meguid MM, Kasuga M. Stomach regulates energy balance via acylated ghrelin and desacyl ghrelin. Gut. 2005;54(1):18-24.
Neary NM, Druce MR, Small CJ, Bloom SR. Acylated ghrelin stimulates food intake in the fed and fasted states but desacylated ghrelin has no effect. Gut. 2006;55(1):135.
Chen CY, Inui A, Asakawa A, Fujino K, Kato I, Chen CC, Ueno N, Fujimiya M. Des-acyl ghrelin acts by CRF type 2 receptors to disrupt fasted stomach motility in conscious rats. Gastroenterology. 2005;129(1):8-25.
Popovic V, Damjanovic S, Micic D, Djurovic M, Dieguez C, Casanueva FF. Blocked growth hormone-releasing peptide (GHRP-6)-induced GH secretion and absence of the synergic action of GHRP-6 plus GH-releasing hormone in patients with hypothalamopituitary disconnection: evidence that GHRP-6 main action is exerted at the hypothalamic level. J Clin Endocrinol Metab. 1995;80(3):942-947.
Seoane LM, Tovar S, Baldelli R, Arvat E, Ghigo E, Casanueva FF, Dieguez C. Ghrelin elicits a marked stimulatory effect on GH secretion in freely-moving rats. Eur J Endocrinol. 2000;143(5):R7-9.
Bowers CY, Sartor AO, Reynolds GA, Badger TM. On the actions of the growth hormone-releasing hexapeptide, GHRP. Endocrinology. 1991;128(4):2027-2035.
Garcia JM, Swerdloff R, Wang C, Kyle M, Kipnes M, Biller BM, Cook D, Yuen KC, Bonert V, Dobs A, Molitch ME, Merriam GR. Macimorelin (AEZS-130)-stimulated growth hormone (GH) test: validation of a novel oral stimulation test for the diagnosis of adult GH deficiency. J Clin Endocrinol Metab. 2013;98(6):2422-2429.
Ge X, Yang H, Bednarek MA, Galon-Tilleman H, Chen P, Chen M, Lichtman JS, Wang Y, Dalmas O, Yin Y, Tian H, Jermutus L, Grimsby J, Rondinone CM, Konkar A, Kaplan DD. LEAP2 Is an Endogenous Antagonist of the Ghrelin Receptor. Cell Metab. 2018;27(2):461-469 e466.
Mani BK, Puzziferri N, He Z, Rodriguez JA, Osborne-Lawrence S, Metzger NP, Chhina N, Gaylinn B, Thorner MO, Thomas EL, Bell JD, Williams KW, Goldstone AP, Zigman JM. LEAP2 changes with body mass and food intake in humans and mice. The Journal of clinical investigation. 2019;129(9):3909-3923.
Casanueva FF, Burguera B, Muruais C, Dieguez C. Acute administration of corticoids: a new and peculiar stimulus of growth hormone secretion in man. J Clin Endocrinol Metab. 1990;70(1):234-237.
Burguera B, Muruais C, Penalva A, Dieguez C, Casanueva FF. Dual and selective actions of glucocorticoids upon basal and stimulated growth hormone release in man. Neuroendocrinology. 1990;51(1):51-58.
Strickland AL, Underwood LE, Voina SJ, French FS, Van Wyk JJ. Growth retardation in Cushing's syndrome. Am J Dis Child. 1972;123(3):207-213.
Giustina A, Wehrenberg WB. The role of glucocorticoids in the regulation of Growth Hormone secretion: mechanisms and clinical significance. Trends Endocrinol Metab. 1992;3(8):306-311.
Veldhuis JD, Roemmich JN, Richmond EJ, Bowers CY. Somatotropic and gonadotropic axes linkages in infancy, childhood, and the puberty-adult transition. Endocr Rev. 2006;27(2):101-140.
Kok P, Paulo RC, Cosma M, Mielke KL, Miles JM, Bowers CY, Veldhuis JD. Estrogen supplementation selectively enhances hypothalamo-pituitary sensitivity to ghrelin in postmenopausal women. J Clin Endocrinol Metab.2008;93(10):4020-4026.
Leung KC, Johannsson G, Leong GM, Ho KK. Estrogen regulation of growth hormone action. Endocr Rev.2004;25(5):693-721.
Amit Tanna RM, Harinderjeet Sandhu, Jake Powrie, Stephen Thomas, Anna Brackenridge, Louise Breen & Paul Carroll. Oral and transdermal oestrogen treatments have differing effects on GH sensitivity in hypopituitary women receiving GH replacement. Endocrine Abstract. 2010;21 P286
Weissberger AJ, Ho KK, Lazarus L. Contrasting effects of oral and transdermal routes of estrogen replacement therapy on 24-hour growth hormone (GH) secretion, insulin-like growth factor I, and GH-binding protein in postmenopausal women. J Clin Endocrinol Metab. 1991;72(2):374-381.
Isotton AL, Wender MC, Casagrande A, Rollin G, Czepielewski MA. Effects of oral and transdermal estrogen on IGF1, IGFBP3, IGFBP1, serum lipids, and glucose in patients with hypopituitarism during GH treatment: a randomized study. Eur J Endocrinol. 2014;166(2):207-213.
Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse obese gene and its human homologue. Nature. 1994;372(6505):425-432.
Pelleymounter MA, Cullen MJ, Baker MB, Hecht R, Winters D, Boone T, Collins F. Effects of the obese gene product on body weight regulation in ob/ob mice. Science. 1995;269(5223):540-543.
Schwartz MW, Woods SC, Porte D, Jr., Seeley RJ, Baskin DG. Central nervous system control of food intake. Nature. 2000;404(6778):661-671.
Jin L, Burguera BG, Couce ME, Scheithauer BW, Lamsan J, Eberhardt NL, Kulig E, Lloyd RV. Leptin and leptin receptor expression in normal and neoplastic human pituitary: evidence of a regulatory role for leptin on pituitary cell proliferation. J Clin Endocrinol Metab. 1999;84(8):2903-2911.
Korbonits M, Chitnis MM, Gueorguiev M, Norman D, Rosenfelder N, Suliman M, Jones TH, Noonan K, Fabbri A, Besser GM, Burrin JM, Grossman AB. The release of leptin and its effect on hormone release from human pituitary adenomas. Clin Endocrinol (Oxf). 2001;54(6):781-789.
Kristiansen MT, Clausen LR, Nielsen S, Blaabjerg O, Ledet T, Rasmussen LM, Jorgensen JO. Expression of leptin receptor isoforms and effects of leptin on the proliferation and hormonal secretion in human pituitary adenomas. Horm Res. 2004;62(3):129-136.
Saleri R, Giustina A, Tamanini C, Valle D, Burattin A, Wehrenberg WB, Baratta M. Leptin stimulates growth hormone secretion via a direct pituitary effect combined with a decreased somatostatin tone in a median eminence-pituitary perifusion study. Neuroendocrinology. 2004;79(4):221-228.
Tannenbaum GS, Lapointe M, Gurd W, Finkelstein JA. Mechanisms of impaired growth hormone secretion in genetically obese Zucker rats: roles of growth hormone-releasing factor and somatostatin. Endocrinology.1990;127(6):3087-3095.
Ozata M, Dieguez C, Casanueva FF. The inhibition of growth hormone secretion presented in obesity is not mediated by the high leptin levels: a study in human leptin deficiency patients. J Clin Endocrinol Metab.2003;88(1):312-316.
Sun Y, Bak B, Schoenmakers N, van Trotsenburg AS, Oostdijk W, Voshol P, Cambridge E, White JK, le Tissier P, Gharavy SN, Martinez-Barbera JP, Stokvis-Brantsma WH, Vulsma T, Kempers MJ, Persani L, Campi I, Bonomi M, Beck-Peccoz P, Zhu H, Davis TM, Hokken-Koelega AC, Del Blanco DG, Rangasami JJ, Ruivenkamp CA, Laros JF, Kriek M, Kant SG, Bosch CA, Biermasz NR, Appelman-Dijkstra NM, Corssmit EP, Hovens GC, Pereira AM, den Dunnen JT, Wade MG, Breuning MH, Hennekam RC, Chatterjee K, Dattani MT, Wit JM, Bernard DJ. Loss-of-function mutations in IGSF1 cause an X-linked syndrome of central hypothyroidism and testicular enlargement. Nat Genet. 2012;44(12):1375-1381.
Joustra SD, Roelfsema F, Endert E, Ballieux BE, van Trotsenburg AS, Fliers E, Corssmit EP, Bernard DJ, Oostdijk W, Wit JM, Pereira AM, Biermasz NR. Pituitary Hormone Secretion Profiles in IGSF1 Deficiency Syndrome. Neuroendocrinology. 2016;103(3-4):408-416.
Joustra SD, Roelfsema F, van Trotsenburg ASP, Schneider HJ, Kosilek RP, Kroon HM, Logan JG, Butterfield NC, Zhou X, Toufaily C, Bak B, Turgeon MO, Brule E, Steyn FJ, Gurnell M, Koulouri O, Le Tissier P, Fontanaud P, Duncan Bassett JH, Williams GR, Oostdijk W, Wit JM, Pereira AM, Biermasz NR, Bernard DJ, Schoenmakers N. IGSF1 Deficiency Results in Human and Murine Somatotrope Neurosecretory Hyperfunction. J Clin Endocrinol Metab. 2020;105(3).
Gutierrez-Pascual E, Martinez-Fuentes AJ, Pinilla L, Tena-Sempere M, Malagon MM, Castano JP. Direct pituitary effects of kisspeptin: activation of gonadotrophs and somatotrophs and stimulation of luteinising hormone and growth hormone secretion. J Neuroendocrinol. 2007;19(7):521-530.
Kadokawa H, Suzuki S, Hashizume T. Kisspeptin-10 stimulates the secretion of growth hormone and prolactin directly from cultured bovine anterior pituitary cells. Anim Reprod Sci. 2008;105(3-4):404-408.
Whitlock BK, Daniel JA, Wilborn RR, Maxwell HS, Steele BP, Sartin JL. Interaction of kisspeptin and the somatotropic axis. Neuroendocrinology. 2010;92(3):178-188.
Jayasena CN, Comninos AN, Narayanaswamy S, Bhalla S, Abbara A, Ganiyu-Dada Z, Busbridge M, Ghatei MA, Bloom SR, Dhillo WS. Acute and chronic effects of kisspeptin-54 administration on GH, prolactin and TSH secretion in healthy women. Clin Endocrinol (Oxf). 2014;81(6):891-898.
Massara F, Camanni F. Effect of various adrenergic receptor stimulating and blocking agents on human growth hormone secretion. J Endocrinol. 1972;54(2):195-206.
Chihara K, Minamitani N, Kaji H, Kodama H, Kita T, Fujita T. Noradrenergic modulation of human pancreatic growth hormone-releasing factor (hpGHRF1-44)-induced growth hormone release in conscious male rabbits: involvement of endogenous somatostatin. Endocrinology. 1984;114(4):1402-1406.
Milner RD, Burns EC. Investigation of suspected growth hormone deficiency. On behalf of the Health Services Human Growth Hormone Committee. Arch Dis Child. 1982;57(12):944-947.
Grossman A, Weerasuriya K, Al-Damluji S, Turner P, Besser GM. Alpha 2-adrenoceptor agonists stimulate growth hormone secretion but have no acute effects on plasma cortisol under basal conditions. Horm Res. 1987;25(2):65-71.
Masala A, Delitala G, Alagna S, Devilla L. Effect of pimozide on levodopa-induced growth hormone release in man. Clin Endocrinol (Oxf). 1977;7(3):253-256.
Cammani F, Massara F. Phentolamine inhibition of human growth hormone secretion induced by L-DOPA. Horm Metab Res. 1972;4(2):128.
Giustina A, Veldhuis JD. Pathophysiology of the neuroregulation of growth hormone secretion in experimental animals and the human. Endocr Rev. 1998;19(6):717-797.
Friend K, Iranmanesh A, Login IS, Veldhuis JD. Pyridostigmine treatment selectively amplifies the mass of GH secreted per burst without altering GH burst frequency, half-life, basal GH secretion or the orderliness of GH release. Eur J Endocrinol. 1997;137(4):377-386.
Taylor BJ, Smith PJ, Brook CG. Inhibition of physiological growth hormone secretion by atropine. Clin Endocrinol (Oxf). 1985;22(4):497-501.
Massara F, Ghigo E, Demislis K, Tangolo D, Mazza E, Locatelli V, Muller EE, Molinatti GM, Camanni F. Cholinergic involvement in the growth hormone releasing hormone-induced growth hormone release: studies in normal and acromegalic subjects. Neuroendocrinology. 1986;43(6):670-675.
Wehrenberg WB, Wiviott SD, Voltz DM, Giustina A. Pyridostigmine-mediated growth hormone release: evidence for somatostatin involvement. Endocrinology. 1992;130(3):1445-1450.
Vance ML, Kaiser DL, Frohman LA, Rivier J, Vale WW, Thorner MO. Role of dopamine in the regulation of growth hormone secretion: dopamine and bromocriptine augment growth hormone (GH)-releasing hormone-stimulated GH secretion in normal man. J Clin Endocrinol Metab. 1987;64(6):1136-1141.
Grossman A. Brain opiates and neuroendocrine function. Clin Endocrinol Metab. 1983;12(3):725-746.
Moretti C, Fabbri A, Gnessi L, Cappa M, Calzolari A, Fraioli F, Grossman A, Besser GM. Naloxone inhibits exercise-induced release of PRL and GH in athletes. Clin Endocrinol (Oxf). 1983;18(2):135-138.
Miki N, Ono M, Shizume K. Evidence that opiatergic and alpha-adrenergic mechanisms stimulate rat growth hormone release via growth hormone-releasing factor (GRF). Endocrinology. 1984;114(5):1950-1952.
Olsen J, Peroski M, Kiczek M, Grignol G, Merchenthaler I, Dudas B. Intimate associations between the endogenous opiate systems and the growth hormone-releasing hormone system in the human hypothalamus. Neuroscience. 2014;258:238-245.
Dudas B, Merchenthaler I. Topography and associations of leu-enkephalin and luteinizing hormone-releasing hormone neuronal systems in the human diencephalon. J Clin Endocrinol Metab. 2003;88(4):1842-1848.
Delitala G, Tomasi PA, Palermo M, Ross RJ, Grossman A, Besser GM. Opioids stimulate growth hormone (GH) release in man independently of GH-releasing hormone. J Clin Endocrinol Metab. 1989;69(2):356-358.
Wenger T, Toth BE, Martin BR. Effects of anandamide (endogen cannabinoid) on anterior pituitary hormone secretion in adult ovariectomized rats. Life Sci. 1995;56(23-24):2057-2063.
Rettori V, Wenger T, Snyder G, Dalterio S, McCann SM. Hypothalamic action of delta-9-tetrahydrocannabinol to inhibit the release of prolactin and growth hormone in the rat. Neuroendocrinology. 1988;47(6):498-503.
Rettori V, Aguila MC, Gimeno MF, Franchi AM, McCann SM. In vitro effect of delta 9-tetrahydrocannabinol to stimulate somatostatin release and block that of luteinizing hormone-releasing hormone by suppression of the release of prostaglandin E2. Proc Natl Acad Sci U S A. 1990;87(24):10063-10066.
Zbucki RL, Sawicki B, Hryniewicz A, Winnicka MM. Cannabinoids enhance gastric X/A-like cells activity. Folia Histochem Cytobiol. 2008;46(2):219-224.
Senin LL, Al-Massadi O, Folgueira C, Castelao C, Pardo M, Barja-Fernandez S, Roca-Rivada A, Amil M, Crujeiras AB, Garcia-Caballero T, Gabellieri E, Leis R, Dieguez C, Pagotto U, Casanueva FF, Seoane LM. The gastric CB1 receptor modulates ghrelin production through the mTOR pathway to regulate food intake. PLoS One.2013;8(11):e80339.
Kola B, Farkas I, Christ-Crain M, Wittmann G, Lolli F, Amin F, Harvey-White J, Liposits Z, Kunos G, Grossman AB, Fekete C, Korbonits M. The orexigenic effect of ghrelin is mediated through central activation of the endogenous cannabinoid system. PLoS One. 2008;3(3):e1797.
Kola B, Wittman G, Bodnar I, Amin F, Lim CT, Olah M, Christ-Crain M, Lolli F, van Thuijl H, Leontiou CA, Fuzesi T, Dalino P, Isidori AM, Harvey-White J, Kunos G, Nagy GM, Grossman AB, Fekete C, Korbonits M. The CB1 receptor mediates the peripheral effects of ghrelin on AMPK activity but not on growth hormone release. FASEB J.2013;27(12):5112-5121.
Lim CT, Kola B, Korbonits M. The ghrelin/GOAT/GHS-R system and energy metabolism. Rev Endocr Metab Disord. 2011;12(3):173-186.
Lim CT, Kola B, Feltrin D, Perez-Tilve D, Tschop MH, Grossman AB, Korbonits M. Ghrelin and cannabinoids require the ghrelin receptor to affect cellular energy metabolism. Mol Cell Endocrinol. 2013;365(2):303-308.
Quabbe HJ, Bratzke HJ, Siegers U, Elban K. Studies on the relationship between plasma free fatty acids and growth hormone secretion in man. The Journal of clinical investigation. 1972;51(9):2388-2398.
Wasada T, Howard B, McCorkle K, Harris V, Unger RH. High plasma free fatty acid levels contribute to the hypersomatostatinemia of insulin deficiency. Diabetes. 1981;30(4):358-361.
Senaris RM, Lewis MD, Lago F, Dominguez F, Scanlon MF, Dieguez C. Effects of free fatty acids on somatostatin secretion, content and mRNA levels in cortical and hypothalamic fetal rat neurones in monolayer culture. J Mol Endocrinol. 1993;10(2):207-214.
Giustina A, Licini M, Schettino M, Doga M, Pizzocolo G, Negro-Vilar A. Physiological role of galanin in the regulation of anterior pituitary function in humans. Am J Physiol. 1994;266(1 Pt 1):E57-61.
Cantalamessa L, Catania A, Reschini E, Peracchi M. Inhibitory effect of calcitonin on growth hormone and insulin secretion in man. Metabolism. 1978;27(8):987-992.
Petralito A, Lunetta M, Liuzzo A, Mangiafico RA, Fiore CE. Effects of salmon calcitonin on insulin-induced growth hormone release in man. Horm Metab Res. 1979;11(11):641-643.
Harfstrand A, Eneroth P, Agnati L, Fuxe K. Further studies on the effects of central administration of neuropeptide Y on neuroendocrine function in the male rat: relationship to hypothalamic catecholamines. Regul Pept.1987;17(3):167-179.
Rettori V, Milenkovic L, Aguila MC, McCann SM. Physiologically significant effect of neuropeptide Y to suppress growth hormone release by stimulating somatostatin discharge. Endocrinology. 1990;126(5):2296-2301.
Catzeflis C, Pierroz DD, Rohner-Jeanrenaud F, Rivier JE, Sizonenko PC, Aubert ML. Neuropeptide Y administered chronically into the lateral ventricle profoundly inhibits both the gonadotropic and the somatotropic axis in intact adult female rats. Endocrinology. 1993;132(1):224-234.
Adams EF, Venetikou MS, Woods CA, Lacoumenta S, Burrin JM. Neuropeptide Y directly inhibits growth hormone secretion by human pituitary somatotropic tumours. Acta Endocrinol (Copenh). 1987;115(1):149-154.
Korbonits M, Little JA, Forsling ML, Tringali G, Costa A, Navarra P, Trainer PJ, Grossman AB. The effect of growth hormone secretagogues and neuropeptide Y on hypothalamic hormone release from acute rat hypothalamic explants. J Neuroendocrinol. 1999;11(7):521-528.
Watanobe H, Tamura T. Stimulation by neuropeptide Y of growth hormone secretion in prolactinoma in vivo. Neuropeptides. 1996;30(5):429-432.
Antonijevic IA, Murck H, Bohlhalter S, Frieboes RM, Holsboer F, Steiger A. Neuropeptide Y promotes sleep and inhibits ACTH and cortisol release in young men. Neuropharmacology. 2000;39(8):1474-1481.
Miyata A, Arimura A, Dahl RR, Minamino N, Uehara A, Jiang L, Culler MD, Coy DH. Isolation of a novel 38 residue-hypothalamic polypeptide which stimulates adenylate cyclase in pituitary cells. Biochem Biophys Res Commun. 1989;164(1):567-574.
Goth MI, Lyons CE, Canny BJ, Thorner MO. Pituitary adenylate cyclase activating polypeptide, growth hormone (GH)-releasing peptide and GH-releasing hormone stimulate GH release through distinct pituitary receptors. Endocrinology. 1992;130(2):939-944.
Jarry H, Leonhardt S, Schmidt WE, Creutzfeldt W, Wuttke W. Contrasting effects of pituitary adenylate cyclase activating polypeptide (PACAP) on in vivo and in vitro prolactin and growth hormone release in male rats. Life Sci.1992;51(11):823-830.
Propato-Mussafiri R, Kanse SM, Ghatei MA, Bloom SR. Pituitary adenylate cyclase-activating polypeptide releases 7B2, adrenocorticotrophin, growth hormone and prolactin from the mouse and rat clonal pituitary cell lines AtT-20 and GH3. J Endocrinol. 1992;132(1):107-113.
Chiodera P, Volpi R, Capretti L, Caffarri G, Magotti MG, Coiro V. Effects of intravenously infused pituitary adenylate cyclase-activating polypeptide on adenohypophyseal Hormone secretion in normal men. Neuroendocrinology.1996;64(3):242-246.
Shahmoon S, Rubinfeld H, Wolf I, Cohen ZR, Hadani M, Shimon I, Rubinek T. The aging suppressor klotho: a potential regulator of growth hormone secretion. Am J Physiol Endocrinol Metab. 2014;307(3):E326-334.
Abboud D, Daly AF, Dupuis N, Bahri MA, Inoue A, Chevigne A, Ectors F, Plenevaux A, Pirotte B, Beckers A, Hanson J. GPR101 drives growth hormone hypersecretion and gigantism in mice via constitutive activation of Gs and Gq/11. Nat Commun. 2020;11(1):4752.
Iacovazzo D, Caswell R, Bunce B, Jose S, Yuan B, Hernandez-Ramirez LC, Kapur S, Caimari F, Evanson J, Ferrau F, Dang MN, Gabrovska P, Larkin SJ, Ansorge O, Rodd C, Vance ML, Ramirez-Renteria C, Mercado M, Goldstone AP, Buchfelder M, Burren CP, Gurlek A, Dutta P, Choong CS, Cheetham T, Trivellin G, Stratakis CA, Lopes MB, Grossman AB, Trouillas J, Lupski JR, Ellard S, Sampson JR, Roncaroli F, Korbonits M. Germline or somatic GPR101 duplication leads to X-linked acrogigantism: a clinico-pathological and genetic study. Acta Neuropathol Commun. 2016;4(1):56.
Iacovazzo D, Korbonits M. Gigantism: X-linked acrogigantism and GPR101 mutations. Growth Horm IGF Res.2016;30-31:64-69.
Beckers A, Lodish MB, Trivellin G, Rostomyan L, Lee M, Faucz FR, Yuan B, Choong CS, Caberg JH, Verrua E, Naves LA, Cheetham TD, Young J, Lysy PA, Petrossians P, Cotterill A, Shah NS, Metzger D, Castermans E, Ambrosio MR, Villa C, Strebkova N, Mazerkina N, Gaillard S, Barra GB, Casulari LA, Neggers SJ, Salvatori R, Jaffrain-Rea ML, Zacharin M, Santamaria BL, Zacharieva S, Lim EM, Mantovani G, Zatelli MC, Collins MT, Bonneville JF, Quezado M, Chittiboina P, Oldfield EH, Bours V, Liu P, W WdH, Pellegata N, Lupski JR, Daly AF, Stratakis CA. X-linked acrogigantism syndrome: clinical profile and therapeutic responses. Endocr Relat Cancer.2015;22(3):353-367.
Trivellin G, Daly AF, Faucz FR, Yuan B, Rostomyan L, Larco DO, Schernthaner-Reiter MH, Szarek E, Leal LF, Caberg JH, Castermans E, Villa C, Dimopoulos A, Chittiboina P, Xekouki P, Shah N, Metzger D, Lysy PA, Ferrante E, Strebkova N, Mazerkina N, Zatelli MC, Lodish M, Horvath A, de Alexandre RB, Manning AD, Levy I, Keil MF, Sierra Mde L, Palmeira L, Coppieters W, Georges M, Naves LA, Jamar M, Bours V, Wu TJ, Choong CS, Bertherat J, Chanson P, Kamenicky P, Farrell WE, Barlier A, Quezado M, Bjelobaba I, Stojilkovic SS, Wess J, Costanzi S, Liu P, Lupski JR, Beckers A, Stratakis CA. Gigantism and acromegaly due to Xq26 microduplications and GPR101 mutation. N Engl J Med. 2014;371(25):2363-2374.
Cowley MA, Grove KL. To be or NUCB2, is nesfatin the answer? Cell Metab. 2006;4(6):421-422.
Velez EJ, Unniappan S. Nesfatin-1 and nesfatin-1-like peptide suppress growth hormone synthesis via the AC/PKA/CREB pathway in mammalian somatotrophs. Sci Rep. 2020;10(1):16686.
Peterfreund RA, Vale WW. Somatostatin analogs inhibit somatostatin secretion from cultured hypothalamus cells. Neuroendocrinology. 1984;39(5):397-402.
Aguila MC, McCann SM. The influence of hGRF, CRF, TRH and LHRH on SRIF release from median eminence fragments. Brain Res. 1985;348(1):180-182.
Sheppard MC, Kronheim S, Pimstone BL. Stimulation by growth hormone of somatostatin release from the rat hypothalamus in vitro. Clin Endocrinol (Oxf). 1978;9(6):583-586.
Ross RJ, Tsagarakis S, Grossman A, Nhagafoong L, Touzel RJ, Rees LH, Besser GM. GH feedback occurs through modulation of hypothalamic somatostatin under cholinergic control: studies with pyridostigmine and GHRH. Clin Endocrinol (Oxf). 1987;27(6):727-733.
Aguila MC, McCann SM. Growth hormone increases somatostatin release and messenger ribonucleic acid levels in the rat hypothalamus. Brain Res. 1993;623(1):89-94.
Qi X, Reed J, Englander EW, Chandrashekar V, Bartke A, Greeley GH, Jr. Evidence that growth hormone exerts a feedback effect on stomach ghrelin production and secretion. Exp Biol Med (Maywood). 2003;228(9):1028-1032.
Goldenberg N, Barkan A. Factors regulating growth hormone secretion in humans. Endocrinol Metab Clin North Am. 2007;36(1):37-55.
Berelowitz M, Szabo M, Frohman LA, Firestone S, Chu L, Hintz RL. Somatomedin-C mediates growth hormone negative feedback by effects on both the hypothalamus and the pituitary. Science. 1981;212(4500):1279-1281.
Yamashita S, Melmed S. Insulin-like growth factor I action on rat anterior pituitary cells: suppression of growth hormone secretion and messenger ribonucleic acid levels. Endocrinology. 1986;118(1):176-182.
Eden S, Bolle P, Modigh K. Monoaminergic control of episodic growth hormone secretion in the rat: effects of reserpine, alpha-methyl-p-tyrosine, p-chlorophenylalanine, and haloperidol. Endocrinology. 1979;105(2):523-529.
Iranmanesh A, Grisso B, Veldhuis JD. Low basal and persistent pulsatile growth hormone secretion are revealed in normal and hyposomatotropic men studied with a new ultrasensitive chemiluminescence assay. J Clin Endocrinol Metab. 1994;78(3):526-535.
Toogood AA, Nass RM, Pezzoli SS, O'Neill PA, Thorner MO, Shalet SM. Preservation of growth hormone pulsatility despite pituitary pathology, surgery, and irradiation. J Clin Endocrinol Metab. 1997;82(7):2215-2221.
Surya S, Symons K, Rothman E, Barkan AL. Complex rhythmicity of growth hormone secretion in humans. Pituitary. 2006;9(2):121-125.
Tannenbaum GS, Painson JC, Lengyel AM, Brazeau P. Paradoxical enhancement of pituitary growth hormone (GH) responsiveness to GH-releasing factor in the face of high somatostatin tone. Endocrinology.1989;124(3):1380-1388.
Plotsky PM, Vale W. Patterns of growth hormone-releasing factor and somatostatin secretion into the hypophysial-portal circulation of the rat. Science. 1985;230(4724):461-463.
Cataldi M, Magnan E, Guillaume V, Dutour A, Conte-Devolx B, Lombardi G, Oliver C. Relationship between hypophyseal portal GHRH and somatostatin and peripheral GH levels in the conscious sheep. J Endocrinol Invest.1994;17(9):717-722.
Vance ML, Kaiser DL, Martha PM, Jr., Furlanetto R, Rivier J, Vale W, Thorner MO. Lack of in vivo somatotroph desensitization or depletion after 14 days of continuous growth hormone (GH)-releasing hormone administration in normal men and a GH-deficient boy. J Clin Endocrinol Metab. 1989;68(1):22-28.
Roelfsema F, Biermasz NR, Veldman RG, Veldhuis JD, Frolich M, Stokvis-Brantsma WH, Wit JM. Growth hormone (GH) secretion in patients with an inactivating defect of the GH-releasing hormone (GHRH) receptor is pulsatile: evidence for a role for non-GHRH inputs into the generation of GH pulses. J Clin Endocrinol Metab.2001;86(6):2459-2464.
van den Berg G, Veldhuis JD, Frolich M, Roelfsema F. An amplitude-specific divergence in the pulsatile mode of growth hormone (GH) secretion underlies the gender difference in mean GH concentrations in men and premenopausal women. J Clin Endocrinol Metab. 1996;81(7):2460-2467.
Chapman IM, Hartman ML, Straume M, Johnson ML, Veldhuis JD, Thorner MO. Enhanced sensitivity growth hormone (GH) chemiluminescence assay reveals lower postglucose nadir GH concentrations in men than women. J Clin Endocrinol Metab. 1994;78(6):1312-1319.
Cordoba-Chacon J, Gahete MD, Castano JP, Kineman RD, Luque RM. Somatostatin and its receptors contribute in a tissue-specific manner to the sex-dependent metabolic (fed/fasting) control of growth hormone axis in mice. Am J Physiol Endocrinol Metab. 2011;300(1):E46-54.
Udy GB, Towers RP, Snell RG, Wilkins RJ, Park SH, Ram PA, Waxman DJ, Davey HW. Requirement of STAT5b for sexual dimorphism of body growth rates and liver gene expression. Proc Natl Acad Sci U S A.1997;94(14):7239-7244.
Zadik Z, Chalew SA, McCarter RJ, Jr., Meistas M, Kowarski AA. The influence of age on the 24-hour integrated concentration of growth hormone in normal individuals. J Clin Endocrinol Metab. 1985;60(3):513-516.
Rudman D, Feller AG, Nagraj HS, Gergans GA, Lalitha PY, Goldberg AF, Schlenker RA, Cohn L, Rudman IW, Mattson DE. Effects of human growth hormone in men over 60 years old. N Engl J Med. 1990;323(1):1-6.
Fontana L, Partridge L, Longo VD. Extending healthy life span--from yeast to humans. Science.2010;328(5976):321-326.
Junnila RK, List EO, Berryman DE, Murrey JW, Kopchick JJ. The GH/IGF-1 axis in ageing and longevity. Nat Rev Endocrinol. 2013;9(6):366-376.
Nass R, Farhy LS, Liu J, Pezzoli SS, Johnson ML, Gaylinn BD, Thorner MO. Age-dependent decline in acyl-ghrelin concentrations and reduced association of acyl-ghrelin and growth hormone in healthy older adults. J Clin Endocrinol Metab. 2014;99(2):602-608.
Nass R. Growth hormone axis and aging. Endocrinol Metab Clin North Am. 2013;42(2):187-199.
Van Cauter E, Kerkhofs M, Caufriez A, Van Onderbergen A, Thorner MO, Copinschi G. A quantitative estimation of growth hormone secretion in normal man: reproducibility and relation to sleep and time of day. J Clin Endocrinol Metab. 1992;74(6):1441-1450.
Holl RW, Hartman ML, Veldhuis JD, Taylor WM, Thorner MO. Thirty-second sampling of plasma growth hormone in man: correlation with sleep stages. J Clin Endocrinol Metab. 1991;72(4):854-861.
Brandenberger G, Gronfier C, Chapotot F, Simon C, Piquard F. Effect of sleep deprivation on overall 24 h growth-hormone secretion. Lancet. 2000;356(9239):1408.
Van Cauter E, Leproult R, Plat L. Age-related changes in slow wave sleep and REM sleep and relationship with growth hormone and cortisol levels in healthy men. Jama. 2000;284(7):861-868.
Van Cauter E, Latta F, Nedeltcheva A, Spiegel K, Leproult R, Vandenbril C, Weiss R, Mockel J, Legros JJ, Copinschi G. Reciprocal interactions between the GH axis and sleep. Growth Horm IGF Res. 2004;14 Suppl A:S10-17.
Golstein J, Van Cauter E, Desir D, Noel P, Spire JP, Refetoff S, Copinschi G. Effects of "jet lag" on hormonal patterns. IV. Time shifts increase growth hormone release. J Clin Endocrinol Metab. 1983;56(3):433-440.
Vgontzas AN, Mastorakos G, Bixler EO, Kales A, Gold PW, Chrousos GP. Sleep deprivation effects on the activity of the hypothalamic-pituitary-adrenal and growth axes: potential clinical implications. Clin Endocrinol (Oxf).1999;51(2):205-215.
Jaffe CA, Friberg RD, Barkan AL. Suppression of growth hormone (GH) secretion by a selective GH-releasing hormone (GHRH) antagonist. Direct evidence for involvement of endogenous GHRH in the generation of GH pulses. J Clin Invest. 1993;92(2):695-701.
Jaffe CA, Turgeon DK, Friberg RD, Watkins PB, Barkan AL. Nocturnal augmentation of growth hormone (GH) secretion is preserved during repetitive bolus administration of GH-releasing hormone: potential involvement of endogenous somatostatin--a clinical research center study. J Clin Endocrinol Metab. 1995;80(11):3321-3326.
Yildiz BO, Suchard MA, Wong M-L, McCann SM, Licinio J. Alterations in the dynamics of circulating ghrelin, adiponectin, and leptin in human obesity. PNAS. 2004;101(28):10434-10439.
Steiger A, Guldner J, Hemmeter U, Rothe B, Wiedemann K, Holsboer F. Effects of growth hormone-releasing hormone and somatostatin on sleep EEG and nocturnal hormone secretion in male controls. Neuroendocrinology.1992;56(4):566-573.
Weikel JC, Wichniak A, Ising M, Brunner H, Friess E, Held K, Mathias S, Schmid DA, Uhr M, Steiger A. Ghrelin promotes slow-wave sleep in humans. Am J Physiol Endocrinol Metab. 2003;284(2):E407-415.
Sutton J, Lazarus L. Growth hormone in exercise: comparison of physiological and pharmacological stimuli. J Appl Physiol. 1976;41(4):523-527.
Lassarre C, Girard F, Durand J, Raynaud J. Kinetics of human growth hormone during submaximal exercise. J Appl Physiol. 1974;37(6):826-830.
Raynaud J, Capderou A, Martineaud JP, Bordachar J, Durand J. Intersubject variability in growth hormone time course during different types of work. J Appl Physiol. 1983;55(6):1682-1687.
Felsing NE, Brasel JA, Cooper DM. Effect of low and high intensity exercise on circulating growth hormone in men. J Clin Endocrinol Metab. 1992;75(1):157-162.
Vanhelder WP, Goode RC, Radomski MW. Effect of anaerobic and aerobic exercise of equal duration and work expenditure on plasma growth hormone levels. Eur J Appl Physiol Occup Physiol. 1984;52(3):255-257.
Schmidt A, Maier C, Schaller G, Nowotny P, Bayerle-Eder M, Buranyi B, Luger A, Wolzt M. Acute exercise has no effect on ghrelin plasma concentrations. Horm Metab Res. 2004;36(3):174-177.
Chennaoui M, Leger D, Gomez-Merino D. Sleep and the GH/IGF-1 axis: Consequences and countermeasures of sleep loss/disorders. Sleep Med Rev. 2020;49:101223.
Naylor E, Penev PD, Orbeta L, Janssen I, Ortiz R, Colecchia EF, Keng M, Finkel S, Zee PC. Daily social and physical activity increases slow-wave sleep and daytime neuropsychological performance in the elderly. Sleep.2000;23(1):87-95.
Ritsche K, Nindl BC, Wideman L. Exercise-Induced growth hormone during acute sleep deprivation. Physiol Rep.2014;2(10).
Roth J, Glick SM, Yalow RS, Berson SA. Hypoglycemia: a potent stimulus to secretion of growth hormone. Science. 1963;140:987-988.
Greenwood FC, Landon J, Stamp TC. The plasma sugar, free fatty acid, cortisol, and growth hormone response to insulin. I. In control subjects. J Clin Invest. 1966;45(4):429-436.
Hindmarsh PC, Smith PJ, Taylor BJ, Pringle PJ, Brook CG. Comparison between a physiological and a pharmacological stimulus of growth hormone secretion: response to stage IV sleep and insulin-induced hypoglycaemia. Lancet. 1985;2(8463):1033-1035.
Tatar P, Vigas M. Role of alpha 1- and alpha 2-adrenergic receptors in the growth hormone and prolactin response to insulin-induced hypoglycemia in man. Neuroendocrinology. 1984;39(3):275-280.
Jaffe CA, DeMott-Friberg R, Barkan AL. Endogenous growth hormone (GH)-releasing hormone is required for GH responses to pharmacological stimuli. J Clin Invest. 1996;97(4):934-940.
Broglio F, Prodam F, Gottero C, Destefanis S, Me E, Riganti F, Giordano R, Picu A, Balbo M, Van der Lely AJ, Ghigo E, Arvat E. Ghrelin does not mediate the somatotroph and corticotroph responses to the stimulatory effect of glucagon or insulin-induced hypoglycaemia in humans. Clin Endocrinol (Oxf). 2004;60(6):699-704.
Carey LC, Cloutier CT, Lowery BD. Growth hormone and adrenal cortical response to shock and trauma in the human. Ann Surg. 1971;174(3):451-460.
Vigas M, Malatinsky J, Nemeth S, Jurcovicova J. Alpha-adrenergic control of growth hormone release during surgical stress in man. Metabolism. 1977;26(4):399-402.
Roth A, Cligg SM, Yalow RS, Berson SA. Secretion of growth hormone: physiological and experimental modification. Metabolism. 1963;12:557-559.
Penalva A, Burguera B, Casabiell X, Tresguerres JA, Dieguez C, Casanueva FF. Activation of cholinergic neurotransmission by pyridostigmine reverses the inhibitory effect of hyperglycemia on growth hormone (GH) releasing hormone-induced GH secretion in man: does acute hyperglycemia act through hypothalamic release of somatostatin? Neuroendocrinology. 1989;49(5):551-554.
Shiiya T, Nakazato M, Mizuta M, Date Y, Mondal MS, Tanaka M, Nozoe S, Hosoda H, Kangawa K, Matsukura S. Plasma ghrelin levels in lean and obese humans and the effect of glucose on ghrelin secretion. J Clin Endocrinol Metab. 2002;87(1):240-244.
Broglio F, Benso A, Gottero C, Prodam F, Grottoli S, Tassone F, Maccario M, Casanueva FF, Dieguez C, Deghenghi R, Ghigo E, Arvat E. Effects of glucose, free fatty acids or arginine load on the GH-releasing activity of ghrelin in humans. Clin Endocrinol (Oxf). 2002;57(2):265-271.
Hayford JT, Danney MM, Hendrix JA, Thompson RG. Integrated concentration of growth hormone in juvenile-onset diabetes. Diabetes. 1980;29(5):391-398.
Asplin CM, Faria AC, Carlsen EC, Vaccaro VA, Barr RE, Iranmanesh A, Lee MM, Veldhuis JD, Evans WS. Alterations in the pulsatile mode of growth hormone release in men and women with insulin-dependent diabetes mellitus. J Clin Endocrinol Metab. 1989;69(2):239-245.
Salgado LR, Semer M, Nery M, Knoepfelmacher M, Lerario AC, Povoa G, Jana S, Villares SM, Wajchenberg BL, Liberman B, Nicolau W. Effect of glycemic control on growth hormone and IGFBP-1 secretion in patients with type I diabetes mellitus. J Endocrinol Invest. 1996;19(7):433-440.
Ho KY, Veldhuis JD, Johnson ML, Furlanetto R, Evans WS, Alberti KG, Thorner MO. Fasting enhances growth hormone secretion and amplifies the complex rhythms of growth hormone secretion in man. J Clin Invest.1988;81(4):968-975.
Soliman AT, Hassan AE, Aref MK, Hintz RL, Rosenfeld RG, Rogol AD. Serum insulin-like growth factors I and II concentrations and growth hormone and insulin responses to arginine infusion in children with protein-energy malnutrition before and after nutritional rehabilitation. Pediatr Res. 1986;20(11):1122-1130.
Veldhuis JD, Iranmanesh A, Ho KK, Waters MJ, Johnson ML, Lizarralde G. Dual defects in pulsatile growth hormone secretion and clearance subserve the hyposomatotropism of obesity in man. J Clin Endocrinol Metab.1991;72(1):51-59.
Vahl N, Jorgensen JO, Skjaerbaek C, Veldhuis JD, Orskov H, Christiansen JS. Abdominal adiposity rather than age and sex predicts mass and regularity of GH secretion in healthy adults. Am J Physiol. 1997;272(6 Pt 1):E1108-1116.
Ghigo E, Mazza E, Corrias A, Imperiale E, Goffi S, Arvat E, Bellone J, De Sanctis C, Muller EE, Camanni F. Effect of cholinergic enhancement by pyridostigmine on growth hormone secretion in obese adults and children. Metabolism. 1989;38(7):631-633.
Loche S, Pintor C, Cappa M, Ghigo E, Puggioni R, Locatelli V, Muller EE. Pyridostigmine counteracts the blunted growth hormone response to growth hormone-releasing hormone of obese children. Acta Endocrinol (Copenh).1989;120(5):624-628.
Cordido F, Casanueva FF, Dieguez C. Cholinergic receptor activation by pyridostigmine restores growth hormone (GH) responsiveness to GH-releasing hormone administration in obese subjects: evidence for hypothalamic somatostatinergic participation in the blunted GH release of obesity. J Clin Endocrinol Metab. 1989;68(2):290-293.
Cordido F, Penalva A, Peino R, Casanueva FF, Dieguez C. Effect of combined administration of growth hormone (GH)-releasing hormone, GH-releasing peptide-6, and pyridostigmine in normal and obese subjects. Metabolism.1995;44(6):745-748.
Maccario M, Aimaretti G, Grottoli S, Gauna C, Tassone F, Corneli G, Rossetto R, Wu Z, Strasburger CJ, Ghigo E. Effects of 36 hour fasting on GH/IGF-I axis and metabolic parameters in patients with simple obesity. Comparison with normal subjects and hypopituitary patients with severe GH deficiency. Int J Obes Relat Metab Disord.2001;25(8):1233-1239.
Grottoli S, Gauna C, Tassone F, Aimaretti G, Corneli G, Wu Z, Strasburger CJ, Dieguez C, Casanueva FF, Ghigo E, Maccario M. Both fasting-induced leptin reduction and GH increase are blunted in Cushing's syndrome and in simple obesity. Clin Endocrinol (Oxf). 2003;58(2):220-228.
Pedersen MH, Svart MV, Lebeck J, Bidlingmaier M, Stodkilde-Jorgensen H, Pedersen SB, Moller N, Jessen N, Jorgensen JOL. Substrate Metabolism and Insulin Sensitivity During Fasting in Obese Human Subjects: Impact of GH Blockade. J Clin Endocrinol Metab. 2017;102(4):1340-1349.
Carro E, Senaris R, Considine RV, Casanueva FF, Dieguez C. Regulation of in vivo growth hormone secretion by leptin. Endocrinology. 1997;138(5):2203-2206.
Tschop M, Weyer C, Tataranni PA, Devanarayan V, Ravussin E, Heiman ML. Circulating ghrelin levels are decreased in human obesity. Diabetes. 2001;50(4):707-709.
Hansen TK, Dall R, Hosoda H, Kojima M, Kangawa K, Christiansen JS, Jorgensen JO. Weight loss increases circulating levels of ghrelin in human obesity. Clin Endocrinol (Oxf). 2002;56(2):203-206.
Leidy HJ, Gardner JK, Frye BR, Snook ML, Schuchert MK, Richard EL, Williams NI. Circulating Ghrelin Is Sensitive to Changes in Body Weight during a Diet and Exercise Program in Normal-Weight Young Women. J Clin Endocrinol Metab. 2004;89(6):2659-2664.
Lindeman JH, Pijl H, Van Dielen FM, Lentjes EG, Van Leuven C, Kooistra T. Ghrelin and the hyposomatotropism of obesity. Obes Res. 2002;10(11):1161-1166.
Yu AP, Ugwu FN, Tam BT, Lee PH, Ma V, Pang S, Chow AS, Cheng KK, Lai CW, Wong CS, Siu PM. Obestatin and growth hormone reveal the interaction of central obesity and other cardiometabolic risk factors of metabolic syndrome. Sci Rep. 2020;10(1):5495.
Tamboli RA, Antoun J, Sidani RM, Clements A, Harmata EE, Marks-Shulman P, Gaylinn BD, Williams B, Clements RH, Albaugh VL, Abumrad NN. Metabolic responses to exogenous ghrelin in obesity and early after Roux-en-Y gastric bypass in humans. Diabetes Obes Metab. 2017;19(9):1267-1275.
Sukkar MY, Hunter WM, Passmore R. Changes in plasma levels of insulin and growth-hormone levels after a protein meal. Lancet. 1967;2(7524):1020-1022.
Parker ML, Hammond JM, Daughaday WH. The arginine provocative test: an aid in the diagnosis of hyposomatotropism. J Clin Endocrinol Metab. 1967;27(8):1129-1136.
Alba-Roth J, Muller OA, Schopohl J, von Werder K. Arginine stimulates growth hormone secretion by suppressing endogenous somatostatin secretion. J Clin Endocrinol Metab. 1988;67(6):1186-1189.

Adolescent Bariatric Surgery

ABSTRACT

The prevalence of adolescent obesity has rapidly increased over the past several decades. With this increase, there has also been a rise in the prevalence of complications of obesity leading to premature mortality. While lifestyle and medical management remain a part of the initial treatment of obesity, these therapies have been shown to be inferior when compared to metabolic and bariatric surgery (MBS) for adolescents with severe obesity. A multidisciplinary approach is recommended to evaluate medically eligible candidates for MBS, prepare patients for surgery, and guide postoperative management. Laparoscopic sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB) are the most common MBS procedures performed in both adolescent and adult patients. Postoperative hospital stays are generally short and long-term routine follow-up with the MBS team is recommended to monitor weight loss, resolution of complications of obesity, and to monitor for postoperative complications. Most adolescent MBS studies demonstrate an average percent body mass index loss between 25-29% after surgery. This is also associated with resolution or improvement of most complications of obesity at rates that are similar or superior to adult studies. Resolution and prevention of type 2 diabetes mellitus (T2DM) after MBS is a particularly compelling reason to pursue surgical treatment due to the complications from T2DM that occur over a patient’s lifetime as well as the overall burden of health-related costs. These adverse consequences of T2DM can be mitigated by early use of MBS. MBS is generally well tolerated. Complication rates are similar to adult patients therefore it is recommended to refer patients for MBS whenever they are medically qualified. Most common short-term (<30 days) complications include leak, bleeding, and surgical site infections. Most common long-term (>30 days) complications are nutritional deficiencies.

INTRODUCTION

The prevalence of worldwide overweight and obesity in adolescents has more than quadrupled since 1975. Currently, it is estimated that over 14 million children and adolescents age 2-19 years suffer from obesity in the United States alone (1, 2). Adolescents with obesity are at risk for developing significant comorbidities including insulin resistance, type 2 diabetes mellitus (T2DM), hypertension, dyslipidemia, obstructive sleep apnea, nonalcoholic fatty liver disease, depression, polycystic ovarian syndrome, impaired quality of life, cardiovascular disease, and longer term, certain malignancies (3-9). Similar to obesity, the prevalence of T2DM has been increasing dramatically (3). Obesity is a major risk factor the development of T2DM with overweight adolescents having close to a three times greater risk of developing T2DM when compared to adolescents with normal weight (10-12). Additionally, obesity in adolescence is associated with persistent obesity into adulthood, increased risk for obesity related comorbidities, and premature mortality in adulthood (13-15). Lifestyle and medical management remain the first-line treatment for adolescent obesity. However, current evidence suggests that pharmacotherapy, dietary, and behavioral modifications rarely lead to long-term weight loss in adolescents with severe obesity (16-18). The use of metabolic and bariatric surgery (MBS) in adolescents with severe obesity and complications of obesity has been shown to have superior results in both efficacy and durability (19). Despite growing evidence of the efficacy and durability of MBS for the treatment of severe obesity in adolescent patients, utilization of MBS in adolescent patients is low and there have been documented racial and socioeconomic disparities (20-22).

PREOPERATIVE EVALUATION

Multidisciplinary Program

A multidisciplinary approach is recommended when considering MBS for an adolescent (23, 24). At a minimum, this includes a bariatric surgeon with adolescent experience, pediatrician, dietitian, nurse, and pediatric psychologist. It is also important that the core providers have access to additional pediatric specialists including anesthesiologists, radiologists, and appropriate specialists to aid the management of complications of obesity (e.g., pulmonology, endocrinology, gastroenterology/hepatology). Adolescents undergoing preoperative work-up should be evaluated for the presence and severity of complications of obesity. Additionally, it is important for the multidisciplinary team to determine a potential patient and caregivers’ ability to assess the risks and benefits of surgery as well as to adhere to postoperative requirements including daily vitamin regimens and attending postoperative visits.

Patient Selection

BODY MASS INDEX (BMI)

The following criteria have been recommended by multiple panels of experts for consideration of weight loss surgery in adolescents under 18 years old: (4, 19, 25)

BMI ≥ 120 percent of the 95^th percentile for BMI for age or BMI ≥ 35kg/m², whichever is lower, with complications of obesity that have a significant effect on health (Table 1).
OR -
BMI ≥ 140 percent of the 95^th percentile of BMI for age or BMI ≥ 40 kg/m², whichever is lower

Of note, the BMI threshold for adult patients for the recommendation has been reduced in the 2022 guidelines, therefore changes to adolescent recommendations may follow suit in future updates (26).

Table 1. Qualifying Comorbidities for Consideration of MBS in Adolescents (4).
Obstructive sleep apnea (apnea-hypoxia index > 5)
Type 2 diabetes mellitus
Idiopathic intracranial hypertension
Nonalcoholic steatohepatitis
Blount’s disease
Slipped capital femoral epiphysis
Gastroesophageal Reflux Disease
Hypertension

CONTRAINDICATIONS

Contraindications to adolescent MBS are listed in Table 2.

Table 2. Contraindications to Adolescent MBS
Medically correctable cause of obesity
Ongoing substance abuse problem (within the preceding year)
Medical, psychiatric, psychosocial, or cognitive condition that prevents adherence to postoperative dietary and medication regimens or impairs decisional capacity
Current or planned pregnancy within 18 months of the procedure
Inability for patient or caregivers to comprehend risks and benefits of surgical weight loss procedure

AGE

A recent cohort analysis of more than 600,000 adolescents aged 13-17 found that 1 in 23 adolescents met criteria for MBS (27). A retrospective review of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) data registry from 2015 to 2018 demonstrated that adolescents and young adults only represented 3.7% of total MBS cases performed, suggesting significant underutilization within this population (28). Multiple studies have evaluated the safety and efficacy of MBS in younger adolescents. Current evidence suggests there are no significant clinical differences in outcomes between MBS in younger (e.g., <13 years) versus older adolescents (e.g., ≥13 years) (29-35). It is therefore not recommended to limit access to MBS based on patient’s age, physical maturity (e.g., bone age), or pubertal status. These findings have prompted increased advocacy for the use of MBS in the adolescent population by the American Academy of Pediatrics (19, 36).

TYPES OF SURGERY

Sleeve Gastrectomy

A laparoscopic sleeve gastrectomy (SG) results in the removal of the greater curvature of the stomach resulting in a smaller, tubular stomach that has a reduced capacity (Figure 1). Given the procedure is less complex than the Roux-en-Y gastric bypass (RYGB) and has less risk for micronutrient deficiencies, it is an appealing option for adolescents. Sleeve gastrectomies currently account for approximately 80% of bariatric procedures in adolescents (28, 37-39). A SG may also be converted to RYGB in the event additional MBS is indicated or in the setting of postoperative medically refractory gastroesophageal reflux disease (GERD).

Figure 1. Sleeve Gastrectomy.

Roux-en-Y Gastric Bypass

Laparoscopic Roux-en-Y gastric bypass (RYGB) involves creating a small, proximal gastric pouch which is separated from the remnant stomach and anastomosed to a Roux-limb of small bowel 70-150 cm distally (Figure 2). The RYGB results in similar weight loss when compared to SG and dramatically improves glycemic control (38, 40). The incidence of postoperative GERD is significantly less following RYGB compared to SG, making the procedure an attractive option for adolescents with GERD at baseline (41).

Figure 2. Roux-en-Y Gastric Bypass.

Others

Additional procedures including intragastric balloons are not currently approved by the United States Food and Drug Administration (FDA) for use in adolescents. Adjustable gastric bands have been previously used in the adolescent population. However, they have fallen out of favor due inferior efficacy compared to SG and RYGB (42).

POSTOPERATIVE MANAGEMENT

Inpatient

Average inpatient stay is typically <2 days following both a SG and RYGB (43). Patients are monitored for immediate postoperative complications including a leak, bleeding, and venous thromboembolism (VTE). Following discharge, patients are seen at regular postoperative visits to monitor body weight, nutritional status, and to manage complications of obesity.

Diet

Following a SG or RYGB, patients gradually progress from a high protein liquid diet to incorporating small volumes of regular food. Patients are encouraged to eat three to four protein-rich meals a day while avoiding carbohydrate rich foods. Supplemental sugar-free fluids between meals are also essential following surgery to avoid dehydration. Patients are typically encouraged to avoid excessive fluids with meals to minimize nausea and maximize nutritional intake with meals due to the restrictive component of both procedures.

Postoperative nausea is not uncommon following surgery but typically self resolves. Meals high in carbohydrates or sugar and fats can result in dumping syndrome or weight regain following surgery. Some providers recommend limiting carbonated or caffeinated beverages following MBS based on theoretical concerns, however there is minimal evidence to support this apprehension.

Similar to non-operative weight loss recommendations, general recommendations including exercising for 30 to 60 minutes daily, drinking sugar-free fluids, and portion-controlled protein rich meals are the same. Overall, it is recommended that patient and caregiver meet with a dietitian prior to discharge to develop a plan tailored to patient’s specific nutritional needs. Regular follow-up visits with a dietitian are also recommended to assist with postoperative weight management and to monitor for nutritional deficiencies.

Nutritional Supplements and Monitoring

Although SG may be associated with a decreased risk of nutritional deficiencies when compared to RYGB, lifelong supplementation with vitamins and minerals is recommended following both operations (Table 3) (44). Patients are particularly at risk for deficiencies in iron, vitamin B12, and vitamin D. Additionally, lifelong annual monitoring of nutritional and micronutrient status is recommended with annual laboratory testing (Table 3). Adjustments in supplements may need to be made over time as specific deficiencies emerge.

Table 3. Nutritional Supplementation and Monitoring Recommendations (45)
Nutritional Supplements
Standard multivitamin with folate or iron, or prenatal vitamin if female (once or twice daily)
Vitamin B12, 500mcg sublingually daily, or 1000mcg intramuscularly monthly
Calcium, 1200 to 1500mg daily (measured as elemental calcium) with 800 to 1000 international units of vitamin D.
Annual Nutritional Monitoring
Complete blood cell count with differential
Serum iron and ferritin
Red blood cell folate, serum vitamin B12, and serum homocysteine
Serum thiamin (vitamin B1)
Hepatic panel (including albumin, total protein, serum aminotransferase levels, gamma-glutamyl transpeptidase, and alkaline phosphatase
Calcium, 25-hydroxyvitamin D, and parathyroid hormone
Dual-energy x-ray absorptiometry (DXA) scan to monitor bone density (optimal frequency not yet established)

Pregnancy Prevention

Pregnancy should be avoided for 12 to 18 months following MBS to allow patients to achieve weight maintenance and to avoid potential micronutrient deficiencies which may affect both patient and fetus (46). Obesity can result in decreased fertility secondary to irregular menstruation and ovulatory dysfunction (47, 48). Weight loss after MBS has been shown to result in more regular ovulation and improved fertility (49, 50). In a retrospective review of 47 adolescents who underwent MBS surgery, seven pregnancies occurred, six of them within 10 to 22 months following surgery (51). While all six deliveries were healthy and at term, the twofold higher than anticipated pregnancy rate highlights the need for contraception counseling following MBS.

Multiple studies have evaluated the efficacy of hormonal contraceptive methods in patients with elevated BMIs and no definitive association was found between higher BMI and effectiveness of hormonal contraceptives (52). Due to concern for malabsorption after intestinal bypass procedures and the subsequent potential for decreased oral contraceptive efficacy, the American College of Obstetrics and Gynecology recommend using non-oral forms of hormonal contraception in patients who have undergone malabsorptive MBS (53). Additionally, oral contraceptives are associated with increased risk of venous thromboembolism (VTE) which may be worrisome for adolescents with elevated BMIs who already have a higher predisposition for VTE (54, 55).

Intrauterine devices (IUDs) are an appealing option following MBS in adolescent patients as they are one of the most effective contraception methods, do not increase risk of VTE, and can be placed at the time of surgery (56). Levonorgestrel-releasing IUDs have the added benefit of promoting amenorrhea which could help reduce the risk of iron deficiency anemia following surgery (57). Regardless of the form of contraception selection, adolescents should be counseled on safe sex practices including the use of barrier protection against sexually transmitted infections.

Adolescent patients who become pregnant following MBS should be counseled on adequate nutritional intake with close monitoring of iron, folate, and vitamin B12 levels. Additionally, one must be cautious when screening for gestational diabetes in pregnant patients who have undergone MBS. In a study of a 119 post-bariatric surgery pregnant patients, oral glucose tolerance test resulted in hypoglycemia in 83% of patients with history of RYGB and 55% of patients with history of SG (58). Alternative methods for screening such as capillary blood glucose measurements are therefore recommended. These methods recommend obtaining capillary blood glucose values before and after each meal for 3-7 days and using pre-and post-prandial capillary glucose values according to recommended cut-off values for defining diabetes mellitus (59, 60).

Comorbidity Reassessment

Regular reassessment of complications of obesity should occur at routine intervals in the postoperative phase to monitor for resolution or need for continued management. Patients with T2DM should be evaluated by their endocrinologist every three months. Repeat polysomnography is generally obtained between three to six months after surgery for patients previously on continuous positive airway pressure therapy (61, 62). Twenty-four-hour blood pressure monitoring can also be repeated three months after surgery to demonstrate resolution or persistence of hypertension. Medication may be restarted if blood pressure is consistently ≥120 mmHg systolic or ≥80 mmHg diastolic. Patients with biopsy proven nonalcoholic fatty liver disease may be re-biopsied 12 months after surgery to document regression. Finally, patients’ mental health needs should be re-evaluated by a pediatric psychologist at 6 and 12 months after surgery.

In the setting of weight regain, patients should be monitored for complications of obesity. There is emerging evidence however, that some complications of obesity may be weight dependent and others non-weight dependent (63). Some surgeons will routinely obtain an upper gastrointestinal contrast study at 12 months after surgery or as needed to assess anatomy which may lead to weight regain. Anatomical abnormalities that may contribute to weight regain include a dilated gastric sleeve or gastrogastric fistula.

Follow Up

Close follow up with the multidisciplinary team including the bariatric surgeon, pediatrician, dietitian, and pediatric psychologist is strongly recommended. Patients are typically followed by a pediatrician to ensure ongoing continuity of care. It is important for the core providers to have access to pediatric specialists including endocrinology, gastroenterology/hepatology, and pulmonology as needed in those with complications of obesity that require ongoing monitoring or management. Additionally, a gynecologist for contraception counseling may be required for female patients. The transition from pediatric to adult medicine can be challenging in patients with chronic medical conditions and frequently requires assistance from multiple members of the team for transition care coordination and preparation as well as to ensure adequate communication, support, and education (64-66).

OUTCOMES

Percent BMI Loss

Both SG and RYGB have resulted in clinically significant weight loss in adolescents. The efficacy of both procedures appears to be similar in the adolescent population(67). In a large, multicenter analysis of 177 adolescents who underwent RYGB and 306 adolescents who underwent SG, there was a three-year postoperative average percent BMI loss of 29% (95% CI, 26 to 33) and 25% (95% CI, 22 to 28) for RYGB and SG, respectively (38). Similar results were seen in the Teen Longitudinal Assessment of Bariatric Surgery (Teen-LABS) the largest prospective, observational study to date of 228 adolescents undergoing either RYGB or SG. The three-year analysis showed an average 28% reduction in BMI following RYGB compared to 26% reduction following SG (62). In the 10 year analysis of Teen-LABS data for Roux-en-Y gastric bypass (RYGB, n = 161) and sleeve gastrectomy (SG, n = 99), 83% of those eligible for 10 year follow up completed the full decade of data collection (68). The findings revealed long-term BMI reductions for both procedures, with RYGB showing a 20.6% decrease and SG a 19.2% decrease. Furthermore, initial BMI loss (within the first six months) proved to be a strong predictor of 10-year outcomes. It is noteworthy that some smaller, single center studies have demonstrated long term (7-14 year) BMI reductions after RYGB up to 30% in patients who underwent surgery in their adolescence (69-71).

Complications of Obesity

TYPE 2 DIABETES MELLITUS

Multiple studies have demonstrated improved glycemic control, even remission as well as prevention of T2DM following MBS, making a compelling case of MBS as a treatment for T2DM (40, 70, 72-75). Of the 242 adolescents enrolled in Teen-LABS, 29 had T2DM at baseline. By 3 years after the procedure, remission of T2DM occurred in 95% (95% CI, 85-100) of participants with no new cases of T2DM in those without the condition at baseline (62). Additionally, 19 participants had prediabetes at baseline with a 76% (95% CI, 56-97) rate of remission at 3 years (62). These remission rates in Teen-LABS were compared to adults who underwent MBS. The Teen-LABS study's 10-year metabolic findings demonstrated sustained improvements in comorbidities for most participants, with a remission rate of 55% for type 2 diabetes (68). In contrast to adult studies, diabetes outcomes when surgery was used in adolescents were comparable between RYGB and SG. It is also worth mentioning that the long-term remission rate for type 2 diabetes (55% at 10 years) significantly exceeds that observed in adults undergoing bariatric surgery for diabetes, where long term remission rates have been estimated to be around 15% (76). These results highlight the durability of both weight loss and diabetes remission in adolescents undergoing RYGB. Finally, among those who underwent RYGB, adolescents were more likely to have remission of T2DM at 5 years with a remission rate of 86% compared to 53% in adults (77). These data underscore that the health benefits of bariatric surgery may be more pronounced in adolescents than in adults.

Similar findings were demonstrated in another study of 226 adolescents undergoing SG, of which 23% of patients were found to have T2DM. Eighty-five percent of patients with T2DM were on medication for diabetes prior to surgery and 89% achieved normal fasting plasma glucose and hemoglobin A1c levels without the use of medication postoperatively (61).

To compare surgical versus medical therapy for T2DM in adolescents with severe obesity, data from participants with T2DM enrolled in the Teen-LABS study were compared to participants of similar age and racial distribution from the Treatment Options of Type 2 Diabetes in Adolescents and Youth (TODAY) studies. Teen-LABS participants underwent MBS. TODAY participants were randomized to metformin alone or in combination with rosiglitazone or intensive lifestyle intervention, with insulin therapy given for glycemic progression. At two years, mean hemoglobin A1c concentration decreased from 6.8% to 5.5% in patients who underwent MBS compared to an increase from 6.4% to 7.8% in those enrolled in the TODAY study. Compared to baseline, average BMI decreased by 29% in Teen-LABS participants while the average BMI increased by 3.7% in TODAY participants (78). Cardiovascular disease (CVD) risk reduction was also explored in a secondary analysis of this study and despite higher pretreatment risk for CVD, treatment with MBS resulted in reduction of estimated CVD that were sustained at 5-year follow-up where medical therapy was associated with an increase in risk of CVD in adolescents with T2DM and severe obesity (79).

While these initial results are promising of the beneficial effects of MBS for the treatment of T2DM, no studies have prospectively compared the efficacy of MBS with that of medical therapy for the treatment of T2DM in adolescents with obesity. Additionally, the majority of initial MBS data in adolescents were from those who underwent RYGB which is no longer the primary MBS procedure performed in adolescents due to its inferior safety profile. In 2019, the National Institute of Health funded the Surgical or Medical Treatment for Pediatric T2DM (ST₂OMP) trial which will compare SG to advanced medical therapy (80, 81).

OTHER COMORBIDITIES

In the Teen-LABS study described above, a mean 74% (95% CI, 64 to 84) remission of hypertension (HTN), 66% (95% CI 57 to 74) remission of dyslipidemia, and 86% (95% CI 72 to 100) resolution of abnormal kidney function was found at 3 years (62). In a secondary analysis of Teen-LABS and TODAY data, medical management of adolescents with obesity was associated with higher odds of diabetic kidney disease when compared to MBS (82). Greater weight loss after MBS in adolescents has also been associated with greater remission of T2DM, HTN, and dyslipidemia (63, 83). In a comparison of adolescents and adults who underwent RYGB, adolescents were more likely to have remission of HTN at 5 years compared to adults (68% vs 41%) (77).

Additional studies have demonstrated a 66% to 84% remission of obstructive sleep apnea as well as improvements in liver disease and polycystic ovarian syndrome (8, 61, 84). Improvements in functional mobility as well as reduction in musculoskeletal pain have also been well described (85, 86).

Mental Health

Multiple studies have reported higher rates of depression, emotional and behavioral disorders, and suicidal ideation in adolescents with obesity (87-90). Additionally, binge and loss of control eating is prevalent among more than one quarter of adolescents with overweight and obesity (91, 92). A recent prospective study demonstrated that undergoing MBS in adolescence did not heighten or lower the risk of suicidal thoughts or behaviors following the initial 4 years after surgery (93). While still unclear whether obesity leads to psychopathology, or vice versa, the association highlights the need for appropriate psychological services in the pre- and postoperative period (87).

MBS can lead to improvements in psychosocial outcomes, although the improvements in some studies are transient. In the TEEN-Labs study, quality of life measured by the Impact of Weight on Quality of Life and Short Form 36 Health Survey improved after MBS (62, 86). When compared to a nonsurgical control, Teen-LABS participants also demonstrated significantly higher levels of self-worth and romantic self-perceptions 6 years after surgery (94). Several studies have demonstrated improved depressive and anxiety symptoms in the months following MBS, although the results were not maintained after the first postoperative year (95, 96). In a multisite study assessing two year follow up of psychopathology prevalence in adolescents undergoing MBS, most patients retained their symptomatic or non-symptomatic psychopathology status at two years, although remission of symptoms was more prevalent than the development of new symptoms (97). These results emphasize the need for long-term psychosocial monitoring following MBS as well as early treatment in those with psychopathology.

Substance and alcohol abuse have been observed in post-MBS adolescents and adults. Pre and postoperative screening and education regarding substance and alcohol addiction should be integrated in long-term follow up care (98).

Short-Term Complications

Short-term complications (<30 days after surgery) in adolescents undergoing MBS are similar to those seen in adults. Early postoperative complications, though rare, include surgical site infections, bleeding, leak, strictures, and pulmonary embolism. In a retrospective review of 21,592 adolescents and young adults who underwent SG or RYGB between 2015 and 2018, 3.7% of patients required readmission, 1.1% of patients required reoperation, and 3.3% required percutaneous, endoscopic, or other intervention (28). Major complications were rare; the most common complication was bleeding (0.4%), followed by leak (0.4%), and deep surgical site infections (0.2%). RYGB was associated with higher rates of reoperation (2.1% vs. 0.8%), readmission (6.3% vs. 3.0%), and serious complications (5.5% vs. 1.8%) compared to SG. Mortality occurred in 0.05% of patients and there were no differences in mortality noted between groups (28). Similar complication rates were found in a more recent analysis of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database in patients aged 10-19 years old (99). In an additional retrospective review of 483 adolescents (SG n=306, RYGB n=177) no perioperative deaths occurred and the rate of major adverse events were too rare for statistical comparison. VTEs occurred in only 0.4% of patients and failure to discharge in 30 days was observed in 0.7% of patients (38).

Multiple studies have also suggested that MBS may be safer in adolescents when compared with adults. In a large study evaluating perioperative outcomes of MBS between 309 adolescents and 55,192 adults, the overall 30-day complication rate was significantly lower in adolescents (5.5%) as compared with adults (9.8%). No in-hospital mortalities occurred in the adolescent group compared to 0.2% in the adult group. The 30-day morbidity for adolescents following SG was zero compared to 4.3% following RYGB (100). In an additional study evaluating 1047 adolescents,10,429 college-aged individuals, and 24,841 young adults who underwent SG or RYGB, there were no differences in 30-day complication rates between age groups (101).

Long-Term Complications

NUTRITIONAL DEFICIENCIES

Long-term complications after MBS in adolescents are primarily nutritional. Patients are particularly at risk for deficiencies in iron, vitamin B12, and vitamin D. Iron deficiency is common in premenopausal females due to menstruation. Some patients may require iron infusion if oral supplementation is not adequate. Symptomatic thiamine deficiency following MBS is rare, however can have serious consequences (102-104).These risks are higher for patients who undergo RYGB compared to SG due to potential malabsorption. In a Teen-LABS study evaluating nutritional deficiencies at 5 years postoperatively, low serum ferritin levels were seen in 71% of patients who underwent RYGB compared to 45% following a SG indicating iron deficiency (102). Iron deficiency anemia can occasionally be severe in adolescent women following MBS which can be compounded by menstruation and challenges in recognizing symptoms therefore daily supplementation and routine nutritional monitoring is essential following MBS.

Vitamin B12 deficiency was seen in approximately 12% of patients after either procedure. Approximately 40% of patients had low vitamin D levels at baseline with no significant change at follow up. Parathyroid hormone concentrations increased in patients undergoing RYGB from an average baseline concentration of 44 pg/ml to 59 pg/ml at 5 years with the risk of abnormal parathyroid hormone levels nearly sixfold higher after RYGB compared with SG (102). Elevated parathyroid hormone is utilized as a surrogate for calcium deficiency and raises concerns about long-term bone health. In adolescents, reduced bone mass has been noted 5-11 years after MBS, whether this increases long term fracture risk remains unclear.(105, 106). Concerns of growth retardation after MBS have been refuted and the most recent adolescent ASMBS guidelines have removed the recommendation of patients reaching physical maturity prior to MBS (4, 30).

The risk of nutritional deficiencies decreases with adherence to prescribed micronutrient supplements and increases with pregnancy (102). Given the high prevalence of nutritional deficiencies, lifelong micronutrient supplementation is required following surgery. One concern emphasized in the adolescent population is adherence to regular multivitamin use. In a prospective study of 41 adolescents who underwent MBS, multivitamin adherence was only 29.8% 23.9 (107).

WEIGHT REGAIN

Current data demonstrates satisfactory maintenance of weight loss at long-term follow up with both SG and RYGB (38, 71, 108), but in other detailed analysis of weight regain trajectories, there are distinct groups that emerge in a large enough dataset. The Teen-LABS data at 10 years showed that 38% of the cohort experienced moderate weight regain. One trajectory group experienced a nadir of 25% weight loss at five years but only maintained 13% loss at 10 years. Another group (11% of the cohort) showed poor results with a weight loss peak at 20% at five years, but then proceeding to regain all weight from 5-10 years, resulting in a 7% BMI increase (above baseline) by 10 years (68). Some adult studies have demonstrated utility of anti-obesity medications after MBS to mitigate weight regain after surgery, however this has not been thoroughly explored in the adolescent population (109, 110). More research is needed to fully understand the mechanisms behind long-term weight maintenance after MBS.

OTHER COMPLICATIONS

Cholelithiasis is a common complication due to rapid weight loss following MBS in both adolescents and adults. In the Teen-LABS study, cholecystectomy was required within three years in 9.9% of adolescents who underwent RYGB and 5.1% who underwent SG (62). Five percent of Teen-LABS participants required other abdominal operations including lysis of adhesions, gastrostomy, ventral hernia repair, or internal hernia repair (62). Symptoms of GERD, nausea, bloating, and diarrhea can also increase following MBS. During five years of follow up, the incidence of GERD increased from 2% to 8% in adolescents who underwent RYGB and from 11% to 24% in those who underwent SG. At five years postoperatively, the SG group had more than fourfold greater odds of having gastrointestinal distress symptoms when compared to RYGB (41). Dumping syndrome can been seen after both procedures, however it is much more common after RYGB compared to SG (111, 112). The incidence of dumping syndrome (~12%) in adolescents after RYGB was similar to adult patients two years after surgery(113).

There are no current established guidelines for surveillance of Barrett’s esophagus after SG for adolescent patients, however routine screening is recommended for adult patients after SG, therefore it would be prudent for adolescent patients to undergo intermittent surveillance also as the length of possible GERD exposure is theoretically longer (114). Similarly, there are no established guidelines for monitoring of bone density following use of MBS in adolescence, but due to inadequate vitamin D levels and rising PTH at least in those who underwent RYGB, periodic monitoring with DEXA may be prudent.

Emerging Evidence

Current evidence evaluating the outcomes and efficacy of adolescent MBS is generally limited to ≤10 years of follow up. Smaller, long-term studies with data available for up to 18 years post-operatively in patients who primary underwent RYGB demonstrate the durability of weight loss and similar rates of complications, although inference is limited due to small sample sizes with reduced attrition rates (70-72, 115, 116). Characteristics including study size, length of follow up, and attrition rate of available studies on MBS published from 2012 to present are available in Table 4. As SG is now the most predominate MBS procedure performed in the Unites States long-term data with this procedure is required. While some longitudinal studies are ongoing (Table 4), there remains a paucity of long-term data in the adolescent population.

Table 4. Characteristics of Studies on MBS, 2012 – Present
Author; Year	Study Design	Sample Size (N)	Type of MBS RYBG SG		Longest follow up	N (1 yr)	N (3 yr)	N (5 yr)	Comments
Inge; 2018 (38)	RO	483	177	306	5 yr	466 (96%)	153 (32%)	41 (8%)	The PCORnet bariatric study (2005 – 2015)
Olbers; 2017 (69)	CC	81	81	0	5 yr	81 (100%)	n/a	81 (100%)	Adolescent Morbid Obesity Surgery (AMOS) study
Inge; 2017(70)	PO	74	74	0	12.5 yr	n/a	n/a	58 (81%)	Adolescent Bariatric Surgery at 5 Plus Years (FABS-5+) study (2001-2007); mean follow up 8.0 yr
Inge; 2016 (62)	PO	228	161	67	3 yr	205 (90%)	194 (85%)	n/a	Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study; (2007-2012)
Vilallonga; 2016 (72)	RO	19	19	0	10.2 yr	n/a	n/a	n/a	Mean follow up 7.2 years; (2003-2008)
Al-Sabah; 2015 (73)	RO	125	0	135	4 yr	54 (40%)	n/a	n/a	2 yr follow up: 46 (34%); (2008-2012)
Cozacov; 2014 (115)	RO	18	8	10	7 yr	15 (83%)	10 (56%)	n/a	7 yr follow up: 3 (17%); (2002 – 2011)
Messiah; 2013 (84)	PO	454	454	0	1 yr	108 (24%)	n/a	n/a	Bariatric Outcomes Longitudinal Database (BOLD) (2004-2010)
Alqahtani; 2012 (31)	RO	108	0	108	2 yr	41 (38%)	n/a	n/a	2 yr follow-up: 8 (7%); (2008 – 2011)
Nijhawan; 2012 (116)	RO	25	25	0	9 yr	n/a	n/a	20 (80%)	Study dates not provided
de la Cruz-Muñoz; 2022 (71)	RO	96	87	1	18 yr	n/a	n/a	n/a	Mean follow up 14.2 years (2002-2010).

RO- Retrospective observational; CC- Case-control; PO- Prospective observational

CONCLUSION

Surgical weight loss is an appropriate consideration for adolescents with severe obesity and/or complications of obesity who have failed to lose weight through other obesity management options. It is essential that adolescents undergoing evaluation for MBS do so in the context of a multidisciplinary program with specific expertise in adolescent medicine and MBS. SG and RYGB are safe and effective treatment options in adolescents. Weight loss outcomes are comparable between SG and RYGB. Both procedures also result in substantial improvement in complications of obesity, including T2DM. SG appears to have an improved safety profile when compared to RYGB and is now the most common adolescent bariatric procedure performed in the United States. Emerging evidence demonstrates advantages of earlier surgical intervention in those with obesity including improved weight loss, increased resolution of comorbidities, and decreased adverse events when compared to adults (77, 117). Perioperative complications in adolescents undergoing MBS are similar to those in adults but occur less frequently (100, 101). Long-term complications are primarily nutritional and life-long vitamin and mineral supplementation is recommended. Regular follow up is required following MBS and it is important for patients to have access to appropriate medical, dietary, and psychological care.

REFERENCES

Obesity and overweight World Health Organization2020 [Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.
Prevention CfDCa. Childhood Obesity Facts[updated APRIL 2, 2024; cited 2024 April 2, 2024]. Available from: https://www.cdc.gov/obesity/php/data-research/childhood-obesity-facts.html.
Rosenbaum M. Special Considerations Relevant to Pediatric Obesity. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, de Herder WW, Dhatariya K, et al., editors. Endotext. South Dartmouth (MA)2000.
Pratt JSA, Browne A, Browne NT, Bruzoni M, Cohen M, Desai A, et al. ASMBS pediatric metabolic and bariatric surgery guidelines, 2018. Surg Obes Relat Dis. 2018;14(7):882-901.
Xanthakos SA, Jenkins TM, Kleiner DE, Boyce TW, Mourya R, Karns R, et al. High Prevalence of Nonalcoholic Fatty Liver Disease in Adolescents Undergoing Bariatric Surgery. Gastroenterology. 2015;149(3):623-34.e8.
Zeller MH, Roehrig HR, Modi AC, Daniels SR, Inge TH. Health-related quality of life and depressive symptoms in adolescents with extreme obesity presenting for bariatric surgery. Pediatrics. 2006;117(4):1155-61.
Legro RS, Arslanian SA, Ehrmann DA, Hoeger KM, Murad MH, Pasquali R, et al. Diagnosis and treatment of polycystic ovary syndrome: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2013;98(12):4565-92.
Kaar JL, Morelli N, Russell SP, Talker I, Moore JM, Inge TH, et al. Obstructive sleep apnea and early weight loss among adolescents undergoing bariatric surgery. Surg Obes Relat Dis. 2021;17(4):711-7.
Avgerinos KI, Spyrou N, Mantzoros CS, Dalamaga M. Obesity and cancer risk: Emerging biological mechanisms and perspectives. Metabolism. 2019;92:121-35.
Tirosh A, Shai I, Afek A, Dubnov-Raz G, Ayalon N, Gordon B, et al. Adolescent BMI trajectory and risk of diabetes versus coronary disease. N Engl J Med. 2011;364(14):1315-25.
Abdullah A, Stoelwinder J, Shortreed S, Wolfe R, Stevenson C, Walls H, et al. The duration of obesity and the risk of type 2 diabetes. Public Health Nutr. 2011;14(1):119-26.
Lee JM, Gebremariam A, Vijan S, Gurney JG. Excess body mass index-years, a measure of degree and duration of excess weight, and risk for incident diabetes. Arch Pediatr Adolesc Med. 2012;166(1):42-8.
Fontaine KR, Redden DT, Wang C, Westfall AO, Allison DB. Years of life lost due to obesity. Jama. 2003;289(2):187-93.
Greenberg JA. Obesity and early mortality in the United States. Obesity (Silver Spring, Md). 2013;21(2):405-12.
Inge TH, King WC, Jenkins TM, Courcoulas AP, Mitsnefes M, Flum DR, et al. The effect of obesity in adolescence on adult health status. Pediatrics. 2013;132(6):1098-104.
Berkowitz RI, Wadden TA, Gehrman CA, Bishop-Gilyard CT, Moore RH, Womble LG, et al. Meal replacements in the treatment of adolescent obesity: a randomized controlled trial. Obesity (Silver Spring, Md). 2011;19(6):1193-9.
Andela S, Burrows TL, Baur LA, Coyle DH, Collins CE, Gow ML. Efficacy of very low-energy diet programs for weight loss: A systematic review with meta-analysis of intervention studies in children and adolescents with obesity. Obes Rev. 2019;20(6):871-82.
Srivastava G, Fox CK, Kelly AS, Jastreboff AM, Browne AF, Browne NT, et al. Clinical Considerations Regarding the Use of Obesity Pharmacotherapy in Adolescents with Obesity. Obesity (Silver Spring, Md). 2019;27(2):190-204.
Armstrong SC, Bolling CF, Michalsky MP, Reichard KW, Section On Obesity SOS. Pediatric Metabolic and Bariatric Surgery: Evidence, Barriers, and Best Practices. Pediatrics. 2019;144(6).
Bouchard ME, Tian Y, Linton S, De Boer C, O'Connor A, Ghomrawi H, et al. Utilization Trends and Disparities in Adolescent Bariatric Surgery in the United States 2009-2017. Child Obes. 2022;18(3):188-96.
Salimi-Jazi F, Chkhikvadze T, Shi J, Pourmehdi-Lahiji A, Moshksar A, Rafeeqi TA, et al. Trends in Adolescent Bariatric Procedures: a 15-Year Analysis of the National Inpatient Survey. Obes Surg. 2022;32(11):3658-65.
Messiah SE, Xie L, Atem F, Mathew MS, Qureshi FG, Schneider BE, et al. Disparity Between United States Adolescent Class II and III Obesity Trends and Bariatric Surgery Utilization, 2015-2018. Ann Surg. 2022;276(2):324-33.
Inge TH, Krebs NF, Garcia VF, Skelton JA, Guice KS, Strauss RS, et al. Bariatric surgery for severely overweight adolescents: concerns and recommendations. Pediatrics. 2004;114(1):217-23.
Styne DM, Arslanian SA, Connor EL, Farooqi IS, Murad MH, Silverstein JH, et al. Pediatric Obesity-Assessment, Treatment, and Prevention: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2017;102(3):709-57.
Cuda S, O'Hara V, Censani M, Conroy R, Sweeney B, Paisley J, et al. Special considerations for the adolescent with obesity: An obesity medicine association (OMA) clinical practice statement (CPS) 2024. Obes Pillars. 2024;9:100096.
Eisenberg D, Shikora SA, Aarts E, Aminian A, Angrisani L, Cohen RV, et al. 2022 American Society of Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) Indications for Metabolic and Bariatric Surgery. Obes Surg. 2023;33(1):3-14.
Shapiro WL, Kunani P, Sidell MA, Li X, Anderson SR, Slezak JM, et al. Prevalence of Adolescents Meeting Criteria for Metabolic and Bariatric Surgery. Pediatrics. 2024;153(3).
Mocanu V, Lai K, Dang JT, Switzer NJ, Birch DW, Ball GDC, et al. Evaluation of the Trends, Characteristics, and Outcomes in North American Youth Undergoing Elective Bariatric Surgery. Obes Surg. 2021;31(5):2180-7.
Ogle SB, Dewberry LC, Jenkins TM, Inge TH, Kelsey M, Bruzoni M, et al. Outcomes of Bariatric Surgery in Older Versus Younger Adolescents. Pediatrics. 2021;147(3).
Alqahtani A, Elahmedi M, Qahtani AR. Laparoscopic Sleeve Gastrectomy in Children Younger Than 14 Years: Refuting the Concerns. Ann Surg. 2016;263(2):312-9.
Alqahtani AR, Antonisamy B, Alamri H, Elahmedi M, Zimmerman VA. Laparoscopic sleeve gastrectomy in 108 obese children and adolescents aged 5 to 21 years. Ann Surg. 2012;256(2):266-73.
El Chaar M, King K, Al-Mardini A, Galvez A, Claros L, Stoltzfus J. Thirty-Day Outcomes of Bariatric Surgery in Adolescents: a First Look at the MBSAQIP Database. Obes Surg. 2021;31(1):194-9.
Poliakin L, Roberts A, Thompson KJ, Raheem E, McKillop IH, Nimeri A. Outcomes of adolescents compared with young adults after bariatric surgery: an analysis of 227,671 patients using the MBSAQIP data registry. Surg Obes Relat Dis. 2020;16(10):1463-73.
Shah A, Liang NE, Bruzoni M, Pratt JSA, Zitsman J, Nadler EP. Outcomes after metabolic and bariatric surgery in preteens versus teens using the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database and center-specific data. Obesity (Silver Spring, Md). 2024;32(1):150-5.
Liang NE, Herdes RE, Balili R, Pratt JSA, Bruzoni M. Sleeve gastrectomy for the treatment of adolescent obesity in children aged 13 and under: a retrospective study. Surg Obes Relat Dis. 2024;20(4):354-61.
Steinberger AE, Nickel KB, Keller M, Wallendorf M, Sprague J, Nicol GE, et al. National Trends in Pediatric Metabolic and Bariatric Surgery: 2010-2017. Pediatrics. 2022;150(6).
Alqahtani A, Alamri H, Elahmedi M, Mohammed R. Laparoscopic sleeve gastrectomy in adult and pediatric obese patients: a comparative study. Surg Endosc. 2012;26(11):3094-100.
Inge TH, Coley RY, Bazzano LA, Xanthakos SA, McTigue K, Arterburn D, et al. Comparative effectiveness of bariatric procedures among adolescents: the PCORnet bariatric study. Surg Obes Relat Dis. 2018;14(9):1374-86.
Jackson WL, Lewis SR, Bagby JP, Hilton LR, Milad M, Bledsoe SE. Laparoscopic sleeve gastrectomy versus laparoscopic Roux-en-Y gastric bypass in the pediatric population: a MBSAQIP analysis. Surg Obes Relat Dis. 2020;16(2):254-60.
Inge TH, Miyano G, Bean J, Helmrath M, Courcoulas A, Harmon CM, et al. Reversal of type 2 diabetes mellitus and improvements in cardiovascular risk factors after surgical weight loss in adolescents. Pediatrics. 2009;123(1):214-22.
Dewberry LC, Khoury JC, Ehrlich S, Jenkins TM, Beamish AJ, Kalkwarf HJ, et al. Change in gastrointestinal symptoms over the first 5 years after bariatric surgery in a multicenter cohort of adolescents. J Pediatr Surg. 2019;54(6):1220-5.
Dewberry LC, Jalivand A, Gupta R, Jenkins TM, Beamish A, Inge TH, et al. Weight Loss and Health Status 5 Years After Adjustable Gastric Banding in Adolescents. Obes Surg. 2020;30(6):2388-94.
Svetanoff WJ, Diefenbach K, Hall B, Craver A, Rutledge S, McManaway C, et al. Utilization of an Enhanced Recovery After Surgery (ERAS) protocol for pediatric metabolic and bariatric surgery. J Pediatr Surg. 2023;58(4):695-701.
Parrott J, Frank L, Rabena R, Craggs-Dino L, Isom KA, Greiman L. American Society for Metabolic and Bariatric Surgery Integrated Health Nutritional Guidelines for the Surgical Weight Loss Patient 2016 Update: Micronutrients. Surg Obes Relat Dis. 2017;13(5):727-41.
Mechanick JI, Apovian C, Brethauer S, Timothy Garvey W, Joffe AM, Kim J, et al. Clinical Practice Guidelines for the Perioperative Nutrition, Metabolic, and Nonsurgical Support of Patients Undergoing Bariatric Procedures - 2019 Update: Cosponsored by American Association of Clinical Endocrinologists/American College of Endocrinology, The Obesity Society, American Society for Metabolic and Bariatric Surgery, Obesity Medicine Association, and American Society of Anesthesiologists. Obesity (Silver Spring, Md). 2020;28(4):O1-o58.
Mechanick JI, Youdim A, Jones DB, Garvey WT, Hurley DL, McMahon MM, et al. Clinical practice guidelines for the perioperative nutritional, metabolic, and nonsurgical support of the bariatric surgery patient--2013 update: cosponsored by American Association of Clinical Endocrinologists, The Obesity Society, and American Society for Metabolic & Bariatric Surgery. Obesity (Silver Spring, Md). 2013;21 Suppl 1(0 1):S1-27.
Broughton DE, Moley KH. Obesity and female infertility: potential mediators of obesity's impact. Fertil Steril. 2017;107(4):840-7.
Silvestris E, de Pergola G, Rosania R, Loverro G. Obesity as disruptor of the female fertility. Reprod Biol Endocrinol. 2018;16(1):22.
Teitelman M, Grotegut CA, Williams NN, Lewis JD. The impact of bariatric surgery on menstrual patterns. Obes Surg. 2006;16(11):1457-63.
Escobar-Morreale HF, Santacruz E, Luque-Ramírez M, Botella Carretero JI. Prevalence of 'obesity-associated gonadal dysfunction' in severely obese men and women and its resolution after bariatric surgery: a systematic review and meta-analysis. Hum Reprod Update. 2017;23(4):390-408.
Roehrig HR, Xanthakos SA, Sweeney J, Zeller MH, Inge TH. Pregnancy after gastric bypass surgery in adolescents. Obes Surg. 2007;17(7):873-7.
Lopez LM, Bernholc A, Chen M, Grey TW, Otterness C, Westhoff C, et al. Hormonal contraceptives for contraception in overweight or obese women. Cochrane Database Syst Rev. 2016(8):Cd008452.
ACOG practice bulletin no. 105: bariatric surgery and pregnancy. Obstet Gynecol. 2009;113(6):1405-13.
de Bastos M, Stegeman BH, Rosendaal FR, Van Hylckama Vlieg A, Helmerhorst FM, Stijnen T, et al. Combined oral contraceptives: venous thrombosis. Cochrane Database Syst Rev. 2014(3):Cd010813.
Lassandro G, Palmieri VV, Palladino V, Amoruso A, Faienza MF, Giordano P. Venous Thromboembolism in Children: From Diagnosis to Management. Int J Environ Res Public Health. 2020;17(14).
ACOG Committee Opinion No. 735: Adolescents and Long-Acting Reversible Contraception: Implants and Intrauterine Devices. Obstet Gynecol. 2018;131(5):e130-e9.
Apter D. International Perspectives: IUDs and Adolescents. J Pediatr Adolesc Gynecol. 2019;32(5s):S36-s42.
Rottenstreich A, Elazary R, Ezra Y, Kleinstern G, Beglaibter N, Elchalal U. Hypoglycemia during oral glucose tolerance test among post-bariatric surgery pregnant patients: incidence and perinatal significance. Surg Obes Relat Dis. 2018;14(3):347-53.
Benhalima K, Minschart C, Ceulemans D, Bogaerts A, Van Der Schueren B, Mathieu C, et al. Screening and Management of Gestational Diabetes Mellitus after Bariatric Surgery. Nutrients. 2018;10(10).
Minschart C, Beunen K, Benhalima K. An Update on Screening Strategies for Gestational Diabetes Mellitus: A Narrative Review. Diabetes Metab Syndr Obes. 2021;14:3047-76.
Alqahtani AR, Elahmedi MO, Al Qahtani A. Co-morbidity resolution in morbidly obese children and adolescents undergoing sleeve gastrectomy. Surg Obes Relat Dis. 2014;10(5):842-50.
Inge TH, Courcoulas AP, Jenkins TM, Michalsky MP, Helmrath MA, Brandt ML, et al. Weight Loss and Health Status 3 Years after Bariatric Surgery in Adolescents. N Engl J Med. 2016;374(2):113-23.
Derderian SC, Patten L, Kaizer AM, Moore JM, Ogle S, Jenkins TM, et al. Influence of Weight Loss on Obesity-Associated Complications After Metabolic and Bariatric Surgery in Adolescents. Obesity (Silver Spring, Md). 2020;28(12):2397-404.
Wafa S, Nakhla M. Improving the Transition from Pediatric to Adult Diabetes Healthcare: A Literature Review. Can J Diabetes. 2015;39(6):520-8.
Coyne I, Sheehan A, Heery E, While AE. Healthcare transition for adolescents and young adults with long-term conditions: Qualitative study of patients, parents and healthcare professionals' experiences. J Clin Nurs. 2019;28(21-22):4062-76.
Butalia S, McGuire KA, Dyjur D, Mercer J, Pacaud D. Youth with diabetes and their parents' perspectives on transition care from pediatric to adult diabetes care services: A qualitative study. Health Sci Rep. 2020;3(3):e181.
Herouvi D, Soldatou A, Paschou SA, Kalpia C, Karanasios S, Karavanaki K. Bariatric surgery in the management of childhood and adolescence obesity. Endocrine. 2023;79(3):411-9.
Ryder JR, Jenkins TM, Xie C, Courcoulas AP, Harmon CM, Helmrath MA, et al. Ten-Year Outcomes after Bariatric Surgery in Adolescents. N Engl J Med. 2024;391(17):1656-8.
Olbers T, Beamish AJ, Gronowitz E, Flodmark CE, Dahlgren J, Bruze G, et al. Laparoscopic Roux-en-Y gastric bypass in adolescents with severe obesity (AMOS): a prospective, 5-year, Swedish nationwide study. Lancet Diabetes Endocrinol. 2017;5(3):174-83.
Inge TH, Jenkins TM, Xanthakos SA, Dixon JB, Daniels SR, Zeller MH, et al. Long-term outcomes of bariatric surgery in adolescents with severe obesity (FABS-5+): a prospective follow-up analysis. Lancet Diabetes Endocrinol. 2017;5(3):165-73.
de la Cruz-Munoz N, Xie L, Quiroz HJ, Kutlu OC, Atem F, Lipshultz SE, et al. Long-Term Outcomes after Adolescent Bariatric Surgery. J Am Coll Surg. 2022;235(4):592-602.
Vilallonga R, Himpens J, van de Vrande S. Long-Term (7 Years) Follow-Up of Roux-en-Y Gastric Bypass on Obese Adolescent Patients (<18 Years). Obes Facts. 2016;9(2):91-100.
Al-Sabah SK, Almazeedi SM, Dashti SA, Al-Mulla AY, Ali DA, Jumaa TH. The efficacy of laparoscopic sleeve gastrectomy in treating adolescent obesity. Obes Surg. 2015;25(1):50-4.
Syn NL, Cummings DE, Wang LZ, Lin DJ, Zhao JJ, Loh M, et al. Association of metabolic-bariatric surgery with long-term survival in adults with and without diabetes: a one-stage meta-analysis of matched cohort and prospective controlled studies with 174 772 participants. Lancet. 2021;397(10287):1830-41.
Stefater MA, Inge TH. Bariatric Surgery for Adolescents with Type 2 Diabetes: an Emerging Therapeutic Strategy. Curr Diab Rep. 2017;17(8):62.
Courcoulas AP, Patti ME, Hu B, Arterburn DE, Simonson DC, Gourash WF, et al. Long-Term Outcomes of Medical Management vs Bariatric Surgery in Type 2 Diabetes. Jama. 2024;331(8):654-64.
Inge TH, Courcoulas AP, Jenkins TM, Michalsky MP, Brandt ML, Xanthakos SA, et al. Five-Year Outcomes of Gastric Bypass in Adolescents as Compared with Adults. N Engl J Med. 2019;380(22):2136-45.
Inge TH, Laffel LM, Jenkins TM, Marcus MD, Leibel NI, Brandt ML, et al. Comparison of Surgical and Medical Therapy for Type 2 Diabetes in Severely Obese Adolescents. JAMA Pediatr. 2018;172(5):452-60.
Ryder JR, Xu P, Nadeau KJ, Kelsey MM, Xie C, Jenkins T, et al. Effect of surgical versus medical therapy on estimated cardiovascular event risk among adolescents with type 2 diabetes and severe obesity. Surg Obes Relat Dis. 2021;17(1):23-33.
Shah AS, Nadeau KJ, Helmrath MA, Inge TH, Xanthakos SA, Kelsey MM. Metabolic outcomes of surgery in youth with type 2 diabetes. Semin Pediatr Surg. 2020;29(1):150893.
Shah AS, Helmrath MA, Inge TH, Xanthakos SA, Kelsey MM, Jenkins T, et al. Study protocol: a prospective controlled clinical trial to assess surgical or medical treatment for paediatric type 2 diabetes (ST(2)OMP). BMJ Open. 2021;11(8):e047766.
Bjornstad P, Hughan K, Kelsey MM, Shah AS, Lynch J, Nehus E, et al. Effect of Surgical Versus Medical Therapy on Diabetic Kidney Disease Over 5 Years in Severely Obese Adolescents With Type 2 Diabetes. Diabetes Care. 2020;43(1):187-95.
Michalsky MP, Inge TH, Jenkins TM, Xie C, Courcoulas A, Helmrath M, et al. Cardiovascular Risk Factors After Adolescent Bariatric Surgery. Pediatrics. 2018;141(2).
Messiah SE, Lopez-Mitnik G, Winegar D, Sherif B, Arheart KL, Reichard KW, et al. Changes in weight and co-morbidities among adolescents undergoing bariatric surgery: 1-year results from the Bariatric Outcomes Longitudinal Database. Surg Obes Relat Dis. 2013;9(4):503-13.
Ryder JR, Edwards NM, Gupta R, Khoury J, Jenkins TM, Bout-Tabaku S, et al. Changes in Functional Mobility and Musculoskeletal Pain After Bariatric Surgery in Teens With Severe Obesity: Teen-Longitudinal Assessment of Bariatric Surgery (LABS) Study. JAMA Pediatr. 2016;170(9):871-7.
Bout-Tabaku S, Gupta R, Jenkins TM, Ryder JR, Baughcum AE, Jackson RD, et al. Musculoskeletal Pain, Physical Function, and Quality of Life After Bariatric Surgery. Pediatrics. 2019;144(6).
Burton ET, Mackey ER, Reynolds K, Cadieux A, Gaffka BJ, Shaffer LA. Psychopathology and Adolescent Bariatric Surgery: A Topical Review to Support Psychologists in Assessment and Treatment Considerations. J Clin Psychol Med Settings. 2020;27(2):235-46.
Kalarchian MA, Marcus MD. Psychiatric comorbidity of childhood obesity. Int Rev Psychiatry. 2012;24(3):241-6.
Rankin J, Matthews L, Cobley S, Han A, Sanders R, Wiltshire HD, et al. Psychological consequences of childhood obesity: psychiatric comorbidity and prevention. Adolesc Health Med Ther. 2016;7:125-46.
Zeller MH, Reiter-Purtill J, Jenkins TM, Ratcliff MB. Adolescent suicidal behavior across the excess weight status spectrum. Obesity (Silver Spring, Md). 2013;21(5):1039-45.
He J, Cai Z, Fan X. Prevalence of binge and loss of control eating among children and adolescents with overweight and obesity: An exploratory meta-analysis. Int J Eat Disord. 2017;50(2):91-103.
Goldschmidt AB, Khoury JC, Mitchell JE, Jenkins TM, Bond DS, Zeller MH, et al. Loss of Control Eating and Health Indicators Over 6 Years in Adolescents Undergoing Metabolic and Bariatric Surgery. Obesity (Silver Spring, Md). 2021;29(4):740-7.
Zeller MH, Reiter-Purtill J, Jenkins TM, Kidwell KM, Bensman HE, Mitchell JE, et al. Suicidal thoughts and behaviors in adolescents who underwent bariatric surgery. Surg Obes Relat Dis. 2020;16(4):568-80.
Reiter-Purtill J, Decker KM, Jenkins TM, Zeller MH. Self-worth and developmental outcomes in young adults after pediatric bariatric surgery. Health Psychol. 2023;42(2):92-102.
Järvholm K, Olbers T, Marcus C, Mårild S, Gronowitz E, Friberg P, et al. Short-term psychological outcomes in severely obese adolescents after bariatric surgery. Obesity (Silver Spring, Md). 2012;20(2):318-23.
Zeller MH, Reiter-Purtill J, Ratcliff MB, Inge TH, Noll JG. Two-year trends in psychosocial functioning after adolescent Roux-en-Y gastric bypass. Surg Obes Relat Dis. 2011;7(6):727-32.
Hunsaker SL, Garland BH, Rofey D, Reiter-Purtill J, Mitchell J, Courcoulas A, et al. A Multisite 2-Year Follow Up of Psychopathology Prevalence, Predictors, and Correlates Among Adolescents Who Did or Did Not Undergo Weight Loss Surgery. J Adolesc Health. 2018;63(2):142-50.
White GE, Boles RE, Courcoulas AP, Yanovski SZ, Zeller MH, Jenkins TM, et al. A Prospective Cohort of Alcohol Use and Alcohol-related Problems Before and After Metabolic and Bariatric Surgery in Adolescents. Ann Surg. 2023;278(3):e519-e25.
Hoeltzel GD, Swendiman RA, Tewksbury CM, Parks EP, Williams NN, Dumon KR. How safe is adolescent bariatric surgery? An analysis of short-term outcomes. J Pediatr Surg. 2022;57(8):1654-9.
Varela JE, Hinojosa MW, Nguyen NT. Perioperative outcomes of bariatric surgery in adolescents compared with adults at academic medical centers. Surg Obes Relat Dis. 2007;3(5):537-40; discussion 41-2.
Grant HM, Perez-Caraballo A, Romanelli JR, Tirabassi MV. Metabolic and bariatric surgery is likely safe, but underutilized in adolescents aged 13-17 years. Surg Obes Relat Dis. 2021;17(6):1146-51.
Xanthakos SA, Khoury JC, Inge TH, Jenkins TM, Modi AC, Michalsky MP, et al. Nutritional Risks in Adolescents After Bariatric Surgery. Clin Gastroenterol Hepatol. 2020;18(5):1070-81.e5.
Armstrong-Javors A, Pratt J, Kharasch S. Wernicke Encephalopathy in Adolescents After Bariatric Surgery: Case Report and Review. Pediatrics. 2016;138(6).
Towbin A, Inge TH, Garcia VF, Roehrig HR, Clements RH, Harmon CM, et al. Beriberi after gastric bypass surgery in adolescence. J Pediatr. 2004;145(2):263-7.
Mitchell DM, Singhal V, Animashaun A, Bose A, Carmine B, Stanford FC, et al. Skeletal Effects of Sleeve Gastrectomy in Adolescents and Young Adults: A 2-Year Longitudinal Study. J Clin Endocrinol Metab. 2023;108(4):847-57.
Wasserman H, Jenkins T, Inge T, Ryder J, Michalsky M, Sisley S, et al. Bone mineral density 5 to 11 years after metabolic and bariatric surgery in adolescents with severe obesity compared to peers. Res Sq. 2023.
Modi AC, Zeller MH, Xanthakos SA, Jenkins TM, Inge TH. Adherence to vitamin supplementation following adolescent bariatric surgery. Obesity (Silver Spring, Md). 2013;21(3):E190-5.
Elhag W, El Ansari W. Durability of Cardiometabolic Outcomes Among Adolescents After Sleeve Gastrectomy: First Study with 9-Year Follow-up. Obes Surg. 2021;31(7):2869-77.
Doyle WN, Reinhart N, Reddy NC, Diab AF, Sujka JA, DuCoin CG, et al. Anti-obesity Medication Use for Adolescent Metabolic and Bariatric Surgery Patients: A Systematic Literature Review. Cureus. 2023;15(12):e50905.
Murvelashvili N, Xie L, Schellinger JN, Mathew MS, Marroquin EM, Lingvay I, et al. Effectiveness of semaglutide versus liraglutide for treating post-metabolic and bariatric surgery weight recurrence. Obesity (Silver Spring, Md). 2023;31(5):1280-9.
Ramadan M, Loureiro M, Laughlan K, Caiazzo R, Iannelli A, Brunaud L, et al. Risk of Dumping Syndrome after Sleeve Gastrectomy and Roux-en-Y Gastric Bypass: Early Results of a Multicentre Prospective Study. Gastroenterol Res Pract. 2016;2016:2570237.
Ahmad A, Kornrich DB, Krasner H, Eckardt S, Ahmad Z, Braslow A, et al. Prevalence of Dumping Syndrome After Laparoscopic Sleeve Gastrectomy and Comparison with Laparoscopic Roux-en-Y Gastric Bypass. Obes Surg. 2019;29(5):1506-13.
Laurenius A, Olbers T, Naslund I, Karlsson J. Dumping syndrome following gastric bypass: validation of the dumping symptom rating scale. Obes Surg. 2013;23(6):740-55.
Campos GM, Mazzini GS, Altieri MS, Docimo S, Jr., DeMaria EJ, Rogers AM. ASMBS position statement on the rationale for performance of upper gastrointestinal endoscopy before and after metabolic and bariatric surgery. Surg Obes Relat Dis. 2021;17(5):837-47.
Cozacov Y, Roy M, Moon S, Marin P, Lo Menzo E, Szomstein S, et al. Mid-term results of laparoscopic sleeve gastrectomy and Roux-en-Y gastric bypass in adolescent patients. Obes Surg. 2014;24(5):747-52.
Nijhawan S, Martinez T, Wittgrove AC. Laparoscopic gastric bypass for the adolescent patient: long-term results. Obes Surg. 2012;22(9):1445-9.
Benedix F, Krause T, Adolf D, Wolff S, Lippert H, Manger T, et al. Perioperative Course, Weight Loss and Resolution of Comorbidities After Primary Sleeve Gastrectomy for Morbid Obesity: Are There Differences Between Adolescents and Adults? Obes Surg. 2017;27(9):2388-97.

Platelets, Coagulation, and Antithrombotic Therapy in Diabetes

ABSTRACT

Diabetes mellitus is a strong, independent risk factor for the development of atherosclerotic cardiovascular disease (ASCVD) and therefore for atherothrombotic events. Compared to those without diabetes, individuals with diabetes are also at increased risk of cardioembolic stroke in the presence of atrial fibrillation (AF) and of venous thromboembolism. Activation of platelets and the coagulation cascade are the central mechanisms of thrombosis. A range of antiplatelet and anticoagulant drugs are now available. Antithrombotic therapy should be considered in all those with diabetes and established ASCVD or AF. Intensification of antithrombotic therapy is typically indicated during the acute phase of an atherothrombotic event or in those with chronic coronary syndromes who are at high ischemic risk, provided this outweighs bleeding risk. Clinical decisions regarding antithrombotic therapy should be made by assessing an individual’s ischemic and bleeding risks, in consultation with the recipient and reviewed upon any change in circumstances.

LIST OF ABBREVIATIONS

5HT	5-hydroxytryptamine
ACS	acute coronary syndrome
ADP	adenosine diphosphate
AF	atrial fibrillation
ALI	acute limb ischemia
APT	antiplatelet therapy
ASCVD	atherosclerotic cardiovascular disease
ATP	adenosine triphosphate
ATT	antithrombotic therapy
CAD	coronary artery disease
CCS	chronic coronary syndromes
CI	confidence interval
COX	cyclo-oxygenase
DAPT	dual antiplatelet therapy
DATT	dual antithrombotic therapy
DM	diabetes mellitus
DVT	deep vein thrombosis
GP	glycoprotein
HR	hazard ratio
LEAD	lower extremity artery disease
MACE	major adverse cardiovascular event
MI	myocardial infarction
miR	microribonucleic acid
NOAC	non-vitamin K antagonist oral anticoagulant
OAC	oral anticoagulant
PAD	peripheral artery disease
PAR	protease-activated receptor
PCI	percutaneous coronary intervention
PGI₂	prostacyclin
RCTs	randomized controlled trials
RRR	relative risk reduction
SAPT	single antiplatelet therapy
TIMI	thrombolysis in myocardial infarction
TP	thromboprostanoid
TXA₂	thromboxane A₂
UA	unstable angina
VKA	vitamin K antagonist
vWF	von Willebrand factor

INTRODUCTION

Despite a century of advances in understanding and management of diabetes mellitus (DM), it continues to increase in prevalence and, furthermore, remains an independent risk factor for atherosclerotic cardiovascular disease (ASCVD), leading to a significant burden of premature mortality and morbidity (1).

ASCVD includes a spectrum of clinical syndromes. This can include acute presentations such as acute coronary syndromes (ACS, including myocardial infarction [MI] or unstable angina [UA]), thrombotic stroke, or acute limb ischemia (ALI) (Figure 1). Similarly, ASCVD can lead to chronic conditions such as chronic coronary syndromes (CCS, for example those with stable angina or a history of MI >1 year previously) or chronic lower extremity arterial disease (LEAD) (2).

Most acute events in ASCVD are caused by thrombosis. The hemostatic response has an important physiological role in the response to trauma but, if it becomes activated inappropriately, thrombosis can be triggered (3). The clinical effects of thrombosis arise primarily from its location, such as in the coronary arteries leading to acute coronary syndrome (ACS, including myocardial infarction [MI] and unstable angina [UA]), cerebral arteries leading to thrombotic stroke, peripheral arteries leading to acute limb ischemia or deep limb veins leading to deep vein thrombosis (DVT). Alternatively, a thrombus formed at a site can embolize, leading to presentations such as acute pulmonary embolism (typically embolism of a DVT to the pulmonary arteries) or embolic stroke (typically left atrial thrombus to the cerebral arteries) (2,4). In addition to atherosclerotic diseases, individuals with DM who have atrial fibrillation are at higher risk of stroke, secondary to atrial thrombosis and subsequent cardioembolic events (5).

There are clear links between pathological processes associated with DM and those responsible for atherogenesis and thrombosis, including inflammation, platelet activation, and coagulation (6,7). Alongside control of glucose levels and optimization of other risk factors, such as dyslipidemia, hypertension, and smoking cessation, antithrombotic therapy (ATT), including antiplatelet therapy (APT) and oral anticoagulation (OAC), has become a key component of the treatment and prevention of atherothrombotic and cardioembolic events. ATT has evolved greatly in the last decades, both in terms of the range of drugs available but also our understanding of how best to deploy them (8).

Whilst ATT reduces thrombotic risk, in particular reducing the composite of major adverse cardiovascular events (MACE, typically defined as cardiovascular death, stroke or MI), it also leads to an increased risk of bleeding. Balancing these risks is central to interpretation of clinical trial data and development of treatment recommendations, including in those with DM (9).

In this chapter, we will review the underlying pathophysiological mechanisms of thrombosis and the pharmacology of commonly prescribed drugs during ATT. With specific reference to individuals with DM, we will appraise evidence for ATT in a broad range of clinical settings, highlighting current treatment recommendations and particular areas in which more data are needed.

Figure 1. The spectrum of acute cardiovascular events relating to thrombosis and hemostasis in DM.

THE THROMBOTIC RESPONSE AND ITS PHARMACOLOGY

As described in Virchow’s triad, prothrombotic changes in the blood flow, constituents and/or vessel wall can trigger thrombosis (10). Broadly, thrombosis involves the activation of platelets and the coagulation cascade (Figure 2). Understanding these processes provides insights into how pharmacological modulation may improve ischemic risk and increase bleeding risk as well as how the individual components of combination ATT interact, including in those with DM.

Platelet Activation

Platelet activation typically occurs upon endothelial injury and atherosclerotic plaque rupture or erosion, resulting in exposure of blood constituents to prothrombotic substances such as collagen. Collagen exposure leads to platelets adhering to the vessel wall via the glycoprotein (GP) Ia receptor and activation via GPVI (11,12). GPIb forms a complex with clotting factors IX, V and von Willebrand Factor (vWF), strengthening adhesion (13).

Platelet activation involves several key processes. Alterations in the cytoskeleton lead to shape change with the formation of filopodia, which increase surface area to volume ratio and may facilitate mechanical adhesion to the vessel wall, other platelets and fibrin strands (14). Platelet activation also involves the release of arachidonic acid from the cell membrane, which is then locally converted to thromboxane A₂ (TXA₂) by cyclo-oxygenase (COX) 1 and TXA₂synthase. TXA₂, via the platelet TP-α receptor, contributes further to platelet activation (15). Aspirin (acetylsalicylic acid) irreversibly inhibits COX1, thereby blocking the downstream release of TXA₂ for the platelet’s lifespan (around 8-10 days in healthy individuals) as, unlike nucleated cells, platelets cannot regenerate the enzyme (8). Endothelial COX1 and 2 generate the antiplatelet and vasodilatory substance prostacyclin (PGI₂). The facts that aspirin is short-lived in the systemic circulation, that platelets are exposed to higher levels of aspirin than endothelium, due to travel through the portal circulation, and that aspirin has relative selectivity for COX1 over COX2 leads to aspirin’s net antiplatelet effect at low doses (16).

Platelets also undergo degranulation on activation; a granules contain procoagulant and proinflammatory factors, including platelet P-selectin (also known as CD62P), the surface expression of which is therefore increased. P-selectin mediates platelet-leukocyte aggregation and therefore contributes to an associated inflammatory response (17). Dense granules contain adenosine triphosphate (ATP), adenosine diphosphate (ADP) and 5-hydroxytryptamine (5HT, also known as serotonin). In particular, ADP stimulates platelet activation via P2Y₁ and, most significantly, P2Y₁₂ receptors (18,19).

Stimulation of the P2Y₁₂ receptor leads to central amplification of the response to a range of agonists and contributes significantly to activation of platelet surface GPIIb/IIIa receptors, the final pathway of platelet aggregation (20). Via vWF and fibrinogen bridges, GPIIb/IIIa mediates platelet-platelet interaction (21).

Figure 2. Pathophysiology of the thrombotic response showing targets for antithrombotic drugs discussed in this chapter. 5HT, 5-hydroxytryptamine (serotonin); AA, arachidonic acid; ADP, adenosine diphosphate; ATP, adenosine triphosphate; Ca2+, calcium; COX1, cyclo-oxygenase 1; GP, glycoprotein; IXa, activated factor IX; P2X1, platelet ATP receptor; P2Y1/P2Y12, platelet ADP receptors; PAR, protease activated receptor; PLA2, phospholipase A2; PSGL1, P-selectin glycoprotein ligand 1; TF, tissue factor; TPα, thromboxane receptor α; TXA2, thromboxane A2; TXA2s, thromboxane A2 synthase; Va, activated factor V; VIIa, activated factor VII; VIIIa, activated factor VIII; VASP, vasodilator-stimulated phosphoprotein; vWF, von Willebrand factor; Xa, activated factor X; XIa, activated factor XI; XIIa, activated factor XII; XIIIa, activated factor XII. Modified from (22).

Several oral platelet P2Y₁₂ receptor antagonists (‘P2Y₁₂ inhibitors’) are currently available (23). Clopidogrel and prasugrel are irreversibly-binding thienopyridines (8). As pro-drugs, they require hepatic metabolism to be activated. In the case of prasugrel this pathway is reliable, whereas there is interindividual variation in the metabolism of clopidogrel meaning around one-third of recipients have poor response when assessed using aggregometry (22). Ticagrelor is a reversibly-binding cyclopentyl-triazolopyrimidine that does not require metabolism to be active. Prasugrel or ticagrelor provide more potent and reliable platelet inhibition compared with clopidogrel (24).

Parenterally administered P2Y₁₂ inhibitors have also been developed. Cangrelor is a reversibly-binding ATP analogue that is potent and has rapid onset and offset (25). Selatogrel is a novel, parenterally-active, reversibly-binding P2Y₁₂inhibitor formulated for subcutaneous administration, but has not yet completed phase III trials and is yet to be marketed (26).

Activation of the Coagulation Cascade

Although likely an oversimplification of the in vivo state, the coagulation cascade can be summarized as two key pathways made up of factors that converge on a final pathway (27).

Loss of endothelium leads to exposure of subendothelial extracellular matrix and contact activation of factor XII, triggering the chain of clotting factor activation known as the intrinsic pathway (28). Tissue factor, expressed on subendothelial cells and released in microparticles from atheromatous plaques, can activate factor IX when in a complex with factor VII: this is the extrinsic pathway (29).

Initiation of either pathway can lead to activation of factor X, which associates with activated factor V, calcium (released from damaged tissue) and phospholipids to form the prothrombinase complex (30). Prothrombin (II) is thus broken down to thrombin (IIa), which completes the process through cleavage of fibrinogen to fibrin, the latter being insoluble and forming strands. Tissue factor pathway inhibitor and antithrombin limit this response, but, as recruitment of activated platelets contributes to higher levels of thrombin generation, this endogenous inhibition is quickly overwhelmed (31). Once fibrin is formed, factor XIIIa, activated by thrombin, stabilizes the structure of clot by forming crosslinks between strands and by crosslinking anti-fibrinolytic proteins into the clot (32).

Fibrin is lysed by plasmin, a proteolytic enzyme that degrades into variously termed fragments (33). Plasmin is cleaved from its precursor, plasminogen, by tissue plasminogen activator, and is endogenously inhibited by antiplasmin.

A number of drugs target the coagulation cascade. During chronic administration, vitamin K antagonists (VKA) such as warfarin reduce the biological activity of prothrombotic vitamin-K-dependent factors (II, VII, IX, X) more than antithrombotic factors (e.g., proteins C and S) (34). Non-vitamin K antagonist oral anticoagulants (NOACs) include the Xa inhibitors apixaban, edoxaban and rivaroxaban and the thrombin inhibitor dabigatran (35).

Crosstalk Between Platelets and the Coagulation Cascade

Despite the fact that platelets and coagulation are often considered separately when discussing physiology and pharmacology, there is significant crosstalk between the two. Thrombin is generated upon activation of coagulation, and is able to stimulate platelet activation via action on protease-activated receptor (PAR) 1 and, at higher concentrations, PAR4 (36). Conversely platelets can contribute to thrombin generation, increasing coagulability, via scramblase activity that leads to greater surface expression of phosphatidylserine, supporting the assembly of prothrombinase complex on the activated platelet surface, which potentiates thrombin generation (37).

SPECIAL PATHOPHYSIOLOGICAL CONSIDERATIONS IN DIABETES

DM is an independent risk factor for atherothrombosis and also thrombosis after vascular interventions (38). Individuals with DM have greater average atherosclerotic plaque burden than those without (39), and onset is at an earlier age (40). There is also some evidence that atherosclerosis in people with DM is more likely to involve distal vessels than those without DM (41). The reasons for this are not completely understood and are likely multifactorial, but a number of relevant pathological processes such as hyperglycemia, chronic inflammation, and oxidative stress are prominent in DM. These contribute to both endothelial injury/dysfunction and increased platelet reactivity, resulting in a prothrombotic milieu (42-44).

Platelet activation markers are enhanced in people with DM (45). Effects of hyperglycemia on platelets include increased expression of GPIba, GPIIb/IIIa, and P2Y₁₂, and reduced platelet membrane fluidity (46,47).Hyperglycemia-induced changes in intracellular magnesium and calcium signaling increase sensitivity of platelets to agonists such as ADP, epinephrine and thrombin (48). TXA₂ and F2-isoprostane synthesis is increased, the latter via oxidative stress, leading to increased TPa receptor stimulation (49). Reduced sensitivity to PGI₂, nitric oxide and insulin, which inhibit platelet activation, also contributes to hyper-reactivity (50,51).

Platelet turnover is accelerated in those with DM compared to those without (52). This increased activity in the creation and destruction of circulating platelets means a higher proportion of immature platelets, which are hyper-reactive, are present at any time (53). As well as increasing baseline platelet reactivity, the more frequent appearance of aspirin-naïve platelets in the circulation means more have uninhibited COX1 between doses (54).

There is also evidence that DM affects expression of platelet-associated microRNAs (miR-223, miR-26b, miR-126, miR-140), which play a role in the expression in a wide range of genes including those encoding the P2Y₁₂ receptor and P-selectin, though the significance of this remains to be fully established (55,56).

As well as platelet activation, DM may affect coagulation and fibrinolysis (57). Changes include increased levels of tissue factor, prothrombin, factor VII and fibrinogen leading to impaired anticoagulant and fibrinolytic activity (58). Increased levels of fibrinogen and its levels of glycation and oxidation lead to more compact, densely-packed fibrin networks and reduced fibrinolysis (59). Hyperglycemia inhibits the fibrinolytic activity of plasminogen through inducing qualitative changes (60). Fibrinolysis is further impaired by elevated levels of plasminogen activator inhibitor 1 and thrombin-activatable fibrinolysis inhibitor as well as incorporation into clot of complement C3 and plasmin inhibitor (59,61).

DM also appears to enhance the crosstalk between platelets and clotting factors, leading to tendency to more externalization of phosphatidylserine in the outer platelet membrane, promoting clotting factor assembly and tissue factor activation (62).

Finally, individuals with DM frequently have other metabolic conditions such as obesity, dyslipidemia, and increased systemic inflammation. These may interact with diabetes to further enhance platelet reactivity and impair fibrinolysis (59).

CURRENT EVIDENCE AND TREATMENT RECOMMENDATIONS FOR ANTITHROMBOTIC THERAPY IN DIABETES

The Need for Therapeutic Oral Anticoagulation

Broadly, when considering the need for antithrombotic therapy (ATT), including in people with DM, it is helpful to make first a distinction between those with an indication for therapeutic anticoagulation and those without. The most common indication is for prevention of cardioembolic stroke in those with current or previous atrial fibrillation (AF). Individuals with atrial flutter are typically regarded as having similar thrombotic risk to those with AF so similar recommendations are followed (63).

DM increases the risk of developing AF by around 40% (64,65). Whilst difficult to completely exclude the effects of confounders such as obesity and hypertension, epidemiological data suggest a causal association between DM and AF, including that poor glycemic control and longer diabetes duration increase AF risk (66). A raised level of HbA1c is also associated with a higher chance of AF recurrence after catheter ablation (67). Hyperglycemia and glycemic fluctuations may contribute to the development of AF though exact mechanisms remain to be determined. Disappointingly, however, there is no clear evidence that intensive glycemic control reduces AF risk, though prospective trials are lacking (66). Treatment with metformin, thiazolidinediones, or dapagliflozin is associated with lower AF risk, suggesting that hypoglycemia avoidance may play a role but adequately designed studies to investigate this possibility are lacking (68-71). AF is often clinically silent and screening with simple pulse checking or using wearable devices should be considered in those over 65 years old (72).

Presence of DM is incorporated into the CHA₂DS₂VASc score used to assess stroke risk when determining whether to recommend oral anticoagulation in people with AF (Table 1 and 2) (73). Long-term oral anticoagulation is strongly recommended in those with AF/atrial flutter and a CHA₂DS₂VASc score of ³2 (if male) or ³3 (if female), and should be considered when the score is 1 (male) or 2 (female). Individuals with DM, technically defined for the purposes of calculating the score as treatment with oral hypoglycemic drugs and/or insulin or fasting blood glucose >7.0 mmol/L (126 mg/dL), will have a score of at least 1 (males) or 2 (females), therefore OAC should be considered in all people with DM and concurrent AF (63). Bleeding risk should also be considered when weighing the benefits and risks of OAC, but there is no concrete evidence that DM itself increases this, including in those with complications such as retinopathy (74). For people with non-valvular AF (i.e., those without at least moderate mitral valve stenosis or a mechanical valve prothesis), there is now good evidence that, unless contraindicated, a NOAC should be preferred over a VKA, offering better stroke prevention whilst leading to less bleeding, including in individuals with DM (75).

Components of the CHA2DS2VASc score are shown in Table 1 and the relation of the score with stroke risk is shown in table 2 (76-78).

Table 1. Components of the CHA₂DS₂VASc Score
Abbreviation	Criterion	Contribution to score	Details
C	Congestive heart failure	1	LVEF £40%
H	Hypertension	1	Includes patients receiving antihypertensive medication
A	Age ³75 years	2
D	Diabetes	1	Treatment with oral hypoglycemic drugs and/or insulin or fasting blood glucose >7.0 mmol/L (126 mg/dL)
S	Stroke/TIA/thromboembolism	2
V	Vascular disease	1	Atherosclerotic disease e.g., prior MI, PAD or aortic plaque
A	Age 65-74	1
Sc	Sex category female	1

LVEF, left ventricular ejection fraction; MI, myocardial infarction; PAD, peripheral artery disease; TIA, transient ischemic attack.

Table 2. Relation of CHA2DS2VASc Score with Stroke Risk
Total CHA₂DS₂VASc score	Adjusted stroke risk (% per year)
0	<1
1	1.3
2	2.2
3	3.2
4	4.0
5	6.7
6	9.8
7	9.6
8	6.7
9	15.2

When choosing between individual non-vitamin K antagonist oral anticoagulants (NOACs), beyond considering specific drug interactions, there is little evidence to support the use of one agent over another as these have never undergone head-to-head clinical outcome-driven randomized controlled trials (RCTs), although observational data have emerged to provide some insights. In a large retrospective observational study of 434,046 participants with non-valvular AF comparing treatment with apixaban, dabigatran, rivaroxaban and warfarin, apixaban led to a lower risk of stroke against both dabigatran (HR 0.72 [ 95% CI 0.60-0.85]) and rivaroxaban (0.80 [0.73-0.89]), whilst also leading to less bleeding (major bleeding: vs. dabigatran 0.78 [0.70-0.87]; vs. rivaroxaban 0.80 [0.55-0.59]) (79). These findings remain hypothesis-generating, however, and prospective trials would clarify this issue more definitively.

Although not discussed in detail in this chapter, OAC may also be indicated for the treatment and prevention of venous thromboembolism. Whilst DM is regarded as a weak risk factor for VTE, beyond this there are no particular considerations relating to DM and usual clinical guidelines as for non-DM individuals should generally be followed (4). Of specific note, however, is that people with DM who are experiencing hyperosmolar states such as ketoacidosis or hyperosmolar hyperglycemic syndrome are at particular risk of VTE. There is ongoing debate around the intensity of anticoagulation that is appropriate for thromboprophylaxis in this group. Consensus is that at least prophylactic doses of low molecular weight heparin, for example, are warranted, with others advocate therapeutic doses (80,81). A robustly-powered clinical outcomes-driven RCT would be welcome to definitively address this issue.

Where indications for both anti-platelet therapy (APT) and therapeutic levels of oral anticoagulant therapy (OAC) exist, the general principle is to prioritize continuation of OAC. Co-prescription of APT and OAC should in general be reserved for those with acute coronary syndrome (ACS), recent percutaneous coronary intervention (PCI) or indication for long-term therapy in selected individuals with chronic coronary syndromes (CCS) where ischemic risk is felt to significantly outweigh bleeding risk (22).

Treating Acute Atherothrombotic Events

ACUTE CORONARY SYNDROMES (ACS)

Current guidelines recommend 12 months of dual antiplatelet therapy (DAPT) with aspirin and a P2Y₁₂ inhibitor, including in those with DM, as the default antithrombotic strategy for ACS (72,82-84).

There is robust evidence for aspirin therapy in ACS. For example, ISIS-2 demonstrated that aspirin led to an odds reduction in 30-day vascular mortality of 23% in those with acute MI (85). Current recommendations advise a loading dose of around 300 mg followed by maintenance therapy with 75 mg once daily, including in those with DM. However, because of higher platelet turnover in people with DM, 24-hour platelet inhibition is greater with twice-daily compared with once-daily aspirin administration (86-88). Any effects of clinical outcomes are yet to be determined, but are being studied in the ANDAMAN trial that aims to recruit 2573 participants (NCT02520921) and is estimated to finish in December 2023.

In ACS, the newer P2Y₁₂ inhibitors prasugrel and ticagrelor are recommended in preference to clopidogrel due to their greater pharmacodynamic and clinical efficacy (83,84). Post-hoc analysis of the TRITON-TIMI trial suggested an impressive benefit of prasugrel over clopidogrel in people with DM (89). Similar findings were noted with regards to ticagrelor over clopidogrel in the PLATO trial, for which post-hoc analysis showing that the absolute benefit of was greatest in individuals with both DM and chronic kidney disease (90).

Table 3. Key Double-Blinded Randomized Controlled Trials of Dual Antiplatelet Therapy in Acute Coronary Syndrome, Including in People with Diabetes.
Trial	n	ACS group included	Group 1	Group 2	Primary efficacy endpoint – whole trial population	Number with DM	Primary efficacy endpoint – DM subgroup
CURE (91)	12,562	NSTE-ACUTE CORONARY SYNDROME	Aspirin + Clopidogrel	Aspirin + Placebo	CV death/MI/stroke:11.4% vs. 9.3%, HR 0.80 [95% CI 0.72-0.90], p<0.001), ARR 2.1%.	2840 (23%)	CV death/MI/stroke:14.2% vs. 16.7%. RR 0.85. ARR 2.5%.
CLARITY (92)	3491	STEMI	Aspirin + Clopidogrel	Aspirin + Placebo	Occluded infarct-related artery/death/recurrent MI: 15.0% vs. 21.7%, odds reduction 36% [95% CI 24-47], p<0.001, ARR 6.7%.	575 (16%)	NR
COMMIT (93)	45,852	STEMI	Aspirin + Clopidogrel	Aspirin + Placebo	Death/reinfarction/stroke: 9.2% vs. 10.1%, OR 0.91 [95% CI 0.86-0.97], p=0.002, ARR 0.9%.	NR	NR
TRITON-THROMBOLYSIS IN MYOCARDIAL INFARCTION 38 (94)	13,608	ACUTE CORONARY SYNDROME with scheduled PCI	Aspirin + Prasugrel	Aspirin + Clopidogrel	CV death/MI/stroke: 9.9% vs. 12.1%, HR 0.81 [95% CI 0.73-0.90], p<0.001, ARR 2.2%.	3146 (23%)	CV death/MI/stroke: 12.2% vs. 17.0%, HR 0.70, ARR 4.8%.
TRILOGY ACUTE CORONARY SYNDROME (95)	7243	NSTE-ACUTE CORONARY SYNDROME with medical management	Aspirin + Prasugrel	Aspirin + Clopidogrel	CV death/MI/stroke: 13.9% vs. 16.0%, HR 0.91 [95% CI 0.79-1.05], p=0.21, ARR 2.1%.	2811 (39%)	CV death/MI/stroke: 17.8% vs. 20.4%, HR 0.90 [95% CI 0.73 to 1.09]), ARR=2.6%, interaction-p for DM status 0.71, ARR 2.6%.
PLATO (96)	18,624	All ACUTE CORONARY SYNDROME (STEMI patients included only if for PPCI)	Aspirin + Ticagrelor	Aspirin + Clopidogrel	CV death/MI/stroke: 9.8% vs. 11.7%, HR 0.84 [95% CI 0.77-0.92], p<0.001, ARR 1.9%.	4662 (25%)	CV death/MI/stroke: 14.1% vs. 16.2, HR 0.88 [95% CI 0.76-1.03], interaction-p for DM status 0.49, ARR 2.1%.

ACS, acute coronary syndrome; ARR, absolute risk reduction; CV, cardiovascular; DM, diabetes mellitus; HR, hazard ratio; MI, myocardial infarction; NR, not reported; NSTE-ACS, non-ST elevation ACS; OR, odds ratio; PCI, percutaneous coronary intervention; PPCI, primary PCI; PPM, permanent pacemaker; RR, relative risk; STEMI, ST elevation MI; NR, not recorded

The recent ISAR-REACT-5 study demonstrated superiority of a prasugrel-based strategy over a ticagrelor-based strategy in reducing cardiovascular events in ACS patients but was an open-label trial with limited power (97,98). Furthermore, data from the pre-specified subgroup with DM suggested there was no difference between the drugs (99).

Early de-escalation from dual antiplatelet therapy (DAPT) to ticagrelor monotherapy after PCI, including for ACS, has recently been trialed as an alternative strategy. In the TWILIGHT study, de-escalation from aspirin and ticagrelor to ticagrelor monotherapy at 3 months after PCI for ACS or stable coronary artery disease (CAD) was compared with continued DAPT in 7,119 participants (100). De-escalating to ticagrelor monotherapy led to a lower incidence at 12 months of the primary end point of Bleeding Academic Research Consortium type 2, 3, or 5 bleeding compared with DAPT (4.0% vs 7.1%, HR 0.56 [95% 0.45-0.68], p<0.001). This finding appeared similar regardless of DM status. There was no evidence of an increase in the secondary combined endpoint of death, MI or stroke. Conversely, 1 month of DAPT followed by ticagrelor alone for 23 months was not superior to 12 months of standard DAPT followed by 12 months of aspirin alone in reducing the primary endpoint of all-cause mortality or new Q-wave MI following PCI in the GLOBAL LEADERS trial, in which 47% of participants had ACS (101). Antiplatelet strategy had no significant effect on BARC type 3 or 5 bleeding in those with and without DM (102). Currently, de-escalation of DAPT may be an option for individuals with high bleeding risk and relatively low risk of vascular re-occlusion but guidelines are yet to recommend more widespread adoption.

In summary, following ACS in individuals with diabetes, DAPT for 12 months with aspirin and prasugrel or aspirin and ticagrelor is recommended by the majority of guidelines/experts and early de-escalation should be reserved to those at high bleeding risk. Longer term DAPT should be considered in those at high thrombosis/low bleeding risk, which is further detailed below.

ACUTE ISCHEMIC STROKE

If no contraindications exist, the first-line treatment for significant acute ischemic stroke is thrombolysis with an intravenous tissue plasminogen activator, or percutaneous mechanical thrombectomy (103). Antiplatelet therapy (APT), typically aspirin monotherapy, is then administered from 24 hours later (104,105).

In those with minor stroke (National Institutes of Health Stroke Score <3), high-risk transient ischemic attack (TIA) (Age, blood pressure, clinical feature, duration and presence of diabetes score>4) or TIA not requiring thrombolysis or thrombectomy, APT can be initiated as soon as hemorrhagic stroke is excluded. The current regimen of choice may be dual antiplatelet therapy (DAPT) with aspirin 75-100 mg once daily and clopidogrel 75 mg once daily, based on findings from the CHANCE and POINT trials (106,107). After 21 days, DAPT should be de-escalated to clopidogrel monotherapy (105).

Both ticagrelor monotherapy and aspirin plus ticagrelor have also been compared to aspirin alone after acute non-severe ischemic stroke or high-risk TIA. The SOCRATES trial narrowly failed to demonstrate statistically-significant difference in the primary endpoint of stroke, MI or death (6.7% vs. 7.5%, HR 0.89 [95% CI 0.78-1.01], p=0.07) between participants receiving ticagrelor vs. aspirin (108). However, exploratory analysis suggested those who received both aspirin and ticagrelor in the peri-event period appeared to gain more benefit compared to individuals not having aspirin pre-randomization (HR 0.76 [95% CI 0.61-0.95], p=0.02; vs. 0.96 [0.82-1.12]). This was explored further in the THALES trial, which demonstrated a significant reduction in the primary composite endpoint of stroke or death at 30 days (5.5% vs. 6.6%, HR 0.83 [95% CI 0.71-0.96, p=0.02) when receiving aspirin plus ticagrelor compared to aspirin alone, but at the expense of more frequent severe bleeding (0.5% vs. 0.1%, HR 3.99 [95% CI 1.74-9.14], p=0.001), defined using the Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries trial criteria (109). Findings from SOCRATES appeared similar in the subgroups with and without DM, whereas in THALES there was less signal of benefit of DAPT in those with DM vs. those without (HR 0.93 [95% CI 0.72-1.20] vs. 0.78 [0.64-0.94]).

In summary, following major stroke requiring thrombolysis or thrombectomy, aspirin monotherapy should be administered 24 hours later. In minor stroke or high-risk TIA, DAPT should be initiated as soon as intracerebral bleeding is ruled out and continued for 21 days with aspirin then withdrawn and individuals treated with long-term clopidogrel monotherapy.

Preventing Atherothrombotic Events in Individuals with Diabetes and Established Cardiovascular Disease

CORONARY ARTERY DISEASE

In those with established CAD, even without an ACS event in the last 12 months, the benefits of antiplatelet therapy (APT) are well-established. Robust evidence for vs. against use of APT in patients with ASCVD, including CAD comes, for example, from the Antithrombotic Trialists Collaboration, who performed a meta-analysis including 135,000 individuals (110). This demonstrated clear benefit, mainly with aspirin as single-antiplatelet therapy (SAPT), in reducing MACE by around a quarter (110). The incidence of diabetes in these studies, many of which are now several decades old, was relatively low, however.

There is evidence from trials with both pharmacodynamic and clinical outcomes that increasing daily aspirin dose beyond 75-100 mg in patients with DM leads to neither greater platelet inhibition nor improved outcomes (111,112).

Daily doses of aspirin in the range 75-100 mg and no higher are recommended for use as APT. Recent data on clinical outcomes relating to aspirin dosing comes from the ADAPTABLE trial, in which the regimens 81 mg OD and 325 mg OD were compared in 15,076 patients with ASCVD (113). After a median of 26 months, there was no significant difference in the rates of a composite primary endpoint of all-cause death, hospitalization for myocardial infarction or hospitalization for stroke (7.28% [81 mg] vs. 7.51% [325 mg], HR 1.02, 95% CI 0.91-1.14; p=0.75). Furthermore, this finding appeared replicated in the subgroup (n=5676) with diabetes (HR 0.99 [0.84-1.17]). This is supported by pharmacodynamic data showing that, whilst individuals with DM have reduced response to aspirin 75 mg once daily compared with healthy controls, increasing the dose to 300 mg does not alter the response (111).

In the CAPRIE study, clopidogrel 75 mg once daily was compared with aspirin 325 mg once daily (114). There was a slightly lower rate of MI, ischemic stroke or CV death with clopidogrel (5.32% vs. 5.83%, RRR 8.7% [95% CI 0.3-16.5], p=0.043) as well as less gastrointestinal bleeding. A fifth of participants in CAPRIE had diabetes and a retrospective subgroup analysis suggested an amplified benefit of clopidogrel over aspirin compared to those without diabetes. Clopidogrel monotherapy is currently recommended in those people with chronic coronary syndromes (CCS) who are unable to take aspirin, or, based on pre-specified subgroup analyses of CAPRIE suggesting particular benefit, as a first-line agent in those with either concurrent CAD and cerebrovascular disease or PAD.

Beyond single antiplatelet therapy (SAPT), there is good evidence for intensification of antithrombotic therapy in select people with CAD who are at high risk of ischemic events but without high risk of bleeding. The Clopidogrel for High Atherothrombotic Risk and Ischemic Stabilization, Management, and Avoidance (CHARISMA) study randomized 19,185 stable aspirin-treated individuals with established atherothrombotic disease or multiple risk factors to receive clopidogrel 75 mg once daily or placebo (115). Though the point estimate of the hazard ratio was below 1, there was no significant reduction in the primary efficacy endpoint of MACE when receiving dual antithrombotic therapy (DAPT) vs. aspirin alone (HR 0.93, [95% CI 0.83-1.05], p=0.22). However, in the subgroup with prior MI, prior stroke or PAD, there was some evidence of benefit (0.77 [0.61-0.98], p=0.031) (116). Around 30% of the participants in CHARISMA had DM and there was in fact a trend towards less benefit of DAPT over SAPT in this group compared to those without DM.

The DAPT study similarly showed that 30 vs. 12 months of clopidogrel (65%) or prasugrel (35%) given to aspirin-treated individuals undergoing PCI significantly reduced death, MI or stroke in those with prior MI (HR 0.56 [95% CI 0.42-0.76], p<0.001), but not those without (0.83 [0.68-1.02], p=0.08) (117). Like CAPRIE, there was some evidence that those in the trial with DM gained less benefit in reduction of MACE from continued thienopyridine vs. placebo, when compared to those without DM (6.6% vs. 7.0% in those with DM, p=0.55; 3.3% vs. 5.2% in those without, p<0.001; interaction-p=0.03). Conversely, DM did not appear to be an interacting factor with regards to stent thrombosis or bleeding.

There is perhaps more convincing evidence, particularly in those with DM, for use of long-term ticagrelor-based DAPT. In the PEGASUS-TIMI 54 study, DAPT with aspirin plus ticagrelor, either 60 mg or 90 mg twice-daily, reduced MACE vs. aspirin alone (e.g. 60 mg twice-daily vs. placebo: HR 0.84 [95% CI 0.74-0.95], p=0.008) in participants with prior MI (>1 year ago) and an additional risk factor (age ≥65 years, DM, recurrent MI, multivessel CAD or non-end stage CKD) (118). Thrombolysis In Myocardial Infarction (TIMI)-major bleeding was significantly more frequent in ticagrelor-treated individuals, but serious events such as intracranial hemorrhage, hemorrhagic stroke or fatal bleeding showed no increase. In contrast to the thienopyridine trials, the 6806 participants with diabetes demonstrated a significant benefit of DAPT over SAPT in reducing MACE (HR 0.84 [95% CI 0.72-0.99], p=0.035) with a greater absolute risk reduction than in the cohort without diabetes (1.5% vs. 1.1%) (119). Patients without a history of anemia or hospitalization for bleeding, important risk factors for bleeding, appeared to derive greater benefit from long-term DAPT (120).

As well as in those with prior MI, ticagrelor-based DAPT has also been tested against aspirin alone in people with type 2 DM and chronic coronary syndromes (CCS) but without prior MI. THEMIS included 19,220 participants randomized to receive ticagrelor (90 mg twice daily, reduced to 60 mg during the trial) or placebo, on a background of aspirin treatment (121). After an average follow-up of 40 months, there was a lower incidence of MACE in those receiving ticagrelor when compared to placebo (HR 0.90 [95% CI 0.81-0.99], p=0.04). Notably, however, there was a relatively greater increase in TIMI-major bleeding (2.32 [1.82-2.94], p<0.001). Whilst meeting its primary endpoint, the net clinical benefit has not supported adoption in European practice, although subgroup analysis has suggested this may have been more favorable in those patients with prior PCI (122). Furthermore, based on the THEMIS data, the US Food and Drug Administration has recently extended the licensed indication for ticagrelor to include the prevention of a first MI or stroke in people with CCS at high risk of MI or stroke, including in those with DM (123).

An alternative to long-term DAPT is low-dose dual antithrombotic therapy (DATT) with aspirin 75-100 mg once daily and rivaroxaban 2.5 mg twice daily. The COMPASS trial included randomization of 27,395 participants with prior MI or multivessel CAD (38% with DM) or PAD to receive either low-dose DATT, rivaroxaban 5 mg twice daily alone or aspirin alone (124). Compared to aspirin alone, low-dose DATT led to a significantly reduced incidence of MACE [4.1% vs 5.4%, HR 0.76 [95% CI 0.66-0.86], p<0.001], people with DM gaining an even greater absolute net benefit.

Current guidelines recommend long-term DAPT or low-dose dual antithrombotic therapy (DATT) in those individuals with CCS without an indication for therapeutic oral anticoagulant (OAC) who are at high ischemic risk but not high bleeding risk (22).

In those undergoing PCI for stable CAD, including in those individuals with DM, the standard DATT regimen is DAPT with aspirin and clopidogrel for 6 months (125).

In summary, individuals with DM who have CCS should be treated with at least one antiplatelet agent, usually aspirin, although clopidogrel can be used if aspirin is contraindicated. However, more recent evidence indicates that those with a previous MI benefit from long-term DAPT (aspirin and ticagrelor) or a combination of antiplatelet and anticoagulant (DATT with aspirin and rivaroxaban) provided they have a low bleeding risk. Individuals with significant CAD but without a previous MI may also benefit from DAPT or DATT, which is best reserved for people with high vascular risk but low bleeding risk.

CEREBROVASCULAR DISEASE

There is good evidence for use of APT with aspirin, clopidogrel, ticlopidine or aspirin and dipyridamole in combination for secondary prevention in people with cerebrovascular disease, including those who also have DM (126). Aspirin plus dipyridamole offers better long-term protection than aspirin alone, but has a frequent adverse effect of headache that can limit its use (127). Clopidogrel monotherapy, without this side effect, offers similar levels of secondary prevention to aspirin plus dipyridamole and is the current preferred agent. In the first 3 months after an ischemic stroke, if reperfusion therapy has been given, aspirin alone is typically prescribed. In cases where reperfusion therapy has not been given, there is good evidence for using either aspirin and clopidogrel or aspirin and ticagrelor over aspirin alone (128,129). After 3 months, typically clopidogrel monotherapy is then given long-term, though aspirin and dipyridamole or aspirin alone are used instead at some centers (127,130,131).

PERIPHERAL ARTERY DISEASE

The effectiveness of APT for secondary prevention of ASCVD, including in those with symptomatic PAD, was established by the Antithrombotic Trialists’ Collaboration as discussed above. Similarly, in the CAPRIE trial, P2Y₁₂inhibitor monotherapy with clopidogrel was compared with aspirin, including in people with PAD (114). Whilst in the overall trial population there was only a modest reduction in MACE, there was evidence of greater efficacy in the subgroup with PAD, meaning clopidogrel may be preferred to aspirin. Current ESC guidelines recommend either aspirin or clopidogrel for patients with symptomatic PAD and/or those who have required revascularization, including in individuals with DM (132).

In those with symptomatic PAD, ticagrelor monotherapy has also been compared with clopidogrel in the EUCLID trial (133). There was no significant difference in the primary composite endpoint of MACE during a median follow-up period of 30 months and therefore ticagrelor monotherapy is not licensed for use in PAD. Prasugrel monotherapy has not been well tested in clinical-outcome studies but may offer pharmacodynamic advantages over clopidogrel, including in individuals with DM (134).

Comparison of DAPT (aspirin plus clopidogrel) with aspirin alone in people with PAD was included in CHARISMA (n=3,096 with PAD, 36.2% with DM). There was no significant difference in MACE (7.6% vs 8.9%, HR 0.85 [0.66–1.08], p=0.18) (135).

Conversely, there is good evidence for intensification of aspirin monotherapy to low-dose DATT with aspirin 75-100 mg once daily and rivaroxaban 2.5 mg twice daily in people with PAD, supported by the analysis of 7,470 participants with PAD in the COMPASS trial (136). The combination of rivaroxaban and aspirin reduced incidence of MACE over a median follow up of 21 months versus aspirin alone [5.1% vs 6.9%, HR 0.72 (0.57-0.90); p=0.0047]. Particularly important benefits observed included a lower incidence of major adverse limb events [1% vs 2%, HR 0·63 [95% CI 0.41–0.96], p=0·032], and lower incidence of major amputation [0.30 [0.11–0.80], p=0.011].

Subsequently, the evidence base for low-dose DATT in people PAD has been enhanced by the results of the VOYAGER-PAD trial, which randomized 6564 individuals with PAD treated by revascularization to receive either low-dose DATT or aspirin alone (137). After a median follow-up of 28 months (interquartile range 22-34), the primary composite endpoint of acute limb ischemia, amputation, MI, ischemic stroke or CV death occurred in 17.3% vs. 19.9% (HR 0.85 [0.76-0.96], p=0.009) without a significant increase in the incidence of TIMI major bleeding (2.65% vs. 1.87%, HR 1.43 [0.97-2.10, p=0.07). Forty percent of the trial population had DM with a similar response observed in this group.

It should be noted that DM individuals with symptomatic PAD are likely to have extensive vascular pathology and therefore DATT is likely to offer benefit in more than one vascular bed. Discussion of antithrombotic therapy for those people with DM and asymptomatic PAD is included in the next section.

Preventing First Atherothrombotic Event in Patients with Diabetes and No Symptomatic Atherosclerotic Cardiovascular Disease

It is rational to hypothesize that antithrombotic therapy (ATT) therapy may reduce the chance of a first atherothrombotic event or limit its severity by preventing thrombosis or reducing its impact. ATT in several distinct groups with DM but without symptomatic ASCVD have been investigated in a number of trials. The largest individual-level meta-analysis was performed in 2009 and included 95,000 participants from 6 trials (138). In individuals with DM, though aspirin led to a 12% proportional reduction in the rate of serious vascular events, this did not reach statistical significance. However, the point estimate was consistent with the statistically significant benefit of aspirin in the non-DM population and the DM population showed an identical trend. Three further trials have been added to the literature since this meta-analysis was performed. Two, JPAD (n=2539) and POPADAD (n=1276) were not adequately powered to draw firm conclusions (139,140). However, most recently ASCEND provided data from 15,480 individuals with DM but without symptomatic ASCVD who were randomized to receive aspirin 100 mg once daily or placebo (141). After a mean follow up of 7.4 years, those randomized to aspirin had a significantly reduced rate of serious vascular events (MI, stroke or TIA, or vascular death excluding intracranial hemorrhage) (RR 0.88 [95 % CI 0.79-0.97], p=0.01). However, major bleeding was significantly more frequent when receiving aspirin (1.24 [1.09-1.52], p=0.003), the majority being gastrointestinal. The investigators concluded that the absolute benefits were largely counterbalanced by the risks, despite a favorable, albeit modest, risk-benefit ratio.

Antiplatelet drugs other than aspirin have not been widely studied for primary prevention in individuals with DM and this remains an area for future research.

CONCLUSIONS

DM leads to a prothrombotic milieu that increases the risk of atherothrombotic and thromboembolic events compared to the non-DM population. Changes in platelets, coagulation, and inflammation appear central to this increased risk. Antithrombotic therapy (ATT) can help treat or prevent thrombotic events but increases bleeding risk. In those with a history of symptomatic ASCVD, long-term antiplatelet therapy (APT) with aspirin or clopidogrel is indicated. Intensification to long-term dual antiplatelet therapy (DAPT) or low-dose dual antithrombotic therapy (DATT) should be considered in those with chronic coronary syndromes (CCS) who have high ischemic risk but not high bleeding risk. Low-dose DATT can also be beneficial to people with symptomatic PAD. Therapeutic levels of oral anticoagulant (OAC) should be considered in all individuals with DM who develop AF. Accurately assessing and balancing a patient’s risk of ischemic and bleeding events is key to making rational treatment recommendations for ATT in DM (Figure 3).

Looking to the future, further work to determine more precisely an individual’s thrombotic and bleeding risk would greatly enhance our ability to make the best treatment recommendations for patients with DM. Whether this is achieved by more complex statistical modelling, novel imaging techniques, and/or better appreciation of circulating biomarkers remains to be determined. This would allow a greater move towards personalized strategies in order to more appropriately balance the benefits and risks of ATT. People with DM often have complex co-morbidities meaning choosing the best regimen is difficult, but is at the same time crucial to ensure an optimal outcome.

Emerging strategies such as early de-escalation of DAPT are encouraging new tools giving more options for subtle adjustment of ATT intensity, but require definitive proof they lead to no significant ischemic penalty and ratification by guideline committees before wider adoption can be recommended. No doubt further clarity will follow in the coming years.

The lack of an ability of ATT to meaningfully improve net clinical outcomes in those with DM without established ASCVD is a source of disappointment and demands future attention. Trials have focused on aspirin but it is clear that people with DM may have a poor response (111). As well as trials exploring novel regimens of aspirin, trials testing P2Y₁₂ inhibitor monotherapy, which may offer pharmacodynamic advantages over aspirin in this group, are warranted (134).

Finally, targeting the pathological abnormalities that cause hypofibrinolysis in diabetes, such as inhibition of PAI-1 activity, may offer an alternative management strategy to further reduce vascular occlusive disease in diabetes, while keeping the risk of bleeding to a minimum.

Figure 3. Principles to consider when deciding on the optimal regimen of antithrombotic therapy in a person with diabetes. ACS, acute coronary syndrome; AF, atrial fibrillation; ASCVD, atherosclerotic cardiovascular disease; CAD, coronary artery disease; CI, contraindication; DAPT, dual antiplatelet therapy; DATT, dual antithrombotic therapy; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; GI, gastrointestinal; OAC, oral anticoagulation; PAD, peripheral artery disease; PCI, percutaneous coronary intervention.

REFERENCES

Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215-2222.
Parker WAE, Gorog DA, Geisler T, Vilahur G, Sibbing D, Rocca B, Storey RF. Prevention of stroke in patients with chronic coronary syndromes or peripheral arterial disease. Eur Heart J Suppl. 2020;22(Supplement_M):M26-M34.
Jackson SP. Arterial thrombosis--insidious, unpredictable and deadly. Nat Med. 2011;17(11):1423-1436.
Konstantinides SV, Meyer G, Becattini C, Bueno H, Geersing G-J, Harjola V-P, Huisman MV, Humbert M, Jennings CS, Jiménez D, Kucher N, Lang IM, Lankeit M, Lorusso R, Mazzolai L, Meneveau N, Ní Áinle F, Prandoni P, Pruszczyk P, Righini M, Torbicki A, Van Belle E, Zamorano JL, ESC Scientific Document Group. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS): The Task Force for the diagnosis and management of acute pulmonary embolism of the European Society of Cardiology (ESC). Eur Heart J. 2020;41(4):543-603.
Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001;285(22):2864-2870.
Libby P, Buring JE, Badimon L, Hansson GK, Deanfield J, Bittencourt MS, Tokgozoglu L, Lewis EF. Atherosclerosis. Nat Rev Dis Primers. 2019;5(1):56.
Biondi-Zoccai GGL, Abbate A, Liuzzo G, Biasucci LM. Atherothrombosis, inflammation, and diabetes. J Am Coll Cardiol. 2003;41(7):1071-1077.
Patrono C, Morais J, Baigent C, Collet JP, Fitzgerald D, Halvorsen S, Rocca B, Siegbahn A, Storey RF, Vilahur G. Antiplatelet agents for the treatment and prevention of coronary atherothrombosis. J Am Coll Cardiol. 2017;70(14):1760-1776.
Storey RF. The long journey of individualizing antiplatelet therapy after acute coronary syndromes. Eur Heart J. 2020;41:3546-3548.
Bagot CN, Arya R. Virchow and his triad: a question of attribution. Br J Haematol. 2008;143(2):180-190.
Moroi M, Jung SM, Okuma M, Shinmyozu K. A patient with platelets deficient in glycoprotein VI that lack both collagen-induced aggregation and adhesion. J Clin Invest. 1989;84(5):1440-1445.
Santoro SA, Rajpara SM, Staatz WD, Woods VL, Jr. Isolation and characterization of a platelet surface collagen binding complex related to VLA-2. Biochem Biophys Res Commun. 1988;153(1):217-223.
Handa M, Titani K, Holland LZ, Roberts JR, Ruggeri ZM. The von Willebrand factor-binding domain of platelet membrane glycoprotein Ib. Characterization by monoclonal antibodies and partial amino acid sequence analysis of proteolytic fragments. J Biol Chem. 1986;261(27):12579-12585.
Aslan JE, Itakura A, Gertz JM, McCarty OJ. Platelet shape change and spreading. Methods Mol Biol. 2012;788:91-100.
Patrono C. Aspirin as an antiplatelet drug. N Engl J Med. 1994;330(18):1287-1294.
Parker WAE, Orme RC, Hanson J, Stokes HM, Bridge CM, Shaw PA, Sumaya W, Thorneycroft K, Petrucci G, Porro B, Judge HM, Ajjan RA, Rocca B, Storey RF. Very-low-dose twice-daily aspirin maintains platelet inhibition and improves haemostasis during dual-antiplatelet therapy for acute coronary syndrome. Platelets. 2019;30(2):148-157.
Harrison P, Cramer EM. Platelet alpha-granules. Blood Rev. 1993;7:52-62.
Fagura MS, Dainty IA, McKay GD, Kirk IP, Humphries RG, Robertson MJ, Dougall IG, Leff P. P2Y1-receptors in human platelets which are pharmacologically distinct from P2Y(ADP)-receptors. Br J Pharmacol. 1998;124(1):157-164.
Mahaut-Smith MP, Jones S, Evans RJ. The P2X1 receptor and platelet function. Purinergic Signal. 2011;7(3):341-356.
Storey RF, Sanderson HM, White AE, May JA, Cameron KE, Heptinstall S. The central role of the P(2T) receptor in amplification of human platelet activation, aggregation, secretion and procoagulant activity. Br J Haematol. 2000;110(4):925-934.
Pytela R, Pierschbacher MD, Ginsberg MH, Plow EF, Ruoslahti E. Platelet membrane glycoprotein IIb/IIIa: member of a family of Arg-Gly-Asp--specific adhesion receptors. Science. 1986;231(4745):1559-1562.
Parker WAE, Storey RF. Antithrombotic therapy for patients with chronic coronary syndromes. Heart 2021;107:925-933.
Parker WAE, Storey RF. Novel approaches to P2Y12 inhibition and aspirin dosing. Platelets. 2020;32(1):7-14.
Joshi RR, Hossain R, Morton AC, Ecob R, Judge HM, Wales C, Walker JV, Karunakaran A, Storey RF. Evolving pattern of platelet P2Y12 inhibition in patients with acute coronary syndromes. Platelets. 2014;25(6):416-422.
Parker WA, Bhatt DL, Prats J, Day JRS, Steg PG, Stone GW, Hamm CW, Mahaffey KW, Price MJ, Gibson CM, White HD, Storey RF. Characteristics of dyspnoea and associated clinical outcomes in the CHAMPION PHOENIX study. Thromb Haemost. 2017;117(6):1093-1100.
Parker W, Storey R. Pharmacology and Potential Role of Selatogrel, a Subcutaneous Platelet P2Y 12 Receptor Antagonist. Expert Opin Emerg Drugs. 2020;25(1):1-6.
Ajjan R, Grant PJ. Coagulation and atherothrombotic disease. Atherosclerosis. 2006;186(2):240-259.
Renné T, Schmaier AH, Nickel KF, Blombäck M, Maas C. In vivo roles of factor XII. Blood. 2012;120(22):4296-4303.
Mackman N, Tilley RE, Key NS. Role of the extrinsic pathway of blood coagulation in hemostasis and thrombosis. Arterioscler Thromb Vasc Biol. 2007;27(8):1687-1693.
Krishnaswamy S, Jones KC, Mann KG. Prothrombinase complex assembly. Kinetic mechanism of enzyme assembly on phospholipid vesicles. J Biol Chem. 1988;263(8):3823-3834.
Crawley JT, Lane DA. The haemostatic role of tissue factor pathway inhibitor. Arterioscler Thromb Vasc Biol. 2008;28(2):233-242.
Ariens RA, Lai TS, Weisel JW, Greenberg CS, Grant PJ. Role of factor XIII in fibrin clot formation and effects of genetic polymorphisms. Blood. 2002;100(3):743-754.
Verstraete M. The fibrinolytic system: from petri dishes to genetic engineering. Thromb Haemost. 1995;74:25-35.
Hurlen M, Abdelnoor M, Smith P, Erikssen J, Arnesen H. Warfarin, aspirin, or both after myocardial infarction. N Engl J Med. 2002;347(13):969-974.
Yeh CH, Hogg K, Weitz JI. Overview of the new oral anticoagulants: opportunities and challenges. Arterioscler Thromb Vasc Biol. 2015;35(5):1056-1065.
Kahn ML, Nakanishi-Matsui M, Shapiro MJ, Ishihara H, Coughlin SR. Protease-activated receptors 1 and 4 mediate activation of human platelets by thrombin. J Clin Invest. 1999;103(6):879-887.
Monroe DM, Hoffman M, Roberts HR. Platelets and thrombin generation. Arterioscler Thromb Vasc Biol. 2002;22(9):1381-1389.
Mi Y, Yan S, Lu Y, Liang Y, Li C. Venous thromboembolism has the same risk factors as atherosclerosis: A PRISMA-compliant systemic review and meta-analysis. Medicine (Baltimore). 2016;95(32):e4495.
Ibebuogu UN, Nasir K, Gopal A, Ahmadi N, Mao SS, Young E, Honoris L, Nuguri VK, Lee RS, Usman N, Rostami B, Pal R, Flores F, Budoff MJ. Comparison of atherosclerotic plaque burden and composition between diabetic and non diabetic patients by non invasive CT angiography. Int J Cardiovasc Imaging. 2009;25(7):717-723.
Larsen JR, Tsunoda T, Tuzcu EM, Schoenhagen P, Brekke M, Arnesen H, Hanssen KF, Nissen SE, Dahl-Jorgensen K. Intracoronary ultrasound examinations reveal significantly more advanced coronary atherosclerosis in people with type 1 diabetes than in age- and sex-matched non-diabetic controls. Diab Vasc Dis Res. 2007;4(1):62-65.
Lowry D, Saeed M, Narendran P, Tiwari A. A review of distribution of atherosclerosis in the lower limb arteries of patients with diabetes mellitus and peripheral vascular disease. Vasc Endovascular Surg. 2018;52(7):535-542.
Carrizzo A, Izzo C, Oliveti M, Alfano A, Virtuoso N, Capunzo M, Di Pietro P, Calabrese M, De Simone E, Sciarretta S, Frati G, Migliarino S, Damato A, Ambrosio M, De Caro F, Vecchione C. The main determinants of diabetes mellitus vascular complications: endothelial dysfunction and platelet hyperaggregation. Int J Mol Sci. 2018;19(10).
Stentz FB, Umpierrez GE, Cuervo R, Kitabchi AE. Proinflammatory cytokines, markers of cardiovascular risks, oxidative stress, and lipid peroxidation in patients with hyperglycemic crises. Diabetes. 2004;53(8):2079-2086.
Chaudhuri A, Umpierrez GE. Oxidative stress and inflammation in hyperglycemic crises and resolution with insulin: implications for the acute and chronic complications of hyperglycemia. J Diabetes Complications. 2012;26(4):257-258.
Patrono C, Rocca B. Measurement of thromboxane biosynthesis in health and disease. Front Pharmacol. 2019;10:1244.
Soma P, Swanepoel AC, du Plooy JN, Mqoco T, Pretorius E. Flow cytometric analysis of platelets type 2 diabetes mellitus reveals 'angry' platelets. Cardiovasc Diabetol. 2016;15:52.
Watala C, Boncler M, Golański J, Koziołkiewcz W, Trojanowski Z, Walkowiak B. Platelet membrane lipid fluidity and intraplatelet calcium mobilization in type 2 diabetes mellitus. Eur J Haematol. 1998;61(5):319-326.
Gawaz M, Ott I, Reininger AJ, Neumann FJ. Effects of magnesium on platelet aggregation and adhesion. Magnesium modulates surface expression of glycoproteins on platelets in vitro and ex vivo. Thromb Haemost. 1994;72(6):912-918.
Santilli F, Simeone P, Liani R, Davì G. Platelets and diabetes mellitus. Prostaglandins Other Lipid Mediat. 2015;120:28-39.
Hunter RW, Hers I. Insulin/IGF-1 hybrid receptor expression on human platelets: consequences for the effect of insulin on platelet function. J Thromb Haemost. 2009;7(12):2123-2130.
Westein E, Hoefer T, Calkin AC. Thrombosis in diabetes: a shear flow effect? Clin Sci (Lond). 2017;131(12):1245-1260.
Vernstrom L, Funck KL, Grove EL, Laugesen E, Baier JM, Hvas AM, Poulsen PL. Antiplatelet effect of aspirin during 24h in patients with type 2 diabetes without cardiovascular disease. Thromb Res. 2018;161:1-6.
Neergaard-Petersen S, Hvas AM, Ajjan R, Larsen SB, Würtz M, Kristensen SD, Grove EL. Platelet count, platelet turnover and fibrin clot structure in patients with coronary artery disease. Thromb Res. 2014;133(6):1161-1163.
Parker WAE, Storey RF. Aspirin dosing in atherosclerotic cardiovascular disease: should we be more ADAPTABLE? Cardiovasc Res. 2021;117(10):e123-e125.
Fejes Z, Poliska S, Czimmerer Z, Kaplar M, Penyige A, Gal Szabo G, Beke Debreceni I, Kunapuli SP, Kappelmayer J, Nagy B, Jr. Hyperglycaemia suppresses microRNA expression in platelets to increase P2RY12 and SELP levels in type 2 diabetes mellitus. Thromb Haemost. 2017;117(3):529-542.
Pordzik J, Jakubik D, Jarosz-Popek J, Wicik Z, Eyileten C, De Rosa S, Indolfi C, Siller-Matula JM, Czajka P, Postula M. Significance of circulating microRNAs in diabetes mellitus type 2 and platelet reactivity: bioinformatic analysis and review. Cardiovasc Diabetol. 2019;18(1):113.
Alzahrani SH, Ajjan RA. Coagulation and fibrinolysis in diabetes. Diab Vasc Dis Res. 2010;7:260-273.
Kim HK, Kim JE, Park SH, Kim YI, Nam-Goong IS, Kim ES. High coagulation factor levels and low protein C levels contribute to enhanced thrombin generation in patients with diabetes who do not have macrovascular complications. J Diabetes Complications. 2014;28(3):365-369.
Kearney K, Tomlinson D, Smith K, Ajjan R. Hypofibrinolysis in diabetes: a therapeutic target for the reduction of cardiovascular risk. Cardiovasc Diabetol. 2017;16(1):34.
Ajjan RA, Gamlen T, Standeven KF, Mughal S, Hess K, Smith KA, Dunn EJ, Anwar MM, Rabbani N, Thornalley PJ, Philippou H, Grant PJ. Diabetes is associated with posttranslational modifications in plasminogen resulting in reduced plasmin generation and enzyme-specific activity. Blood. 2013;122(1):134-142.
Du XL, Edelstein D, Rossetti L, Fantus IG, Goldberg H, Ziyadeh F, Wu J, Brownlee M. Hyperglycemia-induced mitochondrial superoxide overproduction activates the hexosamine pathway and induces plasminogen activator inhibitor-1 expression by increasing Sp1 glycosylation. Proc Natl Acad Sci U S A. 2000;97(22):12222-12226.
Wang Y, Beck W, Deppisch R, Marshall SM, Hoenich NA, Thompson MG. Advanced glycation end products elicit externalization of phosphatidylserine in a subpopulation of platelets via 5-HT2A/2C receptors. Am J Physiol Cell Physiol. 2007;293(1):C328-336.
Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C, Boriani G, Castella M, Dan G-A, Dilaveris PE, Fauchier L, Filippatos G, Kalman JM, La Meir M, Lane DA, Lebeau J-P, Lettino M, Lip GYH, Pinto FJ, Thomas GN, Valgimigli M, Van Gelder IC, Van Putte BP, Watkins CL, ESC Scientific Document Group. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS): The Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC. Eur Heart J. 2021;42(5):373-498.
Pallisgaard JL, Schjerning AM, Lindhardt TB, Procida K, Hansen ML, Torp-Pedersen C, Gislason GH. Risk of atrial fibrillation in diabetes mellitus: A nationwide cohort study. Eur J Prev Cardiol. 2016;23(6):621-627.
Overvad TF, Skjøth F, Lip GY, Lane DA, Albertsen IE, Rasmussen LH, Larsen TB. Duration of diabetes mellitus and risk of thromboembolism and bleeding in atrial fibrillation: nationwide cohort study. Stroke. 2015;46(8):2168-2174.
Dublin S, Glazer NL, Smith NL, Psaty BM, Lumley T, Wiggins KL, Page RL, Heckbert SR. Diabetes mellitus, glycemic control, and risk of atrial fibrillation. J Gen Intern Med. 2010;25(8):853-858.
Anselmino M, Matta M, D'Ascenzo F, Pappone C, Santinelli V, Bunch TJ, Neumann T, Schilling RJ, Hunter RJ, Noelker G, Fiala M, Frontera A, Thomas G, Katritsis D, Jais P, Weerasooriya R, Kalman JM, Gaita F. Catheter ablation of atrial fibrillation in patients with diabetes mellitus: a systematic review and meta-analysis. Europace. 2015;17(10):1518-1525.
Fatemi O, Yuriditsky E, Tsioufis C, Tsachris D, Morgan T, Basile J, Bigger T, Cushman W, Goff D, Soliman EZ, Thomas A, Papademetriou V. Impact of intensive glycemic control on the incidence of atrial fibrillation and associated cardiovascular outcomes in patients with type 2 diabetes mellitus (from the Action to Control Cardiovascular Risk in Diabetes Study). Am J Cardiol. 2014;114(8):1217-1222.
Chang SH, Wu LS, Chiou MJ, Liu JR, Yu KH, Kuo CF, Wen MS, Chen WJ, Yeh YH, See LC. Association of metformin with lower atrial fibrillation risk among patients with type 2 diabetes mellitus: a population-based dynamic cohort and in vitro studies. Cardiovasc Diabetol. 2014;13:123.
Zhang Z, Zhang X, Korantzopoulos P, Letsas KP, Tse G, Gong M, Meng L, Li G, Liu T. Thiazolidinedione use and atrial fibrillation in diabetic patients: a meta-analysis. BMC Cardiovasc Disord. 2017;17(1):96.
Zelniker TA, Bonaca MP, Furtado RHM, Mosenzon O, Kuder JF, Murphy SA, Bhatt DL, Leiter LA, McGuire DK, Wilding JPH, Budaj A, Kiss RG, Padilla F, Gause-Nilsson I, Langkilde AM, Raz I, Sabatine MS, Wiviott SD. Effect of dapagliflozin on atrial fibrillation in patients with type 2 diabetes mellitus. Circulation. 2020;141(15):1227-1234.
Cosentino F, Grant PJ, Aboyans V, Bailey CJ, Ceriello A, Delgado V, Federici M, Filippatos G, Grobbee DE, Hansen TB, Huikuri HV, Johansson I, Juni P, Lettino M, Marx N, Mellbin LG, Ostgren CJ, Rocca B, Roffi M, Sattar N, Seferovic PM, Sousa-Uva M, Valensi P, Wheeler DC. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J. 2020;41(2):255-323.
Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest. 2010;137(2):263-272.
Lip GYH, Clementy N, Pierre B, Boyer M, Fauchier L. The impact of associated diabetic retinopathy on stroke and severe bleeding risk in diabetic patients with atrial fibrillation: the loire valley atrial fibrillation project. Chest. 2015;147(4):1103-1110.
Patti G, Di Gioia G, Cavallari I, Nenna A. Safety and efficacy of nonvitamin K antagonist oral anticoagulants versus warfarin in diabetic patients with atrial fibrillation: A study-level meta-analysis of phase III randomized trials. Diabetes Metab Res Rev. 2017;33(3).
Olesen JB, Lip GYH, Hansen ML, Hansen PR, Tolstrup JS, Lindhardsen J, Selmer C, Ahlehoff O, Olsen A-MS, Gislason GH, Torp-Pedersen C. Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation: nationwide cohort study. BMJ. 2011;342:d124.
January CT, Wann LS, Alpert JS, Calkins H, Cigarroa JE, Cleveland JC, Conti JB, Ellinor PT, Ezekowitz MD, Field ME, Murray KT, Sacco RL, Stevenson WG, Tchou PJ, Tracy CM, Yancy CW. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2014;64(21):e1-e76.
Olesen JB, Torp-Pedersen C, Hansen ML, Lip GY. The value of the CHA2DS2-VASc score for refining stroke risk stratification in patients with atrial fibrillation with a CHADS2 score 0-1: a nationwide cohort study. Thromb Haemost. 2012;107(6):1172-1179.
Lip GYH, Keshishian A, Li X, Hamilton M, Masseria C, Gupta K, Luo X, Mardekian J, Friend K, Nadkarni A, Pan X, Baser O, Deitelzweig S. Effectiveness and Safety of Oral Anticoagulants Among Nonvalvular Atrial Fibrillation Patients. Stroke. 2018;49(12):2933-2944.
Sim SY, Morrison A, Gregory R, Kong M. Anticoagulation in hyperosmolar hyperglycaemic state: a case report and review of the literature. Brit J Diabetes. 2021;21(2):250-254.
Dhatariya K, Weston P. The argument against everyone with hyperosmolar hyperglycaemic syndrome being given prophylactic treatment dose anticoagulation. Brit J Diabetes. 2021;21(2):282-283.
Cosentino F, Ceriello A, Baeres FMM, Fioretto P, Garber A, Stough WG, George JT, Grant PJ, Khunti K, Langkilde AM, Plutzky J, Rydén L, Scheen A, Standl E, Tuomilehto J, Zannad F. Addressing cardiovascular risk in type 2 diabetes mellitus: a report from the European Society of Cardiology Cardiovascular Roundtable. Eur Heart J. 2019;40(34):2907-2919.
Collet J-P, Thiele H, Barbato E, Barthélémy O, Bauersachs J, Bhatt DL, Dendale P, Dorobantu M, Edvardsen T, Folliguet T, Gale CP, Gilard M, Jobs A, Jüni P, Lambrinou E, Lewis BS, Mehilli J, Meliga E, Merkely B, Mueller C, Roffi M, Rutten FH, Sibbing D, Siontis GCM, Group ESD. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: The Task Force for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J. 2021;42(14):1289-1367.
Ibanez B, James S, Agewall S, Antunes MJ, Bucciarelli-Ducci C, Bueno H, Caforio ALP, Crea F, Goudevenos JA, Halvorsen S, Hindricks G, Kastrati A, Lenzen MJ, Prescott E, Roffi M, Valgimigli M, Varenhorst C, Vranckx P, Widimský P, Group ESD. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J. 2017;39(2):119-177.
ISIS-2 Collaborative Group. Randomised trial of intravenous streptokinase, oral aspirin, both, or neither among 17,187 cases of suspected acute myocardial infarction: ISIS-2. Lancet. 1988;2(8607):349-360.
Rocca B, Santilli F, Pitocco D, Mucci L, Petrucci G, Vitacolonna E, Lattanzio S, Mattoscio D, Zaccardi F, Liani R, Vazzana N, Del Ponte A, Ferrante E, Martini F, Cardillo C, Morosetti R, Mirabella M, Ghirlanda G, Davi G, Patrono C. The recovery of platelet cyclooxygenase activity explains interindividual variability in responsiveness to low-dose aspirin in patients with and without diabetes. J Thromb Haemost. 2012;10(7):1220-1230.
Capodanno D, Patel A, Dharmashankar K, Ferreiro JL, Ueno M, Kodali M, Tomasello SD, Capranzano P, Seecheran N, Darlington A, Tello-Montoliu A, Desai B, Bass TA, Angiolillo DJ. Pharmacodynamic effects of different aspirin dosing regimens in type 2 diabetes mellitus patients with coronary artery disease. Circ Cardiovasc Interv. 2011;4:180-187.
Spectre G, Arnetz L, Ostenson CG, Brismar K, Li N, Hjemdahl P. Twice daily dosing of aspirin improves platelet inhibition in whole blood in patients with type 2 diabetes mellitus and micro- or macrovascular complications. Thromb Haemost. 2011;106(3):491-499.
Wiviott SD, Braunwald E, Angiolillo DJ, Meisel S, Dalby AJ, Verheugt FW, Goodman SG, Corbalan R, Purdy DA, Murphy SA, McCabe CH, Antman EM, for the TRITON-TIMI Investigators. Greater clinical benefit of more intensive oral antiplatelet therapy with prasugrel in patients with diabetes mellitus in the trial to assess improvement in therapeutic outcomes by optimizing platelet inhibition with prasugrel-thrombolysis in myocardial infarction 38. Circulation. 2008;118:1626-1636.
Franchi F, James SK, Ghukasyan Lakic T, Budaj AJ, Cornel JH, Katus HA, Keltai M, Kontny F, Lewis BS, Storey RF, Himmelmann A, Wallentin L, Angiolillo DJ. impact of diabetes mellitus and chronic kidney disease on cardiovascular outcomes and platelet P2Y(12) receptor antagonist effects in patients with acute coronary syndromes: insights from the PLATO trial. J Am Heart Assoc. 2019;8(6):e011139.
Yusuf S, Zhao F, Mehta S, Chrolavicius S, Tognoni G, Fox K. Effects of clopidogrel in addition to aspirin in patients with acute coronary syndromes without ST-segment elevation. New Eng J Med. 2001;345:494-502.
Sabatine MS, Cannon CP, Gibson CM, Lopez-Sendon JL, Montalescot G, Theroux P, Claeys MJ, Cools F, Hill KA, Skene AM, McCabe CH, Braunwald E. Addition of clopidogrel to aspirin and fibrinolytic therapy for myocardial infarction with ST-segment elevation. N Engl J Med. 2005;352(12):1179-1189.
Chen ZM, Jiang LX, Chen YP, Xie JX, Pan HC, Peto R, Collins R, Liu LS, COMMIT (ClOpidogrel and Metoprolol in Myocardial Infarction Trial) collaborative group. Addition of clopidogrel to aspirin in 45 852 patients with acute myocardial infarction: randomised placebo-controlled trial. Lancet. 2005;366(9497):1607-1621.
Wiviott S, Braunwald E, McCabe C, Montalescot G, Ruzyllo W, Gottlieb S, Neumann F-J, Ardissino D, De Servi S, Murphy S, Riesmeyer J, Weerakkody G, Gibson C, Antman E. Prasugrel versus clopidogrel in patients with acute coronary syndromes. New Eng J Med. 2007;357:2001-2015.
Roe MT, Armstrong PW, Fox KA, White HD, Prabhakaran D, Goodman SG, Cornel JH, Bhatt DL, Clemmensen P, Martinez F, Ardissino D, Nicolau JC, Boden WE, Gurbel PA, Ruzyllo W, Dalby AJ, McGuire DK, Leiva-Pons JL, Parkhomenko A, Gottlieb S, Topacio GO, Hamm C, Pavlides G, Goudev AR, Oto A, Tseng CD, Merkely B, Gasparovic V, Corbalan R, Cinteza M, McLendon RC, Winters KJ, Brown EB, Lokhnygina Y, Aylward PE, Huber K, Hochman JS, Ohman EM. Prasugrel versus clopidogrel for acute coronary syndromes without revascularization. N Engl J Med. 2012;367(14):1297-1309.
Wallentin L, Becker RC, Budaj A, Cannon CP, Emanuelsson H, Held C, Horrow J, Husted S, James S, Katus H, Mahaffey KW, Scirica BM, Skene A, Steg PG, Storey RF, Harrington RA. Ticagrelor versus clopidogrel in patients with acute coronary syndromes. N Engl J Med. 2009;361(11):1045-1057.
Schupke S, Neumann FJ, Menichelli M, Mayer K, Bernlochner I, Wohrle J, Richardt G, Liebetrau C, Witzenbichler B, Antoniucci D, Akin I, Bott-Flugel L, Fischer M, Landmesser U, Katus HA, Sibbing D, Seyfarth M, Janisch M, Boncompagni D, Hilz R, Rottbauer W, Okrojek R, Mollmann H, Hochholzer W, Migliorini A, Cassese S, Mollo P, Xhepa E, Kufner S, Strehle A, Leggewie S, Allali A, Ndrepepa G, Schuhlen H, Angiolillo DJ, Hamm CW, Hapfelmeier A, Tolg R, Trenk D, Schunkert H, Laugwitz KL, Kastrati A. Ticagrelor or prasugrel in patients with acute coronary syndromes. N Engl J Med. 2019;381(16):1524-1534.
Storey RF. Ticagrelor versus prasugrel for PCI-managed myocardial infarction: the battle of the giants continues. Heart. 2021;107(14):1111.
Ndrepepa G, Kastrati A, Menichelli M, Neumann F-J, Wöhrle J, Bernlochner I, Richardt G, Witzenbichler B, Sibbing D, Gewalt S, Angiolillo Dominick J, Hamm Christian W, Hapfelmeier A, Trenk D, Laugwitz K-L, Schunkert H, Schüpke S, Mayer K. Ticagrelor or prasugrel in patients with acute coronary syndromes and diabetes mellitus. JACC: Cardiovasc Intervent. 2020;13(19):2238-2247.
Mehran R, Baber U, Sharma SK, Cohen DJ, Angiolillo DJ, Briguori C, Cha JY, Collier T, Dangas G, Dudek D, Dzavik V, Escaned J, Gil R, Gurbel P, Hamm CW, Henry T, Huber K, Kastrati A, Kaul U, Kornowski R, Krucoff M, Kunadian V, Marx SO, Mehta SR, Moliterno D, Ohman EM, Oldroyd K, Sardella G, Sartori S, Shlofmitz R, Steg PG, Weisz G, Witzenbichler B, Han YL, Pocock S, Gibson CM. Ticagrelor with or without aspirin in high-risk patients after PCI. N Engl J Med. 2019;381(21):2032-2042.
Vranckx P, Valgimigli M, Juni P, Hamm C, Steg PG, Heg D, van Es GA, McFadden EP, Onuma Y, van Meijeren C, Chichareon P, Benit E, Mollmann H, Janssens L, Ferrario M, Moschovitis A, Zurakowski A, Dominici M, Van Geuns RJ, Huber K, Slagboom T, Serruys PW, Windecker S. Ticagrelor plus aspirin for 1 month, followed by ticagrelor monotherapy for 23 months vs aspirin plus clopidogrel or ticagrelor for 12 months, followed by aspirin monotherapy for 12 months after implantation of a drug-eluting stent: a multicentre, open-label, randomised superiority trial. Lancet. 2018;392(10151):940-949.
Chichareon P, Modolo R, Kogame N, Takahashi K, Chang CC, Tomaniak M, Botelho R, Eeckhout E, Hofma S, Trendafilova-Lazarova D, Kőszegi Z, Iñiguez A, Wykrzykowska JJ, Piek JJ, Garg S, Hamm C, Steg PG, Jüni P, Vranckx P, Valgimigli M, Windecker S, Onuma Y, Serruys PW. Association of diabetes with outcomes in patients undergoing contemporary percutaneous coronary intervention: Pre-specified subgroup analysis from the randomized GLOBAL LEADERS study. Atherosclerosis. 2020;295:45-53.
Bhalla A, Patel M, Birns J. An update on hyper-acute management of ischaemic stroke. Clin Med (Lond). 2021;21(3):215-221.
Capodanno D, Alberts M, Angiolillo DJ. Antithrombotic therapy for secondary prevention of atherothrombotic events in cerebrovascular disease. Nat Rev Cardiol. 2016;13(10):609-622.
Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, Bambakidis NC, Becker K, Biller J, Brown M, Demaerschalk BM, Hoh B, Jauch EC, Kidwell CS, Leslie-Mazwi TM, Ovbiagele B, Scott PA, Sheth KN, Southerland AM, Summers DV, Tirschwell DL, null n. Guidelines for the early management of patients with acute ischemic Stroke: 2019 update to the 2018 guidelines for the early management of acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2019;50(12):e344-e418.
Wang Y, Wang Y, Zhao X, Liu L, Wang D, Wang C, Wang C, Li H, Meng X, Cui L, Jia J, Dong Q, Xu A, Zeng J, Li Y, Wang Z, Xia H, Johnston SC. Clopidogrel with aspirin in acute minor stroke or transient ischemic attack. New Eng J Med. 2013;369(1):11-19.
Johnston SC, Easton JD, Farrant M, Barsan W, Conwit RA, Elm JJ, Kim AS, Lindblad AS, Palesch YY. Clopidogrel and aspirin in acute ischemic stroke and high-risk TIA. N Engl J Med. 2018;379(3):215-225.
Johnston SC, Amarenco P, Albers GW, Denison H, Easton JD, Evans SR, Held P, Jonasson J, Minematsu K, Molina CA, Wang Y, Wong KS. Ticagrelor versus aspirin in acute stroke or transient ischemic attack. N Engl J Med. 2016;375(1):35-43.
Johnston SC, Amarenco P, Denison H, Evans SR, Himmelmann A, James S, Knutsson M, Ladenvall P, Molina CA, Wang Y. Ticagrelor and aspirin or aspirin alone in acute ischemic stroke or tia. New Eng J Med. 2020;383(3):207-217.
Antiplatelet Trialists' Collaboration. Collaborative meta-analysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients. BMJ. 2002;324(7329):71-86.
Parker WAE, Sagar R, Kurdee Z, Hawkins F, Naseem KM, Grant PJ, Storey RF, Ajjan RA. A randomised controlled trial to assess the antithrombotic effects of aspirin in type 1 diabetes: role of dosing and glycaemic control. Cardiovasc Diabetol. 2021;20(1):238.
CURRENT-OASIS 7 Investigators, Mehta S, Bassand J, Chrolavicius S, Diaz R, Eikelboom J, Fox K, Granger C, Jolly S, Joyner C, Rupprecht H, Widimsky P, Afzal R, Pogue J, Yusuf S. Dose comparisons of clopidogrel and aspirin in acute coronary syndromes. New Eng J Med. 2010;363(10):930-942.
Jones WS, Mulder H, Wruck LM, Pencina MJ, Kripalani S, Muñoz D, Crenshaw DL, Effron MB, Re RN, Gupta K, Anderson RD, Pepine CJ, Handberg EM, Manning BR, Jain SK, Girotra S, Riley D, DeWalt DA, Whittle J, Goldberg YH, Roger VL, Hess R, Benziger CP, Farrehi P, Zhou L, Ford DE, Haynes K, VanWormer JJ, Knowlton KU, Kraschnewski JL, Polonsky TS, Fintel DJ, Ahmad FS, McClay JC, Campbell JR, Bell DS, Fonarow GC, Bradley SM, Paranjape A, Roe MT, Robertson HR, Curtis LH, Sharlow AG, Berdan LG, Hammill BG, Harris DF, Qualls LG, Marquis-Gravel G, Modrow MF, Marcus GM, Carton TW, Nauman E, Waitman LR, Kho AM, Shenkman EA, McTigue KM, Kaushal R, Masoudi FA, Antman EM, Davidson DR, Edgley K, Merritt JG, Brown LS, Zemon DN, McCormick TE, 3rd, Alikhaani JD, Gregoire KC, Rothman RL, Harrington RA, Hernandez AF. Comparative effectiveness of aspirin dosing in cardiovascular disease. N Engl J Med. 2021;384(21):1981-1990.
CAPRIE Steering Committee. A randomised, blinded, trial of clopidogrel versus aspirin in patients at risk of ischaemic events (CAPRIE). Lancet. 1996;348(9038):1329-1339.
Bhatt DL, Fox KAA, Hacke W, Berger PB, Black HR, Boden WE, Cacoub P, Cohen EA, Creager MA, Easton JD, Flather MD, Haffner SM, Hamm CW, Hankey GJ, Johnston SC, Mak K-H, Mas J-L, Montalescot G, Pearson TA, Steg PG, Steinhubl SR, Weber MA, Brennan DM, Fabry-Ribaudo L, Booth J, Topol EJ, the CI. Clopidogrel and aspirin versus aspirin alone for the prevention of atherothrombotic events. New Eng J Med. 2006;354(16):1706-1717.
Bhatt DL, Flather MD, Hacke W, Berger PB, Black HR, Boden WE, Cacoub P, Cohen EA, Creager MA, Easton JD, Hamm CW, Hankey GJ, Johnston SC, Mak KH, Mas JL, Montalescot G, Pearson TA, Steg PG, Steinhubl SR, Weber MA, Fabry-Ribaudo L, Hu T, Topol EJ, Fox KA. Patients with prior myocardial infarction, stroke, or symptomatic peripheral arterial disease in the CHARISMA trial. J Am Coll Cardiol. 2007;49(19):1982-1988.
Mauri L, Elmariah S, Yeh RW, Cutlip DE, Steg PG, Windecker S, Wiviott SD, Cohen DJ, Massaro JM, D'Agostino RB, Sr., Braunwald E, Kereiakes DJ. Causes of late mortality with dual antiplatelet therapy after coronary stents. Eur Heart J. 2016;37(4):378-385.
Bonaca MP, Bhatt DL, Cohen M, Steg PG, Storey RF, Jensen EC, Magnani G, Bansilal S, Fish MP, Im K, Bengtsson O, Ophuis TO, Budaj A, Theroux P, Ruda M, Hamm C, Goto S, Spinar J, Nicolau JC, Kiss RG, Murphy SA, Wiviott SD, Held P, Braunwald E, Sabatine MS. Long-term use of ticagrelor in patients with prior myocardial infarction. New Engl J Med. 2015;372:1791-1800.
Bhatt DL, Bonaca MP, Bansilal S, Angiolillo DJ, Cohen M, Storey RF, Im K, Murphy SA, Held P, Braunwald E, Sabatine MS, Steg PG. Reduction in ischemic events with ticagrelor in diabetic patients: from the PEGASUS-TIMI 54 trial. J Am Coll Cardiol. 2016;67:2732-2740.
Magnani G, Ardissino D, Im K, Budaj A, Storey RF, Steg PG, Bhatt DL, Cohen M, Oude Ophius T, Goudev A, Parkhomenko A, Kamensky G, Angiolillo DJ, López-Sendón J, Johanson P, Braunwald E, Sabatine MS, Bonaca MP. Predictors, type, and impact of bleeding on the net clinical benefit of long-term ticagrelor in stable patients with prior myocardial infarction. J Am Heart Assoc. 2021;10(4):e017008.
Steg PG, Bhatt DL, Simon T, Fox K, Mehta SR, Harrington RA, Held C, Andersson M, Himmelmann A, Ridderstrale W, Leonsson-Zachrisson M, Liu Y, Opolski G, Zateyshchikov D, Ge J, Nicolau JC, Corbalan R, Cornel JH, Widimsky P, Leiter LA. Ticagrelor in Patients with Stable Coronary Disease and Diabetes. N Engl J Med. 2019;381(14):1309-1320.
Bhatt DL, Steg PG, Mehta SR, Leiter LA, Simon T, Fox K, Held C, Andersson M, Himmelmann A, Ridderstrale W, Chen J, Song Y, Diaz R, Goto S, James SK, Ray KK, Parkhomenko AN, Kosiborod MN, McGuire DK, Harrington RA. Ticagrelor in patients with diabetes and stable coronary artery disease with a history of previous percutaneous coronary intervention (THEMIS-PCI): a phase 3, placebo-controlled, randomised trial. Lancet. 2019;394(10204):1169-1180.
Lackey LG, Garnett CE, Senatore F. Applying decision analysis to inform the US Food and Drug Administration’s benefit–risk assessment of ticagrelor for primary prevention of myocardial infarction or stroke based on THEMIS. Circulation. 2021;144(8):655-658.
Eikelboom JW, Connolly SJ, Bosch J, Dagenais GR, Hart RG, Shestakovska O, Diaz R, Alings M, Lonn EM, Anand SS, Widimsky P, Hori M, Avezum A, Piegas LS, Branch KRH, Probstfield J, Bhatt DL, Zhu J, Liang Y, Maggioni AP, Lopez-Jaramillo P, O'Donnell M, Kakkar AK, Fox KAA, Parkhomenko AN, Ertl G, Stork S, Keltai M, Ryden L, Pogosova N, Dans AL, Lanas F, Commerford PJ, Torp-Pedersen C, Guzik TJ, Verhamme PB, Vinereanu D, Kim JH, Tonkin AM, Lewis BS, Felix C, Yusoff K, Steg PG, Metsarinne KP, Cook Bruns N, Misselwitz F, Chen E, Leong D, Yusuf S. Rivaroxaban with or without aspirin in stable cardiovascular disease. N Engl J Med. 2017;377(14):1319-1330.
Knuuti J, Wijns W, Saraste A, Capodanno D, Barbato E, Funck-Brentano C, Prescott E, Storey RF, Deaton C, Cuisset T, Agewall S, Dickstein K, Edvardsen T, Escaned J, Gersh BJ, Svitil P, Gilard M, Hasdai D, Hatala R, Mahfoud F, Masip J, Muneretto C, Valgimigli M, Achenbach S, Bax JJ. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2020;41(3):407-477.
Antithrombotic Trialists' Collaboration. Collaborative meta-analysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients. BMJ. 2002;324(7329):71-86.
Halkes PH, van Gijn J, Kappelle LJ, Koudstaal PJ, Algra A. Aspirin plus dipyridamole versus aspirin alone after cerebral ischaemia of arterial origin (ESPRIT): randomised controlled trial. Lancet. 2006;367(9523):1665-1673.
Pan Y, Elm JJ, Li H, Easton JD, Wang Y, Farrant M, Meng X, Kim AS, Zhao X, Meurer WJ, Liu L, Dietrich D, Johnston SC. Outcomes associated with clopidogrel-aspirin use in minor stroke or transient ischemic attack: a pooled analysis of Clopidogrel in High-risk patients with Acute Non-disabling Cerebrovascular Events (CHANCE) and Platelet-Oriented Inhibition in New TIA and minor ischemic stroke (POINT) trials. JAMA Neurol. 2019;76(12):1466-1473.
Johnston SC, Amarenco P, Denison H, Evans SR, Himmelmann A, James S, Knutsson M, Ladenvall P, Molina CA, Wang Y. The acute stroke or transient ischemic attack treated with ticagrelor and aspirin for prevention of stroke and death (THALES) trial: rationale and design. Int J Stroke. 2019:1747493019830307.
Benavente OR, Hart RG, McClure LA, Szychowski JM, Coffey CS, Pearce LA. Effects of clopidogrel added to aspirin in patients with recent lacunar stroke. N Engl J Med. 2012;367(9):817-825.
Greving JP, Diener HC, Reitsma JB, Bath PM, Csiba L, Hacke W, Kappelle LJ, Koudstaal PJ, Leys D, Mas JL, Sacco RL, Algra A. Antiplatelet Therapy After Noncardioembolic Stroke. Stroke. 2019;50(7):1812-1818.
Aboyans V, Ricco JB, Bartelink MEL, Bjorck M, Brodmann M, Cohnert T, Collet JP, Czerny M, De Carlo M, Debus S, Espinola-Klein C, Kahan T, Kownator S, Mazzolai L, Naylor AR, Roffi M, Rother J, Sprynger M, Tendera M, Tepe G, Venermo M, Vlachopoulos C, Desormais I. 2017 ESC Guidelines on the Diagnosis and Treatment of Peripheral Arterial Diseases, in collaboration with the European Society for Vascular Surgery (ESVS): Document covering atherosclerotic disease of extracranial carotid and vertebral, mesenteric, renal, upper and lower extremity arteriesEndorsed by: the European Stroke Organization (ESO)The Task Force for the Diagnosis and Treatment of Peripheral Arterial Diseases of the European Society of Cardiology (ESC) and of the European Society for Vascular Surgery (ESVS). Eur Heart J. 2018;39(9):763-816.
Hiatt WR, Fowkes FG, Heizer G, Berger JS, Baumgartner I, Held P, Katona BG, Mahaffey KW, Norgren L, Jones WS, Blomster J, Millegård M, Reist C, Patel MR. Ticagrelor versus clopidogrel in symptomatic peripheral artery disease. N Engl J Med. 2017;376:32-40.
Parker WAE, Schulte C, Barwari T, Phoenix F, Pearson SM, Mayr M, Grant PJ, Storey RF, Ajjan RA. Aspirin, clopidogrel and prasugrel monotherapy in patients with type 2 diabetes mellitus: a double-blind randomised controlled trial of the effects on thrombotic markers and microRNA levels. Cardiovasc Diabetol. 2020;19(1):3.
Cacoub PP, Bhatt DL, Steg PG, Topol EJ, Creager MA. Patients with peripheral arterial disease in the CHARISMA trial. Eur Heart J. 2009;30(2):192-201.
Anand SS, Bosch J, Eikelboom JW, Connolly SJ, Diaz R, Widimsky P, Aboyans V, Alings M, Kakkar AK, Keltai K, Maggioni AP, Lewis BS, Stork S, Zhu J, Lopez-Jaramillo P, O'Donnell M, Commerford PJ, Vinereanu D, Pogosova N, Ryden L, Fox KAA, Bhatt DL, Misselwitz F, Varigos JD, Vanassche T, Avezum AA, Chen E, Branch K, Leong DP, Bangdiwala SI, Hart RG, Yusuf S. Rivaroxaban with or without aspirin in patients with stable peripheral or carotid artery disease: an international, randomised, double-blind, placebo-controlled trial. Lancet. 2018;391(10117):219-229.
Bonaca MP, Bauersachs RM, Anand SS, Debus ES, Nehler MR, Patel MR, Fanelli F, Capell WH, Diao L, Jaeger N, Hess CN, Pap AF, Kittelson JM, Gudz I, Mátyás L, Krievins DK, Diaz R, Brodmann M, Muehlhofer E, Haskell LP, Berkowitz SD, Hiatt WR. Rivaroxaban in peripheral artery disease after revascularization. New Eng J Med. 2020;382(21):1994-2004.
Baigent C, Blackwell L, Collins R, Emberson J, Godwin J, Peto R, Buring J, Hennekens C, Kearney P, Meade T, Patrono C, Roncaglioni MC, Zanchetti A. Aspirin in the primary and secondary prevention of vascular disease: collaborative meta-analysis of individual participant data from randomised trials. Lancet. 2009;373(9678):1849-1860.
Belch J, MacCuish A, Campbell I, Cobbe S, Taylor R, Prescott R, Lee R, Bancroft J, MacEwan S, Shepherd J, Macfarlane P, Morris A, Jung R, Kelly C, Connacher A, Peden N, Jamieson A, Matthews D, Leese G, McKnight J, O’Brien I, Semple C, Petrie J, Gordon D, Pringle S, MacWalter R. The prevention of progression of arterial disease and diabetes (POPADAD) trial: factorial randomised placebo controlled trial of aspirin and antioxidants in patients with diabetes and asymptomatic peripheral arterial disease. BMJ. 2008;337.
Ogawa H, Nakayama M, Morimoto T, Uemura S, Kanauchi M, Doi N, Jinnouchi H, Sugiyama S, Saito Y. Low-dose aspirin for primary prevention of atherosclerotic events in patients with type 2 diabetes: a randomized controlled trial. JAMA. 2008;300(18):2134-2141.
Bowman L, Mafham M, Wallendszus K, Stevens W, Buck G, Barton J, Murphy K, Aung T, Haynes R, Cox J, Murawska A, Young A, Lay M, Chen F, Sammons E, Waters E, Adler A, Bodansky J, Farmer A, McPherson R, Neil A, Simpson D, Peto R, Baigent C, Collins R, Parish S, Armitage J. Effects of aspirin for primary prevention in persons with diabetes mellitus. N Engl J Med. 2018;379(16):1529-1539.

Dysbetalipoproteinemia (Type III Hyperlipoproteinemia)

ABSTRACT

Dysbetalipoproteinemia is an underrecognized and underdiagnosed genetic lipid disorder characterized by pathogenic variants in the APOE gene, which encodes apolipoprotein (apo) E. It leads to the abnormal accumulation of triglyceride-rich remnant lipoproteins, elevated levels of both cholesterol and triglycerides, and an increased risk of cardiovascular disease. Typically, patients with autosomal recessive form of dysbetalipoproteinemia are homozygous for the e2 allele, which is associated with decreased binding of apo E to the LDL receptor and/or heparan sulfate proteoglycans, resulting in impaired remnant clearance. However, only a minority of apo e2 homozygotes become hyperlipidemic, often due to metabolic conditions that either increase lipoprotein production or decrease remnant clearance. Rarer variants in the APOE gene are linked to autosomal dominant dysbetalipoproteinemia. Palmar xanthoma is considered a characteristic feature of dysbetalipoproteinemia, although it is observed in fewer than half of affected individuals. Both total cholesterol and triglyceride levels are typically elevated and may be of similar magnitude. A low apo B level relative to a high total cholesterol level or a discrepancy between calculated LDL-cholesterol (LDL-C) and direct LDL-C levels can raise suspicion of this condition. There is no simple diagnostic test for dysbetalipoproteinemia, and diagnosis traditionally requires the detection of b-VLDL (remnant lipoproteins) and pathogenic variants in the APOE gene, both of which are not routinely available in clinical laboratories. Several algorithms using various lipid and apo B parameters have been proposed for screening and selecting candidates for genetic testing. Recent data suggest that the phenotype of dysbetalipoproteinemia is heterogeneous. The term multifactorial remnant cholesterol disease has been proposed to describe a milder form of dysbetalipoproteinemia in individuals without the apo e2/e2 genotype, differentiating them from the more severe form associated with apo e2/e2 genotype. Patients with dysbetalipoproteinemia are at an increased risk of cardiovascular diseases, particularly coronary artery disease and peripheral arterial disease. However, they generally respond well to lifestyle modifications and conventional lipid-lowering therapies, including statins and fibrates.

INTRODUCTION

Dysbetalipoproteinemia has been recognized since the 1950s and several names have been used in the literature, including xanthoma tuberosum, familial dysbetalipoproteinemia, broad beta disease, type III hyperlipoproteinemia, and remnant removal disease. Originally described by Gofman and colleagues, affected patients developed tuberous xanthoma of the extensor tendons and palmar xanthoma of the skin creases (1). An abnormal lipoprotein profile determined by analytical ultracentrifugation showed an increase in lipoproteins corresponding to small very low-density lipoprotein (VLDL) and intermediate-density lipoprotein (IDL). Using a combination of ultracentrifugation and paper electrophoresis, these cholesterol-enriched lipoprotein fractions displayed abnormal flotation and b electrophoretic mobility, instead of the normal pre-b mobility (2), and were referred to as floating beta lipoproteins or b-VLDL (3,4). The term “dysbetalipoproteinemia” was used to describe the presence of these b-VLDL in the circulation although the amount may not be high enough to cause elevated lipid levels. Overt hyperlipidemia observed in certain patients with dysbetalipoproteinemia was identified as being identical to type III hyperlipidemia, as classified by Fredrickson et al. in 1967 (4). The term “broad beta disease” represented the peculiar migration pattern of these abnormal b-VLDL on paper electrophoresis (4). These b-VLDL were shown to be remnants of apolipoprotein (apo) B-containing lipoproteins of both hepatic and intestinal origin (5), which accumulated in the plasma due to defective clearance (6). Havel and Kane later demonstrated that subjects with type III hyperlipidemia exhibited elevated levels of apo E, originally referred to as arginine-rich protein (7). Using isoelectric focusing, Utermann et al. found that apo E3 was absent in these subjects (8)and homozygosity for the pathogenic variant of apo E, referred to as apo E2 as opposed to the normal apo E3, was later found to be the underlying genetic defect (9,10). The complete amino acid sequences of different isoforms of apo E were determined by Mahley et al., which helped define the molecular abnormality of apo E in the pathogenesis of dysbetalipoproteinemia (11). Apo E was subsequently shown to be a major ligand for the LDL receptor and heparan sulfate proteoglycans (HSPGs), establishing apo E as the main apolipoprotein responsible for the uptake of remnant particles into hepatocytes (12). Defective binding of apo E to the receptors and impaired hepatic uptake could therefore explain the accumulation of remnant lipoproteins in these patients (13), although other environmental factors could modulate the expression of the abnormal lipid profile.

It is important to note that different terminology is often used in the literature to describe dysbetalipoproteinemia. In general, the term dysbetalipoproteinemia is used to indicate the presence of b-VLDL remnant particles in the circulation, whereas type III hyperlipidemia or type III hyperlipoproteinemia refers to the hyperlipidemic phenotype resulting from the accumulation of these remnant lipoproteins. In this article, we use the term dysbetalipoproteinemia to refer to the lipoprotein disorder characterized by the presence of b-VLDL in the circulation, which is often associated with hyperlipidemic phenotype.

EPIDEMIOLOGY

The prevalence of dysbetalipoproteinemia varies depending upon the definition used for diagnosis and the study population. Using the original gold standard diagnostic criteria by Fredrickson et al. (14) (a VLDL-cholesterol/plasma triglyceride (VLDL-C/TG) ratio >0.30 and the presence of b-VLDL on gel electrophoresis without requiring apo E genotype), the population-based prevalence of dysbetalipoproteinemia in the Northern American population was reported around 0.4% (1 in 250) in men aged 20 years or older and 0.2% (1 in 500) in similarly aged women (15,16). The prevalence is higher in men than in women and it tends to occur earlier in men (17,18). A similar prevalence of 0.2-0.4% was reported from a free-living population in California and in Vermont using lipoprotein electrophoresis as a diagnostic tool (19,20). In the 2011-2014 National Health and Nutrition Examination Survey (NHANES) participants in the U.S., the prevalence of 0.2-0.8% was reported using the lipoprotein levels from ultracentrifugation, but it increased to 1.97% when using only lipid and apo B levels (21). In studies using both lipid levels and the apo E genotype, a prevalence of 0.1% (1 in 889) was reported among 8,888 Dutch population (22), and a prevalence of 0.2% (1 in 469) was reported from 452,469 UK Biobank participants (23). The prevalence among different genetic ancestries was relatively similar and did not exceed 0.2% in any ancestry (23). Another study in Russia showed a prevalence of 0.67% (1 in 150) using the apo E genotype and triglyceride level ³130 mg/dL or 1.5 mmol/L (24). Collectively, the overall prevalence of dysbetalipoproteinemia, based on gold standard criteria and genetic testing, is estimated to be around 0.1–0.8%. Interestingly, this estimate is comparable to that of familial hypercholesterolemia (25).

GENETICS

Dysbetalipoproteinemia is caused by a genetic defect in the APOE gene, which encodes apo E. Apo E is a polymorphic glycoprotein found in various lipoprotein particles, including chylomicrons, chylomicron remnants, VLDL, VLDL remnants, and HDL. The main function of apo E is to mediate the interaction between apo E-containing lipoproteins and lipoprotein receptors. The N-terminal domain of apo E is involved in the interaction with the LDL receptor, the LDL receptor-related protein (LRP), and HSPGs, whereas the C-terminal domain is responsible for lipid binding. Amino acid residues 154-168 in the N-terminus contained several critical basic amino acids (i.e., arginine and lysine) that interact with acidic amino acid residues of the lipoprotein receptors and HSPGs.

The APOE gene is in the apolipoprotein gene cluster on the long arm of chromosome 19. It has 4 exons and 3 introns. Apo E is primarily synthesized in the liver, but other tissues can also produce apo E, including the brain, spleen, lung, kidneys, adrenals, ovaries, macrophages, and smooth muscle cells (26). After cleavage of the 18-amino acid signal peptide, the mature apo E protein has 299 amino acids. Three major isoforms of apo E (E3, E2, and E4) exist, which are caused by a single amino acid substitution at two different sites of the protein (27) as shown in Table 1. The differences among these isoforms result from different apo E alleles. The alleles are given designations using the Greek letter epsilon, i.e., e2, e3, and e4. Although the e3 is suggested to be a normal or wild-type allele, evidence exists that e4 allele may be the ancestral allele (28). The 3 apo E alleles yield 6 possible phenotypes, i.e., E2/E2, E2/E3, E2/E4, E3/E3, E3/E4, and E4/E4. The classical molecular abnormality causing dysbetalipoproteinemia is the homozygous variant known as the E2/E2 phenotype, which leads to a substitution of arginine for cysteine at position 176 (p.Arg176Cys). This variant is associated with an autosomal recessive inheritance of dysbetalipoproteinemia.

Table 1. Major Isoforms of Apo E Due to Different Amino Acids and Charges
Isoform	E2	E3	E4
Apo E allele	e2	e3	e4
rs number	rs7412	-	rs429358
HGVSc	c.526C>T	-	c.388T>C
HGVSp	p.Arg176Cys	-	p.Cys130Arg
Residue 130 (112*)	Cys	Cys	Arg
Residue 176 (158*)	Cys	Arg	Arg
Charge	0	+1	+2
Lipoprotein preference	HDL	HDL	VLDL

* Used in the old literature, which does not include the 18-amino acid signal peptide.

In almost all populations, the e3 allele makes up a majority of the apo E gene pool (70-80%), followed by e4 (10-15%) and e2 (5-10%). Therefore, the most common phenotype is the apo E3/E3 phenotype, which is found in 50-70% of the population, whereas the apo E2/E2 phenotype is relatively rare (24). Data from the UK Biobank indicate that apo E2 homozygosity is present in 0.2–1.3% of individuals, depending on genetic ancestry (23), and less than 20% of those with the apo E2/E2 phenotype develop overt hyperlipidemia (22), despite having demonstrable b-VLDL in the plasma, characteristic of dysbetalipoproteinemia.

Rarer variants in the APOE gene cause an autosomal dominant form of dysbetalipoproteinemia. Except for APOELeiden, which has a tandem duplication of 21 nucleotides coding for 7 amino acids, most of these rare variants involve substitutions of neutral or acidic amino acids for basic ones in the critical amino acid residues 154-168 that interact with lipoprotein receptors. The p.Arg163Cys variant is particularly common in subjects of African descents with the prevalence of 5-12% (29). Another rare cause of autosomal dominant dysbetalipoproteinemia is due to apo E deficiency (30,31).

PATHOPHYSIOLOGY

Chylomicrons produced by the small intestine and VLDL produced by the liver are both processed by lipoprotein lipase in the lipolytic cascade, resulting in triglyceride hydrolysis and the formation of chylomicron remnants and VLDL remnants, respectively. Normally, these remnant lipoproteins are cleared by receptors in the liver, including the LDL receptor and LDL receptor-related protein (LRP). Apo E plays a critical role in the binding, uptake, and hepatic clearance of remnant lipoprotein particles. Synthesized primarily by hepatocytes, apo E is secreted into the space of Disse, where it associates with remnant lipoproteins. Two major pathways mediate the clearance of remnant lipoprotein particles (32,33). First, apo E-containing remnant lipoproteins directly interact with the LDL receptor and are internalized into hepatocytes via the classical LDL receptor-mediated pathway. Second, apo E-enriched remnant lipoproteins interact with the cell-surface HSPGs before being transferred to LRP and internalized into hepatocytes through LRP. In addition, HSPGs alone can directly mediate lipoprotein uptake. HSPGs are transmembrane core proteins with attached heparan sulfate chains. These heparan sulfate chains are highly negatively charged sugar polymers capable of capturing lipoproteins and other ligands (33). Thus, the ligand-binding domains of HSPGs are carbohydrates, not proteins. Syndecan-1, an abundant HSPG on the hepatic surface in the space of Disse, is particularly important for remnant clearance (34,35). Furthermore, there is evidence suggesting that scavenger receptor class B type I (SR-BI) may also serve as an additional hepatic remnant receptor (36). Figure 1 illustrates the pathways involved in the clearance of remnant lipoproteins.

Figure 1. Clearance pathways of remnant lipoproteins.

The presence of abnormal apo E, which is defective in binding to HSPGs or hepatic receptors, or the absence of apo E could lead to impaired clearance of these remnant particles and the accumulation in the circulation, resulting in elevated levels of cholesterol and triglyceride. Different apo E variants likely affect different pathways of remnant lipoprotein particles, resulting in different patterns of hyperlipidemia and inheritance (37). Patients with homozygous familial hypercholesterolemia (FH) who lack LDL receptors do not have remnant accumulation (38). However, mice lacking syndecan-1, a core protein of HSPG, develop remnant accumulation despite intact LDL receptors (35). These studies suggest that HSPGs play a more important role in remnant clearance than the LDL receptor.

Accumulation of cholesterol-rich remnant particles leads to their uptake by macrophages, resulting in foam cells found in atherosclerotic lesions and xanthoma. Elevated levels of remnant cholesterol have been associated with an increased risk of cardiovascular disease, with a hazard ratio similar to that of elevated LDL-C (39,40).

Besides its role in the uptake and clearance of remnant particles, apo E also modulates lipolytic activity. Elevated levels of apo E can impair triglyceride hydrolysis by displacing or masking apo C-II, a cofactor for lipoprotein lipase, resulting in hypertriglyceridemia (41). In addition, apo E has been shown to stimulate hepatic VLDL production in animals, further increasing circulating triglyceride levels (42). However, evidence in humans is rather limited. In individuals with complete apo E deficiency, hypertriglyceridemia is usually not observed since there is no excess apo E and triglyceride lipolysis is not impaired.

Pathogenic variants in the APOE gene play a key role in the pathophysiology of dysbetalipoproteinemia. Most cases of dysbetalipoproteinemia are autosomal recessive, with the majority of affected individuals harboring two e2 alleles. Apo E2 has a binding capacity for the LDL receptor that is only 1–2% of that of apo E3 (43). Notably, the amino acid residue 176 lies outside the critical binding region involved in ionic interaction with lipoprotein receptors. This amino acid change appears to reorganize the salt bridges and alter the conformation of the amino acid residues 154-168, thereby indirectly impairing the receptor binding (44,45). In contrast, apo E2 retains significant binding affinity for HSPGs and the HSPG/LRP (37,46). Therefore, relatively normal binding of apo E2 to HSPG may compensate for defective binding to the LDL receptor, thereby protecting against the development of hyperlipidemia. In fact, most subjects with the E2/E2 phenotype are either normolipidemic or even hypolipidemic (9) and have a reduced risk for coronary artery disease (CAD) (47). Overt hyperlipidemia, also known as type III hyperlipidemia or type III hyperlipoproteinemia, develops only in the presence of additional environmental or genetic factors. These secondary factors may involve conditions associated with overproduction of VLDL or impaired clearance via the LDL receptor or the HSPG/LRP pathways as shown in Table 2. Insulin resistance, for example, is associated with the activation of the SULF2 gene, which encodes sulfatase 2 and causes degradation of HSPGs in mice (48). Thus, the presence of apoE2/E2 is necessary but not sufficient to cause an abnormal lipid profile. In the recessive form of dysbetalipoproteinemia, elevated lipid levels rarely appear before adulthood. Estrogen is known to enhance both LDL receptor expression and the lipolytic process. Therefore, women who are e2/e2 homozygotes are protected against the development of overt hyperlipidemia until after menopause. Additionally, common gene polymorphisms involved in triglyceride metabolism influence susceptibility to overt hyperlipidemia (49).

Table 2. Metabolic Conditions Known to Precipitate Hyperlipidemia in Dysbetalipoproteinemia
Lipoprotein overproduction	Impaired clearance
- Insulin resistance - Type 2 diabetes - Nephrotic syndrome - Excess alcohol intake - Estrogen treatment - Pregnancy - High fat diets - Medications: corticosteroids, retinoids, atypical antipsychotics, antiretrovirals, immunosuppressive drugs	- Increased age - Menopause - Hypothyroidism - Insulin resistance

Table 2. Metabolic Conditions Known to Precipitate Hyperlipidemia in Dysbetalipoproteinemia

Lipoprotein overproduction

Impaired clearance

- Insulin resistance

- Type 2 diabetes

- Nephrotic syndrome

- Excess alcohol intake

- Estrogen treatment

- Pregnancy

- High fat diets

- Medications: corticosteroids, retinoids, atypical antipsychotics, antiretrovirals, immunosuppressive drugs

- Increased age

- Menopause

- Hypothyroidism

- Insulin resistance

In approximately 10% of patients with dysbetalipoproteinemia, the disease is caused by autosomal dominant pathogenic variants in the APOE gene. These rare variants typically involve single amino acid substitutions within the critical binding region of apo E (residues 154–168) that interacts with the LDL receptor, thereby directly impairing receptor binding (50). Other variants disrupt the receptor binding of apo E or result in apo E deficiency. Furthermore, these dominant variants exhibit severely impaired binding to HSPGs. This defective HSPG binding in the dominant form of dysbetalipoproteinemia suggests that normal LDL receptor binding alone is not sufficient to ensure proper clearance of remnant lipoproteins. As a result, the HSPG binding affinity of apo E variants is considered a key determinant of the inheritance pattern of dysbetalipoproteinemia. In the autosomal dominant form, a single allele carrying these variants is sufficient to cause overt hyperlipidemia without the need for secondary factors and lipid abnormalities in these cases presumably begin at birth. To date, approximately 30 APOE variants associated with autosomal dominant dysbetalipoproteinemia have been reported (50-52). Autosomal dominant dysbetalipoproteinemia can occasionally be misdiagnosed as FH (50). The key differences between the autosomal recessive and autosomal dominant forms of dysbetalipoproteinemia are shown in Table 3.

Table 3. Characteristics of Autosomal Recessive and Autosomal Dominant Dysbetalipoproteinemia
	Recessive	Dominant
Presence of b-VLDL	Yes	Yes
Lipoprotein preference of apo E	HDL	Triglyceride-rich lipoproteins
LDL receptor binding	Defective	Defective
HSPG binding	Normal	Defective
Defect in receptor binding	Indirect	Direct
Secondary factors	Required	Not required
Occurrence of hyperlipidemia	Adulthood	From birth

Hypercholesterolemia in dysbetalipoproteinemia arises from impaired receptor-mediated clearance of cholesterol-rich remnant lipoproteins, while hypertriglyceridemia results from both impaired lipolytic processing of remnant particles and increased hepatic VLDL production driven by elevated levels of apo E (41,42). Low LDL-cholesterol levels in individuals with dysbetalipoproteinemia are primarily due to impaired conversion of VLDL to IDL, caused by elevated levels of apo E, and reduced hepatic lipase-mediated conversion of IDL to LDL by apo E2. Apo E plays a crucial role in hepatic lipase activity, with apo E3 and apo E4 being more effective than apo E2 in activating hepatic lipase-mediated lipolysis (53,54). Animal studies also suggest that low LDL-cholesterol levels are not due to upregulation of LDL receptors or enhanced hepatic clearance of LDL (41).

CLINICAL FEATURES

Patients with dysbetalipoproteinemia exhibit variable clinical features. Cutaneous xanthomas, especially palmar xanthoma and tuberous or tuberoeruptive xanthoma, are commonly observed. Palmar xanthoma (or xanthoma striata palmaris) is characterized by yellowish lipid deposits in the palmar creases and is found in 18–72% of patients (figure 2) (17,18,55-57). Although once considered specific to dysbetalipoproteinemia, it is now recognized in other conditions (57). Tuberous xanthoma, frequently found on the knuckles, elbows, knees, and buttocks, may be more common than palmar xanthoma (17,18). Tendon xanthoma is also present in some cases. Neither tuberous xanthoma nor tendon xanthoma is unique to dysbetalipoproteinemia; they can occur in other types of dyslipidemia. These xanthomas typically disappear once lipid levels are brought under control. Several metabolic conditions, including type 2 diabetes, hyperinsulinemia, obesity, hyperuricemia, and hypothyroidism, are associated with dysbetalipoproteinemia, as outlined in Table 2.

Figure 2. Palmer xanthoma

In a large cohort collected over a 35-year period in Canada, 524 patients met the gold standard Fredrickson criteria for dysbetalipoproteinemia (plasma triglyceride between 150-1,000 mg/dL and VLDL-cholesterol/triglyceride mass ratio >0.30) (58). However, only 197 subjects (38%) had the apo e2/e2 genotype. This finding contrasts with earlier reports based on a smaller number of subjects, which indicated that 90% of patients with dysbetalipoproteinemia carried the apo e2/e2 genotype. Clinically, patients who met the Fredrickson criteria and had the apo e2/e2 genotype exhibited more severe phenotypes than those without it. These individuals had significantly higher levels of remnant cholesterol, a greater frequency of xanthomas, and a higher prevalence of atherosclerotic cardiovascular disease (ASCVD) (58). Additionally, those with the apo e2/e2 genotype demonstrated an 11-fold increased risk of peripheral artery disease (PAD) compared to those without it. This study suggests that dysbetalipoproteinemia may manifest as a less severe multifactorial remnant cholesterol disease in individuals without the apo e2/e2 genotype and as a more severe form associated with the apo e2/e2 genotype (58).

Premature ASCVD, particularly CAD and PAD of the lower extremities, is more common in patients with dysbetalipoproteinemia and elevated lipid levels (17,55,59). The risk of CAD is reported to increase by approximately 5- to 10-fold (59). For PAD, the risk is elevated 13-fold compared to normolipidemic controls and 3-fold compared to patients with FH (60). Factors such as age, hypertension, smoking, waist circumference, triglyceride levels, and a polygenic risk score are significant predictors of cardiovascular disease in these individuals (61,62).

A contemporary cross-sectional study of 305 patients with dysbetalipoproteinemia in Europe found CAD in 19% of participants, while PAD was present in 11% (63). Similarly, among 964 patients in the UK Biobank, CAD was identified in 12% and PAD in 3% (23). Notably, as with other genetic lipid disorders, standard risk calculators for estimating the 10-year risk of ASCVD are not applicable, as they tend to underestimate the actual risk.

Rare mutations in the APOE gene are associated with lipoprotein glomerulopathy, a condition most commonly reported in Japan. The most frequent mutation identified is APOEc.488G>C (p.Arg163Pro), also known as apoE Sendai (64,65). This disorder is characterized by progressive proteinuria. Histologically, lipoprotein thrombi are observed in markedly dilated glomeruli. Approximately half of the reported cases progress to renal failure.

BIOCHEMICAL FEATURES

The lipid profile of subjects with dysbetalipoproteinemia is highly variable and sensitive to day-to-day changes in diet (66). Typically, there is an increase in both total cholesterol and triglyceride levels. Plasma triglyceride levels may be within the same range with the total cholesterol levels (cholesterol to triglyceride molar ratio around 2:1) or sometimes higher than total cholesterol levels. Severe hypertriglyceridemia resulting in acute pancreatitis has been reported in some cases of dysbetalipoproteinemia. Although total cholesterol levels are usually elevated, LDL-C levels are almost always reduced (17). The cause of low LDL-C levels in dysbetalipoproteinemia is due to an impairment in the apo E-mediated conversion of remnant lipoproteins to LDL (67). Normally, once apo E on remnant lipoproteins binds to HSPGs on hepatocytes, HSPG-bound hepatic lipase removes triglyceride from these remnants and converts them into LDL. The presence of abnormal apo E2 in dysbetalipoproteinemia appears to impair this process, leading to low levels of LDL-C.

Since remnant lipoproteins are enriched in cholesterol with a higher VLDL-cholesterol/triglyceride (VLDL-C/TG) ratio, a fixed ratio of VLDL-C/TG used in the Friedewald formula is invalid. In fact, dysbetalipoproteinemia is listed as one of the exceptions in the original report that the Friedewald formula should not be used (68). VLDL-C levels, calculated by triglyceride/5, are therefore underestimated, leading to overestimation of calculated LDL-C. Calculated LDL-C levels derived from the Friedewald formula or the NIH equation, as well as measured LDL-C levels from a homogeneous direct LDL-C assay, have been shown to overestimate plasma LDL-C levels in patients with dysbetalipoproteinemia (69,70). HDL cholesterol levels are also modestly reduced in subjects with dysbetalipoproteinemia. Apo B levels are typically not markedly elevated. Although Apo E levels are higher in individuals with dysbetalipoproteinemia, there is an overlap with those without the condition (71).

Based on lipid phenotypes, dysbetalipoproteinemia should be suspected in the following situations (72).

(1) dyslipidemia patients whose total cholesterol and triglyceride levels are both elevated and approximately equal

(2) mixed hyperlipidemia in which apo B level is relatively low in relation to total cholesterol level

(3) Significant disparity between calculated LDL-C and directly measured LDL-C levels

DIAGNOSIS

Dysbetalipoproteinemia cannot be diagnosed with a single straightforward test, nor can it be identified solely through conventional lipid values. Historically, diagnosis usually requires a biochemical approach to demonstrate the presence of remnant accumulation in the circulation and a genetic approach to characterize the apo E genotype. The presence of b-VLDL indicates dysbetalipoproteinemia regardless of whether hyperlipidemia is present or not.

Lipoprotein electrophoresis is a classical method originally used to characterize different lipoproteins and to classify various types of dyslipidemia. Different lipoprotein families display distinct bands on serum electrophoresis. Using paper, agarose, or cellulose acetate as the media, chylomicron stays at the origin whereas HDL migrates to the most advanced position, which is called an a band. Between the origin and the a band, a b band indicates LDL, whereas a pre-b band represents VLDL. On polyacrylamide gel, however, the migration pattern is slightly different in that VLDL (pre-blipoproteins) migrate behind instead of in front of the LDL (b-lipoproteins) (73).

Serum agarose gel electrophoresis has been traditionally used to detect the remnant lipoproteins and to diagnose dysbetalipoproteinemia. On paper, agarose, or cellulose acetate electrophoresis, the demonstration of a broad b band, extending from the b position into the pre-b position, indicates the presence of remnant lipoproteins (74) as shown in Figure 3. However, a broad b band is found in less than half of patients (75) and can be found in other conditions (76), suggesting that the presence of a broad b-band in lipoprotein electrophoresis is neither sensitive nor specific for the diagnosis of dysbetalipoproteinemia. On polyacrylamide gel electrophoresis, the presence of small VLDL and IDL along with the absence of a b-migrating lipoprotein band have also been used to indicate dysbetalipoproteinemia (73,75).

Figure 3. Plasma lipoprotein electrophoresis in 0.5% agarose gel demonstrated a broad  band in a patient with dysbetalipoproteinemia (left) and a normal pattern in a normal subject (right) (from (31)).

Another method used to characterize different lipoproteins is ultracentrifugation. Using preparative ultracentrifugation to isolate various lipoprotein families, lipid composition of different lipoprotein fractions can then be determined. Compared to the normal pre b-VLDL, b-VLDL remnant particles are more cholesterol-enriched and triglyceride-depleted. Normally, the cholesterol/triglyceride mass ratio in VLDL is 0.2 or less and the cholesterol/triglyceride ratio in b-VLDL is higher. A VLDL-C/VLDL TG mass ratio (both in mg/dL) >0.42 or VLDL-C/VLDL TG molar ratio (both in mmol/L) >0.97 is considered diagnostic of dysbetalipoproteinemia (77). Several studies have also tried to identify cut points for detection of b-VLDL using a VLDL-C/plasma or total TG ratio. The most frequently used cutoff for diagnosis of dysbetalipoproteinemia is the Fredrickson criteria, which is VLDL-C/TG >0.30 (mass ratio) or >0.69 (molar ratio) and plasma triglyceride level between 150-1,000 mg/dL (14). A mass ratio between 0.25-0.30 or a molar ratio between 0.57-0.69 is considered suggestive of dysbetalipoproteinemia (14,78).

Both lipoprotein electrophoresis and preparative ultracentrifugation described above are, however, not readily available in routine clinical laboratories. Therefore, other diagnostic methods using common lipid and apolipoprotein levels have been explored.

Two methods for estimating the VLDL-C level without a need for ultracentrifugation have recently been described (79). The first method used results obtained from the standard lipid panel and the Sampson-NIH equation. At a cut point of 0.194, a sensitivity of 74% and a specificity of 83% were reported (79). The second method modified the Sampson-NIH equation by including apo B level for predicting VLDL-C. At a cut-point of 0.209, a better sensitivity of 97% and a better specificity of 95% were demonstrated (79).

Remnant lipoprotein cholesterol (RLP-C) can be measured in serum and serum RLP-C/triglyceride ratio has been shown to be an effective alternative to VLDL-C/triglyceride ratio (80,81). Serum RLP-C/triglyceride ratio >0.23 is highly correlated with the presence of b-VLDL and has been demonstrated to be useful for screening for dysbetalipoproteinemia (81,82)

Since plasma apo B levels are not typically elevated in subjects with dysbetalipoproteinemia, Blom et al. showed that an apo B (in g/L)/total cholesterol (in mmol/L) ratio of <0.15 could identify patients with dysbetalipoproteinemia with a sensitivity of 89% (95% confidence interval [CI] 78-96%) and a specificity of 97% (95% CI 94-98%) among 333 patients with mixed hyperlipidemia with 57 having confirmed dysbetalipoproteinemia (83). In another study of 1,771 patients with various types of dyslipidemia along with 38 confirmed cases of dysbetalipoproteinemia, Sniderman et al. reported that a total cholesterol (in mmol/L)/apo B (in g/L) ratio of >6.2 and a triglyceride/apo B ratio of <10.0 have been shown to discriminate among other types of dyslipidemia based on the Fredrickson classification (84). However, when this method was compared to the ultracentrifugation-based definition of dysbetalipoproteinemia among 3,695 individuals (16 with dysbetalipoproteinemia), a higher prevalence was found (1.43% vs. 0.43%), suggesting that the method of Sniderman et al. using lipids and apo B levels might not be specific (16). When the triglyceride cutoff was raised from 160 mg/dL to 200 mg/dL, the specificity is significantly improved, indicating that triglyceride level is also important in this screening algorithm (16). With increasing levels of triglyceride, more severe cases of dysbetalipoproteinemia may be identified using the apo B algorithm but the sensitivity to detect milder cases drops significantly (85). Similarly, a recent study from Germany using the apo B/total cholesterol ratio as diagnostic criteria proposed by Sniderman et al. (84) or Blom et al. (83), showed that although subjects with the apo e2/e2 genotype were more likely to develop dysbetalipoproteinemia, most subjects with dysbetalipoproteinemia did not have the apo e2/e2 genotype (86). Resequencing of APOE gene further identified only a few cases of rare APOE variants (86). These studies suggest that using only lipid phenotypes and apo B alone without the apo e2 genotype tends to either include more false positive cases or capture milder cases of true dysbetalipoproteinemia (16,21).

In addition to using the total cholesterol/apo B ratio as a screening criterion, the non-HDL-cholesterol (non-HDL-C)/apo B ratio has also been examined. A small study in 9 Japanese patients with dysbetalipoproteinemia proposed a non HDL-C/apo B ratio (both in mg/dL) of >2.6 to differentiate from those with combined hyperlipidemia (87), whereas a subsequent larger study in England (n = 1,637) with 63 cases of dysbetalipoproteinemia showed that a non HDL-C (in mmol/L)/apo B (in g/L) ratio of >4.91 had better diagnostic performance than a total cholesterol/apo B ratio (88).

A study from Canada has also evaluated different lipid values among 4,891 patients with mixed hyperlipidemia (total cholesterol ³5.2 mmol/L [200 mg/dL] and triglyceride ³2.0 mmol/L [175 mg/dL]), 188 of whom had dysbetalipoproteinemia defined from elevated VLDL-C/plasma TG ratio and the presence of apo e2/e2 genotype (56). In this cohort, Paquette et al. showed that the non-HDL-C/apo B ratio was the best predictor of dysbetalipoproteinemia, which was better than the total cholesterol/apo B ratio (56). The non HDL-C/apo B ratio cut point of 3.69 mmol/g or 1.43 in conventional units (both in mg/dL) followed by the identification of apo e2/e2 genotype provided a good sensitivity (94.8%) and specificity (99%) with 99.4% accuracy (56). A review of previous diagnostic strategies proposed for dysbetalipoproteinemia further demonstrated that all other criteria (16,82-84,87-89) exhibited either low sensitivity or low specificity when validated using this cohort.

A combination of non HDL-C/apo B ratio of ³1.7 and TG/apo B ratio of ³1.35, all in mg/dL (non HDL-C in mmol/L/apo B in mg/dL ³4.4 and TG in mmol/L/apo B in mg/dL ³3.5) has recently been proposed as a screening tool for further APOEgenotyping in subjects with TG >150 mg/dL, LDL-C >160 mg/dL or non HDL-C >190 mg/dL (90). This algorithm has been shown to give excellent sensitivity and high specificity compared with other algorithms. Although apo B levels are affected by lipid-lowering therapy, this algorithm has been proposed to be used in those with and without lipid-lowering medications. In the population with lower levels of apo B, however, the algorithm that used non HDL-C/apo B ratio has been shown to give excellent sensitivity but very low specificity for detecting apo e2/e2 genotype (24).

More recently, a large study of dysbetalipoproteinemia patients (n=964) from the UK Biobank has been reported (23). Dysbetalipoproteinemia was diagnosed using the apo e2/e2 genotype and mixed hyperlipidemia (total cholesterol ³200 mg/dL [5.2 mmol/l] and triglyceride ³175 mg/dL [2.0 mmol/l]). The performances of 6 different criteria (56,79,83,84,88,90)were evaluated and 3 criteria by Boot et al.(88), Blom et al. (83), and Sniderman et al. (84) showed sensitivity, specificity, and accuracy >90% with the area under the curve (AUC) of ³0.95 and the negative predictive value of 100% (23). The number of those who met the criteria and should be assessed for APOE genotype in these 3 criteria ranged from 1-6%. When the non HDL-C/apo B cutoff ratio originally proposed by Paquette et al. (56) was raised from ³1.43 (in mg/dL) [3.69 (in mmol/g)] to ³1.78 (in mg/dL) [4.61 (in mmol/g)], the sensitivity, specificity, accuracy and the AUC were all improved similar to the 3 criteria, and the number of individuals that should undergo APOE genetic testing was lower from 23% to 3% (23). It is important to note that all of these criteria should be used for screening for further genetic testing and should not be used solely for diagnosis of dysbetalipoproteinemia. All of these screening criteria have very low positive predictive value, meaning that only a few of those who meet the criteria actually have dysbetalipoproteinemia when tested for APOE genotype (23).

The description of various criteria proposed for further evaluation for dysbetalipoproteinemia is shown in Table 4.

Table 4. Criteria Proposed for Further Evaluation for Dysbetalipoproteinemia
References	Proposed criteria
Apo B assay
Blom et al., 2005 (83)	- apo B (in g/L)/total cholesterol (in mmol/L) <0.15
Sniderman et al., 2007 (84)	- total cholesterol (in mmol/L)/apo B (in g/L) >6.2 - triglyceride (in mmol/L)/apo B (in g/L) <10.0 - triglyceride >75^th percentile for age and gender
Murase et al., 2010 (87)	- non-HDL-C/apo B ratio (both in mg/dL) >2.6
Hopkins et al., 2014 (16)	- total cholesterol (in mmol/L)/apo B (in g/L) >6.2 - triglyceride (in mmol/L)/apo B (in g/L) <10.0 - triglyceride >200 mg/dL (>2.3 mmol/L)
Boot et al., 2019 (88)	- total cholesterol >5.0 mmol/L (>193 mg/dL) and triglyceride >1.5 mmol/L (>133 mg/dL) - non-HDL-C (in mmol/L)/apo B (in g/L) >4.91
Paquette et al., 2020 (56)	- total cholesterol ³5.2 mmol/L (³200 mg/dL) and triglyceride ³2.0 mmol/L (³175 mg/dL) - non-HDL-C/apo B >3.69 mmol/g or 1.43 (both in mg/dL)
Bea et al, 2023 (90)	- triglyceride >150 mg/dL and LDL-C >160 mg/dL or non-HDL-C >190 mg/dL - non-HDL-C/apo B ³1.7 (both in mg/dL) or non-HDL-C (in mmol/L) /apo B (in mg/dL) ³4.4 - triglyceride/apo B ³1.35 (both in mg/dL) or triglyceride (in mmol/L) /apo B (in mg/dL) ³3.5
Remnant lipoprotein cholesterol assay
Nakajima et al., 2007 (82)	- RLP-C/triglyceride >0.23

Identification of apo E phenotype and/or genotype can help establish the diagnosis of dysbetalipoproteinemia. Nowadays, conventional apo E phenotyping by isoelectric focusing is replaced by a number of simple and more accurate APOE genotyping methods. When apo e2/e2 homozygosity is discovered in subjects with dysbetalipoproteinemia, immediate family members should be screened for the presence of hyperlipidemia. The presence of apo e2/e2 by itself without overt hyperlipidemia is not a critical risk factor for premature ASCVD. Therefore, counseling should be focused on eliminating secondary factors known to cause hyperlipidemia, such as obesity, diabetes, or alcohol consumption.

In patients with suspected dysbetalipoproteinemia, if the apo e2/e2 homozygosity is excluded, next generation sequencing can be performed to identify rare APOE variants associated with the autosomal dominant form. Since not all identified variants in the APOE gene are causally related to dysbetalipoproteinemia, a comprehensive approach is advised to determine the pathogenicity of the variants detected using both in vitro and in vivo functional studies (52). In this condition, 50% of first-degree relatives are affected. Therefore, cascade screening should be performed in a manner similar to that for FH. Once the diagnosis is confirmed, appropriate treatment should be initiated.

TREATMENT

Dysbetalipoproteinemia responds well to therapy (17). However, data from the UK Biobank and the US NHANES cohorts show that the majority of subjects with dysbetalipoproteinemia remain untreated despite their high atherogenic risk (21,23). Dietary modifications and addressing secondary metabolic factors form the cornerstone of therapy. Restriction of caloric intake in those who are overweight and reduction of saturated fat and cholesterol in the diet help normalize lipid levels (18). There are no specific dietary guidelines for patients with dysbetalipoproteinemia (91); however, reducing dietary cholesterol and saturated fat while increasing polyunsaturated fat intake is recommended (18). Weight reduction, glycemic control of diabetes, cessation of alcohol intake, and treatment of hypothyroidism can also lower lipid levels.

LDL-C levels cannot be accurately measured or calculated in patients with dysbetalipoproteinemia (70). In addition, LDL-C levels are typically not elevated and do not reflect high cardiovascular risk in these patients. Therefore, LDL-C levels should not be used as a treatment target in dysbetalipoproteinemia. It is recommended that the primary target of treatment is non-HDL-C level (50,73), which can be reliably measured using standard assays of total cholesterol and HDL-C (70). The secondary target of treatment is triglyceride level. In some cases, medications are required to lower cholesterol and triglyceride levels, and statins and fibrates are the medications of choice, respectively. Evolocumab, a PCSK9 inhibitor, has also been shown to reduce total cholesterol, remnant cholesterol, and triglyceride levels in patients with dysbetalipoproteinemia (92,93). Resolution in xanthomas and regression of atherosclerotic lesions have been observed after normalization of lipid levels (94).

CONCLUSION

Dysbetalipoproteinemia remains an underrecognized genetic lipid disorder. Pathogenic variants in the APOE gene lead to defective apo E-mediated remnant clearance and accumulation of remnant lipoproteins characterized by elevation of both total cholesterol and triglyceride levels, palmar and tuberous xanthomas, and an increased risk of CAD and PAD. The HSPG-binding affinity of the apo E variants appears to be an important determinant of the different modes of inheritance. Historically, diagnosis requires sophisticated methods to demonstrate the presence of remnant lipoprotein particles (b-VLDL) and the pathogenic variants in the APOE gene. Currently, a simple diagnostic test for dysbetalipoproteinemia does not exist and several algorithms using various lipid and apo B parameters have been proposed for screening for this condition and further genetic testing. Recent data suggest that the phenotype of dysbetalipoproteinemia may be more heterogeneous and a milder form of dysbetalipoproteinemia without the apo e2/e2 genotype is called multifactorial remnant cholesterol disease to differentiate it from the more severe form in those with apo e2/e2 genotype. Nevertheless, subjects with dysbetalipoproteinemia are usually responsive to lifestyle modifications and conventional lipid-modifying therapy, including statins and fibrates. Despite renewed interest and recent advances in understanding this condition, several knowledge gaps remain. These include the precise mechanisms involved in the clearance of remnant lipoproteins, the true prevalence within the general population, the roles of genetic and environmental factors in modifying disease expression, the underlying mechanisms of PAD involvement, the development of a simplified diagnostic test for clinical use, the establishment of standard guidelines for screening, and the creation of evidence-based guidelines for optimal treatment and cardiovascular risk reduction.

REFERENCES

McGinley J, Jones H, Gofman J. Lipoproteins and xanthomatous diseases. J Invest Dermatol. 1952;19(1):71-82.
Fredrickson DS, Levy RI, Lindgren FT. A comparison of heritable abnormal lipoprotein patterns as defined by two different techniques. J Clin Invest. 1968;47(11):2446-2457.
Quarfordt S, Levy RI, Fredrickson DS. On thelipoprotein abnormality in type 3 hyperlipoproteinemia. J Clin Invest.1971;50(4):754-761.
Fredrickson DS, Levy RI, Lees RS. Fat transport in lipoproteins--an integrated approach to mechanisms and disorders. N Engl J Med. 1967;276(4):215-225.
Kane JP, Chen GC, Hamilton RL, Hardman DA, Malloy MJ, Havel RJ. Remnants of lipoproteins of intestinal and hepatic origin in familial dysbetalipoproteinemia. Arteriosclerosis. 1983;3(1):47-56.
Chait A, Brunzell JD, Albers JJ, Hazzard WR. Type-III Hyperlipoproteinaemia ("remnant removal disease"). Insight into the pathogenetic mechanism. Lancet. 1977;1(8023):1176-1178.
Havel RJ, Kane JP. Primary dysbetalipoproteinemia: predominance of a specific apoprotein species in triglyceride-rich lipoproteins. Proc Natl Acad Sci U S A. 1973;70(7):2015-2019.
Utermann G, Jaeschke M, Menzel J. Familial hyperlipoproteinemia type III: deficiency of a specific apolipoprotein (apo E-III) in the very-low-density lipoproteins. FEBS Lett. 1975;56(2):352-355.
Utermann G, Hees M, Steinmetz A. Polymorphism of apolipoprotein E and occurrence of dysbetalipoproteinaemia in man. Nature. 1977;269(5629):604-607.
Zannis VI, Breslow JL. Characterization of a unique human apolipoprotein E variant associated with type III hyperlipoproteinemia. J Biol Chem. 1980;255(5):1759-1762.
Rall SC, Jr., Weisgraber KH, Mahley RW. Human apolipoprotein E. The complete amino acid sequence. J Biol Chem. 1982;257(8):4171-4178.
Windler E, Chao Y, Havel RJ. Determinants of hepatic uptake of triglyceride-rich lipoproteins and their remnants in the rat. J Biol Chem. 1980;255(11):5475-5480.
Havel RJ, Chao Y, Windler EE, Kotite L, Guo LS. Isoprotein specificity in the hepatic uptake of apolipoprotein E and the pathogenesis of familial dysbetalipoproteinemia. Proc Natl Acad Sci U S A. 1980;77(7):4349-4353.
Fredrickson DS, Morganroth J, Levy RI. Type III hyperlipoproteinemia: an analysis of two contemporary definitions. Ann Intern Med. 1975;82(2):150-157.
LaRosa JC, Chambless LE, Criqui MH, Frantz ID, Glueck CJ, Heiss G, Morrison JA. Patterns of dyslipoproteinemia in selected North American populations. The Lipid Research Clinics Program Prevalence Study. Circulation. 1986;73(1 Pt 2):I12-29.
Hopkins PN, Brinton EA, Nanjee MN. Hyperlipoproteinemia type 3: the forgotten phenotype. Curr Atheroscler Rep.2014;16(9):440.
Morganroth J, Levy RI, Fredrickson DS. The biochemical, clinical, and genetic features of type III hyperlipoproteinemia. Ann Intern Med. 1975;82(2):158-174.
Brewer HB, Jr., Zech LA, Gregg RE, Schwartz D, Schaefer EJ. NIH conference. Type III hyperlipoproteinemia: diagnosis, molecular defects, pathology, and treatment. Ann Intern Med. 1983;98(5 Pt 1):623-640.
Wood PD, Stern MP, Silvers A, Reaven GM, von der Groeben J. Prevalence of plasma lipoprotein abnormalities in a free-living population of the Central Valley, California. Circulation. 1972;45(1):114-126.
Gibson TC, Whorton EB. The prevalence of hyperlipidemia in a natural community. J Chronic Dis. 1973;26(4):227-236.
Pallazola VA, Sathiyakumar V, Park J, Vakil RM, Toth PP, Lazo-Elizondo M, Brown E, Quispe R, Guallar E, Banach M, Blumenthal RS, Jones SR, Marais D, Soffer D, Sniderman AD, Martin SS. Modern prevalence of dysbetalipoproteinemia (Fredrickson-Levy-Lees type III hyperlipoproteinemia). Arch Med Sci. 2020;16(5):993-1003.
de Beer F, Stalenhoef AF, Hoogerbrugge N, Kastelein JJ, Gevers Leuven JA, van Duijn CM, Havekes LM, Smelt AH. Expression of type III hyperlipoproteinemia in apolipoprotein E2 (Arg158 --> Cys) homozygotes is associated with hyperinsulinemia. Arterioscler Thromb Vasc Biol. 2002;22(2):294-299.
Paquette M, Trinder M, Guay SP, Brunham LR, Baass A. Prevalence of Dysbetalipoproteinemia in the UK Biobank According to Different Diagnostic Criteria. J Clin Endocrinol Metab. 2024.
Blokhina AV, Ershova AI, Kiseleva AV, Sotnikova EA, Zharikova AA, Zaicenoka M, Vyatkin YV, Ramensky VE, Kutsenko VA, Shalnova SA, Meshkov AN, Drapkina OM. Applicability of Diagnostic Criteria and High Prevalence of Familial Dysbetalipoproteinemia in Russia: A Pilot Study. Int J Mol Sci. 2023;24(17).
Beheshti SO, Madsen CM, Varbo A, Nordestgaard BG. Worldwide Prevalence of Familial Hypercholesterolemia: Meta-Analyses of 11 Million Subjects. J Am Coll Cardiol. 2020;75(20):2553-2566.
Mahley RW. Apolipoprotein E: cholesterol transport protein with expanding role in cell biology. Science.1988;240(4852):622-630.
Weisgraber KH, Rall SC, Jr., Mahley RW. Human E apoprotein heterogeneity. Cysteine-arginine interchanges in the amino acid sequence of the apo-E isoforms. J Biol Chem. 1981;256(17):9077-9083.
Hanlon CS, Rubinsztein DC. Arginine residues at codons 112 and 158 in the apolipoprotein E gene correspond to the ancestral state in humans. Atherosclerosis. 1995;112(1):85-90.
Abou Ziki MD, Strulovici-Barel Y, Hackett NR, Rodriguez-Flores JL, Mezey JG, Salit J, Radisch S, Hollmann C, Chouchane L, Malek J, Zirie MA, Jayyuosi A, Gotto AM, Jr., Crystal RG. Prevalence of the apolipoprotein E Arg145Cys dyslipidemia at-risk polymorphism in African-derived populations. Am J Cardiol. 2014;113(2):302-308.
Ghiselli G, Schaefer EJ, Gascon P, Breser HB, Jr. Type III hyperlipoproteinemia associated with apolipoprotein E deficiency. Science. 1981;214(4526):1239-1241.
Schaefer EJ, Gregg RE, Ghiselli G, Forte TM, Ordovas JM, Zech LA, Brewer HB, Jr. Familial apolipoprotein E deficiency. J Clin Invest. 1986;78(5):1206-1219.
Mahley RW, Ji ZS. Remnant lipoprotein metabolism: key pathways involving cell-surface heparan sulfate proteoglycans and apolipoprotein E. J Lipid Res. 1999;40(1):1-16.
Williams KJ, Chen K. Recent insights into factors affecting remnant lipoprotein uptake. Curr Opin Lipidol.2010;21(3):218-228.
Fuki IV, Kuhn KM, Lomazov IR, Rothman VL, Tuszynski GP, Iozzo RV, Swenson TL, Fisher EA, Williams KJ. The syndecan family of proteoglycans. Novel receptors mediating internalization of atherogenic lipoproteins in vitro. J Clin Invest. 1997;100(6):1611-1622.
Stanford KI, Bishop JR, Foley EM, Gonzales JC, Niesman IR, Witztum JL, Esko JD. Syndecan-1 is the primary heparan sulfate proteoglycan mediating hepatic clearance of triglyceride-rich lipoproteins in mice. J Clin Invest.2009;119(11):3236-3245.
Out R, Kruijt JK, Rensen PC, Hildebrand RB, de Vos P, Van Eck M, Van Berkel TJ. Scavenger receptor BI plays a role in facilitating chylomicron metabolism. J Biol Chem. 2004;279(18):18401-18406.
Ji ZS, Fazio S, Mahley RW. Variable heparan sulfate proteoglycan binding of apolipoprotein E variants may modulate the expression of type III hyperlipoproteinemia. J Biol Chem. 1994;269(18):13421-13428.
Rubinsztein DC, Cohen JC, Berger GM, van der Westhuyzen DR, Coetzee GA, Gevers W. Chylomicron remnant clearance from the plasma is normal in familial hypercholesterolemic homozygotes with defined receptor defects. J Clin Invest. 1990;86(4):1306-1312.
Varbo A, Benn M, Nordestgaard BG. Remnant cholesterol as a cause of ischemic heart disease: evidence, definition, measurement, atherogenicity, high risk patients, and present and future treatment. Pharmacol Ther.2014;141(3):358-367.
Varbo A, Freiberg JJ, Nordestgaard BG. Extreme nonfasting remnant cholesterol vs extreme LDL cholesterol as contributors to cardiovascular disease and all-cause mortality in 90000 individuals from the general population. Clin Chem. 2015;61(3):533-543.
Huang Y, Liu XQ, Rall SC, Jr., Mahley RW. Apolipoprotein E2 reduces the low density lipoprotein level in transgenic mice by impairing lipoprotein lipase-mediated lipolysis of triglyceride-rich lipoproteins. J Biol Chem.1998;273(28):17483-17490.
Huang Y, Liu XQ, Rall SC, Jr., Taylor JM, von Eckardstein A, Assmann G, Mahley RW. Overexpression and accumulation of apolipoprotein E as a cause of hypertriglyceridemia. J Biol Chem. 1998;273(41):26388-26393.
Weisgraber KH, Innerarity TL, Mahley RW. Abnormal lipoprotein receptor-binding activity of the human E apoprotein due to cysteine-arginine interchange at a single site. J Biol Chem. 1982;257(5):2518-2521.
Innerarity TL, Weisgraber KH, Arnold KS, Rall SC, Jr., Mahley RW. Normalization of receptor binding of apolipoprotein E2. Evidence for modulation of the binding site conformation. J Biol Chem. 1984;259(11):7261-7267.
Wilson C, Mau T, Weisgraber KH, Wardell MR, Mahley RW, Agard DA. Salt bridge relay triggers defective LDL receptor binding by a mutant apolipoprotein. Structure. 1994;2(8):713-718.
Kowal RC, Herz J, Weisgraber KH, Mahley RW, Brown MS, Goldstein JL. Opposing effects of apolipoproteins E and C on lipoprotein binding to low density lipoprotein receptor-related protein. J Biol Chem. 1990;265(18):10771-10779.
Bennet AM, Di Angelantonio E, Ye Z, Wensley F, Dahlin A, Ahlbom A, Keavney B, Collins R, Wiman B, de Faire U, Danesh J. Association of apolipoprotein E genotypes with lipid levels and coronary risk. JAMA. 2007;298(11):1300-1311.
Chen K, Liu ML, Schaffer L, Li M, Boden G, Wu X, Williams KJ. Type 2 diabetes in mice induces hepatic overexpression of sulfatase 2, a novel factor that suppresses uptake of remnant lipoproteins. Hepatology.2010;52(6):1957-1967.
Satny M, Todorovova V, Altschmiedova T, Hubacek JA, Dlouha L, Lanska V, Soska V, Kyselak O, Freiberger T, Bobak M, Vrablik M. Genetic risk score in patients with the APOE2/E2 genotype as a predictor of familial dysbetalipoproteinemia. J Clin Lipidol. 2024;18(2):e230-e237.
Koopal C, Marais AD, Westerink J, Visseren FL. Autosomal dominant familial dysbetalipoproteinemia: A pathophysiological framework and practical approach to diagnosis and therapy. J Clin Lipidol. 2017;11(1):12-23 e11.
Khalil YA, Rabes JP, Boileau C, Varret M. APOE gene variants in primary dyslipidemia. Atherosclerosis.2021;328:11-22.
Heidemann BE, Koopal C, Baass A, Defesche JC, Zuurbier L, Mulder MT, Roeters van Lennep JE, Riksen NP, Boot C, Marais AD, Visseren FLJ. Establishing the relationship between familial dysbetalipoproteinemia and genetic variants in the APOE gene. Clin Genet. 2022;102(4):253-261.
Thuren T, Weisgraber KH, Sisson P, Waite M. Role of apolipoprotein E in hepatic lipase catalyzed hydrolysis of phospholipid in high-density lipoproteins. Biochemistry. 1992;31(8):2332-2338.
Ehnholm C, Mahley RW, Chappell DA, Weisgraber KH, Ludwig E, Witztum JL. Role of apolipoprotein E in the lipolytic conversion of beta-very low density lipoproteins to low density lipoproteins in type III hyperlipoproteinemia. Proc Natl Acad Sci U S A. 1984;81(17):5566-5570.
Blom DJ, Byrnes P, Jones S, Marais AD. Dysbetalipoproteinaemia--clinical and pathophysiological features. S Afr Med J. 2002;92(11):892-897.
Paquette M, Bernard S, Blank D, Pare G, Baass A. A simplified diagnosis algorithm for dysbetalipoproteinemia. J Clin Lipidol. 2020;14(4):431-437.
Roy N, Gaudet D, Brisson D. Palmar striated xanthomas in clinical practice. J Endocr Soc. 2022;6(8):bvac103.
Paquette M, Bernard S, Pare G, Baass A. Dysbetalipoproteinemia: Differentiating Multifactorial Remnant Cholesterol Disease From Genetic ApoE Deficiency. J Clin Endocrinol Metab. 2022;107(2):538-548.
Hopkins PN, Wu LL, Hunt SC, Brinton EA. Plasma triglycerides and type III hyperlipidemia are independently associated with premature familial coronary artery disease. J Am Coll Cardiol. 2005;45(7):1003-1012.
Paquette M, Bernard S, Baass A. Dysbetalipoproteinemia Is Associated With Increased Risk of Coronary and Peripheral Vascular Disease. J Clin Endocrinol Metab. 2022;108(1):184-190.
Paquette M, Bernard S, Pare G, Baass A. Triglycerides, hypertension, and smoking predict cardiovascular disease in dysbetalipoproteinemia. J Clin Lipidol. 2020;14(1):46-52.
Paquette M, Trinder M, Guay SP, Brunham LR, Baass A. Predictors of cardiovascular disease in individuals with dysbetalipoproteinemia: a prospective study in the UK Biobank. J Clin Endocrinol Metab. 2024.
Koopal C, Retterstol K, Sjouke B, Hovingh GK, Ros E, de Graaf J, Dullaart RP, Bertolini S, Visseren FL. Vascular risk factors, vascular disease, lipids and lipid targets in patients with familial dysbetalipoproteinemia: a European cross-sectional study. Atherosclerosis. 2015;240(1):90-97.
Saito T, Oikawa S, Sato H, Sato T, Ito S, Sasaki J. Lipoprotein glomerulopathy: significance of lipoprotein and ultrastructural features. Kidney Int Suppl. 1999;71:S37-41.
Oikawa S, Matsunaga A, Saito T, Sato H, Seki T, Hoshi K, Hayasaka K, Kotake H, Midorikawa H, Sekikawa A, Hara S, Abe K, Toyota T, Jingami H, Nakamura H, Sasaki J. Apolipoprotein E Sendai (arginine 145-->proline): a new variant associated with lipoprotein glomerulopathy. J Am Soc Nephrol. 1997;8(5):820-823.
Sniderman AD, de Graaf J, Thanassoulis G, Tremblay AJ, Martin SS, Couture P. The spectrum of type III hyperlipoproteinemia. J Clin Lipidol. 2018;12(6):1383-1389.
Mahley RW, Huang Y, Rall SC, Jr. Pathogenesis of type III hyperlipoproteinemia (dysbetalipoproteinemia). Questions, quandaries, and paradoxes. J Lipid Res. 1999;40(11):1933-1949.
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18(6):499-502.
Higgins V, Leiter LA, Delaney SR, Beriault DR. Validating the NIH LDL-C equation in a specialized lipid cohort: Does it add up? Clin Biochem. 2022;99:60-68.
Heidemann BE, Koopal C, Roeters van Lennep JE, Stroes ES, Riksen NP, Mulder MT, van Vark-van der Zee LC, Blackhurst DM, Visseren FLJ, Marais AD. Low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol measurement in Familial Dysbetalipoproteinemia. Clin Chim Acta. 2023;539:114-121.
Todo Y, Kobayashi J, Higashikata T, Kawashiri M, Nohara A, Inazu A, Koizumi J, Mabuchi H. Detailed analysis of serum lipids and lipoproteins from Japanese type III hyperlipoproteinemia with apolipoprotein E2/2 phenotype. Clin Chim Acta. 2004;348(1-2):35-40.
Marais AD, Solomon GA, Blom DJ. Dysbetalipoproteinaemia: a mixed hyperlipidaemia of remnant lipoproteins due to mutations in apolipoprotein E. Crit Rev Clin Lab Sci. 2014;51(1):46-62.
Koopal C, Marais AD, Visseren FL. Familial dysbetalipoproteinemia: an underdiagnosed lipid disorder. Curr Opin Endocrinol Diabetes Obes. 2017;24(2):133-139.
Beaumont JL, Carlson LA, Cooper GR, Fejfar Z, Fredrickson DS, Strasser T. Classification of hyperlipidaemias and hyperlipoproteinaemias. Bull World Health Organ. 1970;43(6):891-915.
Blom DJ, Byrnes P, Jones S, Marais AD. Non-denaturing polyacrylamide gradient gel electrophoresis for the diagnosis of dysbetalipoproteinemia. J Lipid Res. 2003;44(1):212-217.
Boot CS, Luvai A, Neely RDG. The clinical and laboratory investigation of dysbetalipoproteinemia. Crit Rev Clin Lab Sci. 2020;57(7):458-469.
Hazzard WR, Porte D, Jr., Bierman EL. Abnormal lipid composition of very low density lipoproteins in diagnosis of broad-beta disease (type 3 hyperlipoproteinemia). Metabolism. 1972;21(11):1009-1019.
Mishkel MA, Nazir DJ, Crowther S. A longitudinal assessment of lipid ratios in the diagnosis of type III hyperlipoproteinaemia. Clin Chim Acta. 1975;58(2):121-136.
Sampson M, Wolska A, Meeusen JW, Donato LJ, Jaffe AS, Remaley AT. Identification of dysbetalipoproteinemia by an enhanced Sampson-NIH equation for very low-density lipoprotein-cholesterol. Front Genet. 2022;13:935257.
Nakajima K, Saito T, Tamura A, Suzuki M, Nakano T, Adachi M, Tanaka A, Tada N, Nakamura H, Murase T. A new approach for the detection of type III hyperlipoproteinemia by RLP-cholesterol assay. J Atheroscler Thromb.1994;1(1):30-36.
Wang T, Nakajima K, Leary ET, Warnick GR, Cohn JS, Hopkins PN, Wu LL, Cilla DD, Zhong J, Havel RJ. Ratio of remnant-like particle-cholesterol to serum total triglycerides is an effective alternative to ultracentrifugal and electrophoretic methods in the diagnosis of familial type III hyperlipoproteinemia. Clin Chem. 1999;45(11):1981-1987.
Nakajima K, Daimon M, Kamiyama K, Takanashi K, Suzuki Y, Watanabe M, Kubono K, Saniabadi AR, Takashima S, Sakurabayashi I. Serum remnant lipoprotein cholesterol/triglyceride ratio as an index for screening familial type III hyperlipidaemia. Ann Clin Biochem. 2007;44(Pt 4):353-359.
Blom DJ, O'Neill FH, Marais AD. Screening for dysbetalipoproteinemia by plasma cholesterol and apolipoprotein B concentrations. Clin Chem. 2005;51(5):904-907.
Sniderman A, Tremblay A, Bergeron J, Gagne C, Couture P. Diagnosis of type III hyperlipoproteinemia from plasma total cholesterol, triglyceride, and apolipoprotein B. J Clin Lipidol. 2007;1(4):256-263.
Varghese B, Park J, Chew E, Sajja A, Brownstein A, Pallazola VA, Sathiyakumar V, Jones SR, Sniderman AD, Martin SS. Importance of the triglyceride level in identifying patients with a Type III Hyperlipoproteinemia phenotype using the ApoB algorithm. J Clin Lipidol. 2021;15(1):104-115 e109.
Evans D, Beil FU, Aberle J. Resequencing the APOE gene reveals that rare mutations are not significant contributory factors in the development of type III hyperlipidemia. J Clin Lipidol. 2013;7(6):671-674.
Murase T, Okubo M, Takeuchi I. Non-HDL-cholesterol/apolipoprotein B ratio: a useful distinguishing feature in the screening for type III hyperlipoproteinemia. J Clin Lipidol. 2010;4(2):99-104.
Boot CS, Middling E, Allen J, Neely RDG. Evaluation of the non-HDL cholesterol to apolipoprotein B ratio as a screening test for dysbetalipoproteinemia. Clin Chem. 2019;65(2):313-320.
de Graaf J, Couture P, Sniderman A. A diagnostic algorithm for the atherogenic apolipoprotein B dyslipoproteinemias. Nat Clin Pract Endocrinol Metab. 2008;4(11):608-618.
Bea AM, Cenarro A, Marco-Bened V, Laclaustra M, Martn C, Ibarretxe D, Pint X, Arrobas T, Vials C, Civeira F, Olmos S. Diagnosis of Familial Dysbetalipoproteinemia Based on the Lipid Abnormalities Driven by APOE2/E2 Genotype. Clin Chem. 2023;69(2):140-148.
Paquette M, Blais C, Fortin A, Bernard S, Baass A. Dietary recommendations for dysbetalipoproteinemia: A need for better evidence. J Clin Lipidol. 2023;17(4):549-556.
Waldmann E, Wu L, Busygina K, Altenhofer J, Henze K, Folwaczny A, Parhofer KG. Effect of PCSK9 inhibition with evolocumab on lipoprotein subfractions in familial dysbetalipoproteinemia (type III hyperlipidemia). PLoS One.2022;17(3):e0265838.
Heidemann BE, Koopal C, Roeters van Lennep JE, Stroes ESG, Riksen NP, Mulder MT, van der Zee L, Blackhurst DM, Marais AD, Visseren FLJ. Effect of evolocumab on fasting and post fat load lipids and lipoproteins in familial dysbetalipoproteinemia. J Clin Lipidol. 2023;17(1):112-123.
Cho EJ, Min YJ, Oh MS, Kwon JE, Kim JE, Kim CJ. Disappearance of angina pectoris by lipid-lowering in type III hyperlipoproteinemia. Am J Cardiol. 2011;107(5):793-796.

Diabetes and Depression

ABSTRACT

Depression is characterized by a disturbance of mood, affecting between 3–5% of the general population at any one time. The prevalence of depression is approximately doubled in people with diabetes compared to the general population, with similar rates between type 1 diabetes and type 2 diabetes. Although many cases of depression are coincidental to the presence of diabetes, certain diabetes factors including diabetes-related complications, diabetes treatments and obesity are associated with an increased risk of depression. There is a bi-directional relationship between diabetes and depression with specific disease and treatment factors explaining why diabetes pre-disposes to depression and vice versa. Genetics, early intra-uterine development, and social determinants of health may create a “common soil” for both conditions. The presence of depression in people with diabetes worsens both diabetes and depression outcomes. Mortality is increased, quality of life diminished, and healthcare costs are increased. Diabetes self-management is also impaired. It may be possible to reduce the incidence of depression in people with diabetes by considering the way in which the diagnosis of diabetes is conveyed and the psychosocial support that is given through an individual’s journey with diabetes. Several short screening questionnaires have been validated in people with diabetes. A diagnosis should be confirmed by a diagnostic interview. The main aims of treatment are to improve both diabetes and mental health outcomes with complete remission of depressive symptoms. Various psychological treatments, including cognitive behavioral therapy, problem-solving, and psychodynamic techniques have been used to treat depression in people with diabetes. Antidepressants reduce depressive symptoms in people with diabetes as well as the general population. All antidepressants appear to have similar effects on depressive symptoms as long as adequate doses are used. Treatment should be maintained for at least 4–6 months after remission of symptoms to reduce the risk of relapse and recurrence. The choice of antidepressant depends largely on the side-effect profile, individual preference, and response. Selective serotonin reuptake inhibitors are widely used as first-choice agents. A common model of care for depression is the Stepped Care Model which is designed to provide a rational approach to the treatment of depression, while reducing costs and side effects of antidepressants through more appropriate prescribing. A case management model known as collaborative care is a clinical- and cost-effective treatment of depression that also improves diabetes outcomes by involving a multidisciplinary team that works together to identify and treat depression within primary care settings. Although diabetes and depression remain a considerable clinical challenge, there are grounds for considerable optimism as the scientific knowledge that underpins clinical practices has expanded markedly in the last two decades. However, further research is needed to understand what can be done to prevent depression in people with diabetes and to identify the optimal treatment for an individual that improves both depressive symptoms and diabetes outcomes.

INTRODUCTION

The importance of considering the interaction between mind and body in the management and outcome of chronic diseases has been recognized for over 2,500 years but is particularly poignant for people with diabetes. Diabetes places high behavioral demands on those living with the condition whilst mental disorders, such as depression, may compromise an individual’s ability to perform the self-care needed to optimize health and prevent the long-term consequences of diabetes. Much of diabetes care is focused around the identification and treatment of long-term diabetes-related complications and diabetes healthcare professionals are adept in managing microvascular and macrovascular conditions. An appreciation, however, of the psychological consequences of diabetes has lagged behind, despite these being common and the morbidity, mortality, and health costs associated with the co-morbidity being disproportionately increased compared with the effects of either condition alone (1, 2).

Several factors contribute to the poorer health outcomes seen in people with diabetes and mental disorders. Despite the increased burden of disease, people with co-morbid mental disorders have often been disadvantaged by health services and have received sub-optimal medical care (3). They have been less likely to receive the necessary diabetes processes of care, self-management education, and cardiovascular preventative medication despite increased visits to their primary healthcare teams and despite similar interest in caring for their physical illness as the general population (4). Clinicians may fail to recognize that those with mental illness are more likely to develop physical illnesses and so physical complaints are either ignored or not taken seriously. Mental health symptoms often “over-shadow” other complaints leading healthcare professionals to focus on the mental illness to the detriment of any physical illness (5). Health services are often poorly configured with clinics focusing on either the treatment of physical illnesses or mental disorders rather than treating both conditions at the same time (3). The stigma associated with mental illness may prevent people and their families from seeking help for mental illness, thereby depriving them of effective treatments, which not only harms mental well-being but is detrimental to diabetes management (6).

Diabetes and mental disorders are both common, and so a degree of co-occurrence would be expected purely by chance. The evidence suggests, however, that diabetes is more frequently associated with a range of mental and psychosocial disorders than expected (7, 8). Furthermore, several mental disorders, including depression, are associated with an increased risk of developing diabetes. An understanding of this complex interaction is crucial to the management and outcome of people with diabetes.

This chapter focuses on the co-morbidity of diabetes and depression; both are common, are relatively easy to diagnose, and have established effective treatments (8). They may also serve as an exemplar for other mental disorders and provide a model for the successful management of other co-morbid mental and physical health conditions. The chapter will describe the epidemiology of diabetes and depression and will discuss the mechanisms underlying the association between diabetes and depression. It will also highlight the clinical implications and consequences of co-occurring diabetes and depression. Diabetes healthcare professionals need to be aware of how to screen for depression and to provide “first response” management, while recognizing when to refer for specialist psychiatric care (9).

DEPRESSION

Depression belongs to a group of mental disorders where the primary abnormality is a disturbance of mood. The cardinal features of depression are low mood, and loss of interest or pleasure, lasting longer than two weeks. During a depressive episode, other symptoms may include poor concentration, feelings of excessive guilt or low self-worth, hopelessness about the future, thoughts about dying or suicide, disrupted sleep, changes in appetite or weight, and feeling especially tired or low in energy. People with depression are at an increased risk of suicide. Depressive symptoms exist on a continuum of severity, and it is important to recognize that depression is different from usual fluctuations in mood that occur with everyday life.

Major depressive disorder (also known as clinical depression, unipolar depression, or major depression) is defined by the diagnostic criteria of the American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders(DSM-5), based on the number and duration of symptoms (Table 1) (10). The DSM-5 definition approximates a level of severity of symptoms that is associated with both disability and dysfunction. DSM-5 also recognizes several sub-types of depressive disorder where the symptoms are less severe but nevertheless may still compromise diabetes self-care and outcomes.

Table 1. DSM-5 “Major” Depressive Episode
A. Five (or more) of the following symptoms have been present during the same 2-week period and represent a change from previous functioning; at least one of the symptoms is either (1) depressed mood, or (2) loss of interest or pleasure. • Depressed mood most of the day, nearly every day, as indicated by either subjective report (e.g. feels sad or empty) or observation made by others (e.g. appears tearful). • Markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day (as indicated by either subjective account or observation made by others). • Significant weight loss when not dieting or weight gain (e.g. a change of >5% of body weight in a month) or decrease or increase in appetite nearly every day. • Insomnia or hypersomnia nearly every day. • Psychomotor agitation or retardation nearly every day (observable by others, not merely subjective feelings of restlessness or being slowed down). • Fatigue or loss of energy nearly every day. • Feelings of worthlessness or excessive or inappropriate guilt (which may be delusional) nearly every day (not merely self-reproach or guilt about being sick). • Diminished ability to think or concentrate, or indecisiveness, nearly every day (either by subjective account or as observed by others). • Recurrent thoughts of death (not just fear of dying), recurrent suicidal ideation without a specific plan, or a suicide attempt or a specific plan for committing suicide.
B. B. The symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.
C. C. The symptoms are not due to the direct physiological effects of a substance (e.g. a drug of abuse, a medication) or a general medical condition (e.g. hypothyroidism).

Table 1. DSM-5 “Major” Depressive Episode

A. Five (or more) of the following symptoms have been present during the same 2-week period and represent a change from previous functioning; at least one of the symptoms is either (1) depressed mood, or (2) loss of interest or pleasure.

• Depressed mood most of the day, nearly every day, as indicated by either subjective report (e.g. feels sad or empty) or observation made by others (e.g. appears tearful).

• Markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day (as indicated by either subjective account or observation made by others).

• Significant weight loss when not dieting or weight gain (e.g. a change of >5% of body weight in a month) or decrease or increase in appetite nearly every day.

• Insomnia or hypersomnia nearly every day.

• Psychomotor agitation or retardation nearly every day (observable by others, not merely subjective feelings of restlessness or being slowed down).

• Fatigue or loss of energy nearly every day.

• Feelings of worthlessness or excessive or inappropriate guilt (which may be delusional) nearly every day (not merely self-reproach or guilt about being sick).

• Diminished ability to think or concentrate, or indecisiveness, nearly every day (either by subjective account or as observed by others).

• Recurrent thoughts of death (not just fear of dying), recurrent suicidal ideation without a specific plan, or a suicide attempt or a specific plan for committing suicide.

B. B. The symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.

C. C. The symptoms are not due to the direct physiological effects of a substance (e.g. a drug of abuse, a medication) or a general medical condition (e.g. hypothyroidism).

Epidemiology of Depression

Depression is one of the commonest mental disorders, affecting between 3–5% of the general population at any one time; the lifetime prevalence is 8-12% but there is considerable geographical variation ranging from 3% in Japan to 17% in India. The highest rates of depression are found in the United States of America (USA), the Middle East and South Asia (11). In 2019, 280 million people were living with depression, including 23 million children and adolescents (12). The incidence of depression worldwide increased by 50% between 1990 and 2017 to an age standardized rate of 3.25 per 1000 (13). Depressive disorders are now ranked as the single largest contributor to non-fatal health loss (7.5% of all years lost to disability) (14).

Depression can affect any age group, with depression being seen in infants as young as 6 months old after separation from their mothers (15). The commonest age of onset is between the ages of 30 and 40 years, but there is a second, smaller peak in incidence between ages 50 and 60 years (16). The risk of depression is doubled in women compared with men (17). Although the cause of depression remains uncertain, other risk factors for a depressive episode are recognized and include a family history of depression, certain personality types, childhood adversity, the postpartum period, social isolation, and a lack of close interpersonal relationships (18). An episode of depression is often triggered by a stressful life event, particularly for the first few depressive episodes (Table 2). Depression may accompany other mental illnesses and long-term physical conditions (19). All these risk factors apply to people living with diabetes and so consequently much of the depression seen in people living with diabetes is coincidental to the diabetes.

Table 2. Risk Factors for Depression
· Female gender · Age · Family History o Genetics o Shared Environment · Personality type o Introversion o Neuroticism § Insecure, worried § Obsessive o Unassertive, dependent o Low conscientiousness o Disorganization o Stress-sensitive · Childhood adversity o Separation o Neglect o Abuse § Mental § Physical § Sexual o Early bereavement o Unequal parental treatment of siblings · Life Events o Childbirth o Menopause o Rape or assault o Natural disasters o Job loss or unemployment o Stress o Financial difficulties o Bullying o Relationship or marriage breakdown o Bereavement o Catastrophic injury	· Mental illness o Schizophrenia o Drug or alcohol misuse · Physical illness o Infection § HIV o Nutritional deficiencies o Cardiovascular disease § Myocardial infarction § Stroke o Pernicious anemia o Neurological § Parkinsonism § Multiple sclerosis o Endocrine § Diabetes § Obesity § Hypoandrogenism § Cushing syndrome § Hypothyroidism § Hyperparathyroidism o Cancer o Arthritis o Chronic pain o Inflammation · Side effects of medication o β-blockers o α-interferon o Finasteride o Isotretinoin o Dopamine receptor agonists o Some anticonvulsants o Some antimigraine agents o Some antipsychotics

Table 2. Risk Factors for Depression

· Female gender

· Age

· Family History

o Genetics

o Shared Environment

· Personality type

o Introversion

o Neuroticism

§ Insecure, worried

§ Obsessive

o Unassertive, dependent

o Low conscientiousness

o Disorganization

o Stress-sensitive

· Childhood adversity

o Separation

o Neglect

o Abuse

§ Mental

§ Physical

§ Sexual

o Early bereavement

o Unequal parental treatment of siblings

· Life Events

o Childbirth

o Menopause

o Rape or assault

o Natural disasters

o Job loss or unemployment

o Stress

o Financial difficulties

o Bullying

o Relationship or marriage breakdown

o Bereavement

o Catastrophic injury

· Mental illness

o Schizophrenia

o Drug or alcohol misuse

· Physical illness

o Infection

§ HIV

o Nutritional deficiencies

o Cardiovascular disease

§ Myocardial infarction

§ Stroke

o Pernicious anemia

o Neurological

§ Parkinsonism

§ Multiple sclerosis

o Endocrine

§ Diabetes

§ Obesity

§ Hypoandrogenism

§ Cushing syndrome

§ Hypothyroidism

§ Hyperparathyroidism

o Cancer

o Arthritis

o Chronic pain

o Inflammation

· Side effects of medication

o β-blockers

o α-interferon

o Finasteride

o Isotretinoin

o Dopamine receptor agonists

o Some anticonvulsants

o Some antimigraine agents

o Some antipsychotics

DIABETES AND DEPRESSION

The association between diabetes and depression has been recognized for many years. In the 17^th century, Thomas Willis, an English physician, described how “diabetes is a consequence of prolonged sorrow” (20). Until the last two decades, the focus of any discussion of mood and diabetes was on the increased likelihood of depression in people with diabetes, where the comorbidity was viewed as an understandable reaction to the difficulties and challenges of living with a demanding and life-limiting long-term physical illness. In this regard, it was treated no differently from other long-term physical conditions that are also associated with increased rates of depression. We now understand that the relationship between the two conditions is more complex and, at least for type 2 diabetes, is bidirectional (8).

Understanding the scale of the co-morbidity is challenging because the epidemiological studies examining the relationship have been hampered by considerable variation in measurement, study design, and use of terminology that have contributed to significant heterogeneity and inconsistency between studies (8). An example of this variability is illustrated by one meta-analysis that reported a range of prevalence rates of depression in people with diabetes from 1.8% to 88% (21).

The gold standard for the diagnosis of depression is a diagnostic interview, but many studies have relied on self-rating scales (22). These scales identify depressive symptoms rather than depression and do not differentiate between symptoms that could be caused by either diabetes or depression, for example, fatigue or weight change. This can lead to significant overestimates of the prevalence of depression in those with diabetes, as shown in an early meta-analysis where the prevalence of depression in people with diabetes identified by diagnostic interview was 11.4% compared to 31.0% in studies using self-rating questionnaire (23). However, a more recent meta-analysis argued that the symptom overlap does not affect prevalence (21). Nevertheless, the authors argue that depression measures that focus on the cardinal symptoms of depression rather than overlapping symptoms may most accurately diagnose depression.

Studies have often used mixed populations of people with type 1 diabetes and type 2 diabetes. This distinction is important because people with type 2 diabetes are generally older, and depression prevalence varies with age (16).There are differences in the prevalence of diabetes-related complications and other comorbid conditions such as obesity and heart disease, which independently affect the likelihood of developing depression (24). The pathogenesis and etiology of the two main types of diabetes differ, which may affect the risk of depression in different ways (25). Finally, the burden of management differs between type 1 diabetes and type 2 diabetes.

Many studies have not taken broad population approaches but have concentrated on convenience samples, usually drawn from specialist diabetes clinics, where the participants may not reflect the wider population of people living with diabetes. This bias is illustrated in the meta-analysis by Farooqi et al which reported that the prevalence of depression in people with diabetes was 36% in studies carried out in specialist care compared to 12% in community or primary care settings (26). Biases may also occur where there are low or unknown response rates, because the presence of depressive symptoms may affect the willingness of an individual to participate.

A further confounding factor is the concept of diabetes distress which describes the emotional response to living with diabetes, including the demands of self-management, the threat of complications, the social impact of stigma and discrimination, and the financial costs of treatment (27). Diabetes distress can fluctuate over time and may peak during challenging periods such as soon after diagnosis, during major treatment changes, or during the development or worsening of long-term complications (Table 3). Diabetes distress is distinct from depression in its association with self-management and glycemic levels, but the two conditions may co-exist in about 5-15% of people with diabetes. By contrast depression occurs without distress in 5-10% of people while distress alone affects 20-30% (28). The importance of diabetes distress was first proposed in 1995, and it is likely that early studies of diabetes and depression were capturing distress as well as depression, thereby contributing to an overestimate of the prevalence of depression.

Table 3. Common Features of Diabetes Distress
• Feeling overwhelmed by the demands of living with diabetes • Feeling concerned about “failures” with diabetes management • Feeling powerless or hopeless • Worrying over the risk of low blood glucose or long-term complications • Feeling frustrated that diabetes cannot be predicted or controlled from one day to the next • Feeling frustrated with care givers • Feeling guilty when the diabetes management go ‘off track’.

Table 3. Common Features of Diabetes Distress

• Feeling overwhelmed by the demands of living with diabetes

• Feeling concerned about “failures” with diabetes management

• Feeling powerless or hopeless

• Worrying over the risk of low blood glucose or long-term complications

• Feeling frustrated that diabetes cannot be predicted or controlled from one day to the next

• Feeling frustrated with care givers

• Feeling guilty when the diabetes management go ‘off track’.

Despite these caveats, several meta-analyses have indicated that the prevalence of depression is approximately doubled in people with diabetes compared to the background population (23, 26), with the prevalence of depression similar between type 1 diabetes (22%) and type 2 diabetes (19%) (26). Although most studies come from Western Europe or North America, the increased rates of depression or depressive symptoms have been found across the world (29, 30), with the prevalence being higher in low- and middle-income countries (26). A meta-analysis of 248 observational studies including over 8 million people with type 2 diabetes found a global prevalence of depression of 28%, with the highest rates observed in Asia and Australia whilst the lowest rates were found in studies from Europe (31). Cohort studies have shown an increase in incident depression in people with diabetes; one meta-analysis of 11 studies involving approximately 50,000 people with type 2 diabetes but without depression at baseline reported that the incidence of depression was 24% higher in people with diabetes (32), while another meta-analysis of 13 studies found incident depression was increased by 15% in people with diabetes (33).

An increased prevalence of depression has also been found in children with diabetes. A meta-analysis of 109 studies involving over 50,000 children with diabetes estimated that the prevalence of depression was 22.2% among children with type 1 diabetes and 22.7% in children with type 2 diabetes (34). Consistent with studies in adults, the prevalence of depression was higher among girls than boys (29.7% vs. 19.7%) and in low- to- middle-income countries.

Type 2 diabetes is a common comorbidity in people with mental disorders, with a reported prevalence ranging from 5% to 22% depending on the specific psychiatric disorder. Overall, the prevalence of diabetes in people with depression is 9% but there is considerable heterogeneity between studies (35). Consistent with this finding, the incidence of diabetes in people with depression is increased by 18-60% (33, 36, 37). People with depression, however, may receive more screening for diabetes than those without because of their increased contact with healthcare professionals and an awareness of the risk of diabetes by mental health practitioners, which may lead to an overestimate of the difference in diabetes risk between those with and without depression, particularly in studies that rely on routinely collected healthcare data.

Diabetes Factors That Increase the Risk of Depression

Although many cases of depression are coincidental to the presence of diabetes, certain diabetes factors including diabetes-related complications and obesity are associated with an increased risk of depression (38).

DIABETES COMPLICATIONS

The development of macrovascular and microvascular complications increases the risk of depression in people with type 1 diabetes and type 2 diabetes (24, 39). Overall, the presence of diabetes complications increases the risk of incident depressive disorder by 14% but the increased risk of developing depression is 24% higher for microvascular complications compared with 9% higher for those with macrovascular complications (39). The risk of depression increases as more complications develop such that the presence of two or more complications more than doubled the risk of depression in people with type 2 diabetes in one specialized outpatient clinic, with neuropathy and nephropathy showing the strongest association (40).

DIABETES TREATMENTS

The use of insulin in type 2 diabetes is associated with higher rates of depression compared to non-insulin medications or dietary and lifestyle interventions alone. One meta-analysis of 28 studies reported an overall 59% higher risk of developing depression in people taking insulin and 42% higher risk when compared with oral anti-diabetes agents (41). It seems unlikely that insulin per se increases depressive symptoms, but insulin is associated with higher treatment demands that not only include self-injection but more intensive self-monitoring, which may adversely affect depressive symptoms (42). Insulin is also used in those with longer duration of type 2 diabetes, which may be associated with a higher prevalence of diabetes-related complications and elevated HbA_1c, a further risk factor of depression (43). Insulin has been used erroneously as a threat by healthcare professionals to encourage people to follow certain health behaviors or take medications. As type 2 diabetes is associated with progressive β-cell decline, many people ultimately need insulin. Where insulin has been used as a threat, commencing insulin can evoke feelings of guilt, blame or failure, which may increase the likelihood of depression. Furthermore, people may have strongly held beliefs about insulin usage, seeing it as an “end of the road” treatment. They may also associate insulin with the development of diabetes complications or death if they have seen a family member with diabetes developing complications while using insulin. Insulin therapy is associated with significant weight gain, again a risk factor for depression, and an increased risk of hypoglycemia. In a 10-year study of 3,742 people with type 1 diabetes requiring emergency room visit or hospitalization, those admitted with a hypoglycemic event were 74% more likely to develop depression (43).

Other anti-diabetes treatments, by contrast, may be associated with a reduced risk of depression and there has been discussion about whether these could be re-purposed as treatments for depression (44). A meta-analysis of current therapies indicated that pioglitazone was associated with improved depressive symptoms, more so in women, but metformin had no consistent benefit (44). A more recent systematic review, however, suggested that metformin might help treat comorbid depression, although the evidence was too weak to recommend its use for this indication (45). A review of observational studies also indicated that metformin was associated with reduced depressive symptoms (46). GLP-1 receptors are widely expressed in the brain and have putative neuroprotective properties. A meta-analysis of six studies including 2,071 participants showed a small but significant reduction in depressive symptoms in those treated with GLP-1 receptor agonists (47). Whether the improvement is a direct effect or mediated through weight loss is unknown. This observation was also seen in a large population-based cohort and nested case-control study that found that low doses of metformin, dipeptidyl peptidase-4 (DPP4) inhibitors, GLP-1 receptor agonists, and sodium-glucose transporter 2 (SGLT2) inhibitors were associated with lower risk of depression in people with diabetes compared to those using other treatments, with the lowest risk seen with SGLT2 inhibitors (48). Further studies of the impact of SGLT2 inhibitors are warranted as abnormal brain bioenergetic metabolism occurs in depression and endogenous ketones may exert a neuroprotective effect that might improve mood. As SGLT2 inhibitors induce ketogenesis, there is a rationale to test whether SGLT2 inhibitors improve depressive symptoms (49).

MECHANISMS TO EXPLAIN THE LINK BETWEEN DIABETES AND DEPRESSION

No one mechanism explains the association between diabetes and depression, but specific disease and treatment factors may account for why diabetes pre-disposes to depression and vice versa (Figure 1). These are, however, superimposed on other factors, such as genetics, early intra-uterine development, and social determinants of health, that create a “common soil” for both conditions.

Figure 1. The possible mechanisms that lead to the co-morbidity of diabetes and depression.

Underlying Factors That Predispose to Both Diabetes and Depression

GENETICS

Modern genetic technologies, such as genome-wide association (GWAS) studies and Mendelian randomization analyses have revolutionized our understanding of how genetics may underlie many polygenic mental and physical disorders and their association as well as health behavior traits, such as smoking and alcohol consumption that influence health. These studies have shown overlap of genetic polymorphisms that increase the risk of several mental disorders, including depression, and physical disorders, including diabetes, metabolic syndrome, and obesity (50). There are nearly 500 single nuclear polymorphisms that are associated with an increased risk of both diabetes and depression across a broad range of pathways that include immune function, lipid metabolism, cancer-related pathways, and cell signaling (51).

FETAL DEVELOPMENT

The ‘developmental origins of health and disease’ hypothesis emerged from epidemiological studies that found that infants with low birth weight had an increased risk of cardiovascular disease, diabetes, and other chronic conditions in adulthood (52, 53). Although the early studies focused on physical illness, the fetal environment is linked to psychiatric conditions, including depression, although the effect size is weak and inconsistent across studies (54).

The broad conditions in which people are born, live, learn, work, play, worship, and age affect a wide range of health, functioning, and quality-of-life outcomes and risks throughout the life course, which together are known as the ‘social determinants of health’ (55). These can be divided into macro-level factors, such as government policy, meso-level factors, such as neighborhood and workplace, and individual factors, such as health behaviors and are broadly grouped into five domains: economic stability, educational access and quality, health care access and quality, neighborhood and built environment, and social and community context, which include gender and race. These social factors are more robust predictors of population health than either the provision of healthcare services or individual health behaviors and explain up to 80% of a person’s health (56).

Many of the risk factors for depression described earlier in the chapter include or are affected by social factors, such as childhood adversity, low socio-economic status, or lived environment. Many of these same factors also affect the risk of diabetes. For example, access to recreational spaces, safe housing and surroundings, clean air, and shops that sell nutritious and wholesome foods provide an environment where an individual can more easily choose behaviors that would reduce the risk of diabetes.

Diabetes-Specific Factors

Both psychological and biological mechanisms contribute to the increased risk of depression in people with diabetes.

PSYCHOLOGIOCAL FACTORS

The psychological model proposes that depression is an understandable response to the difficulties of living with a demanding and life-shortening long-term physical illness that is associated with potentially debilitating complications. This model is supported by a systematic review of 11 studies that found no difference in the prevalence of depression between those with undiagnosed diabetes, those with impaired glucose metabolism, and people with normal glucose metabolism (57). By contrast, an increased prevalence of depression was only found in those with diagnosed diabetes suggesting that the knowledge of the diagnosis and the burden of managing the condition and its complications are associated with the development of depression. A more recent meta-analysis showed an 11% and 27% increased risk of depression in those with pre-diabetes and undiagnosed diabetes, respectively, compared with people with normal glucose metabolism but this was lower than the 80% increase in those with known diabetes (58). The increase was only seen in people aged less than 60 years old and was partially explained by the presence of comorbid cardiovascular disease. Since this publication, studies from Mexico (59), Germany (60) and rural China (61) did not find increased rates of depression in people with undiagnosed diabetes. However, a large study from the Netherlands found a similarly increased rate of depression in those with diagnosed and undiagnosed diabetes (62).

Although these findings generally support the psychological model, it is important to recognize that the people with undiagnosed diabetes differ from those with diagnosed diabetes by more than just the knowledge of their condition. For example, those with diagnosed diabetes are likely to have had diabetes for longer and have developed complications and other co-morbidities that may affect their risk of depression.

EFFECT OF DIABETES ON BRAIN STRUCTURE AND FUNCTION

It is well recognized that acute hyperglycemia and hypoglycemia can affect mood (63, 64). This is unsurprising because the brain is dependent on a continuous supply of glucose as its principal source of energy, and changes in blood glucose levels rapidly affect cerebral function. However, longer term effects of diabetes on brain structure and function have also been seen in animal models of diabetes and in humans. In animals, diabetes negatively affects hippocampal integrity and neurogenesis, both of which are areas that are important in cognition and mood (65). In adults with type 1 diabetes, magnetic resonance imaging (MRI) studies have shown hippocampal atrophy together with increased prefrontal glutamate-glutamine-gamma-aminobutyric acid (GABA) levels in a way that correlates with mild depressive symptoms (65, 66). In the brain, insulin stimulates glucose uptake, in part by increasing the synthesis of the glucose transporters in neurons and neuroglia (67). Consequently, abnormal insulin signaling in the brain could affect glucose transport across the blood-brain barrier leading to reduced neuronal glucose uptake and neuronal loss. As the amygdala and hippocampus are the regions that contain a high density of insulin receptors, they may be disproportionately affected by insulin resistance, which is independently associated with depression (68).

At a cellular level within the hippocampus, diabetes is associated with an increase in astrocytes and microglia reactivity and apoptosis of pyramidal neurons, and reduced neurogenesis and synaptic plasticity with dendritic retraction (69). In addition to the changes in GABA, there are other molecular changes, including increased glucocorticoid signaling, reduced brain-derived neurotrophic factor (BDNF) production, increased mGluR2/3 activity and caspase 3 activation, and an increase in the TLR4/NFκB signaling pathway, together with increased production of reactive oxygen species and pro-inflammatory cytokines, such as TNF-β. These changes lead to increased apoptosis and decreased progenitor proliferation, which in turn lead to a decrease in the hippocampal size.

Depression-Specific Factors

Depression may increase the risk of diabetes through health behaviors as well as the biological effects of depression and its treatment with antidepressants.

ADULT HEALTH BEHAVIORS

Health behaviors play an important role in determining an individual’s risk of developing diabetes.

Diet

A healthy diet protects against many long-term conditions including diabetes, obesity, and depression. Both epidemiological studies and intervention studies have shown how maintaining normal weight, reducing fat, particularly saturated fat, and increasing the fiber content of the diet reduces the risk of type 2 diabetes (70, 71). Certain dietary patterns, such as the Mediterranean diet, are associated with a lower risk of diabetes (72).

High levels of refined sugars and saturated fats may also increase the risk of depression, while a Mediterranean diet and diets that include more vegetables, fruits, fish, and whole grains seem to be protective (73). Once present, depression may entrench less prudent eating habits, creating a vicious cycle where poor diet and depression reinforce each other while simultaneously increasing the risk of diabetes. Depression increases the risk of obesity, with those with depression being 58% more likely to develop obesity than those without (74).

Excessive alcohol intake is associated with an increased risk of diabetes (75). Alcohol misuse is one of the most prevalent mental disorders, especially in more affluent countries (76). About a quarter of those with alcohol dependency have co-morbid mental disorders including depression, where alcohol is often used as a coping mechanism to manage stress, anxiety, or depressive symptoms.

Physical Activity

The health benefits of physical activity are overwhelming and include a lowered risk of type 2 diabetes and depression. There is a graded response with some physical activity being better than none, but further benefits accrue with more physical activity. Avoidance of sedentary behavior is also important for health. People with depression are less physically active than the general population; a meta-analysis of 24 studies including 2901 people with major depression disorder found that compared to the general population, those with depression spent less time engaged in overall and moderate to vigorous physical activity and were more likely to be sedentary. People with depression were 50% less likely to meet the recommended physical activity guidelines of taking at least 150 minutes of moderate-to-high intensity physical activity in a week through a variety of activities (77). Over two-thirds of people with depression do not reach this target (78).

Smoking

Tobacco use is the single most preventable cause of death and disease throughout the life-course and increases the risk of diabetes by 30-40% (79, 80). Smoking is one of the most important modifiable risk factors of physical morbidity and mortality in people with mental illness (81). Adults with depression are twice as likely to smoke as adults without depression. There also appears to be a bi-directional relationship where smoking increases the risk of depression while people with depression are more likely to start smoking (82).

Sleep

The health benefits of sleep include a lower risk of diabetes and maintenance of a healthy weight (83). Sleep problems are a cardinal feature of depression with difficulty falling asleep and waking during the night, being common symptoms of depression (10).

BIOLOGICAL EFFECTS OF DEPRESSION

Several biological changes occur during an episode of depression that might increase the risk of diabetes. First, acute episodes of depression are associated with hyperinsulinemia and insulin resistance and are unaffected by antidepressant treatment (68). Depression is also associated with a state of chronic inflammation that is characterized by increased C-reactive protein, TNF-α, and proinflammatory cytokines that might partially explain the change in insulin sensitivity. These proteins are linked to sickness behavior in animal models of depression and in humans are associated with an increase in type 2 diabetes and the metabolic syndrome (84, 85). Depression is further associated with abnormalities of hypothalamic-pituitary adrenal (HPA) axis function, which manifests as subclinical hypercortisolism, blunted diurnal cortisol rhythm, or hypocortisolism with impaired glucocorticoid sensitivity (86). Brain-derived neurotrophic factor (BDNF) is a neurotrophic factor expressed in several tissues, including the brain, gut, and pancreas. As described earlier, BDNF plays an important role in maintaining neuronal plasticity, including neurogenesis, synaptogenesis, and neuronal maturation. Depression decreases BDNF expression in the hippocampus and prefrontal cortex (87). Outside the brain, BDNF activation leads to reduced hepatic gluconeogenesis, increased hepatic insulin signal transduction, and protects against pancreatic β-cell loss. Serum BDNF concentrations are lower in people with diabetes (88).

ANTIDEPRESSANTS

Although essential components of the management of depression, it is possible that the use of antidepressants contribute to the risk of diabetes. Case reports, and observational studies have generally shown that people receiving antidepressant medications have a higher risk of diabetes but whether this relationship is causative remains unproven (89, 90). Randomized controlled trials have emphasized that antidepressants vary considerably in their association with weight gain and both hyperglycemia and hypoglycemic effects have been observed (89). Some antidepressants, including paroxetine, mirtazapine, and various tricyclic antidepressants are associated with significant weight gain which could increase the risk of diabetes in the long term. By contrast, buproprion is associated with weight loss (91).

CONSEQUENCES OF DIABETES AND DEPRESSION CO-MORBIDITY

The presence of depression in people with diabetes worsens both diabetes and depression outcomes (Figure 2).

Figure 2. The consequences of living with diabetes and depression.

Mortality

Mortality rates from physical illnesses, including cardiovascular disease, cancer, and diabetes, are higher in people with depression. Among people with diabetes, depression increases the risk of mortality by approximately 50% (92, 93). Where depression co-exists with anxiety, which is also more common in people with diabetes, mortality rates are further increased (94).

Depression Outcomes

Once depressive symptoms occur or a diagnosis of depression is made, the symptoms appear to be persistent and likely to recur in people with diabetes. A longitudinal study of 2,460 people with type 2 diabetes in a primary care setting found that 26% met the criterion for depression on at least one occasion, with incident depression occurring in 14% over a 3-year period (95). Recurrent or persistent depression occurred in two-thirds of those with baseline depression. In two other studies from the USA, self-reported depressive symptoms persisted in 73% of people 12 months after a diabetes education program (96) while major depressive disorder relapsed in 79% of people with diabetes over a 5-year period (97).

Depression is a major cause of excess hospitalization in people with diabetes and is the leading cause of psychiatric admissions in people with diabetes accounting for 6.1 admissions per 1,000 person years in people with type 1 diabetes and 7.05 admissions in people with type 2 diabetes in Australia, with higher admission rates for women (98). These rates are 2-3-fold higher than the general Australian population (99).

People with diabetes have an increased risk of completed suicide compared with the general population and are more likely to report suicidal ideation, one of the strongest predictors of completed suicide, and intentional self-harm (100). The risk of suicidal behavior is highest in young people with type 1 diabetes, in whom suicide may account for up to 7% of deaths. Suicidal ideation is also increased among adolescents and young adults with type 1 diabetes compared with the general population (15.0% vs. 9.4%) and is seen in all ethnic groups (101). It is likely, however, that the true incidence of suicidal attempts and completed suicides is considerably higher amongst people with diabetes because of ineffective identification and coding (100). Many hospital admissions for diabetes ketoacidosis or hypoglycemia of ‘unknown’ etiology result from insulin omission or overdose, but whether these are deliberate acts is frequently unrecognized or unrecorded. There is also anecdotal evidence that healthcare professionals are unwilling to record suicide as a cause of death because of the associated stigma. Suicide rates are higher in people with long-term health conditions than in people in the general population, but what makes diabetes stand out is access to insulin, providing a means for suicide either by omission or overdose, the latter of which is the commonest method of suicide in people with insulin-treated diabetes.

Diabetes Outcomes

ACUTE METABOLIC COMPLICATIONS

People with type 1 diabetes and depression have an increased risk of admission to hospital with diabetic ketoacidosis and severe hypoglycemia. In one study involving 3,742 people with type 1 diabetes who attended the emergency room or who were admitted to hospital between 1996 and 2015, those with depression had a 2.5-fold increased risk of severe hyperglycemia events and an 89% increased risk of severe hypoglycemia (43). The risk was greatest within the first 6 months following a diagnosis of depression, when the risk was 7.14-fold higher for hyperglycemia events and 5.58-fold higher for hypoglycemia.

MICROVASCULAR COMPLICATIONS

An early meta-analysis showed that the risk of microvascular complications was increased with small to moderate weighted effect sizes of 0.17 to 0.32 (24). The increased risk was similar in people with type 1 diabetes and people with type 2 diabetes while sexual dysfunction and painful peripheral neuropathy seemed to be associated with the highest risk. Most of these studies were cross-sectional but a more recent meta-analysis of 16 studies that examined the relationship between baseline depression and incident diabetes complications found that depression was associated with a 33% increased risk of incident microvascular disease (39). Most studies reported a composite of neuropathy, retinopathy, and nephropathy but one study reported nephropathy alone and found a 18% increase in incident chronic kidney disease (102). Depression is associated with a 68% increased risk of a first diabetes-related foot ulcer but not ulcer recurrence (103). This contrasted an earlier study that found a third of all individuals with diabetes-related foot ulcer had depression and that depression was associated with a threefold increased risk of dying (104).

MACROVASCULAR COMPLICATIONS

A recent meta-analysis has reported that incident macrovascular complications were increased by 38% in people with baseline depression (39). Most studies used a composite macrovascular outcome which included atherosclerotic vascular disease, myocardial infarction, and stroke as well as congestive heart failure and stroke. Some studies also included cardiovascular procedures, such as coronary artery bypass grafting or other revascularization techniques. Only one study reported separate outcomes for stroke (HR 1.22) and coronary heart disease (HR 1.32) (102).

QUALITY OF LIFE

Quality of life has been assessed by several different measures in people with diabetes and depression, including the Diabetes Specific Quality of Life scale and SF-36. These studies consistently show that quality of life is impaired in people with the co-morbidity (105). The effect of diabetes and depression appears to be additive across several domains with the exception of mental health where most of the effect stems from depression (106).

COST OF TREATMENT

The presence of depression among people with diabetes can substantially increase health care costs. An analysis of 147,095 adults living in the US found that depression and diabetes alone increased healthcare expenditure by $2,654 and $2,692, respectively, compared with neither condition but when both conditions occurred together, the cost was increased by $6,037 (107). Based on these figures, the estimated total cost of treating co-morbid diabetes and depression in the US was $77.6 billion per year. A more recent study found that total health costs increased from $11,550 for people with diabetes alone to $16,511 for people with diabetes and depression (108). This was in part driven by higher rates of hospitalization (26.1% vs 17.4%) and emergency room visits (55.3% vs 43.0%). Ironically, the increased cost occurred despite decreased healthcare utilization. In a US study of 22,642 people with diabetes enrolled in the 2019 Behavioral Risk Factor Surveillance System, those with a diagnosis of a depressive disorder were 82% more likely to report not seeing a doctor because of healthcare costs in the previous year (109).

DIABETES MANAGEMENT

Glycemic Levels

It has been hypothesized that changes in glycemic levels may mediate the association between depression and diabetes micro- and macrovascular complications and mortality. However, studies that have investigated this have produced inconsistent findings. An early meta-analysis reported a small to moderate association between depression and elevated HbA_1c for type 1 diabetes and type 2 diabetes, but included mainly cross-sectional studies that precluded an inference on temporality (110). A recent meta-analysis investigated the longitudinal association between self-reported depressive symptoms and HbA_1c. The six longitudinal studies had a combined sample size of 3,683 participants who were followed for a mean period of 37 months (range six months to five years). There was a small significant association between baseline depressive symptoms and subsequent HbA_1c levels (111). A further meta-analysis of 14 studies in children and adolescents with type 1 diabetes reported a correlation between depressive symptoms and HbA_1c(112). The timing of the diagnosis of diabetes and depression may also be important. In a study of 11,837 people with type 2 diabetes registered with the UK Biobank followed for a median of 6.9 years, those diagnosed with major depression decades prior to type 2 diabetes had lower HbA_1c over time compared to individuals without depression and those diagnosed closer to their diabetes diagnosis date (113). For individuals whose depression was diagnosed after diabetes, the time since the onset of depression also shaped the trajectory of HbA_1c, with the adverse effect of a diagnosis of depression on HbA_1cbeing greatest in those whose diagnosis occurred shortly after the onset of diabetes. Furthermore, the variability of HbA_1c within any individual was 16% higher in those with post-diabetes depression (113).

Diabetes Self-Management

Optimizing glucose levels is highly dependent on self-care activities that include regular glucose monitoring, taking medication as prescribed, and engaging in health behavior change to improve diet and physical activity. Depression compromises an individual’s ability to self-manage their diabetes. A meta-analysis of 47 studies reported that depression significantly reduced the likelihood of engaging in self-management behaviors, including missed medical appointments, less medication taking and glucose monitoring, and less foot care (114, 115). Similar to anti-diabetes medications, people with co-morbid depression are also less likely to take anti-hypertensive medications and lipid-lowering therapy (115). Depression is associated with a less nutritious diet that is characterized by lower consumption of fruit and vegetables and increased refined carbohydrates (116). Physical activity is reduced while smoking and alcohol consumption is increased (115). The effect of depression appears to be mediated through its adverse effects on self-efficacy and illness perception (115).

MANAGEMENT OF DIABETES AND DEPRESSION

Preventing Depression in People with Diabetes

The implication of the psychological model of depression in diabetes is that healthcare professionals could play an important role in moderating the psychological burden associated with diabetes by considering the way in which the diagnosis of diabetes is conveyed and the psychosocial support that is given through an individual’s journey with diabetes. Many people with diabetes experience stigma, some of which stem from their healthcare team. They report feelings of shame and blame because they are held responsible for developing overweight, obesity, or diabetes (117). However well-intentioned the healthcare professional is, it is clear that evoking these feelings is associated with worse clinical outcomes. By contrast, the use of person-centered, non-stigmatizing language can create a trusted and safe space for meaningful clinical discussion (118).

Several individual and group-based interventions with the aim of preventing the development of depressive symptoms have been trialed in people with diabetes. Of the twelve studies reported in a recent narrative review, half had a positive effect (119). Features associated with a reduction in the likelihood of developing depressive symptoms included diabetes self-management education and support, problem-solving and resilience-focused approaches, and emotion-targeted techniques.

Screening and Diagnosis of Depression

Given the importance of depression in people with diabetes and the availability of effective treatment, there is a strong rationale to screen for depression in people with diabetes (120), not least because depression is under-recognized in clinical practice. Primary care doctors do not diagnose and treat depression in 50–77% of cases (121, 122), while diabetologists only initiate antidepressant treatment in approximately one-third of their patients with clinical depression (123). Similarly diabetes nurses do not recognize depression and anxiety, missing 75-80% of those with the conditions (124).

A formal diagnosis of depression requires a validated interview method, such as the Mini International Neuropsychiatric Interview (MINI) or Composite International Diagnostic Interview (CIDI). No laboratory investigations are needed to diagnose depression, but it is prudent to rule out general medical conditions that may mimic the symptoms of a depressive episode. The diagnostic interviews are too labor-intensive to make them suitable for population screening or for screening in primary care or other clinical settings. However, numerous brief screening instruments or questionnaires that are simple to administer and have reasonable clinical specificity and sensitivity have been developed (Table 4). Not all screening questionnaires are appropriate because of the overlap of symptoms of depression and diabetes, including tiredness, lethargy, lack of energy, appetite changes, and sleeping difficulties. However, the Beck Depression Inventory (BDI), the Centre for Epidemiologic Studies Depression Scale (CED), the Patient Health Questionnaire (PHQ-9), and the Hospital Anxiety and Depression Scale (HADS) are all suitable for use in people with diabetes (22). Of these, the PHQ-9 is the best validated and most widely used in people with diabetes (125). It is also short, containing nine questions making it easy to administer in primary and secondary care settings. It has been suggested that the cut-off for major depression, which is ≥10 in primary care populations, should be increased by two points to ≥12 points in people with diabetes to help differentiate between diabetes-related symptoms and depressive symptoms (126).

Table 4. Reported sensitivity, specificity, positive and negative predictive value and reliability and validity in tools screening for depression in people with diabetes. Adapted from (22).
Tool	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	Reliability/ Validity (α)
CES.	60.0 – 100	86.7	28.6	97.0	0.80
PHQ-9	66.0 - 100	52.0 - 80.0	43.8 - 64.4	93.4 - 100	0.80 - 0.84
BDI	82.0 - 90.0	84.0 - 89.0	59.0 - 89.0	82.0 - 97.0
HADS	74.0 - 85.0	37.5 – 86.0	28.0 – 49.0	95.0 - 96.0	0.55 – 0.78

Sensitivity= Number of true positives (cases of depression)/Number of true positives + number of false negatives; Specificity = Number of true negatives/ Number of true negatives + false positives; Positive Predictive Value (PPV) = the proportion of cases with positive test results who are correctly diagnosed. Negative Predictive Value (NPV) = the proportion of cases with negative test results who are correctly diagnosed.

Another simple approach with good sensitivity and reasonable specificity is to ask two questions (127):

During the past month, have you been bothered by having little interest or pleasure in doing things?
During the past month, have you been bothered by feeling down, depressed, or hopeless?

If the answer to either is yes, and the person with diabetes wants helps with this problem, the healthcare professional should undertake a diagnostic interview and offer appropriate referral and treatment.

Although screening for depression is acceptable to people living with diabetes (128), its value has not been proven and remains controversial despite being recommended by several professional bodies, including the International Diabetes Federation (129), American Diabetes Association (130), and the UK National Institute for Health and Clinical Excellence (131). A 2008 Cochrane review reported that depression screening alone in the general population had little or no impact on the detection and management of depression (132). However, a more recent meta-analysis of depression screening interventions, many of which included additional components beyond screening, showed these were associated with less depression or depressive symptoms in the general population 6-12 months after screening (133). This issue is important because of the potential harms of screening, which include the stigma associated with depression, the risk of transient distress being labelled as having depression, and discrimination from insurance companies, and so studies demonstrating the effectiveness of screening in people with diabetes are needed.

Primary care depression screening in people with diabetes was introduced in the UK in 2006 as part of the Quality and Outcomes Framework (a performance management and payment scheme for NHS general practitioners) with mixed results. In one semi-rural general practice, 365 of 435 eligible people with diabetes or ischemia heart disease were screened, but only three people without a current diagnosis of depression screened positive and none were subsequently diagnosed with depression (134). By contrast, in a study of 112 general practices in Leeds, UK, the rates of diagnosis of depression increased from 21 to 94 per 100,000 population per month after introduction of the screening compared with 27 to 77 per 100,000 population per month in people without screening (135). Despite the increased diagnosis, after an initial increase in antidepressant treatment, screening had little impact on prescribing habits.

Two clinical trials of depression screening in people with diabetes have not demonstrated a benefit. In the first study from the Netherlands, written feedback was provided to both the person with diabetes and the doctor following depression screening, but this did not change use of mental health services or improve depression scores compared with routine care (136). The second study from the USA examined the benefits of training healthcare technicians about the importance of discussing mental health with their patients (137). Although there was an improvement in depressive symptoms, this was no different from the control group and all the participants continued to have moderate to severe depressive symptoms.

Several reasons may explain the lack of effectiveness of depression screening in people with diabetes including a low acceptance of screening and subsequent referral to further care by people with diabetes, failure to screen those at highest risk of depression, reluctance by healthcare professionals, and generally poor quality of depression care in primary care systems (138). While identification of those with depression is an essential first step in treatment, screening alone will not improve clinical outcomes unless linked to appropriate care pathways and treatment (120, 139). By contrast, studies of care pathways that have clearly linked screening to diagnosis and treatment improved depression outcomes (140, 141).

Treatment of Depression

The main aims of treatment are to improve both mental health and diabetes outcomes (Table 5). Ideally, any depression treatment for people with diabetes would simultaneously improve both sets of outcomes, but from a clinical perspective, the rapid improvement or remission of depression should be the first priority (138). This recommendation partly reflects the time course of treatment responses, which can be seen within 2–4 weeks for depression but also because treating the depression may aid optimal diabetes self-management.

Table 5. Aims of Depression Treatment in People with Diabetes
Mental health outcomes	Diabetes outcomes
Decreased depressive symptoms	Optimal diabetes self-management
Remission of depression	Decreased HbA_1c
Suicide prevention	Increased time in glucose range
Improved health-related quality of life	Less hypoglycemia
Restoration of psychosocial functioning	Reduced long-term complications
	Reduced mortality

Until relatively recently, people with diabetes have been under-represented in trials of depression treatment and so, there were few studies examining antidepressant and psychological treatment of depression. However, over the last two decades, the evidence base for treatment has grown substantially and has clearly indicated that treatment with either psychological therapies or antidepressant medication is effective (142) .

PSYCHOLOGICAL TREATMENT

Various psychological treatments, including cognitive behavioral therapy, problem-solving, and psychodynamic techniques have been used to treat depression in people with diabetes. Different members of the healthcare team have been utilized to deliver these interventions in primary and secondary care either in person or virtually through the internet or telephone (142, 143). The majority of trials have included people with type 2 diabetes with no trials conducted solely in people with type 1 diabetes.

A meta-analysis of psychological treatments, including group-based and online therapies, reported they were effective for the treatment of depression with large effect sizes (142). The follow-up ranged between 4 weeks and 1 year and thus, the longer term effects are unknown. Cognitive behavioral therapy is the most studied intervention, with its core components being cognitive restructuring, behavioral activation, and problem solving. This intervention was judged to be moderately effective in two recent meta-analyses (144, 145). Mindfulness also has an moderate benefit in treating depression (146), but there is mixed evidence on the benefit of motivational interviewing in reducing depressive symptoms (147, 148). Although psychological treatments are better than no treatment, the rates of recovery are low post-psychological intervention (17% vs 9% in controls) (149), indicating that many people will need additional support if they are to recover fully from their depression.

There is more debate about the effect of psychological interventions on diabetes outcomes (138) with one systematic review reporting a reduction in HbA_1c of ~0.6 % (6 mmol/mol) (150) while another only reporting a non-significant improvement in glycemic levels (151). A meta-analysis of cognitive behavioral therapy showed a statistically significant but clinically insignificant reduction in HbA_1cof 0.14% (1 mmol/mol). There was a greater effect on HbA_1c if the intervention was delivered in a group-based and face-to-face fashion and included psycho-education, behavioral, cognitive, goal-setting, and homework assignment strategies as central components (145).

One of the challenges in delivering psychological interventions is the lack of trained personnel, a situation which appears to be worsening, at least in the United Kingdom (152). To address this deficiency, interventions have been designed to be delivered online or using mobile technologies, a trend which has increased dramatically since the Covid-19 pandemic. This has the potential to increase accessibility to treatment while limiting costs (142). One meta-analysis reported large effect sizes on depressive symptoms for online therapy and a moderate effect for telephone interventions, although no change in diabetes outcomes was seen (142). The beneficial effect on depressive symptoms up to 12 months after the interventions was supported by another systematic review, albeit again without improvement in diabetes outcomes (153). However, this finding was contradicted by a recent meta-analysis of 24 randomized controlled trials, 14 non-randomized controlled trials and three observational studies which reported no significant effect on depression outcomes (154). The discrepancy may partly explained by drop-out rates which vary from 13% to 42%; for those who remain in treatment, the interventions appear effective (155) and so the challenge will be to deliver services that engage people with diabetes and depression.

In the United Kingdom in 2008, the National Health Service introduced the Improving Access to Psychological Therapies (now NHS Talking Therapies for anxiety and depression) program to improve the delivery of, and access to, psychological therapies for depression. By 2021/22, nearly 1.2 million people had accessed these services. Although the clinical workforce is appropriately trained and supervised, many practitioners do not have experience of the challenges of living with diabetes. To address this issue, the Southampton diabetes team has formed a partnership with the local NHS Talking Therapies service. A practitioner joins the multidisciplinary team in the young adult clinic once a fortnight, helping to engage the person with diabetes and facilitate referral and access to the service. There is also a wider benefit to the city as the NHS Talking Therapies team have become much more aware of the challenges of living with diabetes. Introducing this service led to reductions in depressive symptoms and diabetes distress and was well received by people with diabetes and staff alike (156).

ANTIDEPRESSANTS

Antidepressants have been used to treat depressive symptoms since the late 1950s. There are many different antidepressants, but these fall into five main categories:

Selective Serotonin Reuptake Inhibitors (SSRI)
Serotonin and Noradrenaline Reuptake Inhibitors (SNRI)
Noradrenaline and Specific Serotoninergic Antidepressants (NASSA)
Tricyclics (TCA)
Monoamine Oxidase Inhibitors (MAOI)

The discovery of the first clinically useful antidepressants paved the way for an understanding of the underlying biological or neuroanatomical basis for depression. The first antidepressant was the tricyclic antidepressant (TCA), imipramine. It was first synthesized in 1951 as a potential antipsychotic and derived from work on chlorpromazine, which had pronounced sedative and antihistamine effects (157). Although imipramine has no antipsychotic effect, it was found to possess antidepressant effects. Other TCAs, such as amitriptyline, were subsequently synthesized by modifying the structure of imipramine. Iproniazid, a monoamine oxidase inhibitor (MAOI), was the next antidepressant to be discovered; again, this drug was initially developed for a different purpose, the treatment of tuberculosis, before its antidepressant effect was recognized. MAOIs prevent the breakdown of monoamine neurotransmitters (e.g. noradrenaline, dopamine and serotonin) while TCAs block the uptake of serotonin and noradrenaline resulting in an elevation of the synaptic concentrations of these transmitters. An understanding of the pharmacology led to the hypothesis that depression was caused by low catecholamine levels in the central nervous system (158). Both TCA and MAOI affect the serotonin system and in 1967, Coppen proposed that this was a more important neurotransmitter in depression than noradrenaline (159). Fluoxetine was the first in the class of selective serotonin re-uptake inhibitors (SSRI) and was developed by design following a search for molecules that could selectively block the re-uptake of serotonin. A major advantage of this approach was that it minimized adverse effects such as cardiovascular toxicity and anticholinergic effects. First synthesized in 1972 and launched in 1987, fluoxetine became the most widely prescribed drug in North America by 1990 (157). Although better tolerated than earlier antidepressants, SSRI still caused side effects, including sexual dysfunction, appetite change, nausea and vomiting, irritability, anxiety, insomnia, and headaches. In an attempt to reduce these adverse effects, other antidepressant classes were developed, including serotonin and noradrenaline reuptake inhibitors (SNRI, e.g. venlafaxine) and noradrenaline and specific serotoninergic antidepressants (NASSA, e.g. mirtazapine).

Antidepressants reduce depressive symptoms in people with diabetes as well as the general population; however, there have been relatively few formal efficacy trials in people with diabetes and even these have been are limited to a small group of antidepressants, including fluoxetine, sertraline, paroxetine, citalopram, escitalopram, agomelatine, nortriptyline, and vortioxetine (138, 160). Furthermore, most studies are short-term and so the medium- and long-term sustainability of pharmacological interventions after treatment cessation is uncertain. A systematic review and meta-analysis suggested that all antidepressants have similarly large effect size on depression outcomes as long as adequate doses are used (151). However, a more recent network meta-analysis of 12 randomized controlled trials involving 792 participants reported that there may be a greater reduction in depressive symptoms with escitalopram and agomelatine (160). Vortioxetine was associated with the greatest reduction in HbA_1c with escitalopram, agomelatine, sertraline and fluoxetine also associated with a fall in HbA_1c. No antidepressant was found to disrupt glucose levels (160). These differences should be viewed with caution as the number of trials and participants for each drug is small. Further head-to-head randomized controlled trials would help us understand more about the relative benefits and safety of different antidepressants on depression and glucose metabolism.

Given the similar efficacy between antidepressants, the treatment of choice depends largely on the side-effect profile, individual preference, and response. SSRI are widely used as first-choice agents because they are less cardiotoxic than TCA and are safer in overdose. Some antidepressants, notably mirtazapine, paroxetine and some TCA, may cause undesirable weight gain (91) and should be used with caution in people with type 2 diabetes. By contrast, buproprion, which is available in the USA, is associated with weight loss and, unlike SSRIs, does not appear to worsen sexual function (161).

The aim of treatment is complete remission of depressive symptoms. Treatment should be maintained at an adequate dose for at least 4–6 months after remission of symptoms to reduce the risk of relapse and recurrence. Recovery from depression may lead to a change in the individual’s behavior and routine which may have an effect on diabetes self-management. For example, if appetite improves, insulin requirements may increase, while on the other hand, if the person becomes more active, they may decrease. An individual approach is therefore needed to support the person’s glycemic management. There are important drug–drug interactions between antidepressants and oral anti-diabetes agents through inhibition of the cytochrome P450 3A4 and 2C9 isoenzyme. For example, the use of fluoxetine may potentiate the effect of sulfonylureas precipitating hypoglycemia (84).

EXERCISE

Many depression guidelines recommend exercise and other aspects of a healthy lifestyle as an integral component of management. Coupled with the importance of exercise in glycemic management, interventions to increase physical activity have been trialed and shown to be effective in reducing depressive symptoms and improving glycemic measures (162).

PREVENTING SUICIDE

A detailed description of the many effective interventions to prevent suicide is beyond the scope of this article (163),however, it is important for diabetes healthcare professionals to understand how to identify those at risk, particularly given the high prevalence of suicidal ideation and acts and immediate availability of a means of suicide. It is crucial that suicide can be discussed with people with diabetes in a safe and non-judgmental way. Talking about suicide remains highly stigmatized and choosing to reveal suicidal ideation can be difficult. The isolation that suicidal people feel can be reinforced by a critical response from the healthcare team. A recent survey of diabetes healthcare professionals found that the vast majority of respondents believed it is their professional responsibility to ask about suicide and self-harm, with nearly half reporting that this should be addressed every visit (164). Around three-quarters reported feeling comfortable discussing these issues, but those who were more reluctant to do so were concerned about their lack of training and uncertainty about what to do if someone reported self-harming behavior. Once an individual has discussed suicidal intention, it is important that the person is supported and has access to mental healthcare and suicide prevention interventions.

ORGANIZATION OF CARE

A common model of care of depression is the Stepped Care Model which provides a framework in which service delivery is organized to help those with depression, their caregivers, and healthcare professionals identify and access the most effective interventions (Figure 3) (131). The model utilizes a sequenced treatment process depending on the severity of depressive symptoms and response to previous treatments. The model allows a rational approach to the treatment of depression, while reducing costs and side effects of antidepressant through more appropriate prescribing.

Figure 3. Stepped Care Model for management of depression (131).

The first step involves the recognition of depression through screening and diagnostic interview and is reserved for those with suspected depression. For those with mild depression, step 2 involves the use of guided self-help, computerized CBT, and brief psychological interventions which can be delivered by the primary healthcare team or psychologist. The third step, which is also delivered in primary care settings, is indicated for those who do not respond to step 2 interventions, or for those with moderate and severe depression. Treatments include medication, high-intensity psychological interventions, or combined treatment. Step 4 corresponds to severe or treatment-resistant depression; the interventions are similar to those used in step 3 but now involve the mental health team. The final step is for those with life-threatening depression and/or severe self-neglect. In addition to medication and high-intensity psychological interventions, electroconvulsive therapy may be required under the supervision of a mental health crisis services and involve hospitalization.

A meta-analysis of 18 randomized controlled trial of stepped care showed improvements in depressive symptoms and better remission rates (165). A significant benefit on quality of life was also observed. More people in the stepped care model were prescribed antidepressants.

The increasing fragmentation of medical services and super-specialization in modern medicine has resulted in clinicians focusing on the conditions with which they are most familiar and being unable or unwilling to recognize and treat comorbid illnesses when they occur (166). The need for integrated holistic healthcare has never been greater but many diabetes healthcare professionals feel ill-equipped to manage depression. To address this, a case management model known as collaborative care was developed in the U.S., that involves a multidisciplinary team working together to identify and treat depression within primary care settings. The prototype intervention led to improvements in depression symptoms but without change in glycemia (167). Subsequently, greater attention was paid to intervention strategies for diabetes, resulting in simultaneous improvements in glycemic and blood pressure management and improved depressive symptoms (140). In a meta-analysis of five studies from the U.S., collaborative care was shown to be a clinical- and cost-effective treatment of depression, with a moderate effect size for depression outcomes and a small effect size for glycemic levels (142, 168).

CONCLUSION

Diabetes and depression remain a considerable clinical challenge. While an awareness of this co-morbidity has increased in recent years, this has not necessarily translated into better care or outcomes. Effective treatments are available and these need to be made available to those with diabetes and depression in clear treatment pathways. There are grounds for considerable optimism as the scientific knowledge that underpins clinical practices has expanded markedly in the last two decades. However, further research is needed to understand what can be done to prevent depression in people with diabetes and to identify the optimal treatment for an individual that improves both depressive symptoms and diabetes outcomes.

REFERENCES

Katon WJ. Epidemiology and treatment of depression in patients with chronic medical illness. Dialogues Clin Neurosci. 2011;13(1):7-23.
Ciechanowski PS, Katon WJ, Russo JE. Depression and diabetes: impact of depressive symptoms on adherence, function, and costs. Arch Intern Med. 2000;160(21):3278-85.
Mitchell AJ, Malone D, Doebbeling CC. Quality of medical care for people with and without comorbid mental illness and substance misuse: systematic review of comparative studies. Br J Psychiatry. 2009;194(6):491-9.
Buhagiar K, Parsonage L, Osborn DP. Physical health behaviours and health locus of control in people with schizophrenia-spectrum disorder and bipolar disorder: a cross-sectional comparative study with people with non-psychotic mental illness. BMC Psychiatry. 2011;11:104.
Disability Rights Commission. Equal Treatment: Closing the gap. A formal investigation into physical Health inequalities experienced by people with learning difficulties and mental health problems. London: Disability Rights Commission; 2006.
Schomerus G, Angermeyer MC. Stigma and its impact on help-seeking for mental disorders: what do we know? Epidemiol Psichiatr Soc. 2008;17(1):31-7.
Holt RI, Mitchell AJ. Diabetes mellitus and severe mental illness: mechanisms and clinical implications. Nat Rev Endocrinol. 2015;11(2):79-89.
Holt RI, de Groot M, Golden SH. Diabetes and depression. Curr Diab Rep. 2014;14(6):491.
Royal College of Psychiatrists. Positive Cardiometabolic Health Resource: Don't just screen, intervene! 2014 [Available from: https://www.rcpsych.ac.uk/docs/default-source/improving-care/ccqi/national-clinical-audits/ncap-library/rcp17056-lester-uk-adaptation-4pp-a4-leaflet_4_updated.pdf?sfvrsn=7bc177e9_2.
American Psychiatric Association. Diagnostic and statistical manual of mental disorders. Arlington: American Psychiatric Association; 2013. 1-947 p.
Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, et al. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS Med. 2013;10(11):e1001547.
GBD Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022;9(2):137-50.
Liu Q, He H, Yang J, Feng X, Zhao F, Lyu J. Changes in the global burden of depression from 1990 to 2017: Findings from the Global Burden of Disease study. J Psychiatr Res. 2020;126:134-40.
World Health Organisation. Depression and Other Common Mental Disorders: Global Health Estimates. Geneva: World Health Organisation; 2017. 1-24 p.
Ayuso-Mateos JL, Vazquez-Barquero JL, Dowrick C, Lehtinen V, Dalgard OS, Casey P, et al. Depressive disorders in Europe: prevalence figures from the ODIN study. Br J Psychiatry. 2001;179:308-16.
Eaton WW, Anthony JC, Gallo J, Cai G, Tien A, Romanoski A, et al. Natural history of Diagnostic Interview Schedule/DSM-IV major depression. The Baltimore Epidemiologic Catchment Area follow-up. Arch Gen Psychiatry. 1997;54(11):993-9.
Ford DE, Erlinger TP. Depression and C-reactive protein in US adults: data from the Third National Health and Nutrition Examination Survey. Arch Intern Med. 2004;164(9):1010-4.
Ferenchick EK, Ramanuj P, Pincus HA. Depression in primary care: part 1-screening and diagnosis. BMJ. 2019;365:l794.
Holt RI, Phillips DI, Jameson KA, Cooper C, Dennison EM, Peveler RC. The relationship between depression and diabetes mellitus: findings from the Hertfordshire Cohort Study. Diabet Med. 2009;26(6):641-8.
Willis T. Pharmaceutice rationalis sive diabtriba de medicamentorum operantionibus in humano corpore. Oxford; 1675.
Harding KA, Pushpanathan ME, Whitworth SR, Nanthakumar S, Bucks RS, Skinner TC. Depression prevalence in Type 2 diabetes is not related to diabetes-depression symptom overlap but is related to symptom dimensions within patient self-report measures: a meta-analysis. Diabet Med. 2019;36(12):1600-11.
Roy T, Lloyd CE, Pouwer F, Holt RI, Sartorius N. Screening tools used for measuring depression among people with Type 1 and Type 2 diabetes: a systematic review. Diabet Med. 2012;29(2):164-75.
Anderson BJ, Edelstein S, Abramson NW, Katz LE, Yasuda PM, Lavietes SJ, et al. Depressive symptoms and quality of life in adolescents with type 2 diabetes: baseline data from the TODAY study. Diabetes Care. 2011;34(10):2205-7.
de Groot M, Anderson R, Freedland KE, Clouse RE, Lustman PJ. Association of depression and diabetes complications: a meta-analysis. Psychosom Med. 2001;63(4):619-30.
Mehdi S, Wani SUD, Krishna KL, Kinattingal N, Roohi TF. A review on linking stress, depression, and insulin resistance via low-grade chronic inflammation. Biochem Biophys Rep. 2023;36:101571.
Farooqi A, Gillies C, Sathanapally H, Abner S, Seidu S, Davies MJ, et al. A systematic review and meta-analysis to compare the prevalence of depression between people with and without Type 1 and Type 2 diabetes. Prim Care Diabetes. 2022;16(1):1-10.
Fisher L, Polonsky WH, Hessler D. Addressing diabetes distress in clinical care: a practical guide. Diabet Med. 2019;36(7):803-12.
Skinner TC, Joensen L, Parkin T. Twenty-five years of diabetes distress research. Diabet Med. 2020;37(3):393-400.
Mommersteeg PM, Herr R, Pouwer F, Holt RI, Loerbroks A. The association between diabetes and an episode of depressive symptoms in the 2002 World Health Survey: an analysis of 231,797 individuals from 47 countries. Diabet Med. 2013;30(6):e208-e14.
Hussain S, Habib A, Singh A, Akhtar M, Najmi AK. Prevalence of depression among type 2 diabetes mellitus patients in India: A meta-analysis. Psychiatry Res. 2018;270:264-73.
Khaledi M, Haghighatdoost F, Feizi A, Aminorroaya A. The prevalence of comorbid depression in patients with type 2 diabetes: an updated systematic review and meta-analysis on huge number of observational studies. Acta Diabetol. 2019;56(6):631-50.
Nouwen A, Winkley K, Twisk J, Lloyd CE, Peyrot M, Ismail K, et al. Type 2 diabetes mellitus as a risk factor for the onset of depression: a systematic review and meta-analysis. Diabetologia. 2010;53(12):2480-6.
Mezuk B, Eaton WW, Albrecht S, Golden SH. Depression and type 2 diabetes over the lifespan: a meta-analysis. Diabetes Care. 2008;31(12):2383-90.
Akbarizadeh M, Naderi Far M, Ghaljaei F. Prevalence of depression and anxiety among children with type 1 and type 2 diabetes: a systematic review and meta-analysis. World J Pediatr. 2022;18(1):16-26.
Lindekilde N, Scheuer SH, Rutters F, Knudsen L, Lasgaard M, Rubin KH, et al. Prevalence of type 2 diabetes in psychiatric disorders: an umbrella review with meta-analysis of 245 observational studies from 32 systematic reviews. Diabetologia. 2022;65(3):440-56.
Yu M, Zhang X, Lu F, Fang L. Depression and Risk for Diabetes: A Meta-Analysis. Can J Diabetes. 2015;39(4):266-72.
Graham EA, Deschenes SS, Khalil MN, Danna S, Filion KB, Schmitz N. Measures of depression and risk of type 2 diabetes: A systematic review and meta-analysis. J Affect Disord. 2020;265:224-32.
Busili A, Kumar K, Kudrna L, Busaily I. The risk factors for mental health disorders in patients with type 2 diabetes: An umbrella review of systematic reviews with and without meta-analysis. Heliyon. 2024;10(7):e28782.
Nouwen A, Adriaanse MC, van Dam K, Iversen MM, Viechtbauer W, Peyrot M, et al. Longitudinal associations between depression and diabetes complications: a systematic review and meta-analysis. Diabet Med. 2019;36(12):1562-72.
van Steenbergen-Weijenburg KM, van Puffelen AL, Horn EK, Nuyen J, van Dam PS, van Benthem TB, et al. More co-morbid depression in patients with Type 2 diabetes with multiple complications. An observational study at a specialized outpatient clinic. Diabet Med. 2011;28(1):86-9.
Bai X, Liu Z, Li Z, Yan D. The association between insulin therapy and depression in patients with type 2 diabetes mellitus: a meta-analysis. BMJ Open. 2018;8(11):e020062.
Li C, Ford ES, Strine TW, Mokdad AH. Prevalence of depression among U.S. adults with diabetes: findings from the 2006 behavioral risk factor surveillance system. Diabetes Care. 2008;31(1):105-7.
Gilsanz P, Karter AJ, Beeri MS, Quesenberry CP, Jr., Whitmer RA. The Bidirectional Association Between Depression and Severe Hypoglycemic and Hyperglycemic Events in Type 1 Diabetes. Diabetes Care. 2018;41(3):446-52.
Moulton CD, Hopkins CWP, Ismail K, Stahl D. Repositioning of diabetes treatments for depressive symptoms: A systematic review and meta-analysis of clinical trials. Psychoneuroendocrinology. 2018;94:91-103.
Hamal C, Velugoti L, Tabowei G, Gaddipati GN, Mukhtar M, Alzubaidee MJ, et al. Metformin for the Improvement of Comorbid Depression Symptoms in Diabetic Patients: A Systematic Review. Cureus. 2022;14(8):e28609.
Zhang Y, Chan VK, Chan SSM, Chan EWY, Lee CH, Wong IC, et al. Effect of metformin on the risk of depression: A systematic review and meta-regression of observational studies. Asian J Psychiatr. 2024;92:103894.
Chen X, Zhao P, Wang W, Guo L, Pan Q. The Antidepressant Effects of GLP-1 Receptor Agonists: A Systematic Review and Meta-Analysis. Am J Geriatr Psychiatry. 2024;32(1):117-27.
Wium-Andersen IK, Osler M, Jorgensen MB, Rungby J, Wium-Andersen MK. Diabetes, antidiabetic medications and risk of depression - A population-based cohort and nested case-control study. Psychoneuroendocrinology. 2022;140:105715.
Liebers DT, Ebina W, Iosifescu DV. Sodium-Glucose Cotransporter-2 Inhibitors in Depression. Harv Rev Psychiatry. 2023;31(4):214-21.
Postolache TT, Del Bosque-Plata L, Jabbour S, Vergare M, Wu R, Gragnoli C. Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome. Am J Med Genet B Neuropsychiatr Genet. 2019;180(3):186-203.
Ji HF, Zhuang QS, Shen L. Genetic overlap between type 2 diabetes and major depressive disorder identified by bioinformatics analysis. Oncotarget. 2016;7(14):17410-4.
Barker DJ. The Wellcome Foundation Lecture, 1994. The fetal origins of adult disease. Proc Biol Sci. 1995;262(1363):37-43.
Barker DJ. Fetal origins of coronary heart disease. BMJ. 1995;311(6998):171-4.
Schlotz W, Phillips DI. Fetal origins of mental health: evidence and mechanisms. Brain Behav Immun. 2009;23(7):905-16.
Marmot M, Friel S, Bell R, Houweling TA, Taylor S, Commission on Social Determinants of H. Closing the gap in a generation: health equity through action on the social determinants of health. Lancet. 2008;372(9650):1661-9.
Hood CM, Gennuso KP, Swain GR, Catlin BB. County Health Rankings: Relationships Between Determinant Factors and Health Outcomes. Am J Prev Med. 2016;50(2):129-35.
Nouwen A, Nefs G, Caramlau I, Connock M, Winkley K, Lloyd CE, et al. Prevalence of depression in individuals with impaired glucose metabolism or undiagnosed diabetes: a systematic review and meta-analysis of the European Depression in Diabetes (EDID) Research Consortium. Diabetes Care. 2011;34(3):752-62.
Chen S, Zhang Q, Dai G, Hu J, Zhu C, Su L, et al. Association of depression with pre-diabetes, undiagnosed diabetes, and previously diagnosed diabetes: a meta-analysis. Endocrine. 2016;53(1):35-46.
Olvera RL, Fisher-Hoch SP, Williamson DE, Vatcheva KP, McCormick JB. Depression in Mexican Americans with diagnosed and undiagnosed diabetes. Psychol Med. 2016;46(3):637-46.
Weikert B, Buttery AK, Heidemann C, Rieckmann N, Paprott R, Maske UE, et al. Glycaemic status and depressive symptoms among adults in Germany: results from the German Health Interview and Examination Survey for Adults (DEGS1). Diabet Med. 2018;35(11):1552-61.
Li Z, Guo X, Jiang H, Sun G, Sun Y, Abraham MR. Diagnosed but Not Undiagnosed Diabetes Is Associated with Depression in Rural Areas. Int J Environ Res Public Health. 2016;13(11).
Meurs M, Roest AM, Wolffenbuttel BH, Stolk RP, de Jonge P, Rosmalen JG. Association of Depressive and Anxiety Disorders With Diagnosed Versus Undiagnosed Diabetes: An Epidemiological Study of 90,686 Participants. Psychosom Med. 2016;78(2):233-41.
Sommerfield AJ, Deary IJ, Frier BM. Acute hyperglycemia alters mood state and impairs cognitive performance in people with type 2 diabetes. Diabetes Care. 2004;27(10):2335-40.
Hermanns N, Scheff C, Kulzer B, Weyers P, Pauli P, Kubiak T, et al. Association of glucose levels and glucose variability with mood in type 1 diabetic patients. Diabetologia. 2007;50(5):930-3.
Ho N, Sommers MS, Lucki I. Effects of diabetes on hippocampal neurogenesis: links to cognition and depression. Neurosci Biobehav Rev. 2013;37(8):1346-62.
Lyoo IK, Yoon S, Jacobson AM, Hwang J, Musen G, Kim JE, et al. Prefrontal cortical deficits in type 1 diabetes mellitus: brain correlates of comorbid depression. ArchGenPsychiatry. 2012;69(12):1267-76.
Leonard BE, Wegener G. Inflammation, insulin resistance and neuroprogression in depression. Acta Neuropsychiatr. 2020;32(1):1-9.
Fernandes BS, Salagre E, Enduru N, Grande I, Vieta E, Zhao Z. Insulin resistance in depression: A large meta-analysis of metabolic parameters and variation. Neurosci Biobehav Rev. 2022;139:104758.
Mazala-de-Oliveira T, Silva BT, Campello-Costa P, Carvalho VF. The Role of the Adrenal-Gut-Brain Axis on Comorbid Depressive Disorder Development in Diabetes. Biomolecules. 2023;13(10).
Crandall JP, Knowler WC, Kahn SE, Marrero D, Florez JC, Bray GA, et al. The prevention of type 2 diabetes. Nat Clin Pract Endocrinol Metab. 2008;4(7):382-93.
Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393-403.
Dyson PA, Twenefour D, Breen C, Duncan A, Elvin E, Goff L, et al. Diabetes UK evidence-based nutrition guidelines for the prevention and management of diabetes. Diabet Med. 2018;35(5):541-7.
Shafiei F, Salari-Moghaddam A, Larijani B, Esmaillzadeh A. Adherence to the Mediterranean diet and risk of depression: a systematic review and updated meta-analysis of observational studies. Nutr Rev. 2019;77(4):230-9.
Luppino FS, de Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BW, et al. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry. 2010;67(3):220-9.
Knott C, Bell S, Britton A. Alcohol Consumption and the Risk of Type 2 Diabetes: A Systematic Review and Dose-Response Meta-analysis of More Than 1.9 Million Individuals From 38 Observational Studies. Diabetes Care. 2015;38(9):1804-12.
Carvalho AF, Heilig M, Perez A, Probst C, Rehm J. Alcohol use disorders. Lancet. 2019;394(10200):781-92.
King AC, Whitt-Glover MC, Marquez DX, Buman MP, Napolitano MA, Jakicic J, et al. Physical Activity Promotion: Highlights from the 2018 Physical Activity Guidelines Advisory Committee Systematic Review. Med Sci Sports Exerc. 2019;51(6):1340-53.
Schuch F, Vancampfort D, Firth J, Rosenbaum S, Ward P, Reichert T, et al. Physical activity and sedentary behavior in people with major depressive disorder: A systematic review and meta-analysis. J Affect Disord. 2017;210:139-50.
World Health Organisation. Effects of tobacco on health 2016 [Available from: https://www.who.int/europe/news-room/fact-sheets/item/effects-of-tobacco-on-health.
Pan A, Wang Y, Talaei M, Hu FB, Wu T. Relation of active, passive, and quitting smoking with incident type 2 diabetes: a systematic review and meta-analysis. Lancet Diabetes Endocrinol. 2015;3(12):958-67.
Tam J, Warner KE, Meza R. Smoking and the Reduced Life Expectancy of Individuals With Serious Mental Illness. Am J Prev Med. 2016;51(6):958-66.
Fluharty M, Taylor AE, Grabski M, Munafo MR. The Association of Cigarette Smoking With Depression and Anxiety: A Systematic Review. Nicotine Tob Res. 2017;19(1):3-13.
Cappuccio FP, D'Elia L, Strazzullo P, Miller MA. Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies. Sleep. 2010;33(5):585-92.
Musselman DL, Betan E, Larsen H, Phillips LS. Relationship of depression to diabetes types 1 and 2: epidemiology, biology, and treatment. Biol Psychiatry. 2003;54(3):317-29.
Dantzer R, O'Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci. 2008;9(1):46-56.
Champaneri S, Wand GS, Malhotra SS, Casagrande SS, Golden SH. Biological basis of depression in adults with diabetes. Curr Diab Rep. 2010;10(6):396-405.
Duman RS, Deyama S, Fogaca MV. Role of BDNF in the pathophysiology and treatment of depression: Activity-dependent effects distinguish rapid-acting antidepressants. Eur J Neurosci. 2021;53(1):126-39.
Moosaie F, Mohammadi S, Saghazadeh A, Dehghani Firouzabadi F, Rezaei N. Brain-derived neurotrophic factor in diabetes mellitus: A systematic review and meta-analysis. PLoS One. 2023;18(2):e0268816.
Barnard K, Peveler RC, Holt RI. Antidepressant medication as a risk factor for type 2 diabetes and impaired glucose regulation: systematic review. Diabetes Care. 2013;36(10):3337-45.
Greene CRL, Ward-Penny H, Ioannou MF, Wild SH, Wu H, Smith DJ, et al. Antidepressant and antipsychotic drug prescribing and diabetes outcomes: A systematic review of observational studies. Diabetes Res Clin Pract. 2023;199:110649.
Serretti A, Mandelli L. Antidepressants and body weight: a comprehensive review and meta-analysis. J Clin Psychiatry. 2010;71(10):1259-72.
Park M, Katon WJ, Wolf FM. Depression and risk of mortality in individuals with diabetes: a meta-analysis and systematic review. Gen Hosp Psychiatry. 2013;35(3):217-25.
van Dooren FE, Nefs G, Schram MT, Verhey FR, Denollet J, Pouwer F. Depression and risk of mortality in people with diabetes mellitus: a systematic review and meta-analysis. PLoS One. 2013;8(3):e57058.
Meier SM, Mattheisen M, Mors O, Mortensen PB, Laursen TM, Penninx BW. Increased mortality among people with anxiety disorders: total population study. Br J Psychiatry. 2016;209(3):216-21.
Nefs G, Pouwer F, Denollet J, Pop V. The course of depressive symptoms in primary care patients with type 2 diabetes: results from the Diabetes, Depression, Type D Personality Zuidoost-Brabant (DiaDDZoB) Study. Diabetologia. 2012;55(3):608-16.
Peyrot M, Rubin RR. Persistence of depressive symptoms in diabetic adults. Diabetes Care. 1999;22(3):448-52.
Lustman PJ, Griffith LS, Clouse RE. Depression in adults with diabetes. Results of 5-yr follow-up study. Diabetes Care. 1988;11(8):605-12.
Tomic D, Morton JI, Salim A, Lambert T, Magliano DJ, Shaw JE. Hospitalisation for mental health disorders in Australians with type 1 or type 2 diabetes. Diabetes Res Clin Pract. 2023;196:110244.
Draper B, Low LF. Patterns of hospitalisation for depressive and anxiety disorders across the lifespan in Australia. J Affect Disord. 2009;113(1-2):195-200.
Barnard-Kelly KD, Naranjo D, Majidi S, Akturk HK, Breton M, Courtet P, et al. Suicide and Self-inflicted Injury in Diabetes: A Balancing Act. J Diabetes Sci Technol. 2020;14(6):1010-6.
Majidi S, O'Donnell HK, Stanek K, Youngkin E, Gomer T, Driscoll KA. Suicide Risk Assessment in Youth and Young Adults With Type 1 Diabetes. Diabetes Care. 2020;43(2):343-8.
Novak M, Mucsi I, Rhee CM, Streja E, Lu JL, Kalantar-Zadeh K, et al. Increased Risk of Incident Chronic Kidney Disease, Cardiovascular Disease, and Mortality in Patients With Diabetes With Comorbid Depression. Diabetes Care. 2016;39(11):1940-7.
Westby M, Norman G, Vedhara K, Game F, Cullum N. Psychosocial and behavioural prognostic factors for diabetic foot ulcer development and healing: a systematic review. Diabet Med. 2020;37(8):1244-55.
Ismail K, Winkley K, Stahl D, Chalder T, Edmonds M. A cohort study of people with diabetes and their first foot ulcer: the role of depression on mortality. Diabetes Care. 2007;30(6):1473-9.
Jing X, Chen J, Dong Y, Han D, Zhao H, Wang X, et al. Related factors of quality of life of type 2 diabetes patients: a systematic review and meta-analysis. Health Qual Life Outcomes. 2018;16(1):189.
Goldney RD, Phillips PJ, Fisher LJ, Wilson DH. Diabetes, depression, and quality of life: a population study. Diabetes Care. 2004;27(5):1066-70.
Egede LE, Bishu KG, Walker RJ, Dismuke CE. Impact of diagnosed depression on healthcare costs in adults with and without diabetes: United States, 2004-2011. J Affect Disord. 2016;195:119-26.
Kangethe A, Lawrence DF, Touya M, Chrones L, Polson M, Evangelatos T. Incremental burden of comorbid major depressive disorder in patients with type 2 diabetes or cardiovascular disease: a retrospective claims analysis. BMC Health Serv Res. 2021;21(1):778.
McClintock HF, Edmonds SE, Bogner HR. Depression and Cost-Related Health Care Utilization Among Persons with Diabetes. Popul Health Manag. 2023;26(4):232-8.
Lustman PJ, Anderson RJ, Freedland KE, de GM, Carney RM, Clouse RE. Depression and poor glycemic control: a meta-analytic review of the literature. Diabetes Care. 2000;23(7):934-42.
Beran M, Muzambi R, Geraets A, Albertorio-Diaz JR, Adriaanse MC, Iversen MM, et al. The bidirectional longitudinal association between depressive symptoms and HbA(1c) : A systematic review and meta-analysis. Diabet Med. 2022;39(2):e14671.
Buchberger B, Huppertz H, Krabbe L, Lux B, Mattivi JT, Siafarikas A. Symptoms of depression and anxiety in youth with type 1 diabetes: A systematic review and meta-analysis. Psychoneuroendocrinology. 2016;70:70-84.
Gillett AC, Hagenaars SP, Handley D, Casanova F, Young KG, Green H, et al. The impact of major depressive disorder on glycaemic control in type 2 diabetes: a longitudinal cohort study using UK Biobank primary care records. BMC Med. 2024;22(1):211.
Gonzalez JS, Peyrot M, McCarl LA, Collins EM, Serpa L, Mimiaga MJ, et al. Depression and diabetes treatment nonadherence: a meta-analysis. Diabetes Care. 2008;31(12):2398-403.
Derese A, Gebreegzhiabhere Y, Medhin G, Sirgu S, Hanlon C. Impact of depression on self-efficacy, illness perceptions and self-management among people with type 2 diabetes: A systematic review of longitudinal studies. PLoS One. 2024;19(5):e0302635.
Sumlin LL, Garcia TJ, Brown SA, Winter MA, Garcia AA, Brown A, et al. Depression and adherence to lifestyle changes in type 2 diabetes: a systematic review. Diabetes Educ. 2014;40(6):731-44.
Speight J, Holmes-Truscott E, Garza M, Scibilia R, Wagner S, Kato A, et al. Bringing an end to diabetes stigma and discrimination: an international consensus statement on evidence and recommendations. Lancet Diabetes Endocrinol. 2024;12(1):61-82.
Holt RIG, Speight J. The language of diabetes: the good, the bad and the ugly. Diabet Med. 2017;34(11):1495-7.
Guerin E, Jaafar H, Amrani L, Prud'homme D, Aguer C. Intervention Strategies for Prevention of Comorbid Depression Among Individuals With Type 2 Diabetes: A Scoping Review. Front Public Health. 2019;7:35.
Holt RI, van der Feltz-Cornelis CM. Key concepts in screening for depression in people with diabetes. J Affect Disord. 2012;142 Suppl:S72-S9.
Mitchell AJ, Vaze A, Rao S. Clinical diagnosis of depression in primary care: a meta-analysis. Lancet. 2009;374(9690):609-19.
Mitchell AJ, Rao S, Vaze A. Can general practitioners identify people with distress and mild depression? A meta-analysis of clinical accuracy. J Affect Disord. 2011;130(1-2):26-36.
Lustman PJ, Harper GW. Nonpsychiatric physicians' identification and treatment of depression in patients with diabetes. Compr Psychiatry. 1987;28(1):22-7.
Pouwer F, Beekman AT, Lubach C, Snoek FJ. Nurses' recognition and registration of depression, anxiety and diabetes-specific emotional problems in outpatients with diabetes mellitus. Patient Educ Couns. 2006;60(2):235-40.
Kroenke K, Spitzer RL, Williams JB, Lowe B. The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review. Gen Hosp Psychiatry. 2010;32(4):345-59.
van Steenbergen-Weijenburg KM, de Vroege L, Ploeger RR, Brals JW, Vloedbeld MG, Veneman TF, et al. Validation of the PHQ-9 as a screening instrument for depression in diabetes patients in specialized outpatient clinics. BMC Health Serv Res. 2010;10:235.
Whooley MA, Avins AL, Miranda J, Browner WS. Case-finding instruments for depression. Two questions are as good as many. J Gen Intern Med. 1997;12(7):439-45.
Lloyd CE, Dyer PH, Barnett AH. Prevalence of symptoms of depression and anxiety in a diabetes clinic population. Diabet Med. 2000;17(3):198-202.
International Diabetes Federation Guideline Development Group. Global guideline for type 2 diabetes. Diabetes Res Clin Pract. 2014;104(1):1-52.
American Diabetes Association Professional Practice C. 4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Care in Diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S52-S76.
National Collaborating Centre for Mental Health. Depression in adults with a chronic physical health problem CG91. London: The British Psychological Society and The Royal College of Psychiatrists; 2010.
Gilbody S, Sheldon T, House A. Screening and case-finding instruments for depression: a meta-analysis. CMAJ. 2008;178(8):997-1003.
O'Connor EA, Perdue LA, Coppola EL, Henninger ML, Thomas RG, Gaynes BN. Depression and Suicide Risk Screening: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2023;329(23):2068-85.
Subramanian DN, Hopayian K. An audit of the first year of screening for depression in patients with diabetes and ischaemic heart disease under the Quality and Outcomes Framework. Qual Prim Care. 2008;16(5):341-4.
McLintock K, Russell AM, Alderson SL, West R, House A, Westerman K, et al. The effects of financial incentives for case finding for depression in patients with diabetes and coronary heart disease: interrupted time series analysis. BMJ Open. 2014;4(8):e005178.
Pouwer F, Tack CJ, Geelhoed-Duijvestijn PH, Bazelmans E, Beekman AT, Heine RJ, et al. Limited effect of screening for depression with written feedback in outpatients with diabetes mellitus: a randomised controlled trial. Diabetologia. 2011;54(4):741-8.
Scollan-Koliopoulos M, Herrera I, Romano K, Gregory C, Rapp K, Bleich D. Healthcare technician delivered screening of adults with diabetes to improve primary care provider recognition of depression. J Family Med Prim Care. 2012;1(2):97-102.
Petrak F, Baumeister H, Skinner TC, Brown A, Holt RI. Depression and diabetes: treatment and health-care delivery. Lancet Diabetes Endocrinol. 2015;3(6):472-85.
Hermanns N, Caputo S, Dzida G, Khunti K, Meneghini LF, Snoek F. Screening, evaluation and management of depression in people with diabetes in primary care. Prim Care Diabetes. 2013;7(1):1-10.
Katon WJ, Lin EH, Von KM, Ciechanowski P, Ludman EJ, Young B, et al. Collaborative care for patients with depression and chronic illnesses. N Engl J Med. 2010;363(27):2611-20.
Ell K, Katon W, Xie B, Lee PJ, Kapetanovic S, Guterman J, et al. Collaborative care management of major depression among low-income, predominantly Hispanic subjects with diabetes: a randomized controlled trial. Diabetes Care. 2010;33(4):706-13.
van der Feltz-Cornelis C, Allen SF, Holt RIG, Roberts R, Nouwen A, Sartorius N. Treatment for comorbid depressive disorder or subthreshold depression in diabetes mellitus: Systematic review and meta-analysis. Brain Behav. 2021;11(2):e01981.
van Bastelaar KM, Pouwer F, Cuijpers P, Riper H, Snoek FJ. Web-based depression treatment for type 1 and type 2 diabetic patients: a randomized, controlled trial. Diabetes Care. 2011;34(2):320-5.
An Q, Yu Z, Sun F, Chen J, Zhang A. The Effectiveness of Cognitive Behavioral Therapy for Depression Among Individuals with Diabetes: a Systematic Review and Meta-Analysis. Curr Diab Rep. 2023;23(9):245-52.
Li Y, Storch EA, Ferguson S, Li L, Buys N, Sun J. The efficacy of cognitive behavioral therapy-based intervention on patients with diabetes: A meta-analysis. Diabetes Res Clin Pract. 2022;189:109965.
Ni YX, Ma L, Li JP. Effects of mindfulness-based intervention on glycemic control and psychological outcomes in people with diabetes: A systematic review and meta-analysis. J Diabetes Investig. 2021;12(6):1092-103.
Berhe KK, Gebru HB, Kahsay HB. Effect of motivational interviewing intervention on HgbA1C and depression in people with type 2 diabetes mellitus (systematic review and meta-analysis). PLoS One. 2020;15(10):e0240839.
Bilgin A, Muz G, Yuce GE. The effect of motivational interviewing on metabolic control and psychosocial variables in individuals diagnosed with diabetes: Systematic review and meta-analysis. Patient Educ Couns. 2022;105(9):2806-23.
Mather S, Fisher P, Nevitt S, Cherry MG, Maturana C, Warren JG, et al. The limited efficacy of psychological interventions for depression in people with Type 1 or Type 2 diabetes: An Individual Participant Data Meta-Analysis (IPD-MA). J Affect Disord. 2022;310:25-31.
Ismail K, Winkley K, Rabe-Hesketh S. Systematic review and meta-analysis of randomised controlled trials of psychological interventions to improve glycaemic control in patients with type 2 diabetes. Lancet. 2004;363(9421):1589-97.
Baumeister H, Hutter N, Bengel J. Psychological and pharmacological interventions for depression in patients with diabetes mellitus and depression. Cochrane Database Syst Rev. 2012;12:CD008381.
Winocour PH, Gosden C, Walton C, Nagi D, Turner B, Williams R, et al. Association of British Clinical Diabetologists (ABCD) and Diabetes-UK survey of specialist diabetes services in the UK, 2006. 1. The consultant physician perspective. Diabet Med. 2008;25(6):643-50.
Varela-Moreno E, Carreira Soler M, Guzman-Parra J, Jodar-Sanchez F, Mayoral-Cleries F, Anarte-Ortiz MT. Effectiveness of eHealth-Based Psychological Interventions for Depression Treatment in Patients With Type 1 or Type 2 Diabetes Mellitus: A Systematic Review. Front Psychol. 2021;12:746217.
Fernandez-Rodriguez R, Zhao L, Bizzozero-Peroni B, Martinez-Vizcaino V, Mesas AE, Wittert G, et al. Are e-Health Interventions Effective in Reducing Diabetes-Related Distress and Depression in Patients with Type 2 Diabetes? A Systematic Review with Meta-Analysis. Telemed J E Health. 2024;30(4):919-39.
Franco P, Gallardo AM, Urtubey X. Web-Based Interventions for Depression in Individuals with Diabetes: Review and Discussion. JMIR Diabetes. 2018;3(3):e13.
Holt RIG. Transforming the diabetes outcomes for people with mental illness. Practical Diabetes. 2024;41(4):3-8.
Pereira VS, Hiroaki-Sato VA. A brief history of antidepressant drug development: from tricyclics to beyond ketamine. Acta Neuropsychiatr. 2018;30(6):307-22.
Schildkraut JJ, Gordon EK, Durell J. Catecholamine metabolism in affective disorders. I. Normetanephrine and VMA excretion in depressed patients treated with imipramine. J Psychiatr Res. 1965;3(4):213-28.
Coppen A. The biochemistry of affective disorders. Br J Psychiatry. 1967;113(504):1237-64.
Srisurapanont M, Suttajit S, Kosachunhanun N, Likhitsathian S, Suradom C, Maneeton B. Antidepressants for depressed patients with type 2 diabetes mellitus: A systematic review and network meta-analysis of short-term randomized controlled trials. Neurosci Biobehav Rev. 2022;139:104731.
Sayuk GS, Gott BM, Nix BD, Lustman PJ. Improvement in sexual functioning in patients with type 2 diabetes and depression treated with bupropion. Diabetes Care. 2011;34(2):332-4.
Mohammad Rahimi GR, Aminzadeh R, Azimkhani A, Saatchian V. The Effect of Exercise Interventions to Improve Psychosocial Aspects and Glycemic Control in Type 2 Diabetic Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Biol Res Nurs. 2022;24(1):10-23.
Hofstra E, van Nieuwenhuizen C, Bakker M, Ozgul D, Elfeddali I, de Jong SJ, et al. Effectiveness of suicide prevention interventions: A systematic review and meta-analysis. Gen Hosp Psychiatry. 2020;63:127-40.
Majidi S, Cohen L, Holt RIG, Clements M, O'Neill S, Renard E, et al. Healthcare Professional Experiences and Opinions on Depression and Suicide in People With Diabetes. J Diabetes Sci Technol. 2024;18(3):667-75.
Rivero-Santana A, Perestelo-Perez L, Alvarez-Perez Y, Ramos-Garcia V, Duarte-Diaz A, Linertova R, et al. Stepped care for the treatment of depression: a systematic review and meta-analysis. J Affect Disord. 2021;294:391-409.
Holt RI, Katon WJ. Dialogue on Diabetes and Depression: Dealing with the double burden of co-morbidity. JAffectDisord. 2012;142 Suppl:S1-S3.
Katon WJ, Von Korff M, Lin EH, Simon G, Ludman E, Russo J, et al. The Pathways Study: a randomized trial of collaborative care in patients with diabetes and depression. Arch Gen Psychiatry. 2004;61(10):1042-9.
Simon GE, Katon WJ, Lin EH, Rutter C, Manning WG, Von Korff M, et al. Cost-effectiveness of systematic depression treatment among people with diabetes mellitus. Arch Gen Psychiatry. 2007;64(1):65-72.

Diabetes In The Tropics

ABSTRACT

Diabetes mellitus (DM), an important non-communicable disease, is a major global health problem. Of the major three types of DM, namely type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus, T2DM constitutes more than 90% of cases. The diabetes prevalence is on the rise in tropical regions. T1DM, caused by an autoimmune process, is influenced not only by genetic susceptibility but also to a greater extent by environmental factors. Among the multitude of environmental factors viral triggers, environmental toxins, exposure to exogenous antigens, and geographical factors play a significant role in T1DM pathogenesis. The hygiene hypothesis as explained by prevalent helminthic infection in the tropics, intense ultraviolet exposure translating to improved vitamin D synthesis serving as immune modulator, delayed exposure to cow’s milk and gluten thereby avoiding the allergen provoking beta cell autoimmunity, are a few of the postulated protective mechanisms for T1DM in tropical regions. Tropical regions comprise almost 40 percent of the world’s diabetic load with six countries in the top ten countries with DM. Reports from the IDF also predict a great increase in the coming decades with the maximum increment expected in Africa, Middle East, South-East Asia and South America. The incidence rate of diabetes among those with prediabetes in the Indian subcontinent is also one of the highest reported when compared to the Caucasian population yet comparable to Native Americans and Micronesian populations. World estimates indicate that 16.7% of pregnancies are complicated by some form of hyperglycemia. More than 80% of this is due to gestational DM. While the majority of hyperglycemia in pregnancy is seen in low- and middle-income countries, the prevalence between countries in tropical regions varies with South-East Asian countries topping the prevalence list while Middle East countries and northern Africa show the lowest prevalence (IDF). Diet patterns including greater consumption of tropical fruits with moderate or high glycemic index have been postulated to increase the likelihood of gestational DM. Fibro calculus pancreatic diabetes (FCPD) is a rare but unique and unexplored type of DM found specifically in tropical countries including India, Indonesia, Bangladesh, Sri-Lanka, Brazil and a few African countries. Most of the chronic pancreatitis originates from chronic alcoholism in developed countries contrasting with FCPD, which develops in the absence of alcohol use. Despite rising awareness about DM, the problem of ignorance about DM still exists. Data indicates the alarming fact that one in two adults with DM were unaware of their condition. The increasing incidence and prevalence of DM in the tropics add to the infectious disease load and severity in the tropics. Infections are an important cause of morbidity and mortality in DM. Although disease duration and glycemic control are important risk factors, ethnicity may also play a role as a risk factor for complications.

INTRODUCTION

Diabetes mellitus (DM), an important non-communicable disease, is a major global health problem. Of the major three types of DM, namely type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and gestational DM, T2DM constitutes more than 90% of cases. According to the International Diabetes Federation (IDF), the prevalence of DM was 537 million with an almost equal number of the population having impaired glucose tolerance, which if not acted upon will contribute to the future burden of DM. Keeping in mind the current trends, the estimated worldwide prevalence of DM in two decades will be 784 million. Despite originally conceived as a disease of the affluent in developed, temperate countries, DM has skyrocketed to an alarming rate in developing tropical countries.

The IDF report also highlights the same fact that the burden of DM is increasing at a more rapid pace in low- as well as middle-income countries in comparison to high-income countries. Apart from geographical differences between tropical and temperate countries, they also diverge in terms of DM in substantial ways. Tropical region includes all the South-East Asian countries, part of Middle Eastern countries, a major part of Africa, South America, and a portion of Australia. Among the top ten countries contributing to the world’s DM’ burden, tropical countries occupy six slots including India which solely harbors one sixth of the world’s burden. Not only the disease burden, but also the pattern, types, demography, and epidemiology of DM is considerably different in tropical regions in comparison to the rest of the globe. It is also highlighted that most countries in tropical regions show lower rates of DM disease detection and limited access to management measures.

History dates to almost a century ago when the distinct aspects of people with DM in the tropics were beginning to be acknowledged as evidenced by an opinion by Sir Havelock Charles in the British Medical Journal (1). In 1950s Hugh Jones reported an unclassifiable form of DM in a small proportion of people with DM in Jamaica which he named as J-type (Jamaican type) (2). J-type was different from the then recognized two major forms of DM namely insulin dependent and noninsulin dependent DM in having mixed characteristics like young onset of disease, ketosis resistance, lean body habitus but with insulin resistance. Similar forms of DM were reported from the Indian subcontinent and Africa (3,4). With observation and follow-up, the clinical spectrum became more inconstant and perplexing with some patients becoming insulin independent, while a few becoming ketosis prone (5).

Amplifying the perplexity, abundance of nomenclature like tropical diabetes, Z-type, M-type, type 3 DM, pancreatic DM, malnutrition- related DM, fibro-calculous pancreatic DM, protein-deficient pancreatic DM, etc. exist. The WHO study group in 1985 recognized this group of DM and conglomerated it as a distinct entity naming it as malnutrition–related DM and also put forward the existence of two subtypes: protein-deficient pancreatic DM and fibro-calculous pancreatic diabetes (FCPD) (8). Likewise, a consensus statement from a workshop conducted in India also drew attention to those special types of DM peculiar to the tropics (6). Yet the most recent WHO classification of DM categorizes FCPD in the other specific types of DM (WHO 2019). Strangely, T2DM, which is the most common form of DM even in tropical regions has been overlooked when DM in the tropics is discussed. This review discusses the various aspects of all forms of DM in the tropics.

EPIDEMIOLOGY

The prevalence of DM is on the rise globally, including in tropical regions. The epidemiology of all types of DM in the tropical region is as follows.

Type 1 Diabetes Mellitus

The global prevalence of T1DM in children and adolescents below 20 years is estimated to be more than one million (IDF). T1DM, caused by an autoimmune process, is influenced not only by genetic susceptibility but also to a greater extent by environmental factors. Among the multitude of environmental factors viral triggers, environmental toxins, exposure to exogenous antigens, and geographical factors play a very significant role in T1DM pathogenesis (7,8). The prevalence of disease follows a latitudinal gradient showing a direct relationship with the distance from the equator. Tropical regions show a lower prevalence while European countries exhibit a higher rate (9).

The incidence rates are highest in the northern European population and not surprisingly among the top ten countries based on incidence rates of T1DM, only one tropical country is included (IDF). The hygiene hypothesis as explained by prevalent helminthic infection in the tropics, intense ultraviolet exposure translating to improved vitamin D synthesis serving as an immune modulator, delayed exposure to cow’s milk and gluten thereby avoiding the allergen provoking beta cell autoimmunity are a few of the postulated protective mechanisms for T1DM in tropical regions (10–12). Data from temperate regions suggest the onset of T1DM occurs more often in winter while such differences were not shown in tropical countries (13,14). Likewise, the prevalence of anti-islet cell antibodies seems heterogenous in studies with some showing concordance to Western data while others showing higher antibody negative T1DM in tropical countries than in Western countries, although the number of antibodies tested vary between studies (15–17).

Type 2 Diabetes Mellitus

DM is estimated to affect around one-tenth of the adults aged 20-79 years of which the major type is T2DM. Tropical regions comprise almost 40 percent of the world’s diabetic load with six countries in the top ten countries with DM. Reports from the IDF also predict a rampant increase in the coming decades with maximum increment expected in the tropical regions (Africa, Middle East, South-East Asia, and South America). This increase in DM could be due to increasing life expectancy, improved access to health care, urbanization, and Westernization of lifestyle (18). Poorer lifestyle in the form of unhealthy food options, inaccessible recreational physical activity, and lack of awareness of healthy living accelerate the DM risk. Much evidence for T2DM in the tropics come from India which throws light on the distinguishing features from that of the Western population. The distribution of DM in developed nations is predominantly among the underprivileged strata whereas in developing countries including India, DM has been a disease of the affluent populations. However, it is bothersome to note that the prevalence is now increasing even among the lower socioeconomic strata. The nationwide study which investigated the epidemiology of DM in India showed that the prevalence was higher in urban in comparison to rural areas, although the rate of prediabetes is comparable in urban and rural areas thereby projecting that rural areas will reach the DM numbers akin to urban regions in the near future (ICMR) (19). Higher socioeconomic status remained a risk factor for DM in rural areas while the same was not true in urban areas reflecting the epidemiological transition in urban areas, probably owing to improved health awareness among higher socioeconomic strata. It was also shown that male sex is considered an independent risk factor for developing DM, which is at variance to what is shown in temperate zone showing female preponderance. The plausible explanation for this disparity between regions could be due to neglected healthcare among women in certain communities. Likewise, evidence from the same study did not favor smoking and alcohol as independent risk factors for DM, which contrast with the data from wealthier nations.

The incidence rate of DM among those with prediabetes in the Indian subcontinent is also one of the highest reported when compared to the Caucasian population yet comparable to the Pima Indians, Native Americans, and Micronesian population (20). Besides it is also interesting to note that Asian Indians develop DM at younger ages and at lesser obesity levels as compared to Western counterparts. This could be explained by virtue of South Asians having higher abdominal fat, more insulin resistance, and higher C-reactive protein levels despite lower body mass index (21,22). Among the individuals with prediabetes, prevalence of impaired fasting glucose is higher than that of impaired glucose tolerance in Asian Indians. This finding is in accordance with the evidence that an insulin secretory defect plays a significant role in T2DM pathogenesis in Indians compared to other ethnicities (1). This is also in line with the evidence from IDF which shows that age adjusted prevalence of impaired glucose tolerance is lowest in the southeast Asian region while that of impaired fasting glucose is considerably higher in southeast Asian region than other regions.

Hyperglycemia in Pregnancy

World estimates indicate that 16.7% of pregnancies are complicated by some form of hyperglycemia. More than 80% of this is due to gestational DM. While the majority of hyperglycemia in pregnancy is seen in low- and middle-income countries, the prevalence between tropical countries is vast with South-East Asian countries topping the prevalence list while Middle East countries and northern Africa show the least prevalence (IDF). Studies have also elucidated the possible effect of season and temperature on the prevalence of gestational DM with increased prevalence in summer and higher temperature (23,24). Factors like diet patterns including greater consumption of tropical fruits with moderate or high glycemic index have been postulated to increase the likelihood of gestational DM (25).

Maturity Onset Diabetes of the Young

The pioneering reports from Fajans and Tattersal described an intermediate form of DM different from the two classical forms of insulin dependent and non-insulin dependent DM (26). They coined the term Maturity Onset Diabetes of the young (MODY) showcasing its characteristics of age of onset below 25 years, absence of ketosis, and glycemic control without insulin for a minimum of at least 2 years. They also demonstrated an autosomal dominant inheritance (27). Since its recognition, reports confirm the existence of such youth onset DM which if different from the insulin dependent DM. The prevalence of this distinct form of DM also shows divergence between regions of the world.

Fibro Calculus Pancreatic Diabetes (FCPD)

Fibro calculus pancreatic diabetes (FCPD) is a rare but unique and unexplored type of DM found specifically in tropical countries including India, Indonesia, Bangladesh, Sri-Lanka, Brazil and a few African countries (28). FCPD was earlier called “tropical calcific pancreatitis (TCP)”. According to the American Diabetes Association (ADA) classification, DM originating secondary to any pancreatic origin is classified as type 3c DM. Chronic pancreatitis remains the most common etiology for the development of type 3c DM and chronic alcoholism in developed countries is a major cause of chronic pancreatitis contrasting with FCPD, which develops in the absence of alcohol intake.

FCPD is seen in the spectrum of DM associated with chronic pancreatitis and characterized by the presence of large calculi in the dilated pancreatic ducts along with significant fibrosis and atrophy of the gland. This leads to both exocrine and endocrine dysfunction. Population based studies of FCPD are scarce and the majority are reported from India. The reported population prevalence of FCPD was 0.019% among all DM patients (29). FCPD prevalence has declined from 1.6% in 1991-1995 to 0.2% during 2006-2010 while the BMI in FCPD increased (30). Similarly, Balakrishnan et al (31)found that only 3.8% among type 3c DM patients have FCPD, making chronic idiopathic chronic pancreatitis as the major contributor. The prevalence is approximately15% in young patients referred to a tertiary center (32). The declining prevalence of FCPD is principally attributed to an improvement in nutritional status however the real cause remains to be determined.

GAPS AND CHALLENGES

Despite rising awareness of DM, the problem of ignorance about DM still exists. Data reveal the alarming fact that one in two adults with DM were ignorant about their condition. The majority of the undiagnosed cases occur in low- and middle-income countries. Likewise, the proportion of DM that is undiagnosed differs between regions. More than half of the patients living with DM in tropical regions like Africa and South-East Asia are undiagnosed while in European and North American countries the proportion undiagnosed is remarkably lower (IDF). Such high rates of undiagnosed cases reflect insufficient access to healthcare, poorer capacity of healthcare models, lack of pertinent diagnostic modalities, trained personnel, and inadequate patient health education. It should also be borne in mind that such remarkable levels of undiagnosed cases unquestionably impact morbidity and mortality because the later the diagnosis the higher the chances of disease complications. Additionally, people with a delayed diagnosis of DM, place an extra pressure on the healthcare structure due to higher complications (31).

Existing international guidelines for DM management are based on research conducted in developed countries. Extrapolating and applying such evidence to low- and middle-income countries may not be appropriate and requires a shift from being only developed country centric to more inclusive and international. Widespread effective patient awareness, modified affordable screening methods, appropriate diagnostic strategies, the need to diagnose people with DM earlier, and an increase in the coverage of preventive counselling is needed. In addition to diagnosing DM, efforts to diagnose complications earlier with non-invasive affordable screening tools could also improve outcomes (33,34). Lifestyle modification the most promising tool to prevent DM becomes the foremost inexpensive and best option in resource poor settings (35). DM takes a huge toll and is a major economic burden both to the individual as well as at the national level. The total DM related health expenditure has shown a steady rise over time, and this has been found to be lower in tropical regions as compared to temperate zones.

The North American and European regions display higher total DM related health expenditure while the tropical regions, despite having more than a third of the DM population are responsible for only one-tenth of the global DM related health expenditure. Along the same lines, DM becomes a major contributor to total health expenditure. In tropical regions like South America, Middle East, and North Africa expenditure due to DM contributes to almost one fifth of the total health expenditure while in Europe, DM expenditure as a proportion of total health expenditure is less than one-tenth. This can plausibly be explained by the fact that delayed diagnosis and greater chances of pre-existing complications result in higher expenditures. It is estimated that one third of all deaths from DM occur in the working age group which contributes to the economic burden. The Middle East and North Africa regions have the highest proportion of total deaths related to DM in the working age group. Similar challenges exist for T1DM as well with most developing countries reporting a very sub-optimal glycemic target achievement and control. Guidelines coordinating with existing government programs and primary care facilities aid in benefiting patients (36).

COMPLICATIONS

DM related mortality contributes to 12% of all-cause mortality in the 20-79 years age group. DM related morbidity also augments the economic burden of the disease globally. The microvascular and macrovascular complications of DM account for the majority of the morbidity & mortality. Although disease duration and glycemic control are important risk factors, ethnicity may also be a risk factor for complications.

Microvascular Complications

The prevalence of retinopathy varies between tropical countries. Indian studies report a prevalence ranging from 12-18% (37–39) which is lower than in Western cohorts. In contrast, data from Tanzania and other regions in Africa show a prevalence of 27-31% (70). In India, the prevalence of retinopathy at diagnosis was also strikingly lower among Indians with diabetes than seen in Western counterparts (40–43). Although duration of diabetes and glycemic control are consistent risk factors for retinopathy, diet patterns with increased antioxidants may serve as a probable protective factor (39).

Racial differences in the prevalence of diabetic nephropathy exist with Asian and African groups showing a higher nephropathy prevalence. Risk of end stage renal disease is higher in these populations than in Western populations (44). The prevalence of nephropathy ranges from 30-36% in various tropical regions (45,46) while one study from India reported a lower prevalence (47).

The prevalence of DM neuropathy is very heterogenous among different regions of the tropics. The prevalence estimates from Indian studies show lower figures in comparison to other tropical countries like Cuba, Mexico, Peru, and Caribbean countries (48–50). The different definitions used for DM neuropathy and characteristics of study populations may account for the differences in prevalence data. Asians when compared to Caucasians have a lower prevalence of neuropathy and possible explanations include lower smoking rates resulting in better peripheral vascularity and preserved skin micro-vascularization, and shorter height of Asians (increased height is a known risk factor for neuropathy).

Macrovascular Complications

Cardiovascular disease is the most common reason for mortality in people with DM. The pattern and prevalence vary between regions. The prevalence is less in tropical countries compared to Western countries, probably due to the relatively young population, lack of diagnostic facilities, and death due to other causes which prevail in most tropical countries (51). With Western countries now showing a progressive decrease in cardiovascular deaths, several tropical regions have reported a significant increase in cardiovascular mortality in recent decades (50,52). This could be attributable to the rampant Westernization with harmful transition in lifestyle increasing cardiovascular risk factors, growing population, and aging (53). Data from India show the susceptibility of Asian Indians to coronary artery disease. Asian Indians show early onset, more severe disease, and higher risk of mortality that Caucasians (54). DM by virtue of its insulin resistance and atherogenic dyslipidemia further aggravate this risk. On the contrary, peripheral vascular disease is comparatively rare among Indians. Younger age of onset of DM and lesser prevalence of smoking contributes to the decreased prevalence (55).

Diabetic Foot Ulcer & Tropical Diabetic Hand Syndrome

DM foot, a serious chronic complication of DM, shows an increasing prevalence worldwide owing to the rising DM prevalence and increased life expectancy. The prevalence of DM foot ulcer is heterogenous even between tropical regions with the Africa region showing higher caseloads than Asia and Australia. Still the overall prevalence is greater in North America and the reason for such differences could be increased prevalence of smoking among Americans than South Asians or poor screening processes in tropical countries (56). One of the important risk factors for developing a foot ulcer is barefoot walking, which prevails in most communities in Africa and Asia. Other risk factors, which are peculiar to these populations, include utilizing inappropriate footwear, more susceptible to rodent bites during farming activities, etc. (57). It is also shown that the duration between DM onset and onset of foot ulceration is shorter probably due to late diagnosis of DM (58). The bacteriology of foot infections also depends on climatic conditions with gram negative organism showing higher prevalence in the tropical and sub-tropical regions. DM foot ulcers increase healthcare costs, risk of amputation, and mortality (59). In the tropical regions, native practices to treat DM foot ulcers with plant parts remain widespread even in the modern era.

Tropical DM hand syndrome (TDHS) is a comparatively less recognized complication than DM foot. Since its earliest description from Africa, many cases have been reported in Africa and India (60). It is distinct from the DM hand syndrome where the latter predominantly involves joints and skin, leading to limited mobility. TDHS usually follows a trivial trauma and involves cellulitis ultimately progressing to fulminant sepsis or gangrene. Early aggressive antibiotic therapy with or without surgical intervention is needed for adequate management (61).

Acute Complications

Hyperglycemic emergencies constitute an important cause of emergency presentation of T1DM as well as T2DM. Up to a maximum of 80% of T1DM patients present with diabetic ketoacidosis (DKA) at diagnosis and this varies between countries. It has been shown that countries with higher background prevalence of T1DM have lower frequency of DKA at presentation with Sweden showing the lowest frequency of DKA at presentation while the United Arab Emirates and Saudi Arabia show the highest frequency. The same study showed that the frequency of DKA at presentation progressively decreases with increasing latitude thereby demonstrating a higher risk in tropical countries (62). Heat exposure has been shown to be associated with hyperglycemic emergencies through various mechanisms such as reduced insulin activity in insulin preparations exposed to high ambient temperatures, higher environmental temperature leading to increased counter regulatory hormones, higher risk of dehydration, and decreased thermoregulatory activity in the elderly (99). Interestingly higher environmental temperature is also an important risk factor for hypoglycemia. Asian countries also report a higher frequency of DKA among T2DM than Western populations (63). The mortality rates are also comparatively higher in tropical countries (64). It is also important to note that FCPD despite beta cell destruction, does not commonly lead to DKA episodes (65).

Diabetes & Infections

Uncontrolled DM is a well-known risk factor for infections and poor outcomes, due to altered immune responses (97). For some infections, there is evidence that poor glycemic control correlates with infection risk as well as severity. The following mechanisms confer increased susceptibility to infections in people with DM:

(i) Altered skin flora and increased risk of breach in integrity due to neuropathy and angiopathy (66)

(ii) Altered gut microbiome (67)

(iii) Impaired neutrophil function (68)

(iv) Impaired function of macrophages, T-cells, and NK cells (69)

(iv) Endothelial dysfunction, oxidative stress (70)

Some infections like rhino cerebral mucormycosis, Klebsiella pneumoniae related liver abscess, emphysematous pyelonephritis or cholecystitis, and Fournier’s gangrene are DM specific (71,72). Certain infections like candidiasis, bacterial pneumonia, urinary tract infections, skin and soft tissue infections, and bloodstream infections, although not exclusive for patients with DM are more common and severe among people with DM (73,74).

The increasing incidence and prevalence of DM in the tropics add to the infectious disease load and severity in the tropics. Infections are an important cause of morbidity and mortality in people with DM. Tropical regions are home to endemic infections like tuberculosis, dengue, melioidosis, leishmaniasis, helminthic, and parasitic infections. Patients with DM are affected out of proportion by tuberculosis, malaria, and Human immunodeficiency virus (HIV). The plausible reason for a higher risk of infections in people with DM in the tropics include:

(i) higher possibility of DM being undiagnosed or the diagnosis delayed

(ii) poorly controlled DM due to suboptimal management

(iii) co-existing malnutrition and poor hygiene

(iv) reduced access to healthcare facilities & infection care

Therefore, the tropical countries face a double disease burden, persisting communicable diseases and DM worsening the communicable disease burden. While DM, a proven risk factor for infections, confers higher rates of infection with common bacterial organisms in high income countries in tropical countries, in addition to higher rates of common organisms, the risk of tropical infections poses additional concerns.

BACTERIAL INFECTIONS

Among bacterial infections, tuberculosis has a bidirectional relationship with DM. People with uncontrolled DM have a three times higher risk of developing active tuberculosis, more atypical presentation, higher rate of treatment failure, and recurrence (75). Conversely active tuberculosis leads to stress hyperglycemia (76). Recent reports also suggest the number of patients of tuberculosis with coexisting DM exceeds the number of TB-HIV coinfection (77). Among the top 10 countries harboring global tuberculosis cases, most of the countries also show a high prevalence of DM (78). Understanding the impact of DM on tuberculosis, some countries have implemented collaborative interventions to improve detection of DM among patients with tuberculosis by screening all TB cases for DM (78). In contrast, screening all patients with DM for TB, despite being very important, still has practical difficulty owing to the limitations of available screening tests.

Melioidosis, another important tropical disease, is caused by Burkholderia pseudomallei, a gram-negative bacterium. DM increases the risk of melioidosis, which is usually prevalent in rice farming countries such as South-East Asia (79). With the rising prevalence of DM in tropical countries along with the increasing life expectancy, the burden of melioidosis may prove disastrous. Contradictory evidence also exists with regards to the impact of sulfonylurea treatment on the immune effects against melioidosis (80). DM serves as an independent risk factor for severity of scrub typhus, a rickettsial disease in tropical regions (81).

VIRAL INFECTIONS

Viral infections of significance in the tropics include dengue, arbovirus, severe acute respiratory syndrome, Middle East respiratory syndrome virus, and Ebola virus. Dengue, a mosquito borne infection, has shown a relation with DM. DM is associated with more severe dengue-induced thrombocytopenia, dengue shock syndrome, and higher risk of acute kidney injury (82–84). Similar evidence of DM predisposing to more severe chikungunya, West Nile fever disease does exist although such evidence on zika virus is inadequate (85,86). Likewise, DM is an important risk factor for Middle East Respiratory Syndrome (MERS) and is associated with higher mortality among severe acute respiratory syndrome (SARS) virus (87,88). Hepatitis B virus (HBV) also shows a close association with DM. Its prevalence is higher among people with DM, and DM is described to be associated with HBV disease progression. On the other hand, people with chronic HBV have an increased risk of developing DM. DM is more common among people living with HIV with data from tropical regions showing a more consistent and stronger association then those from high income countries (89,90). Advancements in retroviral therapy have transformed HIV infection from being associated with acquired immunodeficiency syndrome to a chronic disease associated with DM. The fact that DM in patients living with HIV develops at a much younger age than the general population is of great public health importance (61).

PARASITIC INFECTIONS

Malaria, caused by Plasmodium sp., is transmitted via mosquito bites. Africa accounts for the majority of cases. With co-existent increasing DM prevalence in Africa, a study from Ghana found that people with DM had a 46% increased risk of Plasmodium falciparum infection (91). Malaria infection during pregnancy is associated with intrauterine growth retardation, which in later life heightens the risk of insulin resistance and DM risk. DM is linked to an increased risk of leishmaniasis, whereas hyperglycemia was more common in patients with Chagas disease and cardiomyopathy than patients without cardiomyopathy (92,93). Interestingly a few helminthic infections like Schistosomiasis, round worm, and hook worm have a possible protective effect against DM (94).

FUNGAL INFECTIONS

Certain fungi are more frequent in the tropics than temperate regions due to the hotter and wetter conditions prevailing in the tropics. Fungal infections, typically the invasive ones, are also more common among immunocompromised individuals constituting opportunistic infections. Uncontrolled DM, a relatively immunocompromised state, and the climatic conditions of tropical regions favoring the prevalence of fungi, lead to fungal infections contributing importantly to the infection disease burden in the tropics. Mucormycosis caused by Zygomycetes, presents specifically as rhino-orbital-cerebral disease in people with DM. Although different forms of mucormycosis like pulmonary, gastrointestinal, and cutaneous types exist, rhino-orbital-cerebral mucormycosis is specifically associated with poorly controlled DM (95). Records from tropics show that among all patients with Mucormycosis, DM was seen in more than three-fourths of the patients. In the low-income countries, mortality due to mucormycosis is also higher than that in the developed countries owing to the shortcomings in medical and surgical management as well as poor glycemic control (96). Additionally, invasive aspergillus infections are also on the rise in the tropical regions.

FIBRO CALCULUS PANCREATIC DIABETES (FCPD)

Pathogenesis

The exact pathogenesis remains elusive. Factors like environmental toxins, nutrient deficiency, and genetic factors in combination may have a role.

(i) Environmental toxins: The most popular concept in the pathogenesis was the cassava hypothesis by McMillan and Geevarghese (4). Cassava contains cyanogenic glycosides. Cyanide detoxification in the body requires sulfur containing amino acids. In coexisting malnutrition, cyanide detoxification is impaired leading to pancreatic damage. Although cyanide ingestion in experiment rat models lead to transient hyperglycemia, permanent diabetes was not reported even with long term cassava consumption in rat models, thereby questioning this hypothesis (4). Geographic distribution of FCPD coincides with areas that consume cassava yet other areas where cassava consumption is not documented also have FCPD. The possible role of other cyanide containing foods such as jowar and sorghum may play a role.

(ii) Nutrient deficiency: The role of nutrient deficiency in the pathogenesis of FCPD has been a matter of debate. Nutrient deficiency could be the cause of as well as an effect of FCPD. Micronutrient deficiency and low vitamin C, vitamin E and beta carotene intake leading to oxidative stress may play a role in the etiology. Oxidative stress may also play a crucial role as evidenced by higher malondialdehyde levels and reduced antioxidant markers. Special interest with regards to selenium deficiency has been proposed. Western data showing that serum selenium levels were lower in those with chronic pancreatitis than in controls has kindled the hypothesis that lower selenium levels are associated with an accelerated course leading to DM in tropical pancreatitis. Yet a study comparing the selenium levels in healthy volunteers and patients with chronic pancreatitis in tropical and temperate regions did not confirm that selenium levels are involved in the DM that occurs in association with chronic pancreatitis (97).

(iii) Genetic factors: Studies have shown a familial aggregation, observed in up to one-tenth of cases (91) (98). Alterations in genes such as serum protease inhibitor Kazal type (SPINK1), cationic trypsinogen (PRSS1), anionic trypsinogen (PRSS2), and chymotrypsinogen C have been highlighted in FCPD cases.

Overall, no one factor is responsible for the pathogenesis while probable involvement of multiple factors may explain the occurrence. The pathogenesis of DM includes defective insulin secretion as well as insulin resistance in FCPD. Deficiency of pancreatic polypeptide and storage of triglyceride in liver due to reduced fat store, contributes to insulin resistance (65).

Unfortunately, there is no specific etiology identified in FCPD despite several proposed theories. The initial explanation of cassava (tapioca) induced injury to the pancreatic acini through cyanide generation is flawed by the fact that not all with cassava intake develop the disease (6,7). A diet pattern of high carbohydrate and low protein is also implicated but the underlying mechanism is not known. Perhaps, genetic predisposition partly explains the FCPD etiology. A recent study has shown that 62.5 percent of FCPD patients harbor variation in the serine protease inhibitor Kazal type 1 (SPINK1) gene , particularly the N34S polymorphism (8). The role of other genes like PRSS1, PRSS2, CFTR, CTSB are not fully elucidated.

Apart from pancreatitis development, how diabetes develops is also not understood. Insulin deficiency and beta cell dysfunction are the primary pathology found. However, newer evidence suggests that altered glucagon dynamics, incretin abnormalities, and the presence of abnormal body composition leading to selective insulin resistance may contribute to the development of diabetes in FCPD (1,9) (99).

Clinical Features and Diagnosis of FCPD

The clinical features of FCPD are unique. The natural history usually progresses through three distinct stages. The initial period, where recurrent abdomen pain is the main clinical feature, often occurs in adolescents or early second decades. The second stage is characterized by classical exocrine pancreatic insufficiency with resultant steatorrhea symptoms. Steatorrhea is characterized by recurrent diarrhea with bulky, foul smelling, greasy stool, and predominant symptoms of fat malabsorption. Subsequently, fat related vitamin deficiency (A,D,E,K) features ensue. Other macro and micronutrients deficiencies are also present. In the third stage, that usually occurs in the late second to third decade, frank hyperglycemia occurs. FCPD patients are classically lean and malnourished. They have very brittle DM with high glycemic variability that is difficult to control.

Abdominal pain is conspicuously absent or less in intensity and frequency in the third stage, but the full-blown picture of both endocrine and exocrine deficiency persists. 50% of patients with FCPD without DM at baseline develop DM after 5 years of follow-up (100), mostly at the third decade, however the percentage is even higher as age advances. The diagnostic criteria proposed by the Mohan et al encompasses all the clinical features described (See Table 1, Adapted from reference) (101). Despite a very high glucose, FCPD patients do not develop diabetic ketoacidosis (DKA). The reasons proposed are : 1) simultaneous destruction of pancreatic alpha cells leading to absence of glucagon which is a crucial hormone for ketogenesis in the liver. This is coupled with absence of absolute insulin deficiency in FCPD, as compared to T1DM, preventing lipolysis; 2) these patients are chronically malnourished and have very low free fatty acid reserve thus adequate substrate for ketone generation is usually absent and 3) carnitine deficiency as a part of generalized malnutrition as carnitine is required for the mitochondrial beta oxidation (28,101).

TABLE 1. DIAGNOSTIC CRITERIA FOR FCPD
1. Occurrence in a tropical country
2. Diabetes as per standard diagnostic criteria
3. Evidence of chronic pancreatitis: a. Pancreatic calculi on X-ray or b. At least 3 of the following: i. Abnormal pancreatic morphology by imaging ii. Chronic abdominal pain since childhood iii. Steatorrhea c. Abnormal pancreatic function test
4. Absence of other causes of pancreatitis like alcoholism, hyperparathyroidism, marked hypertriglyceridemia, hepatobiliary disease etc.

Table from the Endotext chapter entitled Fibrocalculus Pancreatic Diabetes

The diagnosis of FCPD is mostly clinical and supported by imaging. Since FCPD has an asymptomatic course when the pancreatic injury has happened and frank glycemia is not present, the diagnosis is often delayed and there is an unmet need for screening in such patients. The classical patient is a lean malnourished patient with severe hyperglycemia requiring multiple insulin doses. Abdominal imaging, particularly computed tomography (CT) scans are helpful to diagnose pancreatic pathology. The CT hallmark is 1) pancreatic duct dilation, 2) large pancreatic calculi involving the major ducts and 3) pancreatic atrophy and fibrosis. These features differ from alcoholic chronic pancreatitis where the pancreatic stones are smaller and have speckled pattern and involves smaller pancreatic ducts (101). However, other common causes of pancreatitis like alcohol, hyperparathyroidism, gallstones, and hypertriglyceridemia should be ruled out in such patients.

Despite having high glycemic variability and an elevated HbA1C, FCPD patients are at lower risk of micro and macrovascular complications compared to classical (T2DM). In a study from the Southern part of India it was shown that the prevalence of coronary artery disease, cerebrovascular stroke, and retinopathy was significantly higher in the T2DM patients compared to FCPD patients confirming this notion (102). This difference is possibly related to the absence of insulin resistance and other risk factors like obesity and dyslipidemia in FCPD patients, but further work is required to better understand this dichotomy. Nevertheless, all patients should undergo careful investigation for the routine micro and macrovascular complications. Periodontal disease is common in FCPD similar to that seen in T2DM and the severity correlates with poor glycemia (103). Hypoglycemia unawareness is found in 73% of FCPD patients and classically is related to the lower fasting and post prandial glucagon levels in a subset of patients and contributes to the higher glycemic variability (104).

It is important to evaluate pancreatic exocrine insufficiency by fecal elastase estimation. However, fat malabsorptive features may be absent in tropical countries since the diet may be low in fat. Other abnormalities such as high triglycerides during hyperglycemia can be seen. Pancreatic amylase and lipase are not elevated in the chronic phase but may rise if an acute attack is present. Pancreatic carcinoma is a dreaded long-term complication of FCPD. Usually, pancreatic carcinoma develops much earlier, around the 5^th decade in these patients and is diagnosed at an advanced stage (105). Unexplained weight loss and sudden deterioration in glycemic control along with abdominal pain distinct from the usual pancreatitis pain, warrants urgent investigation for pancreatic carcinoma (101).

Management and Challenges in FCPD

The mainstay of management of hyperglycemia is insulin. However, the doses may be quite variable and require frequent adjustment. Sometimes metformin and sulphonylureas are sufficient to control glycemia in milder cases. Lack of evidence of management of FCPD is a concern and should be addressed urgently. Incretin mimetics like DPP-4 inhibitors and GLP-1 analogues should be used cautiously if at all in FCPD. Ideally a closed loop system for continuous subcutaneous insulin delivery coupled with continuous glucose monitoring should be used whenever possible in FCPD patients but need further studies for this recommendation. Recent studies have shown the impact of SGLT-2 inhibitors in pancreatectomized patients, and hence they can be an important choice in FCPD patients, but one must be cautious about potential weight loss (106).

With documented exocrine pancreatic insufficiency in FCPD, pancreatic enzyme replacement therapy (PERT) may help improve glycemia and hence should be considered in patients with chronic pancreatitis (107). The usual dose is 10,000-25,000 lipase units and requires escalation to higher dose up to 50,000 per meal or less for snacks. The capsules should be spread throughout the meal to maximize the benefits. Usually, dietary fat restrictions are not advised but a high fiber diet may aggravate abdominal symptoms in FCPD, thus better avoided. Fat soluble vitamin replacement is necessary. Eventually some patients having refractory pain require either endoscopic or open surgical procedures for drainage. Unfortunately, there is no therapy to halt the progression from the pancreatitis phase to the FCPD phase, however antifibrotic treatment like pirfenidone has shown some effect in experimental preclinical studies (108).

REFERENCES

Gujral UP, Narayan KMV, Kahn SE, Kanaya AM. The relative associations of β-cell function and insulin sensitivity with glycemic status and incident glycemic progression in migrant Asian Indians in the United States: the MASALA study. J Diabetes Complications. J Diabetes Complications. 2014;28(1):45-50. Available from: https://pubmed.ncbi.nlm.nih.gov/24211090/
Hugh-Jones P. Diabetes in Jamaica. Lancet. 1955;269(6896):891–7. Available from: https://pubmed.ncbi.nlm.nih.gov/13264638/
Tripathy BB, Kar BC. Observations on Clinical Patterns of Diabetes Mellitus in India. Diabetes. 1965;14:404-412. Available from: http://diabetesjournals.org/ diabetes/article-pdf/14/7/404/338504/14-7-404.pdf
McMillan DE, Geevarghese PJ. Dietary cyanide and tropical malnutrition diabetes. Diabetes Care. 1979;2(2):202-208. Available from: https://pubmed.ncbi.nlm.nih.gov/574813/
Tulloch JA, Macintosh D. “J”-type diabetes. Lancet. 1961;2(7194):119-121.Available from: https://pubmed.ncbi.nlm.nih.gov/13778587/
Hoet JJ, Tripathy BB. Report of the International Workshop on types of Diabetes Peculiar to the Tropics. Diabetes Care. 1996;19(9):1014. Available from: https://pubmed.ncbi.nlm.nih.gov/8875102/
Zorena K, Michalska M, Kurpas M, Jaskulak M, Murawska A, Rostami S. Environmental Factors and the Risk of Developing Type 1 Diabetes-Old Disease and New Data. Biology (Basel). 2022;11(4):608. Available from: https://pubmed.ncbi.nlm.nih.gov/35453807/
Alruhaili M, Alruhaili MH. Type 1 diabetes in the tropics: the protective effects of environmental factors. African Journal of Diabetes Medicine. 2010;18(2):1-4.
Mohr SB, Garland CF, Gorham ED, Garland FC. The association between ultraviolet B irradiance, vitamin D status and incidence rates of type 1 diabetes in 51 regions worldwide. Diabetologia. 2008;51(8):1391-1398. Available from: https://pubmed.ncbi.nlm.nih.gov/18548227/
Zaccone P, Fehervari Z, Phillips JM, Dunne DW, Cooke A. Parasitic worms and inflammatory diseases. Parasite Immunol. 2006;28(10):515-523. Available from: https://pubmed.ncbi.nlm.nih.gov/16965287/
Virtanen SM, Räsänen L, Aro A, Lindström J, Sippola H, Lounamaa R, et al. Infant feeding in Finnish children less than 7 yr of age with newly diagnosed IDDM. Childhood Diabetes in Finland Study Group. Diabetes Care. 1991;14(5):415-417. Available from: https://pubmed.ncbi.nlm.nih.gov/2060453/
Norris JM, Barriga K, Klingensmith G, Hoffman M, Eisenbarth GS, Erlich HA, et al. Timing of Initial Cereal Exposure in Infancy and Risk of Islet Autoimmunity. JAMA. 2003;290(13):1713-1720. Available from: https://jamanetwork.com/ journals/jama/fullarticle/197392
Variation and trends in incidence of childhood diabetes in Europe. EURODIAB ACE Study Group. [published correction appears in Lancet 2000 Nov 11;356(9242):1690]. Lancet. 2000;355(9207):873-876. Available from: https://pubmed.ncbi.nlm.nih.gov/10752702/
Basu M, Banerjee M, Mukhopadhyay P, Ghosh S. Trends of Seasonality and Age of onset in T1DM: A snapshot from Eastern India. Indian J Endocrinol Metab. 2020;24(2):219-220. Available from: /pmc/articles/PMC7333758/
Basu M, Pandit K, Banerjee M, Mondal SA, Mukhopadhyay P, Ghosh S. Profile of Auto-antibodies (Disease Related and Other) in Children with Type 1 Diabetes. Indian J Endocrinol Metab. 2020;24(3):256-259. Available from: /pmc/articles/PMC7539037/
Balasubramanian K, Dabadghao P, Bhatia V, Colman PG, Gellert SA, Bharadwaj U, et al. High frequency of type 1B (idiopathic) diabetes in North Indian children with recent-onset diabetes. Diabetes Care. 2003;26(9):2697. Available from: https://pubmed.ncbi.nlm.nih.gov/12941746/
Shivaprasad C, Mittal R, Dharmalingam M, Kumar P. Zinc transporter-8 autoantibodies can replace IA-2 autoantibodies as a serological marker for juvenile onset type 1 diabetes in India. Indian J Endocrinol Metab. 2014;18(3):345-9. Available from: /pmc/articles/PMC4056133/
van Crevel R, van de Vijver S, Moore DAJ. The global diabetes epidemic: what does it mean for infectious diseases in tropical countries? Lancet Diabetes Endocrinol. 2017 Jun;5(6):457-468.
Mohan V, Anjana RM, Tandon N. Lessons Learnt from the ICMR-INDIAB Study. Natl Med J India. 2023;36(3):137-139. Available from: https://pubmed.ncbi.nlm.nih.gov/38692603/
Anjana RM, Rani CSS, Deepa M, Pradeepa R, Sudha V, Nair HD, et al. Incidence of diabetes and prediabetes and predictors of progression among Asian Indians: 10-year follow-up of the Chennai urban rural epidemiology study (CURES). Diabetes Care. 2015;38(8):1441-1448.
Unnikrishnan R, Anjana RM, Mohan V. Diabetes in South Asians: Is the Phenotype Different? Diabetes. 2014;63(1):53-55. Available from: https://dx.doi.org/10.2337/db13-1592
Ramachandran A, Snehalatha C, Naik RAS, Mohan V, Shobana R, Viswanathan M. Significance of impaired glucose tolerance in an Asian Indian population: a follow-up study. Diabetes Res Clin Pract. 1986;2(3):173-178. Available from: https://pubmed.ncbi.nlm.nih.gov/3527626/
Retnakaran R, Ye C, Kramer CK, Hanley AJ, Connelly PW, Sermer M, et al. Impact of daily incremental change in environmental temperature on beta cell function and the risk of gestational diabetes in pregnant women. Diabetologia. 2018;61(12):2633-2642. Available from: https://pubmed.ncbi.nlm.nih.gov /30112689/
Wang P, Wu CS, Li CY, Yang CP, Lu MC. Seasonality of gestational diabetes mellitus and maternal blood glucose levels: Evidence from Taiwan. Medicine (Baltimore). 2020;99(41):e22684. Available from: https://pubmed. ncbi.nlm.nih.gov/33031338/
Huang WQ, Lu Y, Xu M, Huang J, Su YX, Zhang CX. Excessive fruit consumption during the second trimester is associated with increased likelihood of gestational diabetes mellitus: a prospective study. Sci Rep. 2017;7:43620. Available from: https://www.nature.com/articles/srep43620
Tattersall RB. Mild familial diabetes with dominant inheritance. Q J Med. 1974;43(170):339-357. Available from: https://pubmed.ncbi. nlm.nih.gov/4212169/
Tattersall RB, Fajans SS. A difference between the inheritance of classical juvenile-onset and maturity-onset type diabetes of young people. Diabetes. 1975;24(1):44-53. Available from: https://pubmed.ncbi.nlm.nih.gov/1122063/
Dasgupta R, Naik D, Thomas N. Emerging concepts in the pathogenesis of diabetes in fibrocalculous pancreatic diabetes. J Diabetes. 2015;7(6):754-761. Available from: https://pubmed.ncbi.nlm.nih.gov/25707547/
Mohan V, Farooq S, Deepa M. Prevalence of fibrocalculous pancreatic diabetes in Chennai in South India. JOP. 2008;9(4):489-492. Available from: https://pubmed.ncbi.nlm.nih.gov/18648140/
Papita R, Nazir A, Anbalagan VP, et al. Secular trends of fibrocalculous pancreatic diabetes and diabetes secondary to alcoholic chronic pancreatitis at a tertiary care diabetes centre in South India. JOP. 2012;13(2):205-209. Available from: https://pubmed.ncbi.nlm.nih.gov/22406602/
Balakrishnan V, Unnikrishnan AG, Thomas V, Choudhuri G, Veeraraju P, Singh SP, et al. Chronic pancreatitis. A prospective nationwide study of 1,086 subjects from India. JOP. 2008;9(5):593-600. Available from: https://europepmc.org/ article/med/18762690
Sahoo S, Zaidi G, Vipin V, Chapla A, Thomas N, Yu L, et al. Heterogeneity in the aetiology of diabetes mellitus in young adults: A prospective study from north India. Indian J Med Res. 2019;149(4):479-488. Available from: https://pubmed.ncbi.nlm.nih.gov/31411171/
Banerjee M, Mukhopadhyay P, Basu M, Ghosh S. Corneal Confocal Microscopy Identifies Structural Small Fibre Abnormalities in an Adolescent with Type 1 Diabetes and Impaired Awareness of Hypoglycaemia. J ASEAN Fed Endocr Soc. 2023;38(2):128-130. Available from: https://asean-endocrinejournal.org/ index.php/JAFES/article/view/2689
Banerjee M, Mukhopadhyay P, Ghosh S, Basu M, Pandit A, Malik R, et al. Corneal Confocal Microscopy Abnormalities in Children and Adolescents With Type 1 Diabetes. Endocr Pract. 2023;29(9):692-698. Available from: https://pubmed.ncbi.nlm.nih.gov/37343765/
Echouffo-Tcheugui JB, Dagogo-Jack S. Preventing diabetes mellitus in developing countries. [published correction appears in Nat Rev Endocrinol. 2012 Nov;8(11):692]. Nat Rev Endocrinol. 2012;8(9):557-562. Available from: https://pubmed.ncbi.nlm.nih.gov/22488646/
Yasmin M, Mukhopadhyay P, Ghosh S. Model of care for Type 1 diabetes in India: Integrated approach for its incorporation in future national health care policy. Lancet Reg Health Southeast Asia. 2022;3:100014.Available from: http://www.thelancet.com/article/S2772368222000142/fulltext
Raman R, Rani PK, Reddi Rachepalle S, Gnanamoorthy P, Uthra S, Kumaramanickavel G, et al. Prevalence of diabetic retinopathy in India: Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study report 2. Ophthalmology. 2009;116(2):311-318. Available from: https://pubmed.ncbi.nlm.nih.gov/19084275/
Pradeepa R, Rema M, Vignesh J, Deepa M, Deepa R, Mohan V. Prevalence and risk factors for diabetic neuropathy in an urban south Indian population: the Chennai Urban Rural Epidemiology Study (CURES-55). Diabet Med. 2008;25(4):407-412. Available from: https://pubmed.ncbi.nlm.nih.gov/ 18294224/
Rema M, Pradeepa R. Diabetic retinopathy: an Indian perspective. Indian J Med Res. 2007;125(3):297-310. Available from: https://pubmed.ncbi.nlm.nih.gov/ 17496357/
Kohner EM, Aldington SJ, Stratton IM, Manley SE, Holman RR, Matthews DR, et al. United Kingdom Prospective Diabetes Study, 30: diabetic retinopathy at diagnosis of non-insulin-dependent diabetes mellitus and associated risk factors. Arch Ophthalmol. 1998;116(3):297-303. Available from: https://pubmed.ncbi.nlm.nih.gov/9514482/
Harris MI, Klein R, Welborn TA, Knuiman MW. Onset of NIDDM occurs at least 4-7 yr before clinical diagnosis. Diabetes Care. 1992;15(7):815-819. Available from: https://pubmed.ncbi.nlm.nih.gov/1516497/
Ramachandran A, Snehalatha C, Vijay V, Viswanathan M. Diabetic retinopathy at the time of diagnosis of NIDDM in South Indian subjects. Diabetes Res Clin Pract. 1996;32(1-2):111-114.
Scanlon PH, Nevill CR, Stratton IM, Maruti SS, Massó-González EL, Sivaprasad S, et al. Prevalence and incidence of diabetic retinopathy (DR) in the UK population of Gloucestershire. Acta Ophthalmol. 2022;100(2):e560-e570. Available from: https://pubmed.ncbi.nlm.nih.gov/34180581/
Young BA, Maynard C, Boyko EJ. Racial differences in diabetic nephropathy, cardiovascular disease, and mortality in a national population of veterans. Diabetes Care. 2003;26(8):2392-2399. Available from: https://pubmed.ncbi.nlm.nih.gov/12882868/
Wagnew F, Eshetie S, Kibret GD, Zegeye A, Dessie G, Mulugeta H, et al. Diabetic nephropathy and hypertension in diabetes patients of sub-Saharan countries: a systematic review and meta-analysis. BMC Res Notes. 2018;11(1):565. Available from: https://pubmed.ncbi.nlm.nih.gov/30081966/
Chandie Shaw PK, Baboe F, Van Es LA, Van Der Vijver JC, Van De Ree MA, De Jonge N, et al. South-Asian type 2 diabetic patients have higher incidence and faster progression of renal disease compared with Dutch-European diabetic patients. Diabetes Care. 2006;29(6):1383-1385. Available from: https://pubmed.ncbi.nlm.nih.gov/16732026/
Unnikrishnan I R, Rema M, Pradeepa R, Deepa M, Shanthirani CS, Deepa R, et al. Prevalence and Risk Factors of Diabetic Nephropathy in an Urban South Indian PopulationThe Chennai Urban Rural Epidemiology Study (CURES 45). Diabetes Care. 2007;30(8):2019-2024. Available from: https://dx.doi.org/ 10.2337/dc06-2554
Yovera-Aldana M, Velasquez-Rimachi V, Huerta-Rosario A, More-Yupanqui MD, Osores-Flores M, Espinoza R, et al. Prevalence and incidence of diabetic peripheral neuropathy in Latin America and the Caribbean: A systematic review and meta-analysis. PLoS One. 2021;16(5):e0251642. Available from: /pmc/articles/PMC8118539/
Dutta A, Naorem S, Singh TP, Wangjam K. Prevalence of Peripheral Neuropathy In Newly Diagnosed Type 2 Diabetics Mellitus. Int J Diab Dev Countries. 2005;25:30-33.
Sacco RL, Roth GA, Reddy KS, Arnett DK, Bonita R, Gaziano TA, et al. The Heart of 25 by 25: Achieving the Goal of Reducing Global and Regional Premature Deaths From Cardiovascular Diseases and Stroke: A Modeling Study From the American Heart Association and World Heart Federation. Circulation. 2016;133(23):e674-e690. Available from: https:// pubmed.ncbi.nlm.nih.gov/27162236/
Kengne AP, Amoah AGB, Mbanya JC. Cardiovascular complications of diabetes mellitus in sub-Saharan Africa. Circulation. 2005;112(23):3592-3601. Available from: https://pubmed.ncbi.nlm.nih.gov/16330701/
Gouda HN, Charlson F, Sorsdahl K, Ahmadzada S, Ferrari AJ, Erskine H, et al. Burden of non-communicable diseases in sub-Saharan Africa, 1990-2017: results from the Global Burden of Disease Study 2017. Lancet Glob Health. 2019;7(10):e1375-e1387. Available from: https://pubmed.ncbi.nlm. nih.gov/31537368/
Minja NM, Nakagaayi D, Aliku T, Zhang W, Ssinabulya I, Nabaale J, et al. Cardiovascular diseases in Africa in the twenty-first century: Gaps and priorities going forward. Front Cardiovasc Med. 2022;9:1008335. Available from: https://pubmed.ncbi.nlm.nih.gov/36440012/
Mohan V, Venkatraman JV, Pradeepa R. Epidemiology of cardiovascular disease in type 2 diabetes: the Indian scenario. Diabetes Sci Technol. 2010;4(1):158-170. Available from: https://pubmed.ncbi.nlm.nih.gov/20167181/
Pradeepa R, Chella S, Surendar J, Indulekha K, Anjana RM, Mohan V. Prevalence of peripheral vascular disease and its association with carotid intima-media thickness and arterial stiffness in type 2 diabetes: the Chennai urban rural epidemiology study (CURES 111). Diab Vasc Dis Res. 2014;11(3):190-200. Available from: https://pubmed.ncbi.nlm.nih.gov/ 24627461/
Zhang P, Lu J, Jing Y, Tang S, Zhu D, Bi Y. Global epidemiology of diabetic foot ulceration: a systematic review and meta-analysis. Ann Med. 2017;49(2):106-116. Available from: https://pubmed.ncbi.nlm.nih.gov/27585063/
Abbas ZG, Boulton AJM. Diabetic foot ulcer disease in African continent: ‘From clinical care to implementation’ - Review of diabetic foot in last 60 years - 1960 to 2020. Diabetes Res Clin Pract. 2022;183:109155. Available from: https://pubmed.ncbi.nlm.nih.gov/34838640/
Okunola O, Akinwusi P, Kolawole B, Oluwadiya K. Diabetic foot ulcer in a Tropical setting: Presentation and outcome. Nigerian Endo Practice. 2012;6(1):27–31. Available from: https://www.ajol.info/index.php/nep/ article/view/84844
Rabin B, Lockwood SM, Martinson E, Urquhart-Foster K, Bhanushali P, Raymond J, et al. 2901. Associations between climate and diabetic foot infection microbiology: a systematic review and meta-analysis. Open Forum Infect Dis. 2023;10(2):99-101.
Abbas ZG, Archibald LK. Tropical diabetic hand syndrome. Epidemiology, pathogenesis, and management. Am J Clin Dermatol. 2005;6(1):21-28. Available from: https://pubmed.ncbi.nlm.nih.gov/15675887/
Tiwari S, Chauhan A, Sethi NT. Tropical diabetic hand syndrome. Int J Diabetes Dev Ctries. 2008 Oct;28(4):130-1. Available from: /pmc/articles/PMC2822157/
Usher-Smith JA, Thompson M, Ercole A, Walter FM. Variation between countries in the frequency of diabetic ketoacidosis at first presentation of type 1 diabetes in children: a systematic review. Diabetologia. 2012;55(11):2878-2894. Available from: https://pubmed.ncbi.nlm.nih.gov/22933123/
Tan H, Zhou Y, Yu Y. Characteristics of diabetic ketoacidosis in Chinese adults and adolescents -- a teaching hospital-based analysis. Diabetes Res Clin Pract. 2012;97(2):306-312. Available from: https://pubmed.ncbi.nlm.nih.gov/ 22704172/
Musoma SN, Omar A, Mutai BC, Laigong P. Outcomes of Children and Adolescents Admitted with Diabetic Ketoacidosis at Kenyatta National Hospital (KNH), Kenya. J Diabetes Res. 2020;2020:8987403.
Unnikrishnan A, Kumaran S, Kalra S. Fibrocalculous Pancreatic Diabetes. Endotext [Updated 2024 Sep 13]. In: Feingold KR, Anawalt B, Blackman MR, et al., editors. Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000- Available from: https://www.ncbi.nlm.nih.gov/books/NBK578126/
Ahluwalia A, Sood A, Sood A, Lakshmy R, Kapil A, Pandey RM. Nasal colonization with Staphylococcus aureus in patients with diabetes mellitus. Diabet Med. 2000;17(6):487-488. Available from: https://pubmed.ncbi. nlm.nih.gov/10975221/
Forslund K, Hildebrand F, Nielsen T, Falony G, Le Chatelier E, Sunagawa S, et al. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature. 2017 May 3;545(7652):116. Available from: https://pubmed.ncbi.nlm.nih.gov/26633628/
Hulme KD, Gallo LA, Short KR. Influenza Virus and Glycemic Variability in Diabetes: A Killer Combination? Front Microbiol. 2017;8:861. Available from: https://pubmed.ncbi.nlm.nih.gov/28588558/
Hodgson K, Morris J, Bridson T, Govan B, Rush C, Ketheesan N. Immunological mechanisms contributing to the double burden of diabetes and intracellular bacterial infections. Immunology. 2015;144(2):171-185. Available from: https://pubmed.ncbi.nlm.nih.gov/25262977/
Roberts AC, Porter KE. Cellular and molecular mechanisms of endothelial dysfunction in diabetes. Diab Vasc Dis Res. 2013;10(6):472-482. Available from: https://pubmed.ncbi.nlm.nih.gov/24002671/
Singh V, Sharma B, Sen R, Agrawal S, Bhagol A, Bali R. Rhinocerebral mucormycosis: a diagnostic challenge and therapeutic dilemma in immunocompetent host. J Oral Maxillofac Surg. 2012;70(6):1369-1375. Available from: https://pubmed.ncbi.nlm.nih.gov/21864966/
Siu LK, Yeh KM, Lin JC, Fung CP, Chang FY. Lancet Infect Dis. 2012;12(11):881-887. Available from: https://pubmed.ncbi.nlm.nih. gov/23099082/
Hirji I, Guo Z, Andersson SW, Hammar N, Gomez-Caminero A. Incidence of urinary tract infection among patients with type 2 diabetes in the UK General Practice Research Database (GPRD). J Diabetes Complications. 2012;26(6):513-516. Available from: https://pubmed.ncbi.nlm. nih.gov/22889712/
Kornum JB, Thomsen RW, Riis A, Lervang HH, Schønheyder HC, Sørensen HT. Type 2 diabetes and pneumonia outcomes: a population-based cohort study. Diabetes Care. 2007;30(9):2251-2257. Available from: https://pubmed.ncbi.nlm.nih.gov/17595354/
Jeon CY, Murray MB. Diabetes mellitus increases the risk of active tuberculosis: a systematic review of 13 observational studies. PLoS Med. 2008;5(7):e152. Available from: https://pubmed.ncbi.nlm.nih.gov/18630984/
Magee MJ, Salindri AD, Kyaw NTT, Auld SC, Haw JS, Umpierrez GE. Stress Hyperglycemia in Patients with Tuberculosis Disease: Epidemiology and Clinical Implications. Curr Diab Rep. 2018;18(9):71. Available from: https://pubmed.ncbi.nlm.nih.gov/30090969/
Restrepo BI. Diabetes and Tuberculosis. Schlossberg D, editor. Microbiol Spectr. 2016;4(6).10.1128. Available from: https://pubmed.ncbi. nlm.nih.gov/28084206/
World Health Organization (WHO) - Global tuberculosis report 2023. Available from: https://iris.who.int/.
Jenjaroen K, Chumseng S, Sumonwiriya M, Ariyaprasert P, Chantratita N, Sunyakumthorn P, et al. T-Cell Responses Are Associated with Survival in Acute Melioidosis Patients. PLoS Negl Trop Dis. 2015;9(10):e0004152. Available from: https://pubmed.ncbi.nlm.nih.gov/26495852/
Liu X, Foo G, Lim WP, Ravikumar S, Sim SH, Win MS, et al. Sulphonylurea usage in melioidosis is associated with severe disease and suppressed immune response. PLoS Negl Trop Dis. 2014;8(4):e2795. Available from: https://pubmed.ncbi.nlm.nih.gov/24762472/
Park SW, Lee CS, Lee CK, Kwak YG, Moon C, Kim BN, et al. Severity predictors in eschar-positive scrub typhus and role of serum osteopontin. Am J Trop Med Hyg. 2011;85(5):924-30. Available from: https://pubmed.ncbi.nlm. nih.gov/22049051/
Mehta P, Hotez PJ. NTD and NCD Co-morbidities: The Example of Dengue Fever. PLoS Negl Trop Dis. 2016;10(8):e0004619. Available from: https://pubmed.ncbi.nlm.nih.gov/27561091/
Htun NSN, Odermatt P, Eze IC, Boillat-Blanco N, D’Acremont V, Probst-Hensch N. Is diabetes a risk factor for a severe clinical presentation of dengue?--review and meta-analysis. PLoS Negl Trop Dis. 2015;9(4):e0003741. Available from: https://pubmed.ncbi.nlm.nih.gov/25909658/
Toledo J, George L, Martinez E, Lazaro A, Han WW, Coelho GE, et al. Relevance of Non-communicable Comorbidities for the Development of the Severe Forms of Dengue: A Systematic Literature Review. PLoS Negl Trop Dis. 2016;10(1):e0004284. Available from: https://pubmed.ncbi.nlm. nih.gov/26727113/
Lindsey NP, Staples JE, Lehman JA, Fischer M. Medical risk factors for severe West Nile Virus disease, United States, 2008-2010. Am J Trop Med Hyg. 2012;87(1):179-84. Available from: https://pubmed.ncbi.nlm.nih.gov/22764311/
Jean-Baptiste E, Von Oettingen J, Larco P, Raphaël F, Larco NC, Cauvin MM, et al. Chikungunya Virus Infection and Diabetes Mellitus: A Double Negative Impact. Am J Trop Med Hyg. 2016;95(6):1345-1350. Available from: https://pubmed.ncbi.nlm.nih.gov/27729569/
Yang JK, Feng Y, Yuan MY, Yuan SY, Fu HJ, Wu BY, et al. Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS. Diabet Med. 2006;23(6):623-8. Available from: https://pubmed.ncbi.nlm.nih.gov/16759303/
Assiri A, Al-Tawfiq JA, Al-Rabeeah AA, Al-Rabiah FA, Al-Hajjar S, Al-Barrak A, et al. Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: a descriptive study. Lancet Infect Dis. 2013;13(9):752-61. Available from: https://pubmed.ncbi.nlm.nih.gov/23891402/
Ali MK, Magee MJ, Dave JA, Ofotokun I, Tungsiripat M, Jones TK, et al. HIV and metabolic, body, and bone disorders: what we know from low- and middle-income countries. J Acquir Immune Defic Syndr. 2014;67(S1):27-39. Available from: https://pubmed.ncbi.nlm.nih.gov/25117959/
Lo YC, Chen MY, Sheng WH, Hsieh SM, Sun HY, Liu WC, et al. Risk factors for incident diabetes mellitus among HIV-infected patients receiving combination antiretroviral therapy in Taiwan: a case-control study. HIV Med. 2009;10(5):302-309. Available from: https://pubmed.ncbi.nlm.nih.gov/19220492/
Danquah I, Bedu-Addo G, Mockenhaupt FP. Type 2 diabetes mellitus and increased risk for malaria infection. Emerg Infect Dis. 2010;16(10):1601-1604. Available from: https://pubmed.ncbi.nlm.nih.gov/20875289/
dos Santos VM, da Cunha SF, Teixeira Vde P, et al. Freqüência de diabetes mellitus e hiperglicemia em mulheres chagásicas e não-chagásicas [Frequency of diabetes mellitus and hyperglycemia in chagasic and non-chagasic women]. Rev Soc Bras Med Trop. 1999;32(5):489-496. Available from: https://pubmed.ncbi.nlm.nih.gov/10881081/
Sharquie KE, Najim RA, Hussein AK. Reinfestation in cutaneous leishmaniasis: a new look at predisposing conditions. Saudi Med J. 2000;21(5):464-467. Available from: https://pubmed.ncbi.nlm.nih.gov/11500682/
Cooke A, Tonks P, Jones FM, O’Shea H, Hutchings P, Fulford AJC, et al. Infection with Schistosoma mansoni prevents insulin dependent diabetes mellitus in non-obese diabetic mice. Parasite Immunol. 1999;21(4):169-176. Available from: https://pubmed.ncbi.nlm.nih.gov/10320614/
Taborda CP, Muñoz JE, Gonzalez A. Editorial: Tropical fungal diseases. Front Cell Infect Microbiol. 2022;12:1104519.
Singhal I, Arora M, Dave A, Saluja P. Diabetes and Fungal Infection - A Didactic Relationship. J clin and diag res. 2023;17(4):1-4.
Yadav S, Day JP, Mohan V, Snehalatha C, Braganza JM. Selenium and Diabetes in the Tropics. Pancreas. 1991;6(5):528-533.
Mohan V, Chari ST, Hitman GA, Suresh S, Madanagopalan N, Ramachandran A, et al. Familial aggregation in tropical fibrocalculous pancreatic diabetes. Pancreas. 1989;4(6):690-693. Available from: https://pubmed.ncbi.nlm. nih.gov/2813331/
Ghosh I, Mukhopadhyay P, Das K, Anne M B, Ali Mondal S, Basu M, et al. Incretins in fibrocalculous pancreatic diabetes: A unique subtype of pancreatogenic diabetes. J Diabetes. 2021;13(6):506-511.
Mohan V, Barman KK, Rajan VS, Chari ST, Deepa R. Natural history of endocrine failure in tropical chronic pancreatitis: a longitudinal follow-up study. J Gastroenterol Hepatol. 2005;20(12):1927-1934. Available from: https://pubmed.ncbi.nlm.nih.gov/16336455/
Unnikrishnan R, Mohan V. Fibrocalculous Pancreatic Diabetes. Current Diabetes Reports. 2020;20:19.
Shivaprasad C, Anish K, Aiswarya Y, Atluri S, Rakesh B, Anupam B, et al. A comparative study of the clinical profile of fibrocalculous pancreatic diabetes and type 2 diabetes mellitus. Diabetes Metab Syndr. 2019;13(2):1511-1516. Available from: https://pubmed.ncbi.nlm.nih.gov/31336514/
Beatrice Anne M, Chakraborty P, Mukhopadhyay P, Ghosh S. Periodontal disease in fibrocalculous pancreatic diabetes (FCPD): common complication of an uncommon disease. Int J Diabetes Dev Ctries. 2023;43(5):709–14. Available from: https://link.springer.com/article/10.1007/s13410-022-01148-2
Dasgupta R, Jebasingh FK, Anoop S, Seenivasan S, Kurian ME, Christina F, et al. Comprehensive evaluation of patterns of hypoglycemia unawareness (HUA) and glycemic variability (GV) in patients with fibrocalculous pancreatic diabetes (FCPD): A cross-sectional study from South India. PLoS One. 2022;17(7):e0270788. Available from: /pmc/articles/PMC9275701/
Chari ST, Mohan V, Pitchumoni CS, Viswanathan M, N. Madanagopalan, Lowenfels AB. Risk of pancreatic carcinoma in tropical calcifying pancreatitis: an epidemiologic study. Pancreas. 1994;9(1):62-66. Available from: https://pubmed.ncbi.nlm.nih.gov/8108373/
Baekdal M, Nielsen SW, Hansen CP, Storkholm JH, Van Hall G, Hartmann B, et al. Empagliflozin Normalizes Fasting Hyperglycemia and Improves Postprandial Glucose Tolerance in Totally Pancreatectomized Patients: A Randomized, Double-Blind, Placebo-Controlled Crossover Study. Diabetes Care. 2024;47(1):71-80. Available from: https://pubmed.ncbi.nlm.n nih.gov/37703527/
Ghosh I, Basu M, Anne B, Mukhopadhyay P, Ghosh S. Exocrine Pancreatic Dysfunction in Diabetes: An Observational Study. Indian J Endocrinol Metab. 2021;25(1):67-68. Available from: /pmc/articles/PMC8323623/
Palathingal Bava E, George J, Iyer S, Sahay P, Tarique M, Jain T, et al. Pirfenidone ameliorates chronic pancreatitis in mouse models through immune and cytokine modulation. Pancreatology. 2022;22(5):553-563. Available from: https://pubmed.ncbi.nlm.nih.gov/35570091/

Genetic Obesity Syndromes

ABSTRACT

Genetic factors play a major role in the regulation of body weight and in the susceptibility to obesity in the population. A subset of people with severe obesity carry rare, highly penetrant genetic variants that can result in severe childhood-onset obesity. Current estimates suggest that up to 20% of children with severe obesity may carry pathogenic chromosomal abnormalities or mutations. The diagnosis of a genetic obesity syndrome can provide information that has value for the patient and their family and may help them deal with the social stigma that comes with severe obesity in childhood. In an increasing number of cases, the finding of a genetic cause for a patient’s obesity can inform clinical care and the use of targeted therapies.

INTRODUCTION

At a population level, obesity is driven by an increase in the intake of easily available, energy-dense, highly palatable foods and a decrease in physical activity at school/work and in leisure time. However, variation in body mass index (BMI: weight in kg/height in meters squared) within the population is influenced by genetic factors (1,2). Studies in twins and families have shown that food intake, satiety responsiveness (fullness after a fixed meal), basal metabolic rate, the amount of energy utilized during a fixed amount of exercise, and body fat distribution are all heritable traits (3).

Genome-wide association studies (GWAS’s) in large population-based cohorts have identified thousands of common variants (minor allele frequency > 5%) that are associated with BMI and/or obesity (4). While individually each variant often has a small effect on BMI, cumulatively, the effect of millions of common and rare variants can now be combined to compute a polygenic risk score which can predict the development of severe obesity (5). Studies are ongoing to test how such scores might be useful in the clinical setting. Most common obesity associated variants lie in noncoding areas of the genome so identifying the mechanism by which they affect body weight can be challenging. It is interesting to note that most obesity- or BMI-associated variants lie in or near genes which are expressed in the brain and some of these variants have been associated with increased food intake (4,6). In contrast, GWAS associations for body fat distribution/waist-to-hip ratio, mostly seem to be linked to genes expressed in adipose tissue (7).

CLINICAL APPROACH TO DIAGNOSIS OF GENETIC OBESITY SYNDROMES

Rare (less than 1% minor allele frequency), highly penetrant genetic variants in multiple genes have been associated with severe obesity that often presents in childhood. Whilst these disorders are rare, cumulatively up to 20% of children with severe obesity have chromosomal abnormalities or other penetrant rare variants that drive their obesity (8). The assessment of children and adults with severe obesity should be directed at screening for endocrine, neurological, and genetic disorders (9). Important information can be obtained from a detailed family history to identify potential consanguineous relationships, the presence of other family members with severe obesity and those who have had bariatric surgery, and the ethnic origin of family members (Figure 1). The clinical history and examination can then guide the appropriate use of diagnostic tests. For the purposes of clinical assessment, it remains useful to categorize the genetic obesity syndromes as those with and without associated developmental delay.

Figure 1. Diagnosis of genetic obesity syndromes.

OBESITY SYNDROMES WITHOUT DEVELOPMENTAL DELAY

The adipocyte-derived hormone leptin acts mainly to defend against starvation (10), with a fall in leptin levels (as seen in weight loss, acute caloric restriction or congenital leptin deficiency) causing an increase in food intake and physiological responses that act to restore energy balance (11). In most people, circulating leptin levels correlate closely with fat mass (12), although there is considerable variation in leptin levels at any given BMI, which is as yet unexplained. Leptin signals through the long isoform of the leptin receptor, which is widely expressed in the hypothalamus and other brain regions involved in energy homeostasis (13). In the arcuate nucleus of the hypothalamus (which has a permeable blood-brain barrier), there are several neuronal populations known to be important in weight regulation expressing the leptin receptor. In the fed state, leptin stimulates the expression of pro-opiomelanocortin (POMC), which is processed to generate the melanocortin peptides that, in turn, activate the melanocortin 4 receptor (MC4R) on second-order neurons in the paraventricular nucleus. Leptin also inhibits adjacent neurons containing Agouti-related protein (AgRP), a MC4R antagonist. The integration of these two actions leads to reduced food intake (Figure 2). In the fasted state and with weight loss, a drop in leptin levels reduces the activation state of POMC neurons and increases AgRP signaling to cause an increase in food intake. These hypothalamic pathways interact with other brain centers to affect not just eating behaviors but also energy expenditure.

Severe obesity can result from mutations that disrupt key components of the leptin-melanocortin pathway (Figure 2). People with these genetic disorders experience an intense drive to eat (hunger), find food to be highly rewarding, and have impaired fullness (satiety) leading to hyperphagia (increased food intake), resulting in excessive weight gain from early childhood.

Figure 2. Genes involved in the leptin-melanocortin pathway whose disruption causes obesity.

Leptin and Leptin Receptor Deficiency

Congenital leptin (LEP protein; LEP gene) and leptin receptor (LEPR protein; LEPR gene) deficiency are rare, autosomal recessive disorders associated with severe obesity from a very young age (before 1 year) (14,15). Homozygous frameshift, nonsense, and missense mutations involving LEP and LEPR have been identified in 1% and 2-3% of patients with severe obesity from consanguineous families, respectively (16-18). Leptin receptor mutations have been found in some non-consanguineous families, where both parents were unrelated but carried rare heterozygous variants.

Serum leptin is a useful test in patients with severe early onset obesity as an undetectable serum leptin suggests a diagnosis of congenital leptin deficiency. Very rare mutations that result in a detectable but bio-inactive form of leptin or a form of leptin that antagonizes the leptin receptor, have also been described (19,20). Serum leptin concentrations are appropriate for the degree of obesity in leptin receptor deficiency and as such an elevated serum leptin concentration is not necessarily a predictor of leptin receptor deficiency (17). In some patients, particular LEPR mutations that result in abnormal cleavage of the extracellular domain of LEPR (which then acts as a leptin binding protein), are associated with markedly elevated leptin levels (15).

The clinical phenotypes associated with leptin and leptin receptor deficiencies are similar. Patients are born of normal birth weight, experience intense hyperphagia with food seeking behavior and rapid weight gain in the first few months of life resulting in severe obesity (16). While measurable changes in resting metabolic rate or total energy expenditure have not been demonstrated in affected individuals, reduced sympathetic nerve function is associated with impaired fat oxidation and may contribute to obesity (21). Children with leptin deficiency have abnormalities of T cell number and function (16), consistent with reported high childhood infection rates and childhood mortality from infection, particularly in environments where infectious diseases are prevalent (21).

In keeping with severe obesity, patients with leptin and leptin receptor deficiency are hyperinsulinemic and some adults develop type 2 diabetes in the 3^rd to 4^th decade. Affected individuals can exhibit hypothalamic (secondary) hypothyroidism characterized by low free thyroxine levels and inappropriately normal (or high-normal) levels of serum thyroid stimulating hormone (TSH) (14,15). Typically, adults with leptin or leptin receptor deficiency have biochemical evidence of hypogonadotropic hypogonadism and do not undergo normal pubertal development (see below). However, there are reports of delayed spontaneous onset of menses in some leptin and leptin receptor deficient adults (17). Linear growth is appropriate in childhood, but in the absence of a pubertal growth spurt, final height is reduced.

Although leptin deficiency is very rare, it is entirely treatable with daily subcutaneous injections of recombinant human leptin (16,22). The major effect of leptin replacement in these patients is on food intake, with normalization of hyperphagia and enhanced satiety. Leptin administration does not enhance energy expenditure. However, weight loss by caloric restriction is associated with decreased total energy expenditure; the absence of this decrease in patients with congenital leptin deficiency, suggests that leptin does affect energy expenditure (23). Leptin replacement permits progression of appropriately-timed pubertal development, along with expression of secondary sexual characteristics (21). These reproductive system effects are likely mediated through leptin action on hypothalamic neurons containing kisspeptin, which signals via GPR54 to modify the release of gonadotrophin-releasing hormone (24).

Although leptin treatment is not be effective for patients with LEPR deficiency, these patients can now treated with a melanocortin receptor agonist (setmelanotide, Figure 3), which is now licensed in the UK, Europe and USA (25).

Leptin treatment is not clinically effective in people with common obesity (26,27), which may be a manifestation of leptin resistance or defects in downstream neuronal pathways. Studies in heterozygous carriers of LEP mutations who have partial leptin deficiency and an increase in fat mass (28), suggest that people with relatively low leptin levels may benefit from leptin therapy.

Pro-opiomelanocortin Deficiency

Due to impaired production of melanocortin stimulating hormone peptides (a/b MSH) and diminished or absent MC4R signaling (Figure 2), homozygous or compound heterozygous mutations in POMC cause hyperphagia and early-onset obesity (29). People deficient in POMC also have pale skin and red or light colored hair due to the lack of signaling of pigment-inducing melanocortin 1 receptors in the skin (29). In the pituitary gland, POMC is the precursor for adrenocorticotrophin (ACTH). As such, complete POMC deficiency presents in neonatal life with features of ACTH and cortisol deficiency: hypoglycemia and cholestatic jaundice requiring long-term corticosteroid replacement therapy (30). Typically, patients with primary or secondary cortisol deficiency present with hypophagia and weight loss, so adrenal insufficiency with hyperphagia in the absence of a structural hypothalamic abnormality should raise suspicion for a POMC defect. POMC deficiency may also impair the timing of puberty, an effect that appears to be mediated by the melanocortin 3 receptor (MC3R) (31).

Complete POMC deficiency can be treated with a melanocortin receptor agonist (setmelanotide) (32) (Figure 3). Heterozygous missense mutations directly affecting the function of POMC peptides have been described (Figure 2) (33). These variants significantly increase obesity risk but are not invariably associated with obesity. The potential efficacy of MC4R agonists in patients with these heterozygous mutations is currently being tested in clinical trials.

Figure 3. Medical treatment of patients with genetic obesity syndromes. POMC: pro-opiomelanocortin. PCSK1: prohormone convertase-1. MC4R: melanocortin 4 receptor. GLP-1: glucagon receptor-1.

Prohormone Convertase-1-Deficiency

Prohormone convertase-1 (PCSK1, also known as PC1/3) is an enzyme that acts upon a range of substrates including proinsulin, proglucagon, and POMC. Compound heterozygous or homozygous mutations in PCSK1 cause neonatal small bowel enteropathy, glucocorticoid deficiency (secondary to ACTH deficiency), hypogonadotropic hypogonadism, and postprandial hypoglycemia due to impaired processing of proinsulin to insulin, as well as severe, early onset obesity (34,35). Elevated plasma levels of proinsulin and 32/33 split proinsulin in the context of low levels of mature insulin are diagnostic for this disorder. Setmelanotide is now licensed for the treatment of this condition (Figure 3).

Melanocortin 4 Receptor Deficiency

Heterozygous melanocortin 4 receptor (MC4R) mutations have been reported in people with obesity from various ethnic groups (www.mc4r.org.uk) and occur at a frequency of 1 in 300 people in the population (36), 1% of adults with a BMI > 30 kg/m², and 3-5% of children with severe obesity (37,38). MC4R mutations are inherited in a co-dominant manner, with variable penetrance and expression; homozygous mutations have also been reported. In several studies, MC4R deficiency is the most common genetic form of obesity (37-39).

Given the importance of MC4R for leptin signaling (Figure 2), the clinical features of MC4R deficiency include hyperphagia and rapid weight gain, which often emerges in the first few years of life. Alongside the increase in fat mass, MC4R-deficient subjects also have an increase in lean mass and a marked increase in bone mineral density that exceeds what would be expected for their increased body size and, thus, they often appear “big-boned” (37). They exhibit accelerated linear growth in early childhood, which may be a consequence of disproportionate early hyperinsulinemia and effects on pulsatile growth hormone (GH) secretion, which is retained in MC4R-deficient adults in contrast to common forms of obesity (40). Despite this early hyperinsulinemia, adult subjects with obesity who are heterozygous for mutations in the MC4R gene have a comparable risk of developing impaired glucose intolerance and type 2 diabetes to controls of similar age and adiposity. Reduced sympathetic nervous system activity in MC4R-deficient patients is likely to explain the lower prevalence of hypertension and lower systolic and diastolic blood pressures compared to control populations (41). Thus, central melanocortin signaling appears to play an important role in the regulation of blood pressure and its coupling to changes in weight.

At present, there is no specific therapy for MC4R deficiency, but patients with heterozygous MC4R mutations do respond to Glucagon-like peptide- (GLP-1) receptor agonists (42) and to Roux-en-Y-bypass surgery (43) (Figure 3), with a variation in weight loss response that is comparable to people with a normal MC4R gene sequence.

Albright’s Hereditary Osteodystrophy/Pseudohypoparathyroidism

Albright hereditary osteodystrophy (AHO) is an autosomal dominant disorder due to germline mutations in GNAS, an imprinted gene that encodes the G alpha s (Gs) protein, which mediates signaling by multiple G-protein coupled receptors (GPCRs). Classically, heterozygous loss-of-function mutations in GNAS affecting the maternal allele lead to short stature, obesity, skeletal defects, and resistance to several hormones that activate Gs in their target tissues (pseudohypoparathyroidism type IA), while paternal transmission leads only to the AHO phenotype (pseudopseudohypoparathyroidism) (44). GNAS mutations affect coupling to, or signaling by, MC4R, which explains hyperphagia and obesity in affected patients (45). Some patients will carry mutations that affect signaling by other GPCRs including the beta-2 and beta-3 adrenoreceptors which contribute to low basal metabolic rate and other clinical phenotypes (45). These patients may not have classical features such as short stature. As such, this diagnosis should be considered in all patients with severe early-onset obesity (45).

SRC Homology 2B (SH2B1) 1 Deficiency

Deletion of a 220-kb segment of chromosome 16p11.2 is associated with highly penetrant, severe, early-onset obesity and insulin resistance (46). This deletion includes a small number of genes, one of which is SH2B1 (Src homology 2B1)known to be involved in leptin, insulin, and Brain-Derived Neurotrophic Factor (BDNF) signaling. These patients gain weight in the first years of life, with hyperphagia and fasting plasma insulin levels that are disproportionately elevated, with increased risk for type 2 diabetes in early adulthood (47). In some patients loss of function mutations in the SH2B1 gene have also been reported in association with early-onset obesity, severe insulin resistance, and behavioral abnormalities (48).

OBESITY SYNDROMES WITH DEVELOPMENTAL DELAY

Prader-Willi Syndrome

Prader-Willi syndrome is an autosomal dominant disorder caused by deletion or disruption of a paternally imprinted region on chromosome 15q11.2-q12 (49) The clinical features of Prader-Willi syndrome (PWS) include diminished fetal activity, hypotonia, and feeding difficulties in infancy followed by hyperphagia, obesity, developmental delay, short stature, hypogonadotropic hypogonadism, and small hands and feet (Figure 4). Children with PWS display diminished growth, reduced lean body mass and increased fat mass. These body composition abnormalities can be explained, in part, by growth hormone (GH) deficiency and improved with growth hormone treatment, which should be started in early childhood.

Figure 4. Infancy and childhood clinical features of Prader-Willi Syndrome (PWS).

Contained within the 4.5Mb PWS region in 15q11-q13 are silenced paternally imprinted genes and a family of small nucleolar RNAs (snoRNAs) known as the HBII-85 snoRNAs. Small deletions exclusively encompassing these snoRNAs result in the key features of PWS including obesity (Figure 4) (50,51) suggesting that these snoRNAs play a critical role in the development of this syndrome. Histopathological studies on post-mortem brain samples from PWS patients have demonstrated reduced levels of oxytocin expression in the hypothalamus (52) and trials of intranasal administration in PWS are ongoing (53). Brain-derived neurotrophic factor (BDNF) expression is also reduced in PWS, potentially contributing to both the obesity and neurobehavioral features including stereotyped behaviors (54).

Bardet Biedl Syndrome

Bardet-Biedl syndrome (BBS) is a rare, autosomal recessive disease caused by mutations in over 25 genes and characterized by obesity, developmental delay, syndactyly, brachydactyly or polydactyly, retinal dystrophy or pigmentary retinopathy, hypogonadism, and structural abnormalities of the kidney or renal impairment (55). The differential diagnosis includes Biemond syndrome II (iris coloboma, hypogenitalism, obesity, polydactyly) and Alstrom syndrome (retinitis pigmentosa, obesity, diabetes mellitus, and deafness). To date, BBS proteins are all involved in basal body and centrosomal function and impact on ciliary development and transport (56). There is some evidence that BBS genes affect leptin signaling and trafficking of MC4Rs in cilia. Clinical trials of setmelanotide have shown some benefit in treating hyperphagia in these patients (57) and this drug is licensed for BBS in some countries (Figure 3).

Brain-Derived neurotrophic factor (BDNF) activates signaling by the tropomycin-related kinase B (TrkB) to play a key role in the development and maintenance of neurons. Rare chromosomal rearrangements and heterozygous point mutations in BDNF and TrkB are associated with speech and language delay, hyperphagia, and impaired pain sensation (58-60). Disordered behaviors including hyperactivity, fearlessness, anxiety, and aggression are also features of these conditions, which can often present as de-novo genetic abnormalities (61).

Single Minded 1 Deficiency

Single minded 1 (SIM1) is a transcription factor involved in the development of the paraventricular and supraoptic nuclei of the hypothalamus. Chromosomal rearrangements and heterozygous missense mutations in SIM1 and in a closely related transcription factor OTP (Orthopedia) cause severe obesity (62-64). Clinical features of these patients resemble those seen in MC4R deficiency with, in addition, a variable phenotype of developmental delay with autistic like features noted in some, but not all, patients (63).

Other Rare Genetic Mutations

Rare penetrant variants in multiple genes can be associated with, but do not invariably cause, obesity that is inherited in a classical Mendelian manner (Figure 2). Examples include heterozygous loss of function variants affecting the Semaphorin 3 ligands, receptors and co-receptors that direct the development of POMC projections (65); mutations in Steroid receptor coactivator-1 (SRC-1) (66) and Pleckstrin-homology-domain interacting protein, PHIP, which modulate POMC transcription (67); disruption of Serotonin 2c receptor, HTR2C which regulates the electrical activity of POMC neurons causing obesity, social anxiety and impaired memory (68,69) and deletions affecting TRPC5 on the X chromosome, which cause obesity, anxiety, autism (in males), and postnatal depression (in females) (70). Variants in genes that regulate MC4R trafficking (MRAP2) (71) and genes whose precise function in the hypothalamus is not as yet clear, such as Kinase Suppressor of Ras-2 (KSR2) (72) have also been associated with obesity.

FUTURE PERSPECTIVES

The diagnosis of a genetic obesity syndrome can provide information that has diagnostic value for the family to whom genetic counselling can be provided. A genetic diagnosis can help children and their families deal with the social stigma that comes with severe obesity and, in some instances, has prevented children from being taken into care by social services when obesity is blamed on parental neglect. A genetic diagnosis can inform management (many such patients are relatively refractory to weight loss through changes in diet and exercise) and can inform clinical decision-making. For example, bariatric surgery (particularly Roux-en-Y bypass surgery) is contraindicated in many genetic obesity syndromes as it does not reverse the strong hypothalamic drive to eat and continued overeating can be harmful. Importantly, an increasing number of genetic obesity syndromes are now treatable with mechanism-based pharmacologic therapies.

REFERENCES

Maes HH, Neale MC, Eaves LJ. Genetic and environmental factors in relative body weight and human adiposity. Behav Genet. 1997;27(4):325-351.
Stunkard AJ HJ, Pedersen NL, McClearn GE. The body-mass index of twins who have been reared apart. N Engl J Med. 1990;322:1483-1487.
Bouchard C. Genetics of Obesity: What We Have Learned Over Decades of Research. Obesity (Silver Spring).2021;29(5):802-820.
Loos RJF, Yeo GSH. The genetics of obesity: from discovery to biology. Nature reviews Genetics. 2022;23(2):120-133.
Khera AV, Chaffin M, Wade KH, Zahid S, Brancale J, Xia R, Distefano M, Senol-Cosar O, Haas ME, Bick A, Aragam KG, Lander ES, Smith GD, Mason-Suares H, Fornage M, Lebo M, Timpson NJ, Kaplan LM, Kathiresan S. Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood. Cell. 2019;177(3):587-596 e589.
Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J, Croteau-Chonka DC, Esko T, Fall T, Ferreira T, Gustafsson S, Kutalik Z, Luan J, Magi R, Randall JC, Winkler TW, Wood AR, Workalemahu T, Faul JD, Smith JA, Zhao JH, Zhao W, Chen J, Fehrmann R, Hedman AK, Karjalainen J, Schmidt EM, Absher D, Amin N, Anderson D, Beekman M, Bolton JL, Bragg-Gresham JL, Buyske S, Demirkan A, Deng G, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Goel A, Gong J, Jackson AU, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Mangino M, Leach IM, Medina-Gomez C, Medland SE, Nalls MA, Palmer CD, Pasko D, Pechlivanis S, Peters MJ, Prokopenko I, Shungin D, Stancakova A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet-Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Isaacs A, Albrecht E, Arnlov J, Arscott GM, Attwood AP, Bandinelli S, Barrett A, Bas IN, Bellis C, Bennett AJ, Berne C, Blagieva R, Bluher M, Bohringer S, Bonnycastle LL, Bottcher Y, Boyd HA, Bruinenberg M, Caspersen IH, Chen YI, Clarke R, Daw EW, de Craen AJM, Delgado G, Dimitriou M, Doney ASF, Eklund N, Estrada K, Eury E, Folkersen L, Fraser RM, Garcia ME, Geller F, Giedraitis V, Gigante B, Go AS, Golay A, Goodall AH, Gordon SD, Gorski M, Grabe HJ, Grallert H, Grammer TB, Grassler J, Gronberg H, Groves CJ, Gusto G, Haessler J, Hall P, Haller T, Hallmans G, Hartman CA, Hassinen M, Hayward C, Heard-Costa NL, Helmer Q, Hengstenberg C, Holmen O, Hottenga JJ, James AL, Jeff JM, Johansson A, Jolley J, Juliusdottir T, Kinnunen L, Koenig W, Koskenvuo M, Kratzer W, Laitinen J, Lamina C, Leander K, Lee NR, Lichtner P, Lind L, Lindstrom J, Lo KS, Lobbens S, Lorbeer R, Lu Y, Mach F, Magnusson PKE, Mahajan A, McArdle WL, McLachlan S, Menni C, Merger S, Mihailov E, Milani L, Moayyeri A, Monda KL, Morken MA, Mulas A, Muller G, Muller-Nurasyid M, Musk AW, Nagaraja R, Nothen MM, Nolte IM, Pilz S, Rayner NW, Renstrom F, Rettig R, Ried JS, Ripke S, Robertson NR, Rose LM, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Scott WR, Seufferlein T, Shi J, Smith AV, Smolonska J, Stanton AV, Steinthorsdottir V, Stirrups K, Stringham HM, Sundstrom J, Swertz MA, Swift AJ, Syvanen AC, Tan ST, Tayo BO, Thorand B, Thorleifsson G, Tyrer JP, Uh HW, Vandenput L, Verhulst FC, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Warren HR, Waterworth D, Weedon MN, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q, LifeLines Cohort S, Brennan EP, Choi M, Dastani Z, Drong AW, Eriksson P, Franco-Cereceda A, Gadin JR, Gharavi AG, Goddard ME, Handsaker RE, Huang J, Karpe F, Kathiresan S, Keildson S, Kiryluk K, Kubo M, Lee JY, Liang L, Lifton RP, Ma B, McCarroll SA, McKnight AJ, Min JL, Moffatt MF, Montgomery GW, Murabito JM, Nicholson G, Nyholt DR, Okada Y, Perry JRB, Dorajoo R, Reinmaa E, Salem RM, Sandholm N, Scott RA, Stolk L, Takahashi A, Tanaka T, van 't Hooft FM, Vinkhuyzen AAE, Westra HJ, Zheng W, Zondervan KT, Consortium AD, Group A-BW, Consortium CAD, Consortium CK, Glgc, Icbp, Investigators M, Mu TC, Consortium MI, Consortium P, ReproGen C, Consortium G, International Endogene C, Heath AC, Arveiler D, Bakker SJL, Beilby J, Bergman RN, Blangero J, Bovet P, Campbell H, Caulfield MJ, Cesana G, Chakravarti A, Chasman DI, Chines PS, Collins FS, Crawford DC, Cupples LA, Cusi D, Danesh J, de Faire U, den Ruijter HM, Dominiczak AF, Erbel R, Erdmann J, Eriksson JG, Farrall M, Felix SB, Ferrannini E, Ferrieres J, Ford I, Forouhi NG, Forrester T, Franco OH, Gansevoort RT, Gejman PV, Gieger C, Gottesman O, Gudnason V, Gyllensten U, Hall AS, Harris TB, Hattersley AT, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Homuth G, Hovingh GK, Humphries SE, Hunt SC, Hypponen E, Illig T, Jacobs KB, Jarvelin MR, Jockel KH, Johansen B, Jousilahti P, Jukema JW, Jula AM, Kaprio J, Kastelein JJP, Keinanen-Kiukaanniemi SM, Kiemeney LA, Knekt P, Kooner JS, Kooperberg C, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Marchand LL, Lehtimaki T, Lyssenko V, Mannisto S, Marette A, Matise TC, McKenzie CA, McKnight B, Moll FL, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Madden PAF, Pasterkamp G, Peden JF, Peters A, Postma DS, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ridker PM, Rioux JD, Ritchie MD, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schunkert H, Schwarz PEH, Sever P, Shuldiner AR, Sinisalo J, Stolk RP, Strauch K, Tonjes A, Tregouet DA, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Volker U, Waeber G, Willemsen G, Witteman JC, Zillikens MC, Adair LS, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bornstein SR, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PIW, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hui J, Hunter DJ, Hveem K, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, Marz W, Melbye M, Metspalu A, Moebus S, Munroe PB, Njolstad I, Oostra BA, Palmer CNA, Pedersen NL, Perola M, Perusse L, Peters U, Power C, Quertermous T, Rauramaa R, Rivadeneira F, Saaristo TE, Saleheen D, Sattar N, Schadt EE, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Thorsteinsdottir U, Stumvoll M, Tuomilehto J, Uitterlinden AG, Uusitupa M, van der Harst P, Walker M, Wallaschofski H, Wareham NJ, Watkins H, Weir DR, Wichmann HE, Wilson JF, Zanen P, Borecki IB, Deloukas P, Fox CS, Heid IM, O'Connell JR, Strachan DP, Stefansson K, van Duijn CM, Abecasis GR, Franke L, Frayling TM, McCarthy MI, Visscher PM, Scherag A, Willer CJ, Boehnke M, Mohlke KL, Lindgren CM, Beckmann JS, Barroso I, North KE, Ingelsson E, Hirschhorn JN, Loos RJF, Speliotes EK. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197-206.
Rask-Andersen M, Karlsson T, Ek WE, Johansson A. Genome-wide association study of body fat distribution identifies adiposity loci and sex-specific genetic effects. Nat Commun. 2019;10(1):339.
Hendricks AE, Bochukova EG, Marenne G, Keogh JM, Atanassova N, Bounds R, Wheeler E, Mistry V, Henning E, Korner A, Muddyman D, McCarthy S, Hinney A, Hebebrand J, Scott RA, Langenberg C, Wareham NJ, Surendran P, Howson JM, Butterworth AS, Danesh J, Nordestgaard BG, Nielsen SF, Afzal S, Papadia S, Ashford S, Garg S, Millhauser GL, Palomino RI, Kwasniewska A, Tachmazidou I, O'Rahilly S, Zeggini E, Barroso I, Farooqi IS, Understanding Society Scientific G, Consortium E-C, Consortium UK. Rare Variant Analysis of Human and Rodent Obesity Genes in Individuals with Severe Childhood Obesity. Sci Rep. 2017;7(1):4394.
Styne DM, Arslanian SA, Connor EL, Farooqi IS, Murad MH, Silverstein JH, Yanovski JA. Pediatric Obesity-Assessment, Treatment, and Prevention: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2017;102(3):709-757.
Ahima RS, Prabakaran D, Mantzoros C, Qu D, Lowell B, Maratos-Flier E, Flier JS. Role of leptin in the neuroendocrine response to fasting. Nature. 1996;382(6588):250-252.
Flier JS, Maratos-Flier E. Leptin's Physiologic Role: Does the Emperor of Energy Balance Have No Clothes? Cell metabolism. 2017;26(1):24-26.
Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR, Ohannesian JP, Marco CC, McKee LJ, Bauer TL, et al. Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med. 1996;334(5):292-295.
Gautron L, Elmquist JK, Williams KW. Neural control of energy balance: translating circuits to therapies. Cell.2015;161(1):133-145.
Montague CT, Farooqi IS, Whitehead JP, Soos MA, Rau H, Wareham NJ, Sewter CP, Digby JE, Mohammed SN, Hurst JA, Cheetham CH, Earley AR, Barnett AH, Prins JB, O'Rahilly S. Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature. 1997;387(6636):903-908.
Clement K, Vaisse C, Lahlou N, Cabrol S, Pelloux V, Cassuto D, Gourmelen M, Dina C, Chambaz J, Lacorte JM, Basdevant A, Bougneres P, Lebouc Y, Froguel P, Guy-Grand B. A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature. 1998;392(6674):398-401.
Farooqi IS, Matarese G, Lord GM, Keogh JM, Lawrence E, Agwu C, Sanna V, Jebb SA, Perna F, Fontana S, Lechler RI, DePaoli AM, O'Rahilly S. Beneficial effects of leptin on obesity, T cell hyporesponsiveness, and neuroendocrine/metabolic dysfunction of human congenital leptin deficiency. J Clin Invest. 2002;110(8):1093-1103.
Farooqi IS, Wangensteen T, Collins S, Kimber W, Matarese G, Keogh JM, Lank E, Bottomley B, Lopez-Fernandez J, Ferraz-Amaro I, Dattani MT, Ercan O, Myhre AG, Retterstol L, Stanhope R, Edge JA, McKenzie S, Lessan N, Ghodsi M, De Rosa V, Perna F, Fontana S, Barroso I, Undlien DE, O'Rahilly S. Clinical and molecular genetic spectrum of congenital deficiency of the leptin receptor. N Engl J Med. 2007;356(3):237-247.
Saeed S, Bonnefond A, Manzoor J, Shabbir F, Ayesha H, Philippe J, Durand E, Crouch H, Sand O, Ali M, Butt T, Rathore AW, Falchi M, Arslan M, Froguel P. Genetic variants in LEP, LEPR, and MC4R explain 30% of severe obesity in children from a consanguineous population. Obesity (Silver Spring). 2015;23(8):1687-1695.
Wabitsch M, Funcke JB, Lennerz B, Kuhnle-Krahl U, Lahr G, Debatin KM, Vatter P, Gierschik P, Moepps B, Fischer-Posovszky P. Biologically inactive leptin and early-onset extreme obesity. N Engl J Med. 2015;372(1):48-54.
Funcke JB, Moepps B, Roos J, von Schnurbein J, Verstraete K, Frohlich-Reiterer E, Kohlsdorf K, Nunziata A, Brandt S, Tsirigotaki A, Dansercoer A, Suppan E, Haris B, Debatin KM, Savvides SN, Farooqi IS, Hussain K, Gierschik P, Fischer-Posovszky P, Wabitsch M. Rare Antagonistic Leptin Variants and Severe, Early-Onset Obesity. N Engl J Med. 2023;388(24):2253-2261.
Ozata M, Ozdemir IC, Licinio J. Human leptin deficiency caused by a missense mutation: multiple endocrine defects, decreased sympathetic tone, and immune system dysfunction indicate new targets for leptin action, greater central than peripheral resistance to the effects of leptin, and spontaneous correction of leptin-mediated defects. J Clin Endocrinol Metab. 1999;84(10):3686-3695.
Farooqi IS, Jebb SA, Langmack G, Lawrence E, Cheetham CH, Prentice AM, Hughes IA, McCamish MA, O'Rahilly S. Effects of recombinant leptin therapy in a child with congenital leptin deficiency. N Engl J Med.1999;341(12):879-884.
Galgani JE, Greenway FL, Caglayan S, Wong ML, Licinio J, Ravussin E. Leptin replacement prevents weight loss-induced metabolic adaptation in congenital leptin-deficient patients. J Clin Endocrinol Metab. 2010;95(2):851-855.
Navarro VM. Metabolic regulation of kisspeptin — the link between energy balance and reproduction. Nature Reviews Endocrinology. 2020;16(8):407-420.
Clement K, Biebermann H, Farooqi IS, Van der Ploeg L, Wolters B, Poitou C, Puder L, Fiedorek F, Gottesdiener K, Kleinau G, Heyder N, Scheerer P, Blume-Peytavi U, Jahnke I, Sharma S, Mokrosinski J, Wiegand S, Muller A, Weiss K, Mai K, Spranger J, Gruters A, Blankenstein O, Krude H, Kuhnen P. MC4R agonism promotes durable weight loss in patients with leptin receptor deficiency. Nat Med. 2018;24(5):551-555.
Heymsfield SB, Greenberg AS, Fujioka K, Dixon RM, Kushner R, Hunt T, Lubina JA, Patane J, Self B, Hunt P, McCamish M. Recombinant leptin for weight loss in obese and lean adults: a randomized, controlled, dose-escalation trial. JAMA. 1999;282(16):1568-1575.
Zelissen PM, Stenlof K, Lean ME, Fogteloo J, Keulen ET, Wilding J, Finer N, Rössner S, Lawrence E, Fletcher C, McCamish M. Effect of three treatment schedules of recombinant methionyl human leptin on body weight in obese adults: a randomized, placebo-controlled trial. Diabetes, obesity & metabolism. 2005;7(6):755-761.
Farooqi IS, Keogh JM, Kamath S, Jones S, Gibson WT, Trussell R, Jebb SA, Lip GY, O'Rahilly S. Partial leptin deficiency and human adiposity. Nature. 2001;414(6859):34-35.
Krude H, Biebermann H, Luck W, Horn R, Brabant G, Gruters A. Severe early-onset obesity, adrenal insufficiency and red hair pigmentation caused by POMC mutations in humans. Nat Genet. 1998;19(2):155-157.
Krude H, Biebermann H, Schnabel D, Tansek MZ, Theunissen P, Mullis PE, Gruters A. Obesity due to proopiomelanocortin deficiency: three new cases and treatment trials with thyroid hormone and ACTH4-10. J Clin Endocrinol Metab. 2003;88(10):4633-4640.
Lam BYH, Williamson A, Finer S, Day FR, Tadross JA, Gonçalves Soares A, Wade K, Sweeney P, Bedenbaugh MN, Porter DT, Melvin A, Ellacott KLJ, Lippert RN, Buller S, Rosmaninho-Salgado J, Dowsett GKC, Ridley KE, Xu Z, Cimino I, Rimmington D, Rainbow K, Duckett K, Holmqvist S, Khan A, Dai X, Bochukova EG, Trembath RC, Martin HC, Coll AP, Rowitch DH, Wareham NJ, van Heel DA, Timpson N, Simerly RB, Ong KK, Cone RD, Langenberg C, Perry JRB, Yeo GS, O'Rahilly S. MC3R links nutritional state to childhood growth and the timing of puberty. Nature. 2021;599(7885):436-441.
Kuhnen P, Clement K, Wiegand S, Blankenstein O, Gottesdiener K, Martini LL, Mai K, Blume-Peytavi U, Gruters A, Krude H. Proopiomelanocortin Deficiency Treated with a Melanocortin-4 Receptor Agonist. N Engl J Med.2016;375(3):240-246.
Lee YS, Challis BG, Thompson DA, Yeo GS, Keogh JM, Madonna ME, Wraight V, Sims M, Vatin V, Meyre D, Shield J, Burren C, Ibrahim Z, Cheetham T, Swift P, Blackwood A, Hung CC, Wareham NJ, Froguel P, Millhauser GL, O'Rahilly S, Farooqi IS. A POMC variant implicates beta-melanocyte-stimulating hormone in the control of human energy balance. Cell metabolism. 2006;3(2):135-140.
Jackson RS, Creemers JW, Ohagi S, Raffin-Sanson ML, Sanders L, Montague CT, Hutton JC, O'Rahilly S. Obesity and impaired prohormone processing associated with mutations in the human prohormone convertase 1 gene. Nat Genet. 1997;16(3):303-306.
Jackson RS, Creemers JW, Farooqi IS, Raffin-Sanson ML, Varro A, Dockray GJ, Holst JJ, Brubaker PL, Corvol P, Polonsky KS, Ostrega D, Becker KL, Bertagna X, Hutton JC, White A, Dattani MT, Hussain K, Middleton SJ, Nicole TM, Milla PJ, Lindley KJ, O'Rahilly S. Small-intestinal dysfunction accompanies the complex endocrinopathy of human proprotein convertase 1 deficiency. J Clin Invest. 2003;112(10):1550-1560.
Wade KH, Lam BYH, Melvin A, Pan W, Corbin LJ, Hughes DA, Rainbow K, Chen JH, Duckett K, Liu X, Mokrosinski J, Morseburg A, Neaves S, Williamson A, Zhang C, Farooqi IS, Yeo GSH, Timpson NJ, O'Rahilly S. Loss-of-function mutations in the melanocortin 4 receptor in a UK birth cohort. Nat Med. 2021;27(6):1088-1096.
Farooqi IS, Keogh JM, Yeo GS, Lank EJ, Cheetham T, O'Rahilly S. Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med. 2003;348(12):1085-1095.
Stutzmann F, Tan K, Vatin V, Dina C, Jouret B, Tichet J, Balkau B, Potoczna N, Horber F, O'Rahilly S, Farooqi IS, Froguel P, Meyre D. Prevalence of melanocortin-4 receptor deficiency in Europeans and their age-dependent penetrance in multigenerational pedigrees. Diabetes. 2008;57(9):2511-2518.
Collet TH, Dubern B, Mokrosinski J, Connors H, Keogh JM, Mendes de Oliveira E, Henning E, Poitou-Bernert C, Oppert JM, Tounian P, Marchelli F, Alili R, Le Beyec J, Pepin D, Lacorte JM, Gottesdiener A, Bounds R, Sharma S, Folster C, Henderson B, O'Rahilly S, Stoner E, Gottesdiener K, Panaro BL, Cone RD, Clement K, Farooqi IS, Van der Ploeg LHT. Evaluation of a melanocortin-4 receptor (MC4R) agonist (Setmelanotide) in MC4R deficiency. Mol Metab. 2017;6(10):1321-1329.
Martinelli CE, Keogh JM, Greenfield JR, Henning E, van der Klaauw AA, Blackwood A, O'Rahilly S, Roelfsema F, Camacho-Hubner C, Pijl H, Farooqi IS. Obesity due to melanocortin 4 receptor (MC4R) deficiency is associated with increased linear growth and final height, fasting hyperinsulinemia, and incompletely suppressed growth hormone secretion. J Clin Endocrinol Metab. 2011;96(1):E181-188.
Greenfield JR, Miller JW, Keogh JM, Henning E, Satterwhite JH, Cameron GS, Astruc B, Mayer JP, Brage S, See TC, Lomas DJ, O'Rahilly S, Farooqi IS. Modulation of blood pressure by central melanocortinergic pathways. N Engl J Med. 2009;360(1):44-52.
Iepsen EW, Zhang J, Thomsen HS, Hansen EL, Hollensted M, Madsbad S, Hansen T, Holst JJ, Holm JC, Torekov SS. Patients with Obesity Caused by Melanocortin-4 Receptor Mutations Can Be Treated with a Glucagon-like Peptide-1 Receptor Agonist. Cell metabolism. 2018;28(1):23-32.e23.
Hatoum IJ, Stylopoulos N, Vanhoose AM, Boyd KL, Yin DP, Ellacott KL, Ma LL, Blaszczyk K, Keogh JM, Cone RD, Farooqi IS, Kaplan LM. Melanocortin-4 receptor signaling is required for weight loss after gastric bypass surgery. J Clin Endocrinol Metab. 2012;97(6):E1023-1031.
Weinstein LS, Chen M, Liu J. Gs(alpha) mutations and imprinting defects in human disease. Ann N Y Acad Sci.2002;968:173-197.
Mendes de Oliveira E, Keogh JM, Talbot F, Henning E, Ahmed R, Perdikari A, Bounds R, Wasiluk N, Ayinampudi V, Barroso I, Mokrosinski J, Jyothish D, Lim S, Gupta S, Kershaw M, Matei C, Partha P, Randell T, McAulay A, Wilson LC, Cheetham T, Crowne EC, Clayton P, Farooqi IS. Obesity-Associated GNAS Mutations and the Melanocortin Pathway. N Engl J Med. 2021;385(17):1581-1592.
Bochukova EG, Huang N, Keogh J, Henning E, Purmann C, Blaszczyk K, Saeed S, Hamilton-Shield J, Clayton-Smith J, O'Rahilly S, Hurles ME, Farooqi IS. Large, rare chromosomal deletions associated with severe early-onset obesity. Nature. 2010;463(7281):666-670.
Hanssen R, Auwerx C, Joeloo M, Sadler MC, Estonian Biobank Research T, Henning E, Keogh J, Bounds R, Smith M, Firth HV, Kutalik Z, Farooqi IS, Reymond A, Lawler K. Chromosomal deletions on 16p11.2 encompassing SH2B1 are associated with accelerated metabolic disease. Cell Rep Med. 2023;4(8):101155.
Doche ME, Bochukova EG, Su HW, Pearce LR, Keogh JM, Henning E, Cline JM, Saeed S, Dale A, Cheetham T, Barroso I, Argetsinger LS, O'Rahilly S, Rui L, Carter-Su C, Farooqi IS. Human SH2B1 mutations are associated with maladaptive behaviors and obesity. J Clin Invest. 2012;122(12):4732-4736.
Cassidy SB, Schwartz S, Miller JL, Driscoll DJ. Prader-Willi syndrome. Genet Med. 2012;14(1):10-26.
Sahoo T, del Gaudio D, German JR, Shinawi M, Peters SU, Person RE, Garnica A, Cheung SW, Beaudet AL. Prader-Willi phenotype caused by paternal deficiency for the HBII-85 C/D box small nucleolar RNA cluster. Nat Genet. 2008;40(6):719-721.
de Smith AJ, Purmann C, Walters RG, Ellis RJ, Holder SE, Van Haelst MM, Brady AF, Fairbrother UL, Dattani M, Keogh JM, Henning E, Yeo GS, O'Rahilly S, Froguel P, Farooqi IS, Blakemore AI. A deletion of the HBII-85 class of small nucleolar RNAs (snoRNAs) is associated with hyperphagia, obesity and hypogonadism. Hum Mol Genet.2009;18(17):3257-3265.
Swaab DF, Purba JS, Hofman MA. Alterations in the hypothalamic paraventricular nucleus and its oxytocin neurons (putative satiety cells) in Prader-Willi syndrome: a study of five cases. J Clin Endocrinol Metab.1995;80(2):573-579.
Tauber M, Boulanouar K, Diene G, Cabal-Berthoumieu S, Ehlinger V, Fichaux-Bourin P, Molinas C, Faye S, Valette M, Pourrinet J, Cessans C, Viaux-Sauvelon S, Bascoul C, Guedeney A, Delhanty P, Geenen V, Martens H, Muscatelli F, Cohen D, Consoli A, Payoux P, Arnaud C, Salles JP. The Use of Oxytocin to Improve Feeding and Social Skills in Infants With Prader-Willi Syndrome. Pediatrics. 2017;139(2).
Bochukova EG, Lawler K, Croizier S, Keogh JM, Patel N, Strohbehn G, Lo KK, Humphrey J, Hokken-Koelega A, Damen L, Donze S, Bouret SG, Plagnol V, Farooqi IS. A Transcriptomic Signature of the Hypothalamic Response to Fasting and BDNF Deficiency in Prader-Willi Syndrome. Cell Rep. 2018;22(13):3401-3408.
Forsythe E, Beales PL. Bardet-Biedl syndrome. Eur J Hum Genet. 2013;21(1):8-13.
Forsythe E, Sparks K, Best S, Borrows S, Hoskins B, Sabir A, Barrett T, Williams D, Mohammed S, Goldsmith D, Milford DV, Bockenhauer D, Foggensteiner L, Beales PL. Risk Factors for Severe Renal Disease in Bardet-Biedl Syndrome. J Am Soc Nephrol. 2017;28(3):963-970.
Haqq AM, Chung WK, Dollfus H, Haws RM, Martos-Moreno GA, Poitou C, Yanovski JA, Mittleman RS, Yuan G, Forsythe E, Clement K, Argente J. Efficacy and safety of setmelanotide, a melanocortin-4 receptor agonist, in patients with Bardet-Biedl syndrome and Alstrom syndrome: a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial with an open-label period. The lancet Diabetes & endocrinology. 2022;10(12):859-868.
Gray J, Yeo GS, Cox JJ, Morton J, Adlam AL, Keogh JM, Yanovski JA, El Gharbawy A, Han JC, Tung YC, Hodges JR, Raymond FL, O'Rahilly S, Farooqi IS. Hyperphagia, severe obesity, impaired cognitive function, and hyperactivity associated with functional loss of one copy of the brain-derived neurotrophic factor (BDNF) gene. Diabetes. 2006;55(12):3366-3371.
Han JC, Liu QR, Jones M, Levinn RL, Menzie CM, Jefferson-George KS, Adler-Wailes DC, Sanford EL, Lacbawan FL, Uhl GR, Rennert OM, Yanovski JA. Brain-derived neurotrophic factor and obesity in the WAGR syndrome. N Engl J Med. 2008;359(9):918-927.
Yeo GS, Connie Hung CC, Rochford J, Keogh J, Gray J, Sivaramakrishnan S, O'Rahilly S, Farooqi IS. A de novo mutation affecting human TrkB associated with severe obesity and developmental delay. Nat Neurosci.2004;7(11):1187-1189.
Sonoyama T, Stadler LKJ, Zhu M, Keogh JM, Henning E, Hisama F, Kirwan P, Jura M, Blaszczyk BK, DeWitt DC, Brouwers B, Hyvonen M, Barroso I, Merkle FT, Appleyard SM, Wayman GA, Farooqi IS. Human BDNF/TrkB variants impair hippocampal synaptogenesis and associate with neurobehavioural abnormalities. Sci Rep.2020;10(1):9028.
Holder LJ, Nancy F. Butte & Andrew R. Zinn. Profound obesity associated with a balanced translocatioin that disrupts the SIM1 gene. Hum Mol Genet. 2000;9(1):101-108.
Ramachandrappa S, Raimondo A, Cali AM, Keogh JM, Henning E, Saeed S, Thompson A, Garg S, Bochukova EG, Brage S, Trowse V, Wheeler E, Sullivan AE, Dattani M, Clayton PE, Datta V, Bruning JB, Wareham NJ, O'Rahilly S, Peet DJ, Barroso I, Whitelaw ML, Farooqi IS. Rare variants in single-minded 1 (SIM1) are associated with severe obesity. J Clin Invest. 2013;123(7):3042-3050.
Moir L, Bochukova EG, Dumbell R, Banks G, Bains RS, Nolan PM, Scudamore C, Simon M, Watson KA, Keogh J, Henning E, Hendricks A, O'Rahilly S, Barroso I, Sullivan AE, Bersten DC, Whitelaw ML, Kirsch S, Bentley E, Farooqi IS, Cox RD. Disruption of the homeodomain transcription factor orthopedia homeobox (Otp) is associated with obesity and anxiety. Mol Metab. 2017;6(11):1419-1428.
van der Klaauw AA, Croizier S, Mendes de Oliveira E, Stadler LKJ, Park S, Kong Y, Banton MC, Tandon P, Hendricks AE, Keogh JM, Riley SE, Papadia S, Henning E, Bounds R, Bochukova EG, Mistry V, O'Rahilly S, Simerly RB, Interval, Consortium UK, Minchin JEN, Barroso I, Jones EY, Bouret SG, Farooqi IS. Human Semaphorin 3 Variants Link Melanocortin Circuit Development and Energy Balance. Cell. 2019;176(4):729-742 e718.
Cacciottolo TM, Henning E, Keogh JM, Bel Lassen P, Lawler K, Bounds R, Ahmed R, Perdikari A, Mendes de Oliveira E, Smith M, Godfrey EM, Johnson E, Hodson L, Clement K, van der Klaauw AA, Farooqi IS. Obesity Due to Steroid Receptor Coactivator-1 Deficiency Is Associated With Endocrine and Metabolic Abnormalities. J Clin Endocrinol Metab. 2022;107(6):e2532-e2544.
Marenne G, Hendricks AE, Perdikari A, Bounds R, Payne F, Keogh JM, Lelliott CJ, Henning E, Pathan S, Ashford S, Bochukova EG, Mistry V, Daly A, Hayward C, Interval UKKC, Wareham NJ, O'Rahilly S, Langenberg C, Wheeler E, Zeggini E, Farooqi IS, Barroso I. Exome Sequencing Identifies Genes and Gene Sets Contributing to Severe Childhood Obesity, Linking PHIP Variants to Repressed POMC Transcription. Cell metabolism.2020;31(6):1107-1119 e1112.
He Y, Brouwers B, Liu H, Liu H, Lawler K, Mendes de Oliveira E, Lee DK, Yang Y, Cox AR, Keogh JM, Henning E, Bounds R, Perdikari A, Ayinampudi V, Wang C, Yu M, Tu L, Zhang N, Yin N, Han J, Scarcelli NA, Yan Z, Conde KM, Potts C, Bean JC, Wang M, Hartig SM, Liao L, Xu J, Barroso I, Mokrosinski J, Xu Y, Sadaf Farooqi I. Human loss-of-function variants in the serotonin 2C receptor associated with obesity and maladaptive behavior. Nat Med.2022;28(12):2537-2546.
Liu H, He Y, Liu H, Brouwers B, Yin N, Lawler K, Keogh JM, Henning E, Lee DK, Yu M, Tu L, Zhang N, Conde KM, Han J, Yan Z, Scarcelli NA, Liao L, Xu J, Tong Q, Zheng H, Sun Z, Yang Y, Wang C, He Y, Farooqi IS, Xu Y. Neural circuits expressing the serotonin 2C receptor regulate memory in mice and humans. Sci Adv.2024;10(26):eadl2675.
Li Y, Cacciottolo TM, Yin N, He Y, Liu H, Liu H, Yang Y, Henning E, Keogh JM, Lawler K, Mendes de Oliveira E, Gardner EJ, Kentistou KA, Laouris P, Bounds R, Ong KK, Perry JRB, Barroso I, Tu L, Bean JC, Yu M, Conde KM, Wang M, Ginnard O, Fang X, Tong L, Han J, Darwich T, Williams KW, Yang Y, Wang C, Joss S, Firth HV, Xu Y, Farooqi IS. Loss of transient receptor potential channel 5 causes obesity and postpartum depression. Cell.2024;187(16):4176-4192 e4117.
Asai M, Ramachandrappa S, Joachim M, Shen Y, Zhang R, Nuthalapati N, Ramanathan V, Strochlic DE, Ferket P, Linhart K, Ho C, Novoselova TV, Garg S, Ridderstrale M, Marcus C, Hirschhorn JN, Keogh JM, O'Rahilly S, Chan LF, Clark AJ, Farooqi IS, Majzoub JA. Loss of function of the melanocortin 2 receptor accessory protein 2 is associated with mammalian obesity. Science. 2013;341(6143):275-278.
Pearce LR, Atanassova N, Banton MC, Bottomley B, van der Klaauw AA, Revelli JP, Hendricks A, Keogh JM, Henning E, Doree D, Jeter-Jones S, Garg S, Bochukova EG, Bounds R, Ashford S, Gayton E, Hindmarsh PC, Shield JP, Crowne E, Barford D, Wareham NJ, consortium UK, O'Rahilly S, Murphy MP, Powell DR, Barroso I, Farooqi IS. KSR2 mutations are associated with obesity, insulin resistance, and impaired cellular fuel oxidation. Cell. 2013;155(4):765-777.

Osteoporosis: Clinical Evaluation

ABSTRACT

The identification of a patient at high-risk of fracture should be followed by evaluation for factors contributing to low bone mass, skeletal fragility, falls, and fractures. Components of the evaluation include a bone density test, osteoporosis-directed medical history and physical exam, laboratory studies, and possibly skeletal imaging. A bone density test with dual-energy X-ray absorptiometry (DXA) is useful for diagnostic classification, assessment of fracture risk, and establishing a baseline for monitoring the skeletal effects of treatment. FRAX is a fracture risk algorithm that includes input of femoral neck bone mineral density measured by DXA. The DXA T-score, prior fracture history, and FRAX estimation of fracture risk are used with clinical practice guidelines to determine whether treatment is indicated. The medical history may reveal underlying causes of osteoporosis (e.g., nutritional deficiencies, gastric surgery, medications with adverse skeletal effects) and important risk factors for fracture (e.g., past history of fracture, family history of osteoporosis, or recent falls). Physical exam may show skeletal deformities due to unrecognized fractures (e.g., loss of height, kyphosis, or diminished rib-pelvis space), identify possible secondary causes of skeletal fragility (e.g., blue sclera with osteogenesis imperfecta, urticarial pigmentosa with systemic mastocytosis, dermatitis herpetiformis with celiac disease, or bone tenderness with osteomalacia), and help to recognize patients with poor balance and frailty that might lead to falls. Laboratory studies may show potentially reversible abnormalities (e.g., vitamin D deficiency, hypocalcemia, or impaired kidney function) that must be assessed and corrected, if possible, before starting pharmacological therapy. Disorders other than osteoporosis, requiring other types of treatment, may be found; for example, low serum alkaline phosphatase suggests hypophosphatasia, M-component may be due to myeloma, or hypocalciuria due to malabsorption with celiac disease. There are important safety considerations that can be derived from a pre-treatment assessment, as well. A patient with a blood clotting disorder should not be treated with raloxifene, a history of esophageal stricture is a contraindication for oral bisphosphonates, and previous skeletal radiation therapy precludes treatment with teriparatide or abaloparatide. Skeletal imaging may be helpful when a fracture, malignancy, or Paget’s disease of bone is suspected. Bone biopsy is rarely performed in clinical practice, but may be helpful in some situations, such as when it is necessary to determine the underlying bone disease in a patient with severe chronic kidney disease.

INTRODUCTION

Osteoporosis is a common systemic skeletal disease characterized by low bone strength that results in an increased risk of fracture (1). Fractures are associated with serious clinical consequences, including pain, disability, loss of independence, and death, as well as high healthcare costs. Early identification and intervention with patients at high risk for fracture is needed to reduce the burden of osteoporotic fractures (2). Management of a patient with a confirmed diagnosis of osteoporosis or low bone mass (osteopenia) includes assessment of fracture risk, evaluation for secondary causes of skeletal fragility, decisions on initiation of treatment, and identification of all relevant clinical factors that may influence patient management. This is a review of the key components in the care of patients prior to treatment.

DIAGNOSIS OF OSTEOPOROSIS

The World Health Organization (WHO) diagnostic classification (Table 1) (3) is made by bone mineral density (BMD) testing with dual-energy X-ray absorptiometry (DXA) using the T-score, calculated by subtracting the mean BMD (in g/cm²) of a young-adult reference population from the patient’s BMD and dividing by the standard deviation (SD) of the young-adult reference population. The International Society for Clinical Densitometry (ISCD) recommends that BMD be measured at the lumbar spine (ideally L1-L4), total hip, and femoral neck, with the 33% radius (1/3 radius) being measured when the lumbar spine and/or hip cannot be measured (e.g., obese patient who exceeds weight limit of table), is invalid (e.g., patient with lumbar laminectomy or bilateral total hip replacements), or when the patient has hyperparathyroidism (4). Osteoporosis cannot be diagnosed by BMD measurement at skeletal sites other than lumbar spine, total hip, femoral neck, and 33% radius or with technologies other than DXA, except for total hip and femoral neck T-scores calculated from 2D projections of quantitative computed tomography (QCT) data. The quality of DXA instrument maintenance, acquisition, analysis, interpretation, and reporting is important in obtaining valid results that can be used for making appropriate clinical decisions (4-6). In a patient with a fragility fracture, a clinical diagnosis of osteoporosis may be considered independently of BMD results, assuming other causes of skeletal fragility (e.g., osteomalacia, multiple myeloma) are not responsible for the fracture. Establishing a diagnosis of osteoporosis is clinically useful because it facilitates communication among healthcare providers and patients concerning a disease with potentially serious consequences; in some countries, such as the United States (US), a diagnosis is necessary in order to select a numerical code for submission of insurance claims for reimbursement for medical services. The US Bone Health & Osteoporosis Foundation (BHOF) (7) recommends that osteoporosis be diagnosed in postmenopausal women and men over the age ≥ 50 years in any of the following circumstances: T-score ≤ −2.5 at the lumbar spine, femoral neck, total hip, or 33% radius; low-trauma fracture of the hip, spine, and/or forearm; or T-score between -1.0 and -2.5 with FRAX 10-year probability of major osteoporotic fracture ≥ 20% or 10-year probability of hip fracture ≥ 3%.

Table 1. World Health Organization Criteria for Classification of Patients with Bone Mineral Density Measured by Dual-Energy X-ray Absorptiometry (3)
Classification	T-score
Normal	-1.0 or greater
Low bone mass (osteopenia)	Between 1-.0 and -2.5
Osteoporosis	-2.5 and below
Severe osteoporosis	-2.5 and below + fragility fracture

The BHOF indications for BMD testing in the US (7), which are similar to the ISCD Official Positions (4) are listed in Table 2. BMD testing should be done when it is likely to have an influence on patient management decisions. Other organizations and other countries with different economic resources and health care priorities have used a variety of methodologies to develop alternative recommendations (8-10).

Table 2. The BHOF Recommends that Bone Mineral Density Testing be Considered at DXA Facilities using Accepted Quality Assurance Procedures for the Following individuals (7).
Women age ≥ 65 years and men age ≥ 70 years
Postmenopausal women and men age 50-69 years, based on risk profile
Postmenopausal women and men age ≥ 50 years with history of adult-age fracture
Adults with a condition (e.g., rheumatoid arthritis, organ transplant) or taking a medication (e.g., glucocorticoids, aromatase inhibitors, androgen deprivation therapy) associated with low bone mass or bone loss

FRACTURE RISK ASSESSMENT

There is a robust correlation between BMD and fracture risk, with approximately a 2-fold increase in fracture risk for every 1 SD decrease in BMD (11). However, many or most patients with a hip fracture have a T-score better than -2.5 (12); although fracture risk is higher in patients with very low BMD, there are numerically many more patients with a T-score better than -2.5 than with a T-score ≤ -2.5, therefore there are numerically more fractures in those with higher T-scores. The presence of clinical risk factors (CRFs) that are independent of BMD, particularly advancing age, prior fracture, and recency/number/severity of fracture(s), can identify patients at high-risk for fracture by providing information on fracture risk that is complementary to BMD. The BHOF has provided an extensive list of CRFs (summarized in Table 3) for osteoporosis and fractures. Since most fractures occur with a fall, it is helpful to recognize risk factors for falling (summarized in Table 4) so that appropriate interventions can be made, when possible, to reduce the chances of falling.

Table 3. Conditions, Diseases, and Medications that Cause or Contribute to Osteoporosis and Fractures (adapted from guidelines of the BHOF (7)).
Lifestyle Factors
Low Calcium Intake	Vitamin D Insufficiency	Excess Vitamin A	Excessive Thinness
High Salt Intake	Immobilization	Inadequate Physical Activity
Smoking	Frequent Falling
Genetic Factors
Cystic Fibrosis	Homocystinuria	Osteogenesis Imperfecta	Ehlers-Danlos Syndrome
Hypophosphatasia	Gaucher’s Disease	Idiopathic Hypercalciuria	Porphyria
Glycogen storage diseases	Marfan Syndrome	Riley-Day Syndrome	Hemochromatosis
Menkes Steely Hair Syndrome	Parental History of Hip Fracture	Androgen Insensitivity	Turner’s & Klinefelter’s Syndromes
Endocrine Disorders
Obesity	Diabetes Mellitus	Hyperthyroidism	Cushing’s Syndrome
Hyperparathyroidism	Hypogonadism	Panhypopituitarism	Female athlete triad
Anorexia Nervosa	Hyperprolactinemia	Premature Menopause	Androgen Insensitivity
Gastrointestinal Disorders
Celiac Disease	Inflammatory Bowel Disease	Primary Biliary Cirrhosis	Gastric Bypass
Malabsorption	GI Surgery	Pancreatic Disease
Hematologic Disorders
Hemophilia	Monoclonal Gammopathies	Systemic Mastocytosis	Leukemia
Lymphoma	Sickle Cell Disease	Thalassemia	Multiple Myeloma
Rheumatic and Autoimmune Diseases
Ankylosing Spondylitis	Systemic Lupus	Rheumatoid Arthritis	Multiple Sclerosis
Muscular Dystrophy	Parkinson’s Disease	Spinal Cord Injury	Stroke
Epilepsy
Miscellaneous Conditions and Diseases
Chronic Obstructive Pulmonary Disease	Weight Loss	Amyloidosis	End Stage Renal Disease
Parenteral Nutrition	Chronic Metabolic Acidosis	Hyponatremia	Post-Transplant Bone Disease
Congestive Heart Failure	Idiopathic Scoliosis	Prior Fracture as an Adult	Depression
HIV/AIDS	Sarcoidosis
Medications
Anticoagulants (heparin)	Cancer Chemotherapy	Gonadotropin Releasing Hormone Agonists	Anticonvulsants
Lithium	Aromatase Inhibitors	Depo-medroxyprogesterone	Barbiturates
Glucocorticoids (> 5mg of prednisone or equivalent for > 3 months)	Cyclosporine A	Tacrolimus	Aluminum-containing Antacids
Proton Pump Inhibitors	Tamoxifen (premenopausal)	Selective Serotonin Reuptake Inhibitors	Thiazolidinediones

Table 4. Risk Factors for Falls Adapted from Guidelines of the BHOF (7).
Environmental Risk Factors: lack of assistive devices in bathrooms, loose throw rugs, low level lighting, obstacles in the walking path, stairs, slippery outdoor conditions
Medical Risk Factors: advanced age, anxiety and agitation, arrhythmias, dehydration, depression, female gender, impaired transfer and mobility, malnutrition, orthostatic hypotension, poor vison and use of bifocals, previous fall, reduced mental acuity and diminished cognitive skills, urgent urinary incontinence, Vitamin D insufficiency (serum 25-OH-D < 30 ng/mL [75 nmol/L]), medications causing over-sedation (narcotic analgesics, anticonvulsants, psychotropics), diabetes
Neurological and Musculoskeletal Risk Factors: kyphosis, poor balance, reduced proprioception, weak muscles
Psychological Risk Factors: fear of falling

The presence of any of these risk factors should trigger consideration of further evaluation and treatment to reduce the risk of falls and fall-related injuries.

VERTEBRAL FRACTURE ASSESSMENT (VFA)

VFA is a method for imaging the thoracic and lumbar spine by DXA for the purpose of detecting vertebral fracture deformities. Identification of a previously unrecognized vertebral fracture may alter diagnostic classification, change estimation of fracture risk, and influence treatment decisions (13). VFA compares favorably with standard radiographs of the spine, with good correlation for detecting moderate (grade 2) and severe (grade 3) vertebral fractures, a smaller dose of ionizing irradiation, greater patient convenience (i.e., it may be done at the same visit and with the same instrument as BMD testing by DXA), and lower cost. In a study of women age 65 years and older, using the Genant semi-quantitative (SC) method of classifying vertebral deformities (14), the sensitivity of VFA for diagnosing moderate and severe vertebral fractures was 87-93%, with a specificity of 93-95% (15). Indications for vertebral imaging are listed in Table 5. Optimal use of DXA and VFA requires training and adherence to well established quality standards (4).

Table 5. ISCD Indications for Lateral Spine Imaging by Standard Radiography or Vertebral Fracture Assessment (VFA) (4)
Vertebral imaging is indicated when the T-score is < -1.0 and one or more of the following is present:
Women ≥ 70 years of age or men ≥ 80 years of age
Historical height loss > 4 cm (1.5 inches)
Self-reported but undocumented prior vertebral fracture
Glucocorticoid therapy equivalent to ≥ 5 mg of prednisone or equivalent per day for ≥ 3 months

QUALITY OF DXA AND VFA

DXA and VFA should be performed by well-trained and experienced staff operating an instrument that has been maintained and calibrated according to the manufacturer’s standards. Precision assessment and least significant change (LSC) calculation by each DXA technologist are required in order to make quantitative comparisons of serial BMD measurements. The LSC is the smallest change in BMD that is statistically significant, usually with a 95% level of confidence. The use of the correct scan modes, proper patient positioning, consistent vertebral body labeling, and bone edge detection are among the essential elements for serial comparisons of BMD. VFA should be done by a technologist properly trained in acquisition techniques and interpreted by a clinician familiar with methods of diagnosing vertebral fractures using this technology. Bone densitometry facilities should be supervised by a clinician who knows current methods for BMD measurement and fully understands the standards for quality control, interpretation, and reporting of the findings. Poor quality studies may result in inappropriate clinical decisions, generate unnecessary healthcare expenses, and be harmful to patients (5). Assurances of high quality DXA can be attained through education, training, and certification of DXA technologists and interpreters by organizations such as the ISCD. DXA facilities should understand and adhere to ISCD Official Positions (4) and DXA Best Practices (6, 14); facility accreditation (15) provides assurance of adherence to DXA quality standards.

TECHNOLOGIES FOR ASSESSMENT OF SKELETAL HEALTH

Dual-energy X-ray Absorptiometry (DXA)

Devices that measure or estimate BMD differ according to their clinical utility, cost, portability, and use of ionizing radiation. DXA is the “gold standard” method for measuring bone density in clinical practice. There is a strong correlation between mechanical strength and BMD measured by DXA biomechanical studies (16). In observational studies of untreated patients, there is a robust relationship between fracture risk and BMD measured by DXA (11). The WHO diagnostic classification of osteoporosis is based primarily on reference data obtained by DXA (3), and femoral neck BMD provides input into the FRAX algorithm. Most randomized clinical trials showing reduction in fracture risk with pharmacological therapy have selected study participants according to BMD measured by DXA (17). There is a relationship between BMD increases with drug therapy and fracture risk reduction (18, 19). Accuracy and precision of DXA are excellent (20). Radiation exposure with DXA is very low (21). BMD of the 33% (one-third) radius, measured either by a dedicated peripheral DXA (pDXA) device or a central DXA instrument with appropriate software, may be used for diagnostic classification with the WHO criteria and to assess fracture risk, but is generally not clinically useful in monitoring the effects of treatment. DXA measures bone mineral content (BMC in grams [g]) and bone area (cm²), then calculates areal BMD in g/cm² and derives parameters, such as the T-score and Z-score. DXA is used for diagnostic classification, assessment of fracture risk, and for monitoring changes in BMD over time.

Quantitative Ultrasound (QUS)

QUS devices emit inaudible high frequency sound waves in the ultrasonic range, typically between 0.1 and 1.0 megahertz (MHz). The sound waves are produced and detected by means of high-efficiency piezoelectric transducers, which must have good acoustical contact with the skin over the bone being tested. Technical differences among QUS systems are great, with different instruments using variable frequencies, different transducer sizes, and sometimes measuring different regions of interest, even at the same skeletal site. The calcaneus is the skeletal site most often tested, although other bones, including the radius, tibia, and finger phalanges, can be used. Commercial QUS systems usually measure two parameters- the speed of sound (SOS) and broadband ultrasound attenuation (BUA). A proprietary value, such as the “quantitative ultrasound index” (QUI) with the Hologic Sahara or “stiffness index” with the GE Healthcare Achilles Express, may be calculated from a combination of these measurements. SOS varies according to the type of bone, with a typical range of 3000-3600 meters per second (m/sec) with cortical bone and 1650-2300 m/sec for trabecular bone (22). A higher bone density is associated with a higher SOS. BUA, reported as decibels per megahertz (dB/MHz), is a measurement of the loss of energy, or attenuation, of the sound wave as it passes through bone. As with SOS, a higher bone density is associated with a higher BUA. Values obtained from calculations using ultrasound parameters may be used to generate an estimated BMD and a T-score. The T-score derived from a QUS measurement is not the same as a T-score from a DXA. QUS cannot be used for diagnostic classification and is not clinically useful to monitor the effects of therapy (23).

Radiofrequency Echographic Multi Spectrometry (REMS) assesses bone health and fracture risk with an ultrasound scan of the lumbar spine and proximal femur, thereby overcoming the limitation of QUS of only measuring peripheral skeletal sites. REMS technology uses a portable device with a transducer that transmits ultrasound waves to the target axial skeletal site and a receiver that captures the resultant back-scattered waveforms with B-mode image reconstruction of the region of interest. There are studies that support a strong correlation between REMS and DXA measurements of BMD (24). Potential clinical applications include its use in frail patients with limited mobility, bedside measurements in hospitalized patients, and special populations such as pregnant women and children.

Quantitative Computed Tomography (QCT) and Peripheral QCT (pQCT)

QCT and pQCT measure trabecular and cortical volumetric BMD at the axial skeleton and peripheral skeletal sites, respectively. QCT is a useful research tool to enhance understanding of the pathophysiology of osteoporosis and the mechanism of action of pharmacological agents used to treat osteoporosis. QCT predicts fracture risk, with the correlation varying according to skeletal site and bone compartment measured, type of fracture predicted, and population assessed (4). The ISCD Official Positions state that “spinal trabecular BMD as measured by QCT has at least the same ability to predict vertebral fractures as AP spinal BMD measured by central DXA in postmenopausal women with lack of sufficient evidence to support this position in men; pQCT of the forearm at the ultra-distal radius predicts hip, but not spine, fragility fractures in postmenopausal women with lack of sufficient evidence to support this position in men (4).” QCT is more expensive than DXA and QUS and uses higher levels of ionizing radiation than DXA. T-scores by QCT are typically lower than with DXA (27), thereby overestimating the prevalence of osteoporosis, with the exception of total hip and femoral neck T-scores calculated from 2D projections of QCT data, which are similar to DXA-derived T-scores at the same regions of interest and may be used for diagnosis of osteoporosis in accordance with the WHO criteria. T-scores and femoral neck BMD derived from 2D projections of QCT data may also be used as input for the FRAX algorithm to estimate 10-year fracture probabilities.

Other Technologies of Interest

Pulse-echo ultrasonography (PEUS) uses a portable handheld ultrasound device to estimate the thickness of cortical bone at peripheral skeletal sites. When connected to a computer with proprietary software, a value can be generated that that is correlated with hip BMD measured by DXA, with the potential benefit of identifying patients who are likely or unlikely to have osteoporosis (25).

Biomechanical CT (BCT) is an opportunistic analysis of data from pre-existing CT scans of the hip and/or spine that provides DXA-equivalent T-scores for the hip, QCT-equivalent vBMD at the spine, and an estimate of bone strength with finite element analysis (FEA) (26).

3D-Shaper is software that can be added to a DXA system using statistical modelling to reconstruct the 3D shape and density distribution of the proximal femur from 2D DXA data scans. A recent study found that this technology provided an estimation of femur strength that was similar to that derived from QCT FEA (27).

FRACTURE RISK ASSESSMENT TOOL (FRAX® and FRAXplus)

The combination of BMD and clinical risk factors (CRFs) predicts fracture risk better than BMD or CRFs alone (28,29) (2). A fracture risk assessment tool (FRAX) combines CRFs and femoral neck BMD in a computer-based algorithm that estimates the 10-year probability of hip fracture and major osteoporotic fracture (i.e., clinical spine, hip, proximal humerus, and distal forearm fracture). FRAX can be accessed online at http://www.shef.ac.uk/FRAX (Figure 1), on most software versions of DXA systems, and on smartphones. FRAX is based on analysis of data from 12 large prospective observational studies in about 60,000 untreated men and women in different world regions, having over 250,000 person-years of observation and more than 5,000 reported fractures reported.

Figure 1. FRAX online for US Caucasian patients. This example shows a 65-year-old woman who has no clinical risk factors for fracture and a femoral neck BMD of 0.582 g/cm2 with a Hologic instrument. The 10-year probability of major osteoporotic fracture is 11% and the 10-year probability of hip fracture is 2.2%. These levels do not meet the Bone Health & Osteoporosis Foundation guidelines for initiation of pharmacological therapy in the US (7). Image reproduced with permission from Eugene McCloskey, University of Sheffield, Sheffield, UK.

The input for FRAX is the patient’s age, sex, height, weight, a “yes” or “no” response indicating the presence or absence for each of 7 CRFs: 1. previous ‘spontaneous’ or fragility fracture as an adult; 2. parent with hip fracture; 3. current tobacco smoking; 4. ever use of chronic glucocorticoids at least 5 mg prednisolone for at least 3 months; 5. confirmed rheumatoid arthritis; 6. secondary osteoporosis, such as type 1 diabetes, osteogenesis imperfecta in adults, untreated longstanding hyperthyroidism and hypogonadism, or premature menopause (note: this is a “dummy” risk factor that has no effect on the fracture risk calculation unless no femoral neck BMD value is entered); 7. alcohol intake greater than 3 units per day, with a unit of alcohol defined as equivalent to a glass of beer, an ounce of spirits or a medium-sized glass of wine), and if available, femoral neck BMD and trabecular bone score (TBS). Since the introduction of FRAX, upgrades have been introduced to correct errors, enhance its usability, and incorporate new data that have become available.

Benefits of FRAX

The use of FRAX provides a quantitative estimation of fracture risk that is based on robust data in large populations of men and women with ethnic and geographic diversity. Expression of fracture risk as a probability provides greater clinical utility than relative risk. When combined with cost-utility analysis, a fracture risk level at which it is cost-effective to treat may be derived. FRAX can be used to estimate fracture probability without femoral neck BMD, allowing it to be used when DXA in unavailable or inaccessible. FRAX is incorporated into many clinical practice guidelines.

Limitations of FRAX

To generate a valid FRAX output, the responses to CRF questions must be correct; for example, an incorrect entry of self-reported rheumatoid arthritis or use of glucocorticoids could skew the results toward overestimation of fracture risk. FRAX may underestimate or overestimate fracture risk due to dichotomized (yes or no) input for CRFs that in reality are associated with a range of risk that varies according to dose, duration of exposure, or severity; for example, fracture risk may be underestimated when a patient is on high-dose glucocorticoid therapy or has had multiple recent fragility fractures, even when a “yes” response is entered for these CRFs. FRAX is validated only in untreated patients and may overestimate fracture risk when the patient is being treated; the NOF(BHOF)/ISCD guidance on FRAX suggests that “untreated” may be interpreted as never treated or if previously treated, no bisphosphonate for the past 2 years (unless it is an oral agent taken for less than 2 months); and no estrogen, raloxifene, calcitonin, or denosumab for the past 1 year (7). In this context, calcium and vitamin D do not constitute treatment. FRAX in the US allows input for 4 ethnicities (Caucasian, Black, Hispanic, Asian); it is not clear how to use FRAX for patients of other ethnicities or a mix of these ethnicities. Answering “yes” for the category of secondary osteoporosis has no effect on the fracture risk calculation as long as a value for femoral neck BMD is entered. The range of error for a fracture probability generated by FRAX is unknown but may be substantial in some cases.

Some important risk factors, such as falls and frailty, are not directly entered into FRAX, although they are indirectly included insofar as they are a component of aging. FRAX may underestimate fracture risk when the lumbar spine BMD is substantially lower than femoral neck BMD, as may occur in about 15% of patients (30). Despite the limitations of FRAX, it is a helpful clinical tool when used with a good understanding of factors that may result in underestimation or overestimation of fracture risk. FRAX may enhance discussion of risk with the patient and help to identify those who are at sufficiently high for fracture to benefit from therapy.

FRAXplus

FRAXplus (https://www.fraxplus.org/) is an updated version of FRAX that addresses some of the limitations of traditional FRAX, allowing input for these additional rick factors: recency of osteoporotic fracture, high exposure to oral glucocorticoids, type 2 diabetes, concurrent data on lumbar spine BMD, trabecular bone score, falls history, and hip axis length. For patients with fracture risk that is close to the intervention threshold for the applicable clinical practice guideline, the use of an additional risk factor with FRAXplus might influence the decision to treat or not treat with a pharmacological agent.

MEDICAL HISTORY

A thorough medical history may identify risk factors for osteoporosis and fractures, suggesting that a bone density test and/or further evaluation is indicated. The medical history may also reveal symptoms of potentially correctable causes of skeletal fragility (e.g., gluten intolerance with celiac disease) or co-morbidities that could influence treatment decisions (e.g., esophageal stricture suggests that oral bisphosphonates should not be given). A history of falls is a predictor of future falls, with that risk potentially modifiable though appropriate interventions. Finally, some symptoms may trigger further evaluation for the presence of fractures (e.g., historical height loss or development of kyphotic posture suggests the possibility of vertebral fractures that may warrant spine imaging). Table 6 provides examples of helpful information that might be obtained from a thoughtful interactive discussion with the patient.

Medical History for Patients with Osteoporosis

A thorough review of systems and history of relevant familial disorders, previous surgical procedures, medications, dietary supplements, food intolerances, and lifestyle provides helpful information in the management of patients with osteoporosis. Such historical information may play a role in determining who should have a bone density test, assessing fracture risk, providing input for FRAX, evaluating for secondary causes of osteoporosis, selecting the most appropriate treatment to reduce fracture risk, and finding factors contributing to suboptimal response to therapy. Listed here are key components of the skeletal health history and examples of the potential impact on patient care.

Table 6. Clinical Utility of the Medical History
Clinical Utility	Medical History
Assist in determining who need a bone density test	See Table 3
Assessing fracture risk	See Table 3 and 4
Input for FRAX	Age, sex, weight, height, previous fracture, parent with hip fracture, current tobacco smoking, ever use of glucocorticoids, rheumatoid arthritis, secondary osteoporosis, alcohol intake 3 or more units per day, and if available, femoral neck bone mineral density and trabecular bone score
Evaluating for secondary causes of osteoporosis	See Table 3
Selecting most appropriate treatment	Identify co-morbidities of clinical significance. For example, high-risk of breast cancer favors raloxifene use, while history of thrombophlebitis suggests that raloxifene should not be used; esophageal stricture is a contraindication for oral bisphosphonate use; a patient with a skeletal malignancy should not be treated with teriparatide.
Factors contributing to suboptimal response to therapy	Compliance and persistence to therapy; adequacy of calcium and vitamin D; comorbidities listed in Table 3.

PHYSICAL EXAM

Findings of importance on the physical exam of a patient with osteoporosis may be the sequelae of old fractures (e.g., kyphosis due to old vertebral fractures), a consequence of a recent fracture (e.g., localized vertebral spinous process tenderness with a new vertebral fracture), or abnormalities suggestive of a secondary cause of osteoporosis (e.g., thyromegaly with thyrotoxicosis). An accurate measurement of height with a wall-mounted stadiometer is a helpful office tool for evaluating patients at risk for fracture. A height loss of 1.5 inches (4.0 cm) or more compared to the historical maximum (28, 29) or a loss of 0.75 inches (2.0 cm) or more compared to a previous measured height (30) suggests a high likelihood of vertebral fracture. Body weight measurement is part of the osteoporosis evaluation because low body weight (less than 127 lbs) (31), low BMI (20 kg/m² or less) (32), and weight loss of 5% or more ((33)36) are associated with increased risk of fracture. Localized tenderness of the spine, kyphosis, or diminished distance between the lower ribs and the pelvic brim may be the result of one or more vertebral fractures. Abnormalities of gait, posture, balance, muscle strength, or the presence of postural hypotension or impaired level of consciousness may be associated with increased risk of falling. Bone tenderness may be caused by osteomalacia. Atrophic testicles suggest hypogonadism. Patients should be observed for stigmata of hyperthyroidism or Cushing’s syndrome. Blue sclera, hearing loss, and yellow-brown teeth are suggestive of osteogenesis imperfecta. Joint hypermobility and skin fragility could be due to Ehlers-Danlos syndrome. Urticaria pigmentosa may occur with systemic mastocytosis. Table 7 shows examples of abnormal physical exam findings with osteoporosis.

Table 7. Focused Physical Examination in a Patient with Osteoporosis
Component of physical exam	Example of finding of potential skeletal importance	Potential clinical implications for skeletal health
Vital signs	Low body weight or body mass index	Anorexia nervosa
	Loss of height	Vertebral fracture
	Loss of weight	Malignancy, malabsorption
Skin	Urticaria pigmentosa Dermatitis herpetiformis	Systemic mastocytosis Celiac disease
Skin	Striae, acne	Cushing’s syndrome, exogenous glucocorticoids
Head	Cranial dysostosis	Hypophosphatasia
Eyes	Blue sclera	Osteogenesis imperfect
Ears	Hearing loss	Osteogenesis imperfecta, sclerosteosis
Nose	Anosmia	Kallmann syndrome
Throat	Poor dentition	Increased risk of osteonecrosis of the jaw
Neck	Thyromegaly	Thyrotoxicosis
Lungs	Decreased breath sounds	Chronic obstructive pulmonary disease
Heart	Aortic insufficiency	Marfan’s syndrome
Musculoskeletal	Kyphosis	Vertebral fractures
	Spinous process tenderness	Acute vertebral fracture
	Decreased space between lower ribs and pelvis	Vertebral fractures
	Tender bones	Osteomalacia
	Inflammatory joint disease	Rheumatoid arthritis
	Hypermobility of joints	Ehlers-Danlos syndrome
	Muscle weakness	Vitamin D deficiency, osteomalacia
Abdomen	Hepatomegaly	Chronic liver disease
Abdomen	Surgical scars	Bariatric surgery, gastrectomy
Genitalia	Testicular atrophy	Hypogonadism
Neurological	Poor balance	High fall risk, vitamin D deficiency
Neurological	Dementia	Poor adherence to therapy, high fall risk

This table provides examples of findings on physical exam that may be helpful in the evaluation of skeletal health. It is not intended to show all findings of importance.

EVALUATION FOR SECONDARY CAUSES OF OSTEOPOROSIS

The possibility of previously unrecognized causes of skeletal fragility should be considered in every patient with osteoporosis (34), understanding that some patients with a T-score ≤ -2.5 may have a skeletal disease other than osteoporosis and some patients with osteoporosis have contributing disorders and conditions other than estrogen deficiency and advancing age that can be corrected. Collectively, these contributing factors are sometimes called secondary causes of osteoporosis. After an initial medical history is taken and physical exam is performed, appropriate laboratory testing and imaging may provide information that is critical for ongoing patient care.

The reported prevalence of secondary osteoporosis varies depending on the study population, the extent of the medical evaluation, and definitions for laboratory abnormalities. It is likely that many or most patients with osteoporosis have clinically significant contributing factors that may influence patient management. In a study of North American women receiving osteoporosis therapy, it was found that 52% had vitamin D inadequacy, defined as serum 25-hydroxyvitamin D (25-OH-D) levels less than 30 ng/ml (35). In another study of patients referred to an osteoporosis clinic, over 60% were found to have elements of secondary osteoporosis when vitamin D deficiency was very conservatively defined as serum 25-OH-D level less than 12.5 ng/ml (36, 37). In the same study, the number of patients with secondary osteoporosis was much higher when vitamin D inadequacy was more appropriately defined as serum 25-OH-D less than 33 ng/ml (38, 39).

It has been proposed by some that a bone density that is less than expected compared to an age- and sex-matched population, as represented by a low Z-score (e.g., less than -2.0), suggests a high likelihood of secondary osteoporosis and should be one of the triggers for further investigation (40, 41). While there may be some merit to this concept, there are few if any studies validating the use of a Z-score cutoff for this purpose. Since secondary causes of osteoporosis are common, a more effective strategy is to screen all patients with osteoporosis for contributing factors (42). The results of a metabolic evaluation may identify previously unrecognized diseases and conditions that require treatment in addition to, or instead of, standard osteoporosis pharmacological therapy.

Depending on the patient population being studied, different causes of secondary osteoporosis may predominate. Calcium deficiency, vitamin D deficiency, and sedentary lifestyle are common contributing factors for all patients. In women referred to an osteoporosis clinic with previously recognized medications or diseases contributing to osteoporosis, the most common were history of glucocorticoid use (36%), premature ovarian failure (21%), history of unintentional weight loss (10%), history of alcoholism (10%), and history of liver disease (10%) (36). When patients without previously recognized contributing factors were evaluated at the same specialty clinic, most (55%) were found to have vitamin D deficiency or insufficiency (serum 25-OH-D less than 33 ng/ml) (39), while 10% had hypercalciuria, 8% had malabsorption, and 7% had primary or secondary hyperparathyroidism (36). In men, the most common secondary causes of osteoporosis are long-term glucocorticoid use, hypogonadism, and alcoholism (43, 44). The increasing use of aromatase inhibitor therapy for breast cancer in women and androgen deprivation therapy for prostate cancer in men (45) is now recognized as an important factor in the development of osteoporosis in these patients. Other common causes for low BMD and fractures include multiple myeloma (46), gastric bypass surgery (47) and gastric resection (48). Treatable but easily missed secondary causes of osteoporosis include asymptomatic primary hyperparathyroidism (49), subclinical hyperthyroidism (50), mild Cushing’s syndrome (51), and malabsorption due to unrecognized celiac disease (52). Table 8 lists some of the causes of low BMD by category.

Table 8. Causes of Low Bone Mineral Density
Inherited	Nutritional	Endocrine	Drugs	Other
Osteogenesis imperfecta	Malabsorption	Hypogonadism	Glucocorticoids	Multiple myeloma
Homocystinuria	Chronic liver disease	Hyperthyroidism	Anticonvulsants	Rheumatoid arthritis
Marfan’s syndrome	Alcoholism	Hyperparathyroidism	Long-term heparin	Systemic mastocytosis
Hypophosphatasia	Calcium deficient diet	Cushing’s syndrome	Excess thyroid	Immobilization
	Vitamin D deficiency	Eating disorder	GnRH agonists
			Aromatase inhibitors

Although a variety of testing strategies have been proposed as screening for all patients with osteoporosis, a minimal cost-effective work-up for all patients consists of a complete blood count (CBC), serum calcium, phosphorus, creatinine with calculated or measured creatinine clearance, alkaline phosphatase, 24-hour urinary calcium, and serum 25-OH-D. Other laboratory tests may be indicated according to the patient’s clinical profile and the practice setting. A summary of useful common and uncommon laboratory studies with comments on their possible skeletal significance is provided below.

CLINICAL CASE

A 52-year-old postmenopausal woman with a history of irritable bowel syndrome (IBS) and a family history of osteoporosis (mother with hip fracture) is found to have osteoporosis on a DXA study. Evaluation for secondary causes of osteoporosis is unremarkable except for mild iron deficiency anemia (a long-standing problem, previously attributed to heavy menses) and a low 24-hour urinary calcium of 30 mg, with adequate calcium intake and normal renal function. Serum 25-OH-D is 29 ng/ml. Additional work-up shows a high titer of IgA endomysial antibodies consistent with celiac disease. This diagnosis is confirmed by a small bowel biopsy showing villous atrophy. She is started on a gluten-free diet, resulting in resolution of her “IBS” symptoms and correction of her anemia. One year later, with no pharmacological therapy for osteoporosis, there is a statistically significant BMD increase of 9% at the lumbar spine.

Celiac disease may result in osteoporosis due to calcium malabsorption, even in the absence of gastrointestinal symptoms. Treatment is strict lifelong adherence to a gluten-free diet, which may sometimes be followed by a substantial increase in BMD, as seen in this patient. A 24-hour urinary calcium is an inexpensive screening test for calcium malabsorption that should be considered a routine part of the initial evaluation of osteoporosis.

BASIC BLOOD TESTS

CBC- Anemia may be seen in patients with myeloma or malnutrition

Sedimentation rate- May be elevated with myeloma and rheumatic diseases.

Calcium- Among the many causes of hypercalcemia are primary and secondary hyperparathyroidism, hyperthyroidism, renal failure, vitamin D intoxication, and Paget’s disease of bone. Hypocalcemia may be seen with vitamin D deficiency and hyperphosphatemia.

Phosphorus- Hyperphosphatemia may occur with hypoparathyroidism, renal failure, and possibly with bisphosphonate therapy. Hypophosphatemia may be seen with primary or secondary hyperparathyroidism, vitamin D deficiency, tumor induced osteomalacia, and X-linked hypophosphatemia.

Alkaline phosphatase- High values can be seen with healing fractures, osteomalacia, and Paget’s disease, as well as occurring normally in growing children. Low values occur with hypophosphatasia, a rare genetic disorder that causes impaired mineralization of bone and dental tissue.

Vitamin D- The test that best reflects vitamin D stores is the serum 25-OH-D. While there is no consensus on the optimal range of serum 25-OH-D, a reasonable target for good skeletal health is approximately 30-50 ng/ml. This is likely to maximize intestinal absorption of calcium and minimize serum PTH levels. Interpretation of serum 25-OH-D levels is confounded by assay variability (59). Serum 1,25-(OH)₂-D3 is usually not helpful in the evaluation of osteoporosis patients, unless there are concerns regarding renal conversion of 25-OH-D to 1,25-(OH)₂-D3. Deficiency or insufficiency of vitamin D is very common and play a role in the pathogenesis of osteoporosis and osteomalacia.

Creatinine- Chronic kidney disease may cause an elevated creatinine level and renal osteodystrophy. Elderly patients with small muscle mass may have impaired renal function with a “normal” serum creatinine. An estimated glomerular filtration rate can be calculated using one of many formulae, such as that of Cockcroft and Gault (53) or modification of diet in renal disease study equation (54). Impaired renal function not only has adverse skeletal effects but also raises considerations regarding the type and dose of pharmacologic agents used.

TSH- Hyperthyroidism from any cause, including excess thyroid replacement, can usually be recognized by a low TSH. High bone turnover associated hyperthyroidism is associated with loss of bone mass.

Liver enzymes- Abnormalities may be caused by chronic liver disease, which is a risk factor for osteoporosis.

BASIC URINE TESTS

Urinalysis- Proteinuria may occur with multiple myeloma or chronic kidney disease. Abnormal cells may suggest kidney disease.

24-hour urine for calcium- A well-collected 24-hour urine for calcium is a helpful screening test for identifying patients with common disorders of calcium metabolism. The “normal” range of urinary calcium is not well established and varies according to many dietary factors and estrogen status in women (55). As a “rule of thumb,” urinary calcium may be considered elevated when it is greater than 250 mg per 24 hours in women; greater than 300 mg per 24 hours in men; or greater than 4 mg/kg body weight per 24 hours in either sex. It has been proposed that hypercalciuria can be easily classified as “renal” (renal calcium leak), “resorptive” (excess skeletal loss of calcium) or “absorptive” (increased intestinal absorption of calcium) (56). However, in clinical practice, these distinctions are not so easily established. Idiopathic hypercalciuria, perhaps the most common type of hypercalciuria (57), may be diagnosed if there are no underlying medical disorders (e.g., hyperparathyroidism, vitamin D toxicity, Paget’s disease of bone, multiple myeloma, sarcoidosis) and no obvious dietary excesses (e.g., calcium, sodium, protein, carbohydrates, alcohol) or deficiencies (e.g., phosphate, potassium) that are associated with hypercalciuria. In the absence of dietary calcium deficiency, vitamin D deficiency, malabsorption, liver disease, or chronic renal failure, low urinary calcium (less than 50 mg per 24 hours in women or men) is suggestive of calcium malabsorption and warrants further investigation. Celiac disease is a common (58) cause of asymptomatic malabsorption in osteoporosis that is treatable with a gluten-free diet.

ADDITIONAL STUDIES IN SELECTED PATIENTS

Celiac antibodies- Anti-endomysial antibody and tissue transglutaminase antibody are currently the serological markers of choice, with a higher sensitivity and specificity than anti-gliadin antibody and anti-reticulin antibody. If a serological marker is abnormal, or if there is a high clinical suspicion for celiac disease, the patient should be referred for endoscopy and small bowel biopsy.

Intact PTH- This may be elevated in patients with primary hyperparathyroidism or with secondary hyperparathyroidism due to disorders such as chronic kidney disease, vitamin D deficiency, or calcium malabsorption.

Serum protein electrophoresis and serum kappa/lambda light chain ratio- These are helpful tests to screen for possible multiple myeloma. Abnormal results may require further evaluation by an oncologist.

Overnight 1 mg dexamethasone suppression test or 24-hour urinary free cortisol- This is helpful to evaluate patients with suspected Cushing’s syndrome.

Serum total or free testosterone level- May be helpful in the assessment of men with osteoporosis.

Serum homocysteine- Elevated circulating homocysteine levels are associated with an increased risk of fractures (59). It is unknown whether reduction of homocysteine levels by increasing dietary intake of folic acid and vitamins B6 and B12 reduces the risk of fracture.

Serum tryptase and 24-hour urine for N-methylhistamine- Systemic mastocytosis is a rare cause of osteoporosis that can be diagnosed by a biopsy of typical skin lesions of urticaria pigmentosa, when present. Patients with systemic mastocytosis may sometimes present with osteoporosis and no other manifestations of the disease (60). When this disorder is suspected but skin lesions are not present, the finding of an elevated serum tryptase and/or urinary N-methyl histamine can be helpful, especially during or soon after a symptomatic episode of histamine release. However, normal values do not exclude the diagnosis. Bone marrow aspiration or biopsy, or non-decalcified double tetracycline labeled transiliac bone biopsy, may be necessary to confirm the diagnosis.

Serum bicarbonate- Renal tubular acidosis (RTA) has been associated with osteoporosis (61). With distal (type I) RTA, the serum bicarbonate is usually less than 15 mmol/l with a urine pH greater than 5.5 despite having systemic acidosis. This is due to the impaired ability of the distal nephron to secrete hydrogen ions effectively, which is a hallmark of the condition.

BONE TURNOVER MARKERS

Bone turnover markers (BTMs) are noninvasive laboratory tests of serum and urine that are readily available in clinical practice. While BTMs cannot be used to diagnose osteoporosis or determine the cause to osteoporosis, they have been very helpful in research to understand the pathophysiology of osteoporosis and other skeletal diseases and the mechanism of action of interventions used in the treatment of osteoporosis. In clinical practice, BTMs offer the potential of predicting fracture risk independently of BMD and may be useful in monitoring the metabolic effects of therapy (62). Drugs that are approved for the management of osteoporosis modulate bone remodeling in ways that are reflected by changes in BTMs. A decrease in BTMs with antiresorptive therapy is predictive of a subsequent increase in BMD (63)and reduction in fracture risk (64). The magnitude of BTM decrease with antiresorptive therapy is significantly associated with the level of fracture risk reduction, although the proportion of treatment effect due to the reduction in BTMs appears to vary according to the type of drug used (65). Teriparatide and abaloparatide, analogs of PTH and PTHrP, respectfully, are bone forming drugs associated with an increase in bone remodeling, with bone formation markers rising sooner and greater than bone resorption makers. Romosozumab is bone forming drug that uncouples bone resorption and formation, with an initial increase in bone formation markers and decrease in bone resorption markers.

Markers of bone resorption are mostly fragments of type I collagen, the main component of the organic bone matrix, which are released during osteoclastic bone resorption. These are measured in the serum or urine, with those available for clinical use including N-telopeptide of type I collagen (NTX), C-telopeptide of type I collagen (CTX), deoxypyridinoline (DPD), and pyridinoline (PYD). Bone formation markers are proteins secreted by osteoblasts or byproducts of type I collagen production by osteoblasts. They are measured in the serum and include bone specific alkaline phosphatase (BSAP), N-terminal propeptide of type I collagen (P1NP), and osteocalcin. CTX and P1NP have been proposed as the reference BTMs for clinical trials (66) and for clinical practice (67).

Clinical use of BTMs requires knowledge of their limitations as well as benefits. BTMs are subject to pre-analytical (biological) and analytical variability (62). Uncontrollable sources of pre-analytical variability include age, sex, menopausal status, pregnancy, lactation, fractures, co-existing diseases (e.g., diabetes mellitus, impaired renal function, and liver disease), drugs (e.g., glucocorticoids, anticonvulsants, and gonadotropin hormone releasing agonists), and immobility. Controllable pre-analytical sources of variability include time of day (circadian variability), fasting status, and exercise. Analytical sources of variability include specimen processing (e.g., collection, handling, and storage). Between-laboratory variability may be large (reported to be as much as a 7.3-fold difference), casting doubt on the validity of comparing specimens sent to different labs (68). Reference ranges for BTMs are not well established and may vary according to the population tested, the type of BTM, and the circumstances under which it is collected and processed.

In order to compare BTMs measurements longitudinally, it would be ideal to know the least significant change (LSC) and use this in a manner similar to what should be (but is probably not) common practice with DXA. However, the standards for calculating an LSC for a BTM are not as clear as with DXA, and the opportunity to do precision assessment for a BTM may not present itself. The Belgian Bone Club suggests using an estimated LSC by assuming an LSC of about 30% for serum BTMs and about 50-60% for urine BTMs (69). While the LSC for BTMs is almost always greater than for DXA, the magnitude of likely change is greater than DXA, with the “signal to noise ratio” that may be as good or even better than DXA. One strategy for the use of BTMs to monitor patients on antiresorptive therapy is to use absolute values rather that percent changes, as follows: treatment effect can be considered optimal when serum CTX has decreased by 100 ng/L or is below 280 ng/L, or when P1NP has decreased by 10 mcg/L or is less than 35 mcg/L (70).

A significant change of a BTM level in the appropriate direction following therapy is evidence that the patient is taking the drug regularly, taking it correctly, and that it is being absorbed and having the expected effect in modulating bone remodeling. Failure to achieve such a change in the BTM level is cause for concern and suggests that evaluation and possibly a reconsideration of treatment strategies. The use of BTMs allows assessment of drug effect sooner than with DXA, so that evaluation and corrective action, if needed, can be taken early in the course of therapy rather than later. Monitoring BTMs, especially in association with regular contact by a healthcare provider, may improve persistence with therapy (70). Despite the well-described limitations of BTMs, there is emerging support for their use in clinical practice, particularly in the assessment of response to therapy (62). Clinicians who are familiar with the benefits and limitations of BTMs may find them a helpful tool, in association with BMD testing, for managing patients with osteoporosis.

IMAGING STUDIES

Standard X-rays are used to diagnose fractures of all types and may sometimes suggest secondary causes of osteoporosis. Pseudofractures (Looser’s zones) are radiolucent lines running perpendicular to the bone cortex that may be seen in patients with osteomalacia. These probably represent stress fractures that have healed with poorly mineralized osteoid. Punctate radiolucencies may be seen in bone X-rays of patients with systemic mastocytosis. Primary hyperparathyroidism may cause bone cysts, subperiosteal bone resorption, brown tumors, and demineralization (‘salt and pepper’ pattern) of the skull. MRI, CT scanning, or nuclear imaging may be used to detect stress fractures that are not visible on X-ray. MRI of the spine is commonly used prior to vertebroplasty or kyphoplasty to determine the age of the fracture, the likelihood of the fracture being from causes other than osteoporosis, and whether there is retropulsion of bony fragments than could impair neurological function.

BONE BIOPSY

Non-decalcified double tetracycline labeled iliac crest bone biopsy is rarely used in clinical practice but may be helpful with difficult diagnostic problems. In the evaluation of renal osteodystrophy, a bone biopsy can distinguish between high turnover and low turnover bone disease, and possibly be an aid in the selection of therapy. With infiltrative disorders of bone, such as systemic mastocytosis, a bone biopsy or bone marrow aspiration may sometimes be the only way to make the diagnosis. In patients who are not responding to therapy as expected, or in patients with unusual presentations of osteoporosis, a bone biopsy may be indicated. Bone biopsies are required by the FDA for safety monitoring in clinical trials of osteoporosis drugs.

SUMMARY

Osteoporosis is a common skeletal disease with serious clinical consequences. Effective management of skeletal health includes appropriate selection of patients for bone density testing and assessment of risk factors for fracture. Prior to treatment, and when response to treatment is suboptimal, patients should be evaluated for secondary causes of osteoporosis. All reversible factors should be corrected and treatment should be individualized based on the clinical circumstances.

REFERENCES

NIH Consensus Development Panel. Osteoporosis prevention, diagnosis, and therapy. JAMA. 2001;285(6):785-95.
US Department of Health and Human Services. Bone Health and Osteoporosis: A Report of the Surgeon General. Rockville, MD: US Department of Health and Human Services, Office of the Surgeon General; 2004.
WHO Study Group on Assessment of Fracture Risk and its Application to Screening for Postmenopausal Osteoporosis. Technical Report Series 843: Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Geneva: World Health Organization; 1994.
Shuhart C, Cheung A, Gill R, Gani L, Goel H, Szalat A. Executive Summary of the 2023 Adult Position Development Conference of the International Society for Clinical Densitometry: DXA Reporting, Follow-up BMD Testing and Trabecular Bone Score Application and Reporting. J Clin Densitom. 2024;27(1):101435.
Lewiecki EM, Binkley N, Petak SM. DXA Quality Matters. J Clin Densitom. 2006;9(4):388-92.
Lewiecki EM, Binkley N, Morgan SL, Shuhart CR, Camargos BM, Carey JJ, et al. Best Practices for Dual-Energy X-ray Absorptiometry Measurement and Reporting: International Society for Clinical Densitometry Guidance. J Clin Densitom. 2016;19(2):127-40.
LeBoff MS, Greenspan SL, Insogna KL, Lewiecki EM, Saag KG, Singer AJ, et al. The clinician's guide to prevention and treatment of osteoporosis. Osteoporos Int. 2022;33(10):2049-102.
Qaseem A, Hicks LA, Etxeandia-Ikobaltzeta I, Shamliyan T, Cooney TG, Clinical Guidelines Committee of the American College of P, et al. Pharmacologic Treatment of Primary Osteoporosis or Low Bone Mass to Prevent Fractures in Adults: A Living Clinical Guideline From the American College of Physicians. Ann Intern Med. 2023;176(2):224-38.
Gregson CL, Armstrong DJ, Bowden J, Cooper C, Edwards J, Gittoes NJL, et al. UK clinical guideline for the prevention and treatment of osteoporosis. Archives of osteoporosis. 2022;17(1):58.
Kanis JA, Harvey NC, McCloskey E, Bruyere O, Veronese N, Lorentzon M, et al. Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures. Osteoporos Int. 2020;31(1):1-12.
Marshall D, Johnell O, Wedel H. Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ. 1996;312(7041):1254-9.
Wainwright SA, Marshall LM, Ensrud KE, Cauley JA, Black DM, Hillier TA, et al. Hip fracture in women without osteoporosis. J Clin Endocrinol Metab. 2005;90(5):2787-93.
Lewiecki EM, Laster AJ. Clinical applications of vertebral fracture assessment by dual-energy X-ray absorptiometry. J Clin Endocrinol Metab. 2006;91(11):4215-22.
Khan AA, Slart R, Ali DS, Bock O, Carey JJ, Camacho P, et al. Osteoporotic Fractures: Diagnosis, Evaluation, and Significance From the International Working Group on DXA Best Practices. Mayo Clin Proc. 2024;99(7):1127-41.
International Society for Clinical Densitometry. Facility AccreditationMarch 11, 2018. Available from: http://www.iscd.org/accreditation/.
Lotz JC, Cheal EJ, Hayes WC. Fracture prediction for the proximal femur using finite element models: Part I--Linear analysis. J Biomech Eng. 1991;113(4):353-60.
Cranney A, Guyatt G, Griffith L, Wells G, Tugwell P, Rosen C, et al. Summary of meta-analyses of therapies for postmenopausal osteoporosis. Endocr Rev. 2002;23(4):570-8.
Black DM, Bauer DC, Vittinghoff E, Lui LY, Grauer A, Marin F, et al. Treatment-related changes in bone mineral density as a surrogate biomarker for fracture risk reduction: meta-regression analyses of individual patient data from multiple randomised controlled trials. Lancet Diabetes Endocrinol. 2020;8(8):672-82.
Bouxsein ML, Eastell R, Lui LY, Wu LA, de Papp AE, Grauer A, et al. Change in Bone Density and Reduction in Fracture Risk: A Meta-Regression of Published Trials. J Bone Miner Res. 2019;34(4):632-42.
Hangartner TN. A study of the long-term precision of dual-energy X-ray absorptiometry bone densitometers and implications for the validity of the least-significant-change calculation. Osteoporos Int. 2007;18(4):513-23.
Njeh CF, Fuerst T, Hans D, Blake GM, Genant HK. Radiation exposure in bone mineral density assessment. Applied Radiation & Isotopes. 1999;50(1):215-36.
Bonnick SL. Bone densitometry in clinical practice- application and interpretation. 2nd ed ed. Totowa, N.J: Humana Press; 2004 2004.
Lewiecki EM, Richmond B, Miller PD. Uses and misuses of quantitative ultrasonography in managing osteoporosis. CleveClin J Med. 2006;73(8):742-52.
Fuggle NR, Reginster JY, Al-Daghri N, Bruyere O, Burlet N, Campusano C, et al. Radiofrequency echographic multi spectrometry (REMS) in the diagnosis and management of osteoporosis: state of the art. Aging Clin Exp Res. 2024;36(1):135.
Lewiecki EM. Assessment of Skeletal Strength: Bone Density Testing and Beyond. Endocrinol Metab Clin North Am. 2021;50(2):299-317.
Keaveny TM, Clarke BL, Cosman F, Orwoll ES, Siris ES, Khosla S, et al. Biomechanical Computed Tomography analysis (BCT) for clinical assessment of osteoporosis. Osteoporos Int. 2020;31(6):1025-48.
Qasim M, Lopez Picazo M, Ruiz Wills C, Noailly J, Di Gregorio S, Del Rio Barquero LM, et al. 3D-DXA Based Finite Element Modelling for Femur Strength Prediction: Evaluation Against QCT. J Clin Densitom. 2024;27(2):101471.
Vogt TM, Ross PD, Palermo L, Musliner T, Genant HK, Black D, et al. Vertebral fracture prevalence among women screened for the Fracture Intervention Trial and a simple clinical tool to screen for undiagnosed vertebral fractures. Fracture Intervention Trial Research Group. Mayo Clin Proc. 2000;75(9):888-96.
Gunnes M, Lehmann EH, Mellstrom D, Johnell O. The relationship between anthropometric measurements and fractures in women. Bone. 1996;19(4):407-13.
Siminoski K, Jiang G, Adachi JD, Hanley DA, Cline G, Ioannidis G, et al. Accuracy of height loss during prospective monitoring for detection of incident vertebral fractures. Osteoporos Int. 2005;16(4):403-10.
Margolis KL, Ensrud KE, Schreiner PJ, Tabor HK. Body size and risk for clinical fractures in older women. Study of Osteoporotic Fractures Research Group. AnnIntern Med. 2000;133(2):123-7.
de Laet C, Kanis JA, Oden A, Johanson H, Johnell O, Delmas P, et al. Body mass index as a predictor of fracture risk: a meta-analysis. OsteoporosInt. 2005;16(11):1330-8.
Ensrud KE, Ewing SK, Stone KL, Cauley JA, Bowman PJ, Cummings SR. Intentional and unintentional weight loss increase bone loss and hip fracture risk in older women. J AmGeriatrSoc. 2003;51(12):1740-7.
Lewiecki EM. Evaluation of the osteoporosis patient. In: Dempster DW, Cauley JA, Bouxsein ML, Cosman F, editors. Marcus and Feldman’s Osteoporosis. 2. Fifth ed. San Diego, CA, USA: Elsevier; 2021. p. 1475-500.
Holick MF, Siris ES, Binkley N, Beard MK, Khan A, Katzer JT, et al. Prevalence of Vitamin D inadequacy among postmenopausal North American women receiving osteoporosis therapy. J Clin Endocrinol Metab. 2005;90(6):3215-24.
Tannenbaum C, Clark J, Schwartzman K, Wallenstein S, Lapinski R, Meier D, et al. Yield of laboratory testing to identify secondary contributors to osteoporosis in otherwise healthy women. J Clin Endocrinol Metab. 2003;87:4431-7.
Wagman RB, Marcus R. Beyond bone mineral density-navigating the laboratory assessment of patients with osteoporosis. J Clin Endocrinol Metab. 2002;87(10):4429-30.
Barzel US. Recommended testing in patients with low bone density. J Clin Endocrinol Metab. 2003;88(3):1404-5.
Luckey MM, Tannenbaum C. Authors' response: Recommended testing in patients with low bone density. J Clin Endocrinol Metab. 2003;88(3):1405.
Harper KD, Weber TJ. Secondary osteoporosis - Diagnostic considerations. Endocrinol Metab Clin North Am. 1998;27(2):325-48.
Eastell R. Treatment of postmenopausal osteoporosis. NEnglJMed. 1998;338(11):736-46.
Favus MJ. Postmenopausal osteoporosis and the detection of so-called secondary causes of low bone density. J Clin Endocrinol Metab. 2005;90(6):3800-1.
Looker AC, Orwoll ES, Johnston CCJ, Lindsay RL, Wahner HW, Dunn WL, et al. Prevalence of low femoral bone density in older U.S. adults from NHANES III. JBone MinerRes. 1997;12:1761-8.
Orwoll ES, Klein RF. Osteoporosis in men. EndocrRev. 1995;16:87-116.
Bedatsova L, Drake MT. The skeletal impact of cancer therapies. Br J Clin Pharmacol. 2019;85(6):1161-8.
Rasch S, Lund T, Asmussen JT, Lerberg Nielsen A, Faebo Larsen R, Osterheden Andersen M, et al. Multiple Myeloma Associated Bone Disease. Cancers (Basel). 2020;12(8).
Yu EW, Lee MP, Landon JE, Lindeman KG, Kim SC. Fracture Risk After Bariatric Surgery: Roux-en-Y Gastric Bypass Versus Adjustable Gastric Banding. J Bone Miner Res. 2017;32(6):1229-36.
Adachi Y, Shiota E, Matsumata T, Iso Y, Yoh R, Kitano S. Osteoporosis after gastrectomy: bone mineral density of lumbar spine assessed by dual-energy X-ray absorptiometry. CalcifTissue Int. 2000;66(2):119-22.
Bilezikian JP, Silverberg SJ, Bandeira F, Cetani F, Chandran M, Cusano NE, et al. Task Force #8: Management of Primary Hyperparathyroidism. J Bone Miner Res. 2022;Epub.
Földes J, Tarján G, Szathmari M, Varga F, Krasznai I, Horvath C. Bone mineral density in patients with endogenous subclinical hyperthyroidism:Is this thyroid status a risk factor for osteoporosis. ClinEndocrinol(Oxf). 1993;39:521-7.
Mancini T, Doga M, Mazziotti G, Giustina A. Cushing's Syndrome and Bone. Pituitary. 2004;7:249-52.
Katz S, Weinerman S. Osteoporosis and gastrointestinal disease. Gastroenterol Hepatol (N Y). 2010;6(8):506-17.
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31-41.
Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. AnnInternMed. 2006;145(4):247-54.
Heaney RP, Recker RR, Ryan RA. Urinary calcium in perimenopausal women: normative values. Osteoporos Int. 1999;9(1):13-8.
Power ML, Heaney RP, Kalkwarf HJ, Pitkin RM, Repke JT, Tsang RC, et al. The role of calcium in health and disease. Am J Obstet Gynecol. 1999;181(6):1560-9.
Pacifici R. Idiopathic hypercalciuria and osteoporosis--distinct clinical manifestations of increased cytokine-induced bone resorption? J Clin Endocrinol Metab. 1997;82(1):29-31.
Fasano A, Berti I, Gerarduzzi T, Not T, Colletti RB, Drago S, et al. Prevalence of celiac disease in at-risk and not-at-risk groups in the United States: a large multicenter study. ArchInternMed. 2003;163(3):286-92.
McLean RR, Jacques PF, Selhub J, Tucker KL, Samelson EJ, Broe KE, et al. Homocysteine as a predictive factor for hip fracture in older persons. NEnglJ Med. 2004;350(20):2042-9.
Lidor C, Frisch B, Gazit D, Gepstein R, Hallel T, Mekori YA. Osteoporosis as the sole presentation of bone marrow mastocytosis. J Bone Miner Res. 1990;5(8):871-6.
Weger M, Deutschmann H, Weger W, Kotanko P, Skrabal F. Incomplete renal tubular acidosis in 'primary' osteoporosis. Osteoporos Int. 1999;10(4):325-9.
Brown JP, Don-Wauchope A, Douville P, Albert C, Vasikaran SD. Current use of bone turnover markers in the management of osteoporosis. Clin Biochem. 2022;109-110:1-10.
Greenspan SL, Parker RA, Ferguson L, Rosen HN, Maitland-Ramsey L, Karpf DB. Early changes in biochemical markers of bone turnover predict the long-term response to alendronate therapy in representative elderly women: a randomized clinical trial. J Bone Miner Res. 1998;13:1431-8.
Eastell R, Barton I, Hannon RA, Chines A, Garnero P, Delmas PD. Relationship of early changes in bone resorption to the reduction in fracture risk with risedronate. J Bone Miner Res. 2003;18:1051-6.
Bouxsein ML, Delmas PD. Considerations for development of surrogate endpoints for antifracture efficacy of new treatments in osteoporosis: a perspective. J Bone Miner Res. 2008;23(8):1155-67.
Vasikaran S, Cooper C, Eastell R, Griesmacher A, Morris HA, Trenti T, et al. International Osteoporosis Foundation and International Federation of Clinical Chemistry and Laboratory Medicine Position on bone marker standards in osteoporosis. Clin Chem Lab Med. 2011;49(8):1271-4.
Lee J, Vasikaran S. Current recommendations for laboratory testing and use of bone turnover markers in management of osteoporosis. Ann Lab Med. 2012;32(2):105-12.
Seibel MJ, Lang M, Geilenkeuser WJ. Interlaboratory variation of biochemical markers of bone turnover. Clin Chem. 2001;47(8):1443-50.
Bergmann P, Body JJ, Boonen S, Boutsen Y, Devogelaer JP, Goemaere S, et al. Evidence-based guidelines for the use of biochemical markers of bone turnover in the selection and monitoring of bisphosphonate treatment in osteoporosis: a consensus document of the Belgian Bone Club. Int J Clin Pract. 2009;63(1):19-26.
Fontalis A, Eastell R. The challenge of long-term adherence: The role of bone turnover markers in monitoring bisphosphonate treatment of osteoporosis. Bone. 2020;136:115336.

ABSTRACT

SCREENING FOR DIABETES MELLITUS AND PREDIABETES

DIAGNOSING DIABETES AND PREDIABETES

HbA1c

Fasting and Random Plasma Glucose

Oral Glucose Tolerance Test (OGTT)

OGTTS FOR THE DIAGNOSIS OF DIABETES AND IMPAIRED GLUCOSE TOLERANCE IN NON-PREGNANT INDIVIDUALS

OGTTS FOR THE DIAGNOSIS OF GESTATIONAL DIABETES

One-Step Strategy

Two-Step Strategy

OGTTS FOR POSTPARTUM TESTING OF WOMEN WITH GESTATIONAL DIABETES

Special Populations

OGTTS FOR DIAGNOSIS OF CYSTIC FIBROSIS- RELATED DIABETES

FASTING GLUCOSE FOR DIAGNOSIS OF PREDIABETES AND DIABETES IN PEOPLE LIVING WITH HIV

OGTTS FOR DIAGNOSIS OF POST- TRANSPLANTATION DIABETES

TESTS USED FOR CLASSIFICATION OF DIABETES

General Approach

C-peptide

Pancreatic Autoantibodies

Monogenic Diabetes Syndromes

ACKNOWLEDGEMENTS

REFERENCES

ABSTRACT

BACKGROUND

A HISTORICAL PERSPECTIVE OF BARIATRIC SURGERY

Small Bowel Bypass Procedures (1950-1970)

Stomach Stapling Procedures (1970-1990)

Adoption of the Laparoscopic Approach

CURRENT METHODS IN BARIATRIC SURGERY

Sleeve Gastrectomy

Laparoscopic Adjustable Gastric Banding (LAGB)

Roux en Y Gastric Bypass (RYGB)

One Anastomosis Gastric Bypass (OAGB)

Biliopancreatic Diversion / Duodenal Switch (BPD/DS)

Single Anastomosis Duodenal-Ileal Bypass with Sleeve (SADI-S)

Experimental Bariatric Procedures

MECHANISMS OF ACTION IN BARIATRIC SURGERY

Neurohormonal Changes

Bile Acid Metabolism

OUTCOMES AFTER BARIATRIC SURGERY

Mortality And Adverse Events

PERIOPERATIVE MORTALITY

Early Adverse Events (<30 days)

Late Adverse Events

Weight Loss Outcomes

SHORT AND MEDIUM-TERM OUTCOMES

LONG-TERM (>10 YEAR) OUTCOMES

Type 2 Diabetes and Bariatric Surgery

REMISSION RATES IN RCTs

DURABILITY OF REMISSION

MACROVASCULAR AND MICROVASCULAR COMPLICATIONS

OTHER HEALTH OUTCOMES AFTER BARIATRIC SURGERY

Cancer

Cardiovascular Disease

Liver

Dyslipidemia of Obesity

Hypertension

Asthma

Obstructive Sleep Apnea

IMPROVEMENT IN QUALITY OF LIFE (QOL)

IMPROVEMENT IN SURVIVAL

FUTURE DIRECTIONS COMBINING MEDICATIONS WITH SURGERY

WHO SHOULD BE CONSIDERED FOR BARIATRIC SURGERY?

NEEDS AND CHALLENGES

REFERENCES

ABSTRACT

THE HYPOTHALAMO-PITUITARY INTERFACE

REGULATION OF ACTH

Cells of Origin

ACTH/POMC

POMC GENE STRUCTURE

POMC PROMOTER

BIOGENESIS OF ACTH

HYPOPHYSIOTROPIC HORMONES AFFECTING ACTH RELEASE

Corticotropin Releasing Hormone (CRH)

Arginine Vasopressin (AVP)

Other Influences on ACTH Release

PHYSIOLOGY OF ACTH RELEASE

Pulsatility of ACTH Release

Circadian Rhythm