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Depression and Diabetes

ABSTRACT

 

In people with diabetes the comorbidity with depression is associated with micro- and macrovascular complications and increased mortality. Health-related quality of life is often reduced, and the adherence to treatment is generally low. Screening and diagnostic tools for depression are widely available. However, their use is only effective if subsequent treatment pathways are provided, which is often not the case. Meta-analyses on the treatment of depression in diabetes indicate that depression can be effectively treated with a variety of psychological and/or psychopharmacological interventions. However, results from the most frequently studied psychological treatment, cognitive behavioral therapy (CBT), have revealed decreasing effects ranging from large to low-grade, the longer the studies’ follow-up lasts. This may indicate CBT’s reduced long-term efficacy in diabetes patients with depression compared to depressive people without diabetes. As few data are available on the long-term effects of drug treatments, the studies’ conclusiveness is limited. Regarding the amelioration of glycemic control, the treatment results are heterogeneous, indicating a slight improvement by selective serotonin reuptake inhibitors and contradictory evidence for psychological interventions. This chapter concludes with a practice-oriented model of stepped care for depression treatment in people with diabetes. For complete coverage of this and all related areas of Endocrinology, please visit our FREE on-line web-textbook, www.endotext.org.

 

INTRODUCTION

 

Diabetes mellitus can be considered a paradigm of a 21st century chronic disease where prognosis and progression are significantly dependent on the patients’ lifestyle and self- management behaviors. Treatment requires lifelong planning and controlling both one’s food intake and making multiple changes to other lifestyles such as physical activity. The patient bears a high degree of personal responsibility, and many patients have trouble implementing treatment recommendations successfully. Comorbid mental disorders, which often hinder the smooth integration of diabetes into everyday life, constitute a major barrier to successful diabetes self-management.

 

As one of the most common mental disorders, depression occurs frequently in patients with diabetes and has a bi-directional relationship: diabetes raises the risk of depression, and depressed individuals also have an increased risk of developing type 2 diabetes. Since the co-morbidity of diabetes and depression has been understood for many years as a "hen-egg problem", recent findings imply parallel development of biological mechanisms thought to be responsible for both the development of depressive disorders and type 2 diabetes. Among other factors, it is assumed that the hypothalamic pituitary adrenal axis is dysregulated and that the immune system is overactivated over the life span, factors promoting insulin resistance, endothelial dysfunction, and cardiovascular disease, all of which raise the risk of depression, type 2 diabetes, and premature mortality. A direct depression-promoting effect of inflammatory processes on the brain is also assumed. Apart from these biological factors, numerous findings indicate that the psychosocial stress caused by diabetes and its complications also contribute to increased depression rates.

 

The comorbidity of depression and diabetes impacts medical outcome of people suffering from both conditions. More specifically, symptoms of depression are associated with hyperglycemia, micro- and macrovascular complications, and significantly increased mortality in people with diabetes. Patients often suffer from lower general and diabetes-specific quality of life, making how they manage their diabetes and adhere to therapy recommendations much more difficult.

 

The detection rate for depression in patients with diabetes is low and this inevitably goes hand-in-hand with inadequate therapy. Several screening and diagnostic tools have been developed that enable the rapid and reliable diagnosis of depression and are not costly to implement. But, if depression screening and subsequent diagnosis fail to lead to adequate care through an established treatment pathway, the potential adverse effects of not providing an evidence based intervention may outweigh the benefit of screening for depression.

 

The treatment of comorbid depression in diabetes differs mainly in its objectives from those of depression not accompanied by chronic physical illness. In view of the complex psychological and somatic interactions, depression treatment targets not only mental symptoms and problems, it also includes diabetes-related medical goals that focus particularly on improving the patient’s adherence to treatment and glycemic control to help prevent diabetes-related complications. The models of care for depression in diabetes include various approaches ranging from psychopharmacological treatment to psychological interventions. These are complemented by algorithm-based interventions delivered by different professional groups (e.g., collaborative care or stepped-care approaches). These are now being supplemented by telemedical or web-based interventions. Current scientific evidence demonstrated good treatment results regarding depression outcome in diabetes patients with comorbid depression. This applies to a variety of psychopharmacological or psychological interventions or a combination of both. Results are much less consistent regarding the physical targets of diabetes therapy, as contradictory findings reveal that we still do not know which is the most effective therapeutic approach in this field.

 

Based on existing guidelines and updated by current research, we suggest a practice oriented model of stepped care for patients with diabetes and depression that could be adapted to the individual patient’s care requirements.

 

This ENDOTEXT chapter aims to summarize the current state of research on the co-morbidity of diabetes and depression in adult patients with type 1 and type 2 diabetes.

Since a great deal of published research does not differentiate between the different types of diabetes, both types are addressed in this chapter as well. However, where differentiated information is possible, it is specified in the text. The concept that diabetes distress overlaps with depression but should be distinguished from depression as a mental disorder (1, 2) is not the subject of this chapter.

 

DEPRESSION

 

As depression is one of the mental disorders often overlooked by non-psychiatric physicians, it is frequently treated inadequately (3). This is also the case for patients with diabetes and comorbid depression; their diagnostic rate for depression ranges from 45% (4) to 50% (5). The dangerous interactions with diabetes and the frequent disregard of depression highlight the importance of informing healthcare professionals about the diagnostic criteria of depressive disorders.

 

According to the ICD-10 classification of the World Health Organization, depressive symptoms can be assigned to different categories of mental disorders (6). One essential distinguishing feature concerns the course of the depression. For the most part, a distinction is made between depressive episodes of varying degrees of severity that occur for the first time, and recurrent or persistent disorders.  In addition, depressive symptoms are treated in the context of adaptation disorders, other diseases and various diagnostic "residual categories". The present chapter deals only with unipolar depression and not with bipolar affective disorders, cyclothymia, or manic episodes.

 

The main focus of the ICD-10 classification is on the depressive episode, which distinguishes at least two weeks of major symptoms from additional symptoms.

 

Main symptoms

  • depressed mood,
  • loss of interest and enjoyment
  • reduced energy leading to increased fatigability and diminished activity

 

Other common symptoms

  • reduced concentration and attention
  • reduced self-esteem and self-confidence
  • feeling guilty and worthless
  • bleak and pessimistic views of the future;
  • ideas or acts of self-harm or suicide;
  • disturbed sleep;
  • diminished appetite.

 

The severity of the depressive episode is specified by counting the number of current depression symptoms:

  • mild (4-5 symptoms): 2 main and to 2-3 additional symptoms
  • moderate (6-7 symptoms): 2 main and 3-5 additional symptoms
  • severe (at least 8 symptoms): 3 main and at least 4 additional symptoms

 

In addition, a mild or moderate depressive episode can be described as coinciding with "somatic syndrome" or not. This applies if at least four characteristics of the somatic syndrome are fulfilled (in case of severe depressive episodes, the somatic syndrome is generally assumed due to the variety of symptoms).

 

Characteristics of Somatic Syndrome

  • loss of interest or pleasure in normally enjoyable activities
  • inability to react emotionally to a friendly environment or joyful events
  • early morning awakening (two or more hours before the usual time)
  • morning low
  • psychomotor inhibition or agitation
  • significant loss of appetite
  • weight loss, often more than 5% of body weight in the past month;
  • significant loss of libido

 

Furthermore, regarding a severe depressive episode: a distinction between patients "with" and "without" psychotic symptoms can be made. If the patient presents any psychotic symptoms (e g, impoverishment or delusional delusions), hallucinations, or depressive stupor, the patient is additionally referred to as "with psychotic symptoms".

 

The most important diagnostic categories of ICD 10 in which symptoms of unipolar depression occur are the

  • Depressive episode during which the above-mentioned symptoms occur for the first time for at least two weeks;
  • Recurrent depressive disorder diagnosed if a depressive episode has already occurred in the patient’s past;
  • Dysthymia, a persistent affective disorder in which symptoms of depression persist for at least two years but do not or rarely fulfill the criteria of a depressive episode; and
  • Adjustment disorders in which depressive symptoms may occur as part of a disturbed adaptation process following a stressful life event, but at no time are all the criteria of a complete depressive episode fulfilled. A distinction is made between the short depressive reaction (duration shorter than one month), the longer depressive reaction (lasting up to two years) or the adjustment disorder with mixed anxiety and depressed mood.

 

For a comprehensive description of the criteria for each category of specific disorders, see ICD-10 Clinical descriptions and diagnostic guidelines (6). More detailed criteria are defined in the ICD 10 Diagnostic criteria for research (7).

 

EPIDEMIOLOGY OF DEPRESSION IN DIABETES

 

Prevalence and Incidence of Depression in Patients with Diabetes

 

People with diabetes (type 1 and type 2) are affected by depressive symptoms relatively often. They reveal approximately twice the prevalence of depressive disorders as control groups without diabetes. According to the most often-cited meta-analysis of controlled studies published already in 2001, about 9% of patients with diabetes suffer from a depressive disorder (vs. 5% in the control groups) and about 25% of them suffer from clinically significant depression symptoms, some of which do not meet the criteria of a depressive disorder (vs. 14% in the control group) (8).

 

A recent meta-analysis using data from longitudinal studies included 11 studies reporting binary estimates (RR) and five studies reporting time-to-event estimates [hazard ratio (HR)]. Both RR and HR were significant at 1.27 (95 % CI 1.17–1.38) and 1.23 (95 % CI 1.08–1.40) for incident depression associated with diabetes mellitus and confirmed that diabetes is a significant risk factor for the subsequent onset of depression (9).

 

As a limitation to the generalizability of these results, it should be noted that rates of depression differ greatly across studies depending on their methodology and how they were conceived, factors that contribute to the inconsistency of their findings. For example, depressive symptoms and depressive disorders are often not clearly distinguished in scientific publications. Confusion is also caused by the fact that the concepts of diabetes distress and depression symptoms only partially overlap and are often insufficiently differentiated (2, 10, 11).

 

It should also be noted that sample selection effects and confounding sociodemographic variables also contribute to inconsistent results. For example, symptoms of depression were detected more frequently in type 1 than type 2 diabetes (12), in women compared to men (12, 13), in clinical samples compared to population-based samples, in patients with more than two diabetes complications (13) and also more frequently in questionnaire studies than in the more valid (semi-)standardized diagnostic interviews (8, 14, 15). Other differences arise from comparing patient cohorts of different ethnicities and from diverse regions (summarized in: (16)).

 

Recent results of a meta-analysis comparing patients with prediabetes, undiagnosed diabetes, and diagnosed diabetes revealed higher depression rates especially in individuals with diagnosed diabetes. This is likely due to the psychological burden of knowing you have a life-long chronic illness like diabetes and of being confronted with the burden of diabetes treatment – a few of the factors contributing to the occurrence of depressive symptoms (17).

 

Prevalence and Incidence of Diabetes in Patients with Depression

 

The interactions between depression and diabetes are bi-directional: not only does the risk of developing depression in addition to having diabetes increase, but depressed individuals also have a higher risk of developing type 2 diabetes during the course of their affective disorder. Previous meta-analyses of the relationship between depression and subsequent type 2 diabetes have revealed risk increases of 25% (18), 37% (19), 38% (20), and 60% (21). The most recent meta-analysis, published in 2015, included 33 studies covering a total of more than 2.4 million participants. Its results indicate that people with depression have a 41% higher risk of developing diabetes mellitus (with no differentiation between the types of diabetes) (22). Studies of this meta-analysis addressing only type 2 diabetes reported a 32% increase in the risk of developing diabetes in people with depression. Interestingly, this meta-analysis also examined regional differences, showing that studies from the USA reported a 28% risk increase, European studies 31%. By contrast, studies conducted in Asia showed a 149% increase in risk, however, the differences are not explained (22).

 

Interactions Between Diabetes and Comorbid Depression

 

Interactions between depressive disorders and diabetes are life-threatening and affect almost all outcome parameters of diabetes. There is ample evidence that depressive co-morbidity is associated with a markedly worse diabetes course. In patients with diabetes, depressive disorders are associated with hyperglycemia (23-25) and micro- and macrovascular complications (26). They also present markedly increased mortality (27-30), especially in elderly patients with type 2 diabetes (28) and in those with type 2 diabetes after myocardial infarction (31).

 

In terms of gender-specific differences: the results are inconclusive regarding the mortality of people with diabetes and depression. Findings from the Nurses' Health Study, a large prospective cohort study including 78.282 women in the US indicated an 3.1-fold increased relative risk (RRs) of mortality for women with diabetes and depression compared with participants without either condition; the authors interpreted this to mean that women have the higher risk of mortality (32). However, a large population-based longitudinal study in Norway recently revealed an excess mortality risk of 3,4 (Hazard ratio) associated with depression and anxiety only in men with diabetes, but not in women (33).

 

Negative interactions between diabetes and depression are also evident with regards to psychological outcomes. For example, the health-related quality of life of patients with diabetes and depression is considerably reduced (34) and the stress caused by diabetes is perceived as more pronounced than in non-depressed diabetes patients (35).

There is also solid evidence that depressed individuals with diabetes find it much harder to adhere to treatment recommendations. It has been observed that as depression worsens, diabetes medicines are taken less regularly and patients’ satisfaction with diabetes therapy decreases. Depressed patients with diabetes also eat unhealthier diets (36), are physically less active, are often overweight or obese, and are more likely to smoke than non-depressed people with diabetes (37-39).

 

DEPRESSION DIAGNOSIS AND SCREENING IN DIABETES

 

At most, half of depressed patients with diabetes in primary care are acknowledged to be depressed and insufficiently treated (40). Such inadequate diagnostic rates of depressive disorders are not specific to people with diabetes - they are a major problem in medical care (41, 42).

 

However, if patients with diabetes suffer from comorbid depression, diagnosing a depressive disorder can be made even harder because of the two conditions’ overlapping symptoms. Non-depressed individuals with diabetes, especially those with poor glycemic control, may suffer from fatigue, appetite change, or libido reduction (43) - typical symptoms of depression. Yet other symptoms of depression do not overlap with the physical symptoms of diabetes, and their detection by clinicians can facilitate the correct diagnosis of depression. This applies to the cognitive and affective symptoms of depression (e.g., depressive mood, anxiety, diminished self-esteem, feelings of guilt, pessimism, anhedonia, suicidal thoughts) (44). Another difficulty in diagnosing depression in patients with diabetes is that those affected are often unaware they are suffering from depression. They are often more apt to complain about diffuse physical maladies during medical consultation, while psychological symptoms are frequently concealed or trivialized (45).

 

Clinical interviews such as the Structured Clinical Interview for DSM-IV-TR Axis I Disorders SCID interview (46) SKID or the Schedule for Clinical Assessment in Neuropsychiatry 2.1 (47), are considered the gold standard for diagnosing mental disorders like depression. Being time-consuming and requiring appropriate training, they are mainly used in research. In some cases, questionnaires alone are used to screen and diagnose depression concurrently. However, as this method is associated with exaggerated rates of depression (48, 49), it is not an advisable diagnostic option.

 

Given the time constraints of medical consultation in primary care, offering screening questionnaires as the first step can be a time-saving alternative. Only a positive screening result would then be followed by a clinical diagnostic procedure to confirm the diagnosis and consider differential diagnoses. For the subsequent diagnosis of a depressive episode after positive screening, it can be useful to go through the individual items on the Patient Health Questionnaire PHQ-9 (50) together with the patient in conversation to check whether the criteria for a depressive disorder are fulfilled. To diagnose more complex forms of depression, it is advisable to refer the patient to a specialist such as a psychiatrist or clinical psychologist.

 

A confirmed diagnosis of depression must always be followed by a clear treatment pathway and continuous monitoring of therapy results (51).

 

Overview and Evaluation of Screening Tools

 

There are several screening and diagnostic tools that facilitate rapid and reliable diagnosis of depression and are not costly. In their review from 2012, Roy and colleagues (49) identified the following questionnaires as being those most frequently used to detect depression in patients with diabetes: the Beck Depression Inventory (BDI (52); BDI-II (53)), Center for Epidemiologic Studies Depression Scale (CES-D) (54), the Hospital Anxiety and Depression Scale (HADS) (55), and different versions of the Patient Health Questionnaire (PHQ)(56). The WHO-5 Well-Being Index (57) has also been evaluated as a first-step screening instrument for depression in adults with diabetes (58).

 

Many studies to identify the most effective questionnaires for screening depression in people with diabetes have led to contradictory results, some of which are attributable to different populations and settings (35, 48, 59, 60). In conclusion, the BDI, CES-D, PHQ, WHO-5 and HADS exhibit adequate clinical specificity and sensitivity when screening for depression in individuals with diabetes (58, 61). Altogether, the PHQ-9 seems to have the highest validity as the first step in a two-stage screening procedure in people with diabetes (62); it yielded the best evidence for adequate sensitivity (63). A recent population-based cohort study including patients with type 2 diabetes recommended using a PHQ-9 cutoff score of 5, as that demonstrated the best sensitivity (92.3%), with acceptable specificity (70.4%), in a two-stage screening setup in primary care to select individuals who need to undergo further psychological evaluation to confirm or reject the depression diagnosis (63).

 

Effectiveness of Depression Screening in Diabetes Care

 

There is a controversy about the recommendations to screen for illnesses, as long as no advantage of screening has been demonstrated and negative consequences cannot be ruled out. An example of a screening disadvantage is that the stigma of a depression diagnosis can lead to the exclusion of health insurance coverage (64).

 

Results of a Cochrane meta-analysis showed that depression screening in the general population has little or no effect on detection rates or the treatment of depression by practitioners when a positive screening result is not associated with specific treatment options. Thus recommendations for screening for depression without subsequent established treatment pathways are not considered worthwhile (65). Similar conclusions have also been drawn by various reviews addressing the screening for depression in people with diabetes (49, 51, 61, 66).

 

Two RCTs demonstrated the lack of a benefit from depression screening in individuals with diabetes in the absence of subsequent treatment pathways for patients identified as positive for depression. Both studies’ authors found that compared to standard therapy, there was no subsequent alleviation of depressive symptoms thanks to a positive screening result, even when treatment costs rose slightly (67, 68).

 

Various reasons have been identified for the disappointing efficacy of depression screening in people with diabetes (51): First, the quality of treatment for depression in primary care tends to be suboptimal (69) – an assumption we can also make for patients with diabetes (61). Another factor is that individuals with diabetes tend to be reluctant to participate in depression screening and to follow a subsequent treatment recommendation (70-72). There is also evidence that patients (70, 71) or those in poor health (72) are often underrepresented in screening procedures. Finally, an obstacle to effective depression screening also lies in the fact that some medical staff may perceive screening as being incompatible with a patient-centered approach (73).

 

To date, there is insufficient scientific evidence for the cost-effectiveness of depression screening in diabetes patients. Furthermore, as the quality criteria (74) for screening are unfulfilled in many countries, screening recommendations must always be considered against the background of the different health care systems in many countries (75). In contrast to the limitations described above, there is clear scientific evidence that depression screening has a positive effect on the outcome of treatment provided it is followed by subsequent confirmation of the diagnosis and adequate treatment (76, 77).

 

To summarize the latest scientific evidence, we can conclude that depression screening for patients with diabetes is only effective when it is embedded in a comprehensive healthcare system that ensures subsequent diagnosis and treatment. Where these possibilities exist, screening should be offered on a regular basis. Otherwise, depression screening is neither effective nor ethically justifiable (51).

 

Practical Recommendation for Screening

 

Different questionnaires like the Problem Areas in Diabetes (PAID) questionnaire (78) or the WHO-5-Well-Being-Index, which possess good specificity and sensitivity, have been used for depression screening. However, their items are formulated in a manner quite distinct from the diagnostic criteria of a depressive disorder. Screening with the Patient Health Questionnaire PHQ-9 (79) is therefore preferable as its items are almost identical to those of depression criteria – a factor that could help structure the subsequent depression diagnosis in a face-to-face consultation in case of a positive screening result (text box 1).

Text box 1: Example of an effective two-step screening and diagnostic procedure for depression followed by treatment recommendation in primary care

The two questions of the Patient Health Questionnaire PHQ-2 (50) (sensitivity 95%, specificity 57%(80)) can either be presented as a questionnaire in preparation for the consultation or it can be included in the interview. They are identical to the first two items on the PHQ-9. If they are presented during the face-to-face consultation it is advisable to briefly explain the procedure to the patient beforehand. For example: “I’d like to go through a list of symptoms that sometimes occur when you feel unwell. It is simply a question of whether you have suffered from the symptoms on this list over the past two weeks on most days and most of the day.” After the patient has given his or her consent, the questions of the PHQ-9 are read aloud.

 

Start with the two questions ‘Over the past two weeks have you been bothered by

1. a) little interest or pleasure in doing things

1. b) feeling down, depressed or hopeless’.

 

If one of the questions is answered with “yes” ask the remaining seven questions on the PHQ-9 (representing the depression criteria). If not, the procedure can be terminated here.

Since this is a third-party assessment, the decision as to whether a criterion is fulfilled is up to the physician, not the patient. If this procedure is carried out consistently, the diagnostic assessment takes less than 5 minutes.

If you are not qualified to diagnose depression, you should refer the patient to a healthcare professional after a positive screening result. With trained healthcare professionals, the depression diagnosis is confirmed or rejected based on the patient’s answers. If there are doubts about the validity of the depression diagnosis, consultations should be carried out by a specialist (psychiatrist or clinical psychologist).

If the diagnosis is confirmed, it is crucial to inform the patient about treatment options and specific pathways where treatment can be obtained.

 

 

 

 

Overview

 

Patients with type 1 diabetes have a complex management regimen to follow to maintain optimal health. This includes regular and frequent monitoring and keeping a record of blood glucose concentrations, knowing what varying glucose values signify, and being able to calculate and administer insulin doses in line with their carbohydrate intake and physical activity. These self-care activities have a psychological impact, and it is widely acknowledged that many patients have difficulty mastering them while striving towards optimal glycemic control. Understanding the mechanism between type 1 diabetes and depression will be examined along the lifespan from childhood and adolescence to adulthood.

 

Childhood

 

Around half of all cases of type 1 diabetes have their onset in childhood and thus the potential to cause substantial disruption to normal developmental processes which in turn increase the risk of depression.

 

Depression can be difficult but not impossible to diagnose in childhood, yet few studies have investigated the association between depression and type 1 diabetes during that phase of life. It is likely that the child experiences distress that probably goes undetected but which might manifest as irritability, oppositional behavior, refusing to go to school, or abnormal illness behaviors. The adult caregiver is usually responsible for the complex decision-making associated with these tasks, such as dosing insulin based on blood glucose readings and diet, and these issues should be considered in conjunction with the burden of parental responsibility (81).

 

Very few studies have addressed of the effect of the family milieu, and those that exist suggest that children with type 1 diabetes who grow up in an high expressed emotion environment are more likely to have poor glycemic control (82, 83). The quality, nature and strength of attachment between child and parents is a key factor in how well the child adjusts to type 1 diabetes and in its psychological sequelae. The attachment theory proposes that past experiences with caregivers are incorporated psychologically to form cognitive models that inform future interpersonal relationships, and these patterns of attachment persist in later life and may replicate in the individual's relationship to their diabetes (84, 85).

 

Adolescence

 

The transition from childhood to adolescence is when caregiving is transferred from the patient’s parents to self-managing their diabetes. Greater independence coincides with emergence of risk-taking behaviors, such as experimenting with alcohol and other substances, the development of one’s identity, and desire for peer approval (86, 87). Biologically speaking, puberty is associated with physiological insulin resistance in part to increase the production of growth hormone. In view of these rapid psychological and physiological changes, diabetes distress is widely acknowledged in adolescents with type 1 diabetes, and is associated with poor glycemic control, prominent negative beliefs about diabetes, such as the fear of hypoglycemia when with others, and reduced self-efficacy (88). These experiences of transition from childhood dependence towards adulthood and independence can be linked to emotions expressed within the family that are associated with poor glycemic control (89).

 

Adolescence is a critical window for the emergence of eating disorders, as becoming more aware of one’s body and the body image are part of the process of becoming aware of the self, and their interaction with type 1 diabetes is additive at this stage of life. Depression is often a comorbidity of eating disorders (90). In a case-control study comparing patients with both type 1 diabetes and an eating disorder to those with only an eating disorder, the group with type 1 diabetes had statistically significantly lower scores on the Beck Depression Inventory—an unexpected outcome (91).

 

 

Early Adulthood

 

Despite the plethora of studies reporting the prevalence of depression in type 1 diabetes in adulthood, mechanistic studies of depression are sparse. Those who are most depressed have the poorest glycemic control (92). However, cross-sectional evidence suggests that diabetes-specific emotional distress, rather than depression, is associated with poor glycemic control in adults with type 1 diabetes (93). Another mechanism is social problems that are very often neglected in the conventional clinical model; patients with depression are more likely to be of non-Caucasian ethnicity and have lower socioeconomic status (94).

 

 

Common Biological Origins of Depression and Type 2 Diabetes

 

The association between depression and type 2 diabetes is bidirectional and the underlying mechanisms are complex. Mediation by behavioral factors such as reduced self-care do not fully explain this link. For instance, depressive symptoms are not as strongly associated with worse glycemic control as would expect (95). Depressive symptoms appear to have a stronger effect on the risk of type 2 diabetes than the effect of type 2 diabetes on the risk for depression (60% versus 24%, respectively) (21, 96).

 

In terms of the natural history of type 2 diabetes, pooled data suggest there is also a link between depression and insulin resistance (97). A few prospective studies showed that depression is associated with later insulin resistant partly attenuated by obesity (98). These findings suggest there may be preceding risk factors and mechanisms shared by both conditions. Potential common mechanisms include the chronic activation of innate immunity, the HPA axis, and circadian rhythms.

 

Innate Immunity and Inflammation

 

Activation of the innate immunity and an acute-phase inflammatory response underlie the pathogenesis of type 2 diabetes, factors substantiated by systematic reviews of observational studies (99). There is also evidence that the mechanism of some experimental diabetes treatments may be anti-inflammatory, such as interleukin 1 receptor antagonist and non-steroidal anti-inflammatory drugs (100, 101). The cytokine-mediated inflammatory response is also implicated in depression. Increased cytokine serum concentrations appear to communicate across the blood-brain barrier (102). Depressive symptoms are a common side effect of inflammatory agents such as the cytokine interferon alfa (103). A meta-analysis of the association between cytokines and major depression found that depressed individuals presented statistically significantly higher circulating concentrations of tumor necrosis factor (TNF) and interleukin-6 (104). Furthermore, adjunctive therapy with the anti-inflammatory celecoxib (PTGS2 inhibitor) reduced depressive symptoms (105).

 

Whether the role of innate immunity in depression in people with type 2 diabetes is the same as those with depression but without type 2 diabetes is not known, but on face value it is likely to be the same mechanism. In a population-based sample of people with incident-type 2 diabetes, those with significant depressive symptoms already had a poor prognosis at diagnosis. They were more overweight, approximately 5 years younger, had higher concentrations of C-reactive protein (CRP) and interleukin 1-receptor antagonist, and higher white-cell counts, but not worse glycemic control than people with type 2 diabetes who were not depressed (106). Increased concentrations of CRP and interleukin 6 are known to raise the risk of type 2 diabetes (107) and depression (108) after adjusting for covariates. In a large Japanese cohort of over 3500 outpatients with type 2 diabetes, the cross-sectional association between high CRP concentrations and depression was significant in those with high BMI (109). Depression is associated with a significant increased risk of dementia in patients with type 2 diabetes compared to those without depression and without type 2 diabetes, (110) and increased concentrations of interleukin 6 are associated with cognitive decline in patients with type 2 diabetes (111).

 

The association between the activation of innate immunity and depression and type 2 diabetes has been observed early in the life course (112). Childhood abuse, neglect, or both are major mediators of the cross-sectional relation between increased concentrations of inflammatory cytokines and depression in adults (113).

 

If inflammation is involved in pathogenesis of depression in type 2 diabetes, reducing inflammation might be a novel treatment. However, no studies have attempted to modify inflammation when treating depression in patients with type 2 diabetes. With the potential benefit of improving glycemic control and alleviating depressive symptoms concurrently, anti-inflammatory approaches to treat depression in patients with type 2 diabetes should be a focus of the next generation of research.

 

The Hypothalamic-Pituitary-Adrenal Axis (HPA Axis)

 

Acute and chronic stress activates the HPA axis which regulates the adrenal glands’ glucocorticoid production. There are many definitions of psychosocial stress, and depression lies within the stress spectrum. Here stress is understood as what the individual perceives as a psychological burden based on how they interpret their past and present sensory inputs from their environment. Psychosocial stress entails many different environmental processes and factors ranging from socioeconomic deprivation and occupational status and hierarchy, life events, abuse, and trauma.

 

Chronic stress is associated with hypercortisolemia and can lead to increased circulating free fatty acids that can impair the function of insulin (114). These factors are thus on the causal pathway toward metabolic dysfunction, insulin resistance, and type 2 diabetes.

Depression is associated with chronic dysregulation of the HPA axis. Excess cortisol hinders neurogenesis in the hippocampus, a region implicated in both depression and type 2 diabetes (115-117) The difficulty in interpreting many of these studies is that overactivation of the HPA axis is most obvious in patients with severe depression, whereas most depressed individuals suffer from depression of mild-to-moderate severity. The evidence of HPA-axis dysregulation in this group is less convincing (118).

 

Nevertheless, that HPA-axis dysregulation might play a role represents a plausible common link in both depression and type 2 diabetes (119). Excess stress early in the life course leads to attenuated development of the hippocampus and amygdala, which are areas in the brain linked to both depression and type 2 diabetes (120). Pharmacological manipulation of the HPA axis could provide novel treatments for both conditions, as animal models have suggested, but such investigations have not been conducted in humans yet (121).

 

Circadian Rhythms

 

Both depression (122) and type 2 diabetes  reveal disrupted circadian rhythm and sleep patterns. It is noteworthy that increased concentrations of CRP and interleukin 6 are present in a range of disturbed sleep patterns such as hypersomnolence, decreased slow-wave sleep, and increased rapid eye movement density (123-126).

 

At the cellular level, environmental cues such as light–dark cycles, food, and social cues, control the expression clock genes (127). In patients with type 2 diabetes, clock gene expression has been directly associated with fasting glucose concentrations (128). In patients with depression, sleep deprivation therapy might be due to the resetting of abnormal clock genes and subsequent restoration of circadian rhythms (129). This finding highlights the translational potential of these emerging biological pathways, and studies investigating the role of clock genes in depression in patients with type 2 diabetes are needed.

 

Psychological Factors

 

Depression is one of the most common psychological factors in type 2 diabetes, but there are additional independent but not mutually exclusive psychological factors, namely the diabetes distress or burden, and other psychological processes such as disordered eating.

 

Diabetes Distress

 

Generic quality of life, wellbeing and distress measures enable us to compare conditions, but they do not capture the distress and burden that relate specifically to the patient’s disease (2, 35). This is important because these specific cognitions and affect or worries are linked to avoidant disease behaviors. In the context of diabetes, this includes medication administration, the self-monitoring of biodata, and assuming a healthier lifestyle. Thus, there is validity to proposal that detecting and intervening with negative, diabetes-related cognitions and emotions may help improve confidence and the ability to self-manage. Typical type 2 diabetes cognitions are very closely related to guilt and shame worsened by societal stigma and “fat shaming”, namely cultural beliefs that the patient is to be blamed for the condition through the neglect of their health and body. Other diabetes-specific stressors are living with fluctuating blood glucose concentrations, the continuous need to calculate and balance insulin doses with carbohydrate intake and physical activity, and worries about hypoglycemia and about passing the condition on to their offspring. Patients often describe these as burdens that are '24/7'.

 

Delays in initiating insulin treatment are also increasingly acknowledged (130). The reasons are multifactorial, but in essence the patient-clinician relationship sometimes can sometimes discourage the use of insulin. Clinicians may avoid mentioning insulin as a treatment option, as that is akin to giving bad news, and some use insulin as a threat in the ill-founded hope that the patient will then adopt a healthier lifestyle and take their diabetes medication as prescribed. Patients, on the other hand, perceive insulin as the end-of-the-line, that disabling and frightening complications are around the corner, that they have been a 'bad diabetic' and failed; they may worry about injecting, or be afraid of needles (of both injecting insulin and other injectable therapies, and of lancing to check blood glucose) (131). In some cultures, insulin initiation may lead to marital breakdown. When these fears lead to anxious or depressive symptoms, this can lead to the phobic avoidance of insulin therapy.

 

The most commonly used measures  of diabetes distress are the Problem Areas In Diabetes (PAID) scale (78), and its revised and shorter version, the 17-item Diabetes Distress Scale (DDS) (132), both of which quantify diabetes-distress. Up to a third of people with diabetes suffer from diabetes distress, and its severity and frequency differ across clinical settings (less in primary than in secondary care) (133), nations, and ethnicities (134).

Diabetes-distress exhibits moderate to strong positive correlations with self-reported measures of depression (135). There has been longstanding controversy as to which (depression or distress) has the strongest effects on self-care, and whether diabetes distress is a cognitive representation of depression or an independent psychological process (136). In a large longitudinal (lasting over 12 months) multinational study  of adult patients with both types of diabetes, there were slightly higher prevalence rates of diabetes distress versus depressive symptoms (13% versus 10%, respectively ) with about 5% screening positive for both (137). On the other hand, in another study, worse glycemic control increased the risk for diabetes distress, but not for depressive symptoms (138). There is still a need for more observational studies using repeated measures to monitor the onset, progression, and interaction between depressive symptoms and diabetes distress and the relative effects of these on self-management. This is clinically important to develop innovations in psychological interventions, as the scientific community needs to decide which should take priority: treating depressive symptoms, or alleviating diabetes distress.

 

Other Psychological Factors

 

That eating disorders are common in type 2 diabetes was first described over 20 years (139, 140), yet there is still insufficient research in this field. Many patients describe their behavior as grazing, emotional eating, or a feature of boredom especially when they are sedentary, such as when doing office work or watching TV. There is a paucity of cross-sectional studies assessing this comorbidity and determining which of these conditions comes first. This topic would seem important to the primary prevention of type 2 diabetes, and to ensuring the most appropriate treatments are targeted. For instance, interventions to integrate depression management in type 2 diabetes might alleviate depression, but if longstanding habits, e.g., relieving negative emotions by eating, are not also addressed, they will persist.

 

PREVENTION OF DEPRESSION IN PEOPLE WITH DIABETES

 

Given the increased risk of depression in people with diabetes, it seems necessary to offer interventions to prevent depression for this high-risk group of patients. In fact, as results from a meta-analysis demonstrated, there are effective approaches to prevent depression in people without diabetes (141). However, there is presently no scientific evidence on such interventions in people with diabetes (142).

 

Two recent trials focused on the secondary prevention of major depression for patients with diabetes already affected by minor depression, a group with a substantially higher risk for exacerbated depression. In the first trial, a stepped-care program for subthreshold depression was compared with usual care in patients with type 2 diabetes and/or coronary heart disease. Their results indicated that this intervention was no more effective than usual care in preventing major depression (143). In contrast, results from a multicentric, randomized, controlled trial including elderly patients with type 2 diabetes and minor depression demonstrated that after 15 months, cognitive behavioral therapy (CBT) was more effective than treatment as usual to prevent the progression or conversion to major depression (144).

 

TREATMENT OF DEPRESSION IN DIABETES

 

Treatment Goals

 

Considering the deleterious interactions between the two disorders, depression treatment should obviously always focus simultaneously on medical and psychological goals in people with diabetes (51, 145). Depression-related goals prioritize the prevention of suicidal acts where relevant in individual cases. Apart from this, the central aim of the treatment of depression is complete remission or at least significant alleviation of depression symptoms. Further objectives include preventing subsequent depressive episodes and improving health-related quality of life. The most important medical treatment goal is to reduce diabetes-related complications and premature mortality. Glycated hemoglobin (HbA1c) is an established biomarker for the prognosis of diabetes and is thus usually considered a primary target variable. These somewhat general therapy goals are supplemented by the patients’ goals, which are usually defined more concretely and often incorporate other aspects of their life (text box 2). In summary, providing the ideal therapy of depression for patients with diabetes would be an intervention that reduces the symptoms o depression and improves glycemic control concurrently (51, 145).

 

There is no scientific evidence for prioritizing medical or psychological treatment goals for people suffering from depression and diabetes. However, from the clinical perspective it would appear sensible to focus initially on the rapid alleviation or remission of depression. This recommendation is based on the differences in the time course of treatment responses; where response to treatment can be expected within 2 to 4 weeks of starting antidepressants and several weeks longer for psychological interventions. By contrast, behavioral changes towards a healthier lifestyle or changes in diabetes treatment leading to better glycemic control take several months until an assessment is feasible. Most important, alleviating depression may be a prerequisite to good diabetes self-management, as people with diabetes are more likely and willing to adhere to their diabetes management if they are in better spirits and are feeling more positive (51).

 

 

Text box 2: How to improve the adherence to treatment goals in patients with diabetes and depression treated in primary care?

Following a participatory decision-making encounter, it is advantageous to discuss therapy goals together with the patient to heighten their commitment to achieving their goals (146). It is not uncommon, however, for patients to formulate goals that cause the practitioner to worry that ‘diabetes is being neglected’. In such cases, it makes obvious sense to encourage additional diabetes-related targets. However, therapy goals set by healthcare providers are usually only effective when the patient genuinely adopts them. For example, a well-intentioned recommendation to reduce the "HbA1c value by a percentage point" or to become "physically more active" can trigger a socially desirable response in many patients: The patients agreement to the recommendation without actually having decided to commit themselves to this goal. Since they often fail to fulfill this obligation, they often feel guilty or discouraged - factors that can then impair the relationship between the practitioner and patient. To avoid this negative interaction and introduce goals from the practitioner’s perspective, it can be useful to explicitly emphasize that in addition to the patient's goals, a suggestion is made from the practitioner's professional point of view. That goal should be formulated as concretely and as action-oriented as possible to be fulfilled within a specific time frame. Instead of proposing weight loss or lower HbA1c, the specific behaviors that would lead to those conditions should be identified and recommended (147). The patient should then be asked whether they are willing to work toward this objective and how important they find the recommendation. The basic attitude in the conversation should convey serious openness towards the patients‘ potentially different goal. If the patient agrees in principle with the recommended goal, they should be asked what problems are likely to crop up while trying to reach the goal. If the goal seems overly ambitious, the practitioner should attempt to adapt their recommendation to the patient's condition, motivation, and resources as the first step. In the further treatment course the practitioner can then check whether more demanding goals would be acceptable and more apt to be implemented by the patient.

 

Models of Care

 

Various care models are available for treating depression in diabetes, namely conventional consultations, psychopharmacological treatments, psychological interventions and increasingly, telemedical and web-based treatment approaches (51, 148, 149).

The vast majority of the evaluated psychopharmacological treatment used antidepressants, especially selective serotonin reuptake inhibitors (SSRI) and in some cases supplementation with magnesium and vitamin D for patients with corresponding deficiencies.

Psychological interventions delivered by different professional groups include problem-solving techniques, self-management strategies and counseling, cognitive behavioral therapy (CBT) and rarely, psychodynamic therapy. These approaches have also been supplemented by attempts to increase the level of physical activity in depressed patients with type 2 diabetes. The treatment settings of the various interventions ranged from individual or group therapy to complex interventions such as collaborative care or stepped-care approaches.

 

Collaborative care interventions are interdisciplinary team-based and population-focused approaches (150) in which evidence-based treatment options, the routine monitoring of outcomes, and proactive follow-up contacts are provided. This is supplemented by self-management training and support for patients, the supervision of care managers, and decision support for primary care physicians. On the other hand, stepped-care approaches rely on algorithm-based treatment plans that are individually tailored to the needs and problems of each patient. The fundamental idea behind these models is to offer different step-by-step, evidence-based treatments whereby, based on specific cut-off measurements, those involved decide whether the outcome suffices, or whether the next treatment stage should be initiated. Patients' preferences are also taken into account (148).

 

Most recent developments in the treatment of depression in diabetes are web-based interventions and mobile health applications that focus on behavioral health coaching and the CBT-oriented self-management of depression (149).

 

Summary of Meta-Analyses for the Treatment of Depression in Diabetes

 

Interventions to treat depression in people with diabetes have been systematically evaluated since 1998 in randomized controlled trials (151). Since then, this field of research has been developing rapidly and several meta-analyses or systematic reviews are now available (see table 1). However, considering the summarizing results of the meta-analyses it is important to consider that the underlying individual RCTs show large methodological variations. This includes the type of interventions investigated (face-to-face intervention, telephone or web-based treatment, group versus individual treatment, medication, etc.), comparison conditions, the type of health-care provider service providers (e g, primary, secondary or collaborative care) and the methodological quality of the studies. Altogether this leads to the limited comparability of the available studies. While older meta-analyses or systematic reviews attempted to summarize all available intervention studies in this field (51, 152, 153), meta-analyses for specific interventions (154-157) are now increasingly being published.

 

In line with the objective of a summarizing description, this chapter does not present individual studies on the treatment of depression in diabetes, but presents all meta-analyses and systematic reviews of RCTs published so far, supplemented by a meta-review from 2015 (51) (see table 1). The results are presented in individual sections for the different interventions. Effect sizes (Cohen`s d and Hedges’ g) are considered as small from 0.2 to 0.5, moderate from 0.5 to 0.8, and large for > 0.8 based on benchmarks suggested by Cohen among others (158, 159).

 

Psychological Interventions

 

Summarizing the results of the available meta-analyses on the effectiveness of psychological interventions for the treatment of depressive disorders in people with diabetes, moderate to strong treatment effects can be observed in meta-analyses with some methodological limitations, including the use of combined measures not differentiating between glycemic control and depression symptoms (152) or the non-inclusion of a substantial number of relevant RCTs (155).  Meta-analyses or systematic reviews with a more rigorous methodology, on the other hand, tend to indicate only medium effect sizes regarding the reduction of depression intensity and the achievement of remission (51,161).

 

Two recent meta-analyses (154, 157), analyzed exclusively the effectiveness of CBT in people with diabetes and comorbid depression and included some of the RCTs of the aforementioned meta-analysis updated with newer RCTs. Interestingly, the results show decreasing effects for CBT the longer the follow-up duration of the studies lasts, starting with moderate-to-strong effects in the short-term, small-to-moderate effects in the medium-term and small effects in the long-term follow-up analyses. These data may indicate CBT’s reduced long-term efficacy in diabetes patients with depression compared to depressive people not affected by diabetes (160). Thus, the former assumption that people with diabetes can benefit from CBT as much as depressive people without diabetes is challenged by newer data. It can still be assumed that this group of patients benefits well in the short and medium term, but the long-term effects may be lower than expected due to the impact of the comorbidity with diabetes.

 

Results of the meta-analyses are inconclusive in terms of improving glycemic control by psychological interventions in people with diabetes and comorbid depression (51, 153-155, 157). CBT may have a short-term positive effect that is no longer detectable in medium and long-term follow-up examinations, as (only) one meta-analysis revealed (157).

 

In conclusion, psychological interventions including CBT demonstrate moderate effectiveness in reducing depression severity and achieving remission in people with diabetes and depression. Results concerning the improvement in glycemic control, however, are inconsistent and indicate low effectiveness at best.

 

Pharmacological Treatment

 

Results from placebo-controlled RCTs on the treatment of depression in people with diabetes with antidepressants (mostly SSRIs) exhibit medium-to-large short-term effects for up to six months. Due to the limited number of follow-up examinations, no conclusions can be made about the medium-to long-term effectiveness of these drugs in comparison with placebo - an important limitation considering depression’s frequent relapse. Studies comparing various antidepressants showed no significant differences in the effectiveness of depression treatment (51, 153).

 

The results are heterogeneous regarding the amelioration of glycemic control, indicating a slight improvement in HbA1c by selective serotonin reuptake inhibitors in the short term. The comparison of various antidepressants showed no significant difference, with the exception of one trial in which ameliorated glycemic control was observed over the short term in those patients treated with fluoxetine compared with those who took citalopram (51, 153).

 

In summary, pharmacological interventions are effective in the short-term treatment of depression in diabetes when compared to placebo. Antidepressants demonstrated the most consistent mild-to-moderate effect regarding better glycemic control, but the results remain inconclusive and long-term effects are unknown.

Table 1: Meta-analyses, systematic reviews and meta-review of treatment for depression in diabetes.

Reference

Methods, number of RCTs and patients, topic of research

(within diabetes and depression treatment)

Results for depression Results for glycemic control
Li et al (2017) (154)

Meta-Analysis

(10 RCTs, 998 patients)

Topic: Effectiveness of CBT

Summary measure

Standardized mean differences (SMD)

Cognitive behavioral therapy

Depression severity (7 RCTs)

SMD = -0.65 (95%CI -0.98 to -0.31)

Depression severity (short-term, 6 RCTs)

SMD = -0.86 (95%CI -1.41 to -0.31)

Depression severity (long-term, 5 RCTs)

SMD = -0.38 (95%CI -0.57 to -0.19)

Cognitive behavioral therapy

HbA1c (7 RCTs)

SMD = - 0.22 (95% CI –0.53 to – 0.08)

No statistically significant effects

Xie et al (2017) (155)

Meta-Analysis

(31 RCTs, 2616 patients)

Topic: Effectiveness of ‘psychosocial intervention‘(157) (unspecified)

Summary measure: SMD

Psychosocial intervention (unspecified)

Note: 23 RCTs written in Chinese and 5 RCTs written in English. Most internationally published RCTs of the other meta-analyses were not included

Depression severity (28 RCTs)

SMD = -1.50 (95% CI = -1.83 to -1.18).

Psychosocial intervention (unspecified)

Note: 17 RCTs written in Chinese and 5 RCTs written in English. Most internationally published RCTs of the other meta-analyses were missed.

HbA1c (22 RCTs)

SMD = -0.81 (95% CI =-1.10 to -0.53)

 

Reference

Methods, number of RCTs and patients, topic of research

(within diabetes and depression treatment)

Results for depression Results for glycemic control
Uchendu et al (2016) (157)

Meta-Analysis

(12 RCTs, 1445 patients)

Topic: Effectiveness of CBT

Summary measure: SMD

Cognitive behavioral therapy

Depression severity (short-term, 4 RCTs)

SMD = - 0.52 (95% CI –0.79 to – 0.26)

Depression severity (medium-term, 5 RCTs)

SMD = - 0.43 (95% CI –0.79 to –0.06)

Depression severity (long-term, 5 RCTs)

SMD = -0.26 (95% CI -0.41 to -0.10)

Cognitive behavioral therapy

HbA1c (short-term, 5 RCTs)

SMD = - 0.2 (95% CI –0.5 to – 0.02)

No statistically significant effects

HbA1c (medium-term, 7 RCTs)

SMD = - 0.4 (95% CI –0.6 to – 0.2)

HbA1c (long-term, 6 RCTs)

SMD = - 0.1 (95% CI –0.3 to – 0.1)

No statistically significant effects

Petrak et al (2015) (51)

Meta-Review

(29 RCTs, 3739 patients)

Topics

Psychological interventions

(12 RCTs, 1647 patients)

Psychological interventions

Depression severity (12 RCTs)

SMD from -0.14 to -1.47

Psychological interventions

HbA1c (7 RCTs)

SMD from -0.68 to 0.47

 

Reference

Methods, number of RCTs and patients, topic of research

(within diabetes and depression treatment)

Results for depression Results for glycemic control

Petrak et al (2015) (51)

- continued

Pharmacological interventions

(11 RCTs, 470 patients)

Psychological vs. pharmacological interventions

(1 RCTs, 251 patients)

Collaborative/ stepped-care

(5 RCTs, 1371 patients)

Summary measure:

SMD or Odds ratio (OR)

Pharmacological interventions versus placebo

Depression severity (7 RCTs)

SMD from -0.25 to -1.65

Comparison between active interventions

Fluoxetine versus Paroxetine

Remission of depression (1 RCTs)

OR = 1.4 (95% CI 0.23 to 8.46)

Magnesium supplementation versus Imipramine

in depressive patients with a magnesium deficiency

Depression severity (1 RCTs)

SMD = 0.50 (-3.04 to 4.04)

Fluoxetine versus Citalopram

Depression severity (1 RCTs)

SMD = 0.40 (-1.43 to 2.23)

Pharmacological interventions versus placebo

HbA1c (short-term, 6 RCTs)

SMD from -0.10 to -0.98

Comparison between active interventions

Fluoxetine versus paroxetine

(1 RCTs) Not reported

Magnesium supplementation versus Imipramine

in depressive patients with a magnesium deficiency

(1 RCTs) SMD = -0.10 (-1.24 to 1.04)

Fluoxetine versus Citalopram

(1 RCTs) SMD = -1.00 (-1.85 to -0.15)

 

Reference

Methods, number of RCTs and patients, topic of research

(within diabetes and depression treatment)

Results for depression Results for glycemic control

Petrak et al (2015) (51)

- continued

 

Diabetes-specific CBT versus Sertraline

Depression severity (1 RCT)

SMD = -0.39 (-0.02 to 0.76), not significant

Collaborative or stepped-care interventions

Depression severity: SMD from -0.13 to -0.68

Diabetes-specific CBT versus Sertraline

(1 RCT) SMD = -0.12 (-0.49 to 0.24), not significant

Collaborative or stepped-care interventions

SMD from 0.00 to -0.54

Atlantis et al (2014) (156)

Meta-Analysis

(7 RCTs, 1895 patients,

including 2 RCT with mixed samples comprising diabetes patients)

Topic: Effectiveness of collaborative care

Summary measures

Depression severity: SMD

HbA1c: Weighted mean difference (WMD)

Collaborative care vs. usual care

Depression severity (short-to-medium term,

(7 RCTs)

SMD = - 0.32 (95% CI −0.53 to(51, 156) −0.11)

Collaborative care vs. usual care

HbA1c (short-to-medium term, 7 RCTs)

WMD = - 0.33% (95% CI −0.66% to −0.00%)

 

Reference Methods, number of RCTs and patients, topic of research
(within diabetes and depression treatment)
Results for depression Results for glycemic control
Baumeister et al (2012) (153)

Cochrane Systematic Review

(19 RCTs, 1592 patients)

Psychological interventions

Depression severity (8 RCTs)

SMD from -1.47 to -0.14

Psychological interventions

HbA1c (short-term, 4 RCTs)

MD = -0.4% (95% CI -0.6 to -0.1)

 

Topic: Effectiveness of psychotherapy, antidepressant medication and collaborative care

Psychological interventions

(8 RCTs, 1122 patients)

Pharmacological interventions vs. placebo (8 RCTs, 377 patients)

Pharmacological interventions vs other pharmacological interventions

(3 RCTs, 93 patients)

 

Remission of depression (short-term, 4 RCTs)

OR = 2.88 (95% CI 1.58 to 5.25).

Remission of depression (medium-term, 2 RCTs)

OR = 2.49 (95% CI 1.44 to 4.32)

Pharmacological interventions vs. placebo

Depression severity (7 RCTs):

SMD = -0.61 (95% CI -0.94 to -0.27)

Remission of depression (short-term, 3 RCTs)

OR = 2.50 (95% CI 1.21 to 5.15).

Pharmacological interventions vs. placebo

HbA1c (short-term): MD = -0.4% (95% CI -0.6 to -0.1)

Pharmacological interventions

vs other pharmacological interventions

No significant differences between the examined pharmacological agents, Exeption in one trial (Fluoxetine versus Citalopram)

HbA1c (short-term): MD = -1.0% (95% CI -1.9 to -0.2)

Reference Methods, number of RCTs and patients, topic of research
(within diabetes and depression treatment)
Results for depression

Results for glycemic control

 

 

Baumeister et al (2012) (153)

- continued

Summary measures

HbA1c: Mean differences (MD) Depression severity: SMD

Depression remission: OR

Pharmacological interventions

vs other pharmacological interventions

No significant differences between the examined pharmacological agents (3 RCTs)

Pharmacological interventions

vs other pharmacological interventions

No significant differences between the examined pharmacological agents (3 RCTs)

 
van der Feltz-Cornelis et al (2010) (152)

Meta-Analysis

(14 RCTs, 1724 patients)

Topic: Effectiveness of psychotherapy, antidepressant medication and collaborative care

Summary measures

Effect sizes (Cohen's d) for a combined outcome measure (depressive symptoms and HbA1c together)

Estimate of interventions on combined outcomes not differentiating between

depression symptoms and HbA1c

Psychotherapeutic interventions

Cohen's d: - 0.581 (95% CI −0.770 to −0.391)

Pharmacological interventions

Cohen's d: - 0.467 (95% CI −0.665 to −0.270)

Collaborative care interventions

Cohen's d: - 0.292 (95% CI −0.429 to −0.155)

                   

Psychopharmacological vs. Psychological Interventions

 

So far, there has only been one RCT in people with diabetes and co-morbid depression in which the efficacy of an antidepressant, in this case sertraline, was compared to a psychological intervention, in this case CBT (51, 161).

 

The study was conducted in a secondary-care setting and compared the effectiveness of effects of diabetes-specific CBT for 12 weeks compared to sertraline treatment in patients with poorly controlled diabetes and major depression. Continuous treatment to prevent relapse of depression was provided for an additional 12 months in the sertraline group. In the CBT group, investigators assumed that carry-over effects would stabilize the results without further treatment. Both sertraline and CBT reduced depression severity at the end of treatment, but sertraline was more effective than CBT in preventing relapse at the 1-year follow-up for patients who remitted with treatment. Poor glycemic control remained nearly unchanged during the entire trial in both intervention groups. The authors concluded that CBT and sertraline as single treatment are insufficient to treat diabetes patients with depression and poor glycemic control in secondary care (161).

 

Collaborative Care and Stepped-Care Approaches

 

Meta-analyses for collaborative or stepped-care interventions have shown a considerable between-study heterogeneity and altogether have demonstrated moderate effectiveness compared to usual care in alleviating the depression severity in people with diabetes and depression. The targeted improvement in glycemic control revealed small-to-moderate effectiveness in the short-to-medium term (51, 152, 153, 156)

 

In summary: collaborative and stepped-care approaches demonstrating a slight-to-moderate positive influence on depression and glycemic control.

 

 Critical Appraisal of the Current Evidence

 

Considering the current state of research on the treatment of depression in people with diabetes, we notice that despite considerably more intensive research, we have gained little knowledge in recent years.

 

There is ample evidence of the moderate efficacy of psychological or psychopharmacological interventions in alleviating depressive symptoms. However, it should be emphasized that only the short-term efficacy of drug interventions has been well investigated, whereas there are practically no medium- and long-term study results. Combined therapies have been assessed particularly in the USA. In these so-called "collaborative care" and "stepped care" approaches, psychological and drug treatments were flexibly offered or combined according to certain algorithms and depending on the response to individual treatment steps. This study design does not enable us to identify effective components of a treatment and/or to test the superiority of one component over another. The only thing that can be predicted is whether this combined treatment approach offers advantages in contrast to a standard treatment, which has repeatedly been demonstrated with moderate effect sizes.

 

Studies investigating CBT have usually applied more stringent research methodology than have other RCTs of psychological interventions in the field of diabetes research. Recent meta-analytical summaries of these studies showed that CBT’s effect becomes weaker the longer the study lasts; it thus appears to be less effective than in depressed people with diabetes than in those without it.

 

The evidence of improved glycemic control has been far more heterogeneous and contradictory, especially regarding psychological interventions. RCTs that reported a positive influence on HbA1c, yielded at best modest-to-moderate effects and included SSRIs and partly collaborative care interventions. For patients in secondary-care settings with very poor glycemic control, neither CBT nor sertraline led to better glycemic control

 

The generalizability of the available studies is limited by sample selection effects and other methodological limitations. Claims about the treatment of patients in secondary (specialized practices) and tertiary care (in-patient treatment) can hardly be made, as almost all studies were conducted in primary care settings. As a further limitation, it should be noted that most of these studies were conducted in countries with comparatively advanced health care systems, i.e., Europe and the US, while the vast majority of people with diabetes live in low- and middle-income countries (171) with different cultures and under other socioeconomic conditions and healthcare systems – all factors that limit the applicability of the current scientific evidence to those countries. Most important, since comparative therapy studies between active interventions for this group of patients have been so few, the question as to which is the most effective treatment method remains unanswered.

 

Future research needs to be more specific in describing the characteristics of participants (e.g., primary vs. secondary care; good vs. poor glycemic control, etc.) instead of perpetuating the general conclusion that all examined interventions are more or less effective for all people with diabetes and depression. More knowledge is needed about which are the most effective components within complex interventions, and about treatment duration and dosage regimens. Finally, it is of particularly importance to develop suitable communication strategies that allow us to reach those patient groups with special needs, and to adapt treatments according to the requirements of the specific clinical setting, culture, and country.

 

RECOMMENDATIONS FOR CLINICAL PRACTICE

 

The implementation of medical standards is constrained by limited resources in many parts of the developing world, leading to different levels of medical care worldwide. The International Diabetes Federation (IDF) classifies levels of care as ranging from ‘limited care’ (with insufficient medical resources and too little qualified medical staff), to ‘recommended care’ (evidence-based cost-effective care), and finally, ‘comprehensive care’ (most up-to-date, all necessary health technologies available) (75). Until now, only one evidence-based guideline specifically addressing the treatment for depression in people with diabetes has been published in Germany within a healthcare system at the IDF level of ‘recommended’ or ‘comprehensive care’ (145, 162). Other guidelines from the UK National Institute for Health and Care Excellence (NICE) address the treatment of depression in people with chronic physical disorders, including patients with diabetes (163).

 

There is still insufficient scientific evidence to make concrete recommendations regarding the treatment of depression in diabetes patients with specific characteristics such as the type of diabetes, quality of glycemic control, diabetes complications, etc. Nevertheless, such characteristics must be considered when treating individual patients. Diabetes therapy as such does not differ from the treatment of non-depressive patients with comorbid depression, and should follow national and international guidelines, e.g., (164-166).

 

Safety Precautions for the Psychopharmacological Treatment of Depression in
Patients with Diabetes

 

Treatment with antidepressants, especially in patients with diabetes, requires particular attention to the side effects and contraindications, as well as potential interactions with glucose metabolism and other drugs. For this reason, the guidelines "Psychosocial and Diabetes Mellitus" of the German Diabetes Association (145), which also incorporate recommendations from the German National Depression Guidelines (167), make specific recommendations regarding drug-based antidepressant therapy.

 

In particular they warned against tricyclic antidepressants, as well as mirtazapine and mianserin. These drugs can raise blood sugar levels and promote weight gain, which should be avoided in patients with type 2 diabetes. Due to their problematic cardiac profile, patients with heart disease and diabetes are explicitly warned against taking tricyclic antidepressants. Furthermore, the potential of increased insulin sensitivity due to SSRIs and of hypoglycemia, which may require a change in the insulin dose, is also noted. With regards to elderly patients with diabetes, the guidelines recommend that interactions with other drugs be given special attention, as polypharmacy is a frequent an issue due to other co-morbidities. Particular attention is drawn to the interaction within the cytochrome P450 system, which can lead to alterations in drug concentrations.

 

Furthermore, it must be assumed that life-threatening polymorphic ventricular tachyarrhythmias can be triggered by antidepressant medication (especially in the presence of other risk factors) by prolonging the QTc interval in individual cases. This includes tri- and tetracyclic antidepressants as well as citalopram, escitalopram, fluoxetine, paroxetine, and venlafaxine. Cardiac contraindications must be taken into account. In particular, based on the manufacturers' warnings, prescriptions for citalopram and escitalopram should be very carefully considered when treating patients with heart disease; those who present the additional risk of a QT interval prolongation should not be given those drugs at all.

 

A special warning is made against combining certain substances that can lead to an extension of the QT interval. If the benefits are weighed against the risks, SSRIs are considered the first-choice antidepressant medication for patients with diabetes. Risk-benefit analysis should be carried out before prescribing any psychotropic drug, especially when additional cardiac risk factors are known (145).

 

A Practice-Oriented Stepped-Care Model for the Treatment of Depression in Patients with Diabetes

 

In the following, we present a stepped-care model of the treatment of depression in patients with diabetes developed based on current scientific evidence and guidelines from the German Diabetes Society (51, 145); it can be adapted to specific levels of care (see figure 1). The treatment steps are determined by the severity and duration of depressive symptoms and are summarized in four stages. During therapy, it is recommended to regularly monitor response and suicidal ideation through all phases and, depending on the severity and development of depression, the intervention step should be changed. This stepped-care approach should enable flexible and individually-adjustable treatment with the overall goal of complete remission of depression.

Figure 1: Model of stepped care for the treatment of depression in diabetes
adapted from (51, 145, 162)

1) Mild depression (or impairing subthreshold depressive symptoms):

A depression of this severity can usually be treated within the framework of primary care, provided there are no acute crises or suicidal thoughts. The consultation style should be flexible and supportive, and oriented towards problem-solving. It is important to inform patients about their depression and the potential links between depression and diabetes. If possible, individual explanations should be worked out with the patient from which starting points for different interventions can be derived. These could be, for example, identifying dysfunctional thoughts, interpersonal problems, or insufficient adherence to diabetes therapy. Self-help materials or web-based self-help tools for depression can be a useful to overcome the depression at this stage.

 

If there is a history of severe recurrent depression, SSRI medication or psychotherapy should be considered already at this stage of treatment. The course of the depressive symptoms should be carefully monitored over a 2- to 4-week period. If there is no improvement by then, the next step must be initiated, which is also the starting point for moderate depression.

 

2) Moderate depression (or persistent mild depression not responding to step 1):

Depression of moderate severity requires specific treatment, and the patient should be informed of the various treatment options so that informed decision-making is facilitated.

 

Cognitive behavioral therapy is considered the first-choice psychotherapeutic treatment, whereas SSRIs should be given priority in psychopharmacological treatment. The combination of medication and psychotherapy is particularly recommended for recurrent depressive disorders. Psychopharmacological treatment requires continued monitoring so that a change in dosage or medication can be considered after 2-4 weeks of treatment if the response remains insufficient. Psychotherapeutic treatment should also be monitored, but with individualized time frames for the transition to the next treatment stage, which must be initiated if the treatment outcome is inadequate.

 

3) Severe depression (or moderate depression not responding to step 2):

With this severity level, the treatment options include antidepressants, which are often combined with psychotherapy or psychotherapy without medication. Depending on the patient’s individual requirements, outpatient or inpatient therapy can be carried out.

 

4) Very severe depression (or severe depression not responding to step 3):

In case of a very severe depression, psychotherapy will usually not suffice and is often impossible. Treatment should usually be provided on an in-patient basis and often involves a complex medication regime. Depending on the patient’s individual requirements, psychotherapy can be offered concomitantly or frequently after an initial improvement through medication.

 

CONCLUSION

 

The comorbidity of diabetes and depression remains a considerable clinical challenge for patients and healthcare professionals. While the means of screening and diagnosing depressive disorders in people with diabetes have improved significantly in recent years, this does not automatically lead to better care, as clear treatment pathways after a positive diagnosis are often lacking or are rejected by the affected individuals.

 

Taken together, the scientific evidence on various treatments for depression in diabetes is somewhat encouraging, as it demonstrates that depression is treatable with moderate to good results in depressed people with diabetes. However, we still need efficient treatments to achieve simultaneous a long-term improvement in glycemic control.

 

A positive development is that the awareness of the importance of depression in diabetes has grown, and that many treatment alternatives for patients are now available. Although the scientific evidence still has much room for improvement in this area of research, there are many options for individualized treatment that give cause for optimism for the individual patient.

 

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Genetic Defects in Thyroid Hormone Supply

 

ABSTRACT

Congenital hypothyroidism (CH) is the most frequent endocrine-metabolic disease in infancy, with an incidence of about 1/2500 newborns [1, 2]. In the last 20-30 years the incidence of congenital hypothyroidism in newborns has increased from 1:4000 to 1:2000 [3, 4]. This phenomenon could be explained by using a lower b-TSH cutoff, that allowed the detection of an unsuspected number of children with neonatal hypothyroidism [5]. With the exception of rare cases due to hypothalamic or pituitary defects, CH is characterized by elevated TSH in response to reduced thyroid hormone levels. In absence of an adequate treatment, CH determines growth retardation, delays in motor development, and permanent intellectual disability.

Primary CH is determined by alterations occurring during the thyroid gland development (thyroid dysgenesis, TD [6]) or alterations in the thyroid hormone biosynthesis pathways (thyroid dyshormonogenesis). Less common causes of CH are secondary or peripheral defects in TSH synthesis and/or action, defects in thyroid hormone transport, metabolism, or action [7]. Table 1 shows a summary of the forms of CH with a genetic cause.

In the majority of cases (80-85%), primary permanent CH is associated with TD.  These forms include developmental disorders such as athyreosis, ectopy, hemiagenesis or hypoplasia.

TD occurs mostly as sporadic disease, however a genetic cause has been demonstrated in about 2-5% of the reported cases [8]. Genes associated with TD include several thyroid transcription factors expressed in the early phases of thyroid organogenesis (NKX2.1/TITF1, FOXE1/TITF2, PAX8, NKX2.5) as well as genes, like the thyrotropin receptor gene (TSHR) expressed later during gland morphogenesis.

In the remaining 15-20% of cases, CH is caused by inborn errors in the molecular steps required for the biosynthesis of thyroid hormones, and generally it is characterized by enlargement of the gland (goiter), presumably due to elevated TSH levels [9]. Generally, thyroid dyshormonogenesis shows classical Mendelian recessive inheritance.

Rarely CH has a central origin, as consequence of hypothalamic and/or pituitary diseases, with reduced production or function of thyrotropin releasing hormone (TRH) or thyrotropin hormone (TSH) [10]. For complete coverage of this and all related areas of Endocrinology, please visit our FREE on-line web-textbook, www.endotext.org.

 

 

EPIDEMIOLOGY

CH is usually a sporadic disease with a frequency of about two girls for each boy [11]. Familial cases occur with a frequency that is 15-fold higher than by chance alone [12]. The genetic basis of these familial cases has been established in some, but not all pedigrees [13].

An increased prevalence of the disease is reported in twins [14], with approximately 12 fold increased incidence compared to singletons, even if a discordance rate of 92% between monozygotic (MZ) twins has been observed [15].

The incidence of CH differs significantly among different ethnicities and regions, ranging from 1 in 30,000 in the African-American population in the United States [16, 17] to 1 in 900 in Asian populations in the United Kingdom [18].

 

CLINICAL MANIFESTATIONS

In absence of an adequate treatment, severe CH results in serious mental retardation, in motor handicaps as well as in the signs and symptoms of impaired metabolism. Before the introduction of a neonatal screening program, congenital hypothyroidism was one of the most frequent causes of mental retardation.

 

The clinically detectable consequences of CH strongly depend on severity and duration of thyroid hormone deprivation, but there is also a large individual variability in treatment response.

In the first four-six months after birth, only untreated patients with severe CH have clinical manifestations. Milder cases can remain undiscovered for years. Clinical features of CH are subtle and non-specific during the neonatal period due in part to the passage of maternal thyroid hormone across the placenta; however, early symptoms may include:

  • Decreased activity
  • Wide posterior fontanel
  • Poor feeding and weight gain
  • Small stature or poor growth
  • Long-term jaundice
  • Decreased stooling or constipation
  • Hypotonia
  • Hoarse cry
  • Coarse facial features
  • Macroglossia
  • Umbilical hernia
  • Developmental delay
  • Pallor
  • Myxedema
  • Goiter

 

Infants with congenital hypothyroidism are usually born at term or after term. Infants with obvious findings of hypothyroidism (eg, macroglossia, enlarged fontanelle, hypotonia) at the time of diagnosis have intelligence quotients (IQs) 10-20 points lower than infants without such findings. Often, they are described as "good babies" because they rarely cry and sleep most of the time.

Anemia may occur, due to decreased oxygen carrying requirement. The accumulation of subcutaneous fluid (intracellularly and extracellularly) is usually more pronounced in patients with primary (thyroid) hypothyroidism than in those with pituitary hypothyroidism. Thickening of the lips and macroglossia is due to increased accumulation of subcutaneous mucopolysaccharides (i.e., glycosaminoglycans). Alteration of the mandibular second molars may be the consequence of long-term effects of severe hypothyroidism on craniofacial growth and dental development [19]. In addition, histological changes in the vocal cords (VCs) have also been described [20]. A recent study demonstrated that CH children diagnosed during neonatal screening and adequately early treated, showed similar vocal and laryngeal characteristics compared to children without CH [21].

A small but significant number (3-7%) of infants with CH have other birth defects, mainly atrial and ventricular septal defects or other cardiac malformations (approximately 10% of infants with CH, compared with 3% in the general population) [22].

 

NEONATAL SCREENING

Most newborn babies with CH have few or no clinical manifestations of thyroid hormone deficiency, and in the majority of cases the disease is sporadic. Indeed, it is not possible to predict which infants are likely to be affected by CH. For these reasons, newborn screening programs were developed in the mid-1970s to detect this condition as early as possible. The screening consisted in the measurement of thyrotropin (TSH) on heel-stick blood specimens.

Congenital Hypothyroidism was one of the first diseases screened in neonatal screening programs (NS) [23, 24]. Screening programs for CH were initially developed in Quebec, Canada, and Pittsburgh, Pennsylvania, in 1974 [25], and have now been establish in almost all over the World [26].

Since the introduction of the screening, prevalence of CH significantly changed ranging from 1:6500 (estimated before of NS program) [27], to 1:3000 live births in recent years [4]. This fact is probably associated with an increase in the survival of preterm newborns [4, 5], with environmental [14], and ethnic factors, as well as with the reduction in the cutoff values [3, 5] used for neonatal TSH.

Neonatal screening programs allow for early detection and treatment of CH, and have proven to be successful in preventing brain damage.

Worldwide, most neonatal screening programs are TSH based in the first 3 days of life and effectively detect only thyroidal congenital hypothyroidism (CHT), missing the central CH (CCH). This is characterized by an impairment of TSH production, with low circulating thyroid hormones and low, improperly normal, or slightly high TSH levels [28].

Recently, some countries have developed screening methods measuring both T4 and TSH on the same blood spot simultaneously or stepwise (“T4+TSH-method”). These methods allowed also the identification of CCH [29-31], however it should be noted that low T4 and normal TSH can be also associated with thyroxine-binding globulin (TBG) deficiency, a laboratory condition that requires no treatment. Discriminate between these two conditions is crucial [32] and measurements of circulating TBG or other tests may be necessary [33].

In the past years, the diagnosis of primary CH was made when serum TSH was ≥10 mIU/mL, regardless of the T4 concentration. A recent retrospective study including children screened from 2003 to 2010, showed that 9.13% of the children with b-TSH levels between 5 and 10 mIU/mL also developed hypothyroidism [34]. Indeed, the authors suggested to reduce the cut-off for b-TSH to 5 mIU/mL. The lower cut-off levels allowed the identification of undiagnosed CH cases, however determined significant increases in the number of children to recall, leaded to higher costs of the screening and generated anxiety in parents and relatives of healthy babies [35]. Despite these problems, the usage of lower TSH cut-off has also been proposed in several other studies [36-38].

 

ADDITIONAL TESTS FOR DIAGNOSIS

When the TSH concentration on a dried blood spot exceeds the established threshold, additional studies can be performed to obtain diagnostic confirmation end etiological definition of CH. If these studies will determine a delay in the beginning of the treatment, they should be performed later during the babies life.

Tests commonly used to determine the underlying cause of congenital hypothyroidism are presented in Table 2.

 

- Thyroid scintigraphy, with 99mtechnetium or 123I, is the most informative diagnostic procedure in patients with thyroid dysgenesis [39, 40] providing etiologic diagnosis, as in alteration in the iodine transporter (NIS) [40]. If the radioisotope uptake has not been performed at birth, it is necessary performed this imaging screening after 3 years of age, when the T4 treatment interruption does not compromise the neurocognitive development of the child [31]. Recently it has been suggested that intramuscular injections of recombinant human TSH can be useful to perform 123I- uptake studies during L-thyroxine treatment in CH patients [41, 42].

 

- Ultrasound represents the gold standard for measuring thyroid dimensions, but lacks sensitivity for detecting small glands and it is less accurate than scintigraphy in showing ectopic glands [43]. Moreover, visualization of neonatal thyroid on ultrasound may be challenging for unexperienced sonographists [44].

More than 80% of newborn infants with TSH elevation can be diagnosed correctly on initial imaging with combined radioisotope scan and ultrasound.

 

- Assay of serum thyroglobulin (Tg) will be useful in to establish the presence of some thyroid tissue.

- More specialized tests, such as perchlorate discharge, evaluation of serum, salivary, and urinary radioiodine [45], and measurement of serum T4 precursors, may be necessary to delineate specific inborn errors of thyroid hormone biosynthesis [46].

- When both the maternal and fetal thyroid glands are compromised, significant cognitive delay can occur despite early and aggressive postnatal therapy. Maternal thyrotropin-stimulating hormone receptor (TSHR)-blocking antibodies (Abs) can be transmitted to the fetus and cause combined maternal-fetal hypothyroidism. Measurement of TSHR Abs is necessary to establish the diagnosis; the presence of other thyroid Abs is insufficiently sensitive and may miss some cases [47].

- The measurement of the total urinary iodine excretion differentiates inborn errors from acquired transient forms of hypothyroidism due to iodine deficiency or iodine excess.

 

- A small number of infants with abnormal screening values will have transient hypothyroidism as demonstrated by normal serum T4 and TSH concentrations at the confirmatory laboratory tests. Transient hypothyroidism is more frequent in iodine-deficient areas and it is much more common in preterm infants. CH can also be the consequence of intrauterine exposure to maternal antithyroid drugs, maternal TSHR-blocking antibodies (TSHRBAb), as well as heterozygous DUOX1 and DUOX2 or TSHR germ-line mutations [48, 49]. Because the transient nature of the hypothyroidism will not be recognized clinically or through laboratory tests, initial treatment will be similar to that of the infant with permanent CH, however at a later age interruption of therapy allows to distinguish transient from permanent hypothyroidism [50].

 

Genetic classification of congenital thyroid diseases

 

1. Central hypothyroidism

Congenital central hypothyroidism (CCH) is a rare disease in which thyroid hormone deficiency is caused by insufficient thyrotropin (TSH) stimulation of a normally-located thyroid gland. Patients with this disorder cannot be identified by neonatal screening program based on the measurement of TSH alone, while combined assay of T4 and TSH will allow the identification of patients with CCH [29, 32, 51].

Initially the incidence was estimated between 1:29.000 and 1:110.000 [52-54], while the more recent study from the Netherlands suggests that it may occur in 1:16.000 newborns, representing up to 13% of cases of permanent congenital hypothyroidism [55, 56].

So far, rare genetic defects have been identified in patients affected by CCH. The disorder can be caused by mutations in genes involved in pituitary development such as POU1F1, PROP1, HESX1, LHX3, LHX4 and SOX3. In these cases, central hypothyroidism does not occur in isolation, but is one of the evolving pituitary hormone deficiencies [57].

In contrast, the isolated CCH is determined by mutations in genes specific to the hypothalamic-pituitary-thyroid axis such as: TSHB (encoding the B-subunit of the TSH glycoprotein hormone), TRHR (the specific 7-transmembrane domain receptor for hypothalamic thyrotropin-releasing hormone [58]), IGSF1 (a protein regulating the expression of TRHR in pituitary thyrotropes) [59], and the recently identified TBL1X (a subunit of the NCoR-SMRT complex) [60].

 

1.1 Developmental defects of the pituitary

The pituitary gland is formed from an invagination of the floor of the third ventricle and from Rathke’s pouch, developing into the thyrotropic cell lineage and the four other neuroendocrine cell types, each defined by the hormone produced: TSH, growth hormone (GH), prolactin, gonadotropins (luteinizing hormone [57] and follicle-stimulating hormone [61]), and adrenocorticotropic hormone (ACTH).

The ontogeny of the pituitary gland depends on numerous developmental genes that guide differentiation and proliferation. These genes are highly conserved among species, suggesting crucial evolutionary roles for the proteins (PIT1 and PRPO1, HESX1, LHX3, LHX4 and SOX3).

 

Lhx3 and Lhx4 belong to the LIM family of homeobox genes that are expressed early in Rathke’s pouch. In Lhx3 knockout mice the thyrotropes, somatotropes, lactotropes, and gonadotropes cell lineages are depleted, whereas the adrenocorticotropic cell lineage fails to proliferate. This murine knock out model shows that pituitary organ fate commitment depends on Lhx3. Lhx4 null mutants show Rathke’s pouch formation with expression of a glycoprotein subunit, TSH-beta, GH and Pit1 transcripts, although cell numbers are reduced.

In humans, homozygous or compound heterozygous carriers of LHX3 mutations present with combined pituitary hormone deficiency diseases and cervical abnormalities with or without restricted neck rotation. Some patients also present with sensorineural hearing loss. Mutations can also be frameshift or splicing anomalies. In addition, the heterozygous carriers of a dominant negative LHX3 mutation are characterized by limited rotation of the neck.  Patients with heterozygous missense or frameshift mutations in LHX4 have variable phenotypes, including GH disease and variable TSH, gonadotropin and ACTH deficiencies with a hypoplastic anterior pituitary, with or without an ectopic posterior pituitary [62, 63].

 

Hesx1 (also called Rpx), a member of the paired-like class of homeobox genes, is one of the earliest markers of the pituitary primordium [64]. Extinction of Hesx1 is important for activation of downstream genes such as Prop1, suggesting that the proteins act as opposing transcription factors [65]. Targeted disruption of Hesx1 in the mouse revealed a reduction in the prospective forebrain tissue, absent optic vesicles, markedly decreased head size, and severe microphthalmia. A similar phenotype it has been observed in patients with the syndrome of septo-optic dysplasia (SOD). SOD is a complex and highly variable disorder, diagnosed in the presence of: 1) optic nerve hypoplasia, 2) midline neuroradiologic abnormalities and/or 3) anterior pituitary hypoplasia with consequent hypopituitarism [62]. The number of genetic factors implicated in this condition is increasing and currently includes HESX1, OTX2, SOX2 and SOX3. These genes are expressed very early in forebrain and pituitary development and so it is not surprising that mutations affecting these genes can induce the SOD disorders.

Very recently Sonic hedgehog (Shh) has been associated to SOD, since mouse embryos lacking in the gene exhibit key features of the disease, including pituitary hypoplasia and absence of the optic disc [66].

The human HESX1 gene maps to chromosome 3p21.1–3p21.2, and its coding region spans 1.7 Kb, with a highly conserved genomic organization consisting of four coding exons. The first homozygous missense mutation (Arg160Cys) was found in the homeobox of HESX1 in two siblings with SOD [64]. Subsequently several other homozygous and heterozygous mutations have been shown to present with different phenotypes characterized by pituitary hormone deficiency and SOD [65, 67].

 

1.2 Defects in the TRH and TRH receptor

The TRH receptor (TRHR) is a G-protein- coupled receptor located at pituitary thyrotropes and activated by hypothalamic TRH. The synthesis, secretion, and bioactivity of TSH necessary for following production of thyroid hormones, depend by TRH-TRHR signaling [59].

In mice, homozygous deletion of the TRH gene produced a phenotype characterized by hypothyroidism and hyperglycemia [68]. Only a few patients with reduced TRH production have been described in the literature [69, 70], but no human mutations have been identified so far.

Mice lacking the TRH receptor appear almost normal, with some growth retardation, and decreased serum T3, T4, and prolactin (PRL) levels but normal serum TSH [71]. So far, four mutations in TRHR gene were identified in human. In the first case, the patient was a compound heterozygote for an early stop codon (p.R17X) and an in-frame deletion added to a missense change (p.S115- T117del + p.A118T) in the other allele [58]. The same p.R17X mutation was found also in the second patient in homozygous state  [72], whereas the third exhibited a homozygous missense mutation (p.P81R) [73]. More recently has been identified in a consaguineous family a homozygous missense mutation (c.392T>C; p.I131T) located at a highly conserved hydrophobic position of G-protein-coupled receptor, which reduces the affinity for TRH, compromising the signal trasduction [74]. The same mutation, was present in the mother, two brothers and grandmother, but in heterozygous status leading to isolated hyperthyrotropinemia.

 

1.3 Defects in Thyroid-Stimulating Hormone (TSH) synthesis

The thyroid stimulating hormone (TSH) is produced and secreted by the thyrotrophic cells of the anterior pituitary gland and it is the classic ligand for the TSH receptor (TSHR) in the thyroid. TSH is a heterodimeric glycoprotein consisting of an α subunit and β subunit, The α subunit is shared with other glycoprotein hormones (i.e. follicle-stimulating hormone (FSH), luteinizing hormone (LH), and chorionic gonadotropin (CG)), whereas the TSHβ subunit is unique, determining the specificity of TSH. The beta-subunit (gene map locus 1p13) synthesis is under the control of several transcription factors, including POU1F1 and PROP1.

 

Pit1/POU1F1

Pit1 (called POU1F1 in humans) is a pituitary-specific transcription factor belonging to the POU homeodomain family. The human POU1F1 maps to chromosome 3p11 and consists of six exons spanning 17 Kb encoding a 291 aminoacid protein.

Identified mutations of the POU1F1 gene in human result in combined pituitary hormone deficiency (CPHD) with an incidence between 38% and 77% in unselected cohorts, and between 25% and 52% in patients with a family history of CPHD. To date, several recessive and six dominant POU1F1 gene mutations have been described in CPHD patients and include missense, nonsense, frameshift, whole gene deletion and two mutations that result in the mis-splicing of the pre-mRNA [75, 76].

Deficiency of GH, prolactin and TSH is generally severe in patients harbouring mutations in POU1F1. The patients are often affected by extreme short stature, learning difficulties, and anterior pituitary hypoplasia [76].

 

PROP1

Prop1 (Prophet of Pit1) is a pituitary-specific paired-like homeodomain transcription factor required for the expression of Pit1, and transcriptional activator to stimulate pituitary cell differentiation. Dwarf mice, harboring a homozygous missense mutation in Prop1, exhibit GH, TSH and prolactin deficiency, and an anterior pituitary gland reduced in size by about 50%. Additionally, these mice have reduced gonadotropin expression [77].

The human PROP1 maps to chromosome 5q. The gene consists of three exons encoding for a 226 aminoacids protein. After the first report of mutations in PROP1 in four unrelated pedigrees with GH, TSH, prolactin, LH and FSH deficiencies [78], several distinct mutations have been identified in over 170 patients [65], suggesting that mutations in PROP1 are the most prevalent cause of multiple pituitary hormone deficiency, accounting for up to 50% of familial cases, although the incidence of PROP1 mutations is much lower in sporadic cases [62].

Affected individuals exhibit recessive inheritance [67]. The timing of initiation and the severity of hormonal deficiency in patients with PROP1 mutations is highly variable: diagnosis of GH deficiency preceded that of TSH deficiency in 80%. Following the deficiencies in GH and TSH, there is a reduced fertility due to gonadotropin insufficiency. Although most patients fail to enter puberty spontaneously, some start puberty before deficiencies in LH and FSH evolve. ACTH deficiency is a relatively late manifestation of PROP1 mutation, often evolving several decades after birth. The degree of prolactin deficiency and pituitary morphological alterations are variable [65].

1.4 Structural Thyroid-Stimulating Hormone defects

Mutation in the TSH-beta gene are a rare cause of congenital hypothyroidism. Available data have been reviewed by Miyai [79, 80].

Several mutations in TSHB gene were identified in the last years, including missense, non-sense, frameshift and splice-site. The most commonly reported mutation is the C105Vfs114X mutation, located on exon 3 of the TSHB gene, and firstly described in 1996 [81]. In all the reported cases, the mutations were homozygous or compound heterozygous. So far, no genotype-phenotype correlation has been reported. The patients present all clinical sign of hypothyroidism, and the severity of the pathology depend by start of treatment. Very recently [82], direct sequencing of the coding region of the TSHB gene revealed two homozygous nucleotide changes. The first C.40A>G (rs10776792) is a recurrent alteration that can also be found in healthy individuals. The other variation was c.94G>A at codon 32 of exon 2, which results in a change of glutamic acid to lysine (p.E32K). For both variations, both patients were homozygous and the parents were heterozygous.

 

 

1.5 Deficiency of immunoglobulin superfamily member 1 (IGSF1)

IGSF1 is a plasma membrane immunoglobulin superfamily glycoprotein [83, 84]. Human IGSF1 and murine Igsf1 mRNAs are highly expressed in Rathke’s pouch and in adult pituitary gland and testis. Moreover, IGSF1 protein is expressed in murine thyrotropes, somatotropes, and lactotropes, but not in gonadotropes or in the testis [85]. Igsf1 knockout mice showed no alternation of follicle stimulating hormone synthesis or secretion, and normal fertility [61].

The physiological role of IGSF1 is unknown, but it’s lack is responsible for a variety of symptoms such as hypothyroidism, prolactin deficiency, macroorchidism and delayed puberty. IGSF1 is important for the pituitary-thyroid axis and the development puberty and thus represents a new player controlling growth and puberty in childhood and adolescence. So far, 10 distinct IGSF1 mutations have been described in 26 patients [85], one deletion in male patient [86], and other six mutations have been identified in Japanese subjects [87-90]. Recently, a novel insertion mutation, c.2284_2285insA [91], has been discovered by whole-exome sequencing in three siblings affected by mild neurological phenotype. The mutations included in-frame deletions, single nucleotide deletions, nonsense mutations, missense mutations and one single-base duplication. In vitro expression studies of several mutations done to analyze the functional consequences demonstrated that the encoded proteins migrated predominantly as immature glycoforms and were largely retained in the endoplasmic reticulum, resulting in decreased membrane expression [85]. It is likely that there is no clear genotype-phenotype correlation. Even in familial cases sharing the same IGSF1 defects, a variable degree of hypothyroidism was observed [85, 92]. Other genetic or environmental factors may influence the phenotypic expression of IGSF1 deficiency.

 

1.6 TBLX1

TBL1X, transducin β-like protein 1 X-linked, is a part of the nuclear receptor corepressor (NCoR)-silencing mediator for retinoid and thyroid hormone receptors (SMRT) complex. In mice, the reduction of TH synthesis can be caused by disruption of NCoR, while the peripheral sensitivity to TH increases [93]. Initially, TBL1X gene mutations in humans were associated to hearing loss [94], but not to CCH, but Heinen & co recently identified six novel missense mutations in eight patients diagnosed with isolated CCH and hearing defects [60]. Functional studies demonstrated that the mutations cause an aberrant protein folding and stability, altering the structural and functional properties of TBLX1.

 

2. Alterations of thyroid morphogenesis (thyroid dysgenesis)

Thyroid dysgenesis (TD) is the most frequent form (~ 75%) of primary permanent congenital hypothyroidism (CH). TD includes several disorders caused by errors during thyroid development, such as athyreosis (absent gland), hypoplasia (reduced gland) or ectopy (gland located in aberrant position) [46].

The most critical events in thyroid organogenesis occur during the first 60 days of gestation in man and the first 15 days in mice. It is likely that alterations in the molecular events occurring during this period can be associated to TD. Studies on thyroid development in normal and mutated mouse embryos indicate that the simultaneous presence of Pax8, Nkx2-1, Foxe1, and Hhex is required for thyroid morphogenesis. Indeed, thyroid dysgenesis is present in animal models with mutations in these genes, and mutations in the same genes have been identified in patients with congenital hypothyroidism associated with TD.

 

2.1 Athyreosis

Athyreosis is the absence of thyroid follicular cells (TFC) in orthotopic or ectopic location. This condition can either be the consequence of lack of formation of the thyroid bud or results from alterations in any of the step following the specification of the thyroid bud and determining a defective survival and/or proliferation of the precursors of the TFC. In athyreotic patients, the presence of cystic structures resulting from the persistence of remnants of the thyroglossal duct is frequently reported. This finding indicates that in these subjects some of the early events of thyroid morphogenesis have taken place but the cells fated to form the TFCs either did not survive or switched to a different fate. In many cases, scintigraphy failed to demonstrate the presence of thyroid tissue, but thyroid scanning by ultrasound reveals a very hypoplastic thyroid gland.

So far, the absence of thyroid was reported in 3 patients with CH associated to FOXE1 gene defects (Bamforth-Lazarus syndrome) (p.S57N, p.A65V, and p.N132D), in four subjects carrying a mutation in PAX8, in two patients with NKX2-1 mutation, in two patients with NKX2-5 mutation [8, 95] and in one patient with both a heterozygous NKX2-5 mutation and a heterozygous mutation in the PAX8 promoter region [96]. Recently, mutational screening in TSHR, NKX2.1, in FOXE1, in NKX2.5 and in PAX8 was performed in 100 Chinese subjects affected by thyroid athyreosis [97]. Several mutations have been identified, but the most of them were previously reported and the bioinformatics analysis suggested they were benign with no clinical relevance. Only the TSHR variants have been suggested to have deleterious effects by in silico analysis.

 

2.2 Ectopic thyroid

The ectopic thyroid is the consequence of a failure in the descent of the developing thyroid from the thyroid anlage region to its definitive location in front of the trachea. In the majority of cases, the ectopic thyroid appears as a mass in the back of the tongue (lingual thyroid, usually functioning). Sublingual ectopic tissues are less frequent; in this case, thyroid tissue is present in a midline position above, below or at the level of the hyoid bone. Ectopic thyroid tissues within the trachea or thyroid tissue in the submandibular region have also been reported.

The thyroid ectopy is the most common spectrum of thyroid dysgenesis, occurring in up 80% of CH caused by TD, but only the 3% of CH cases are explained by inherited mutation in the gene involved in thyroid development.

To date, mutational analysis performed in several countries, demonstrated the presence of mutation in patients with thyroid ectopy in NKX2-5 gene (p.R25C, p.A119S, p.R161P), FOXE1 (p.R102C) and PAX8 (p.R108X, p. T225M, p.R31H) [8, 23].

Monozygotic (MZ) twins are usually discordant for CH due to thyroid dysgenesis, suggesting that most cases are not caused by transmitted genetic variation. One possible explanation could be the onset of somatic mutations in migrating genes after zygotic twinning. However, significant somatic methylation profile differences were not observed between ectopic and orthotopic thyroids [98], nor somatic mutations were found by exome sequencing of lymphocytic DNA from MZ twins discordant for CHTD [99]. Since the monoallelic genes are more vulnerable to other benign monoallelic genetic or epigenetic mutations, the autosomal monoallelic expression (AME) could explain discordance and the sporadic nature of CH [100]. The study showed that the AME is observed for some genes in ectopic and orthotopic thyroids. These genes are involved in epithelial–mesenchymal transition, cell migration, cancer, and immunity. Therefore, also in this case, no thyroid-specific mutations were observed in ectopic tissues in any of the genes normally involved in thyroid development and associated with thyroid dysgenesis.

Recently, several DUOX2 mutations have been identified in a cohort of 268 children affected by TD (134 of whom were thyroid ectopy cases), by whole-exome sequencing (WES). Seven mutations were nere reported before (G201E, L264CfsX57, P609S, M650T, E810X, and M822V, and E1017G) while eight (P138L, D506N, H678R, R701Q, A728T, S965SfsX29, P982A, and S1067L) have been previously described [101]. These findings suggest that also DUOX2 could play a role in thyroid development.

 

2.3 Hypoplasia

Orthotopic and hypoplastic thyroid is reported in 5% of CH cases. Thyroid hypoplasia is a genetically heterogeneous form of thyroid dysgenesis, since mutations in NKX2-1, PAX8 or TSHR gene have been reported in patients with thyroid hypoplasia.

NKX2.1 mutations have been described in several patients with primary CH, respiratory distress and benign hereditary chorea, which are manifestations of the “Brain-Thyroid-Lung Syndrome” (BLTS). In the majority of cases haplo-insufficiency has been considered to be responsible for the phenotype. Only a few mutations produce a dominant negative effect on the wild type NKX2-1, and among those in two cases a promoter-specific dominant negative effect was reported [102]. So far, more than 96 mutations in the NKX2.1 gene have been identified [103]. Interestingly, not all mutational carriers display the full phenotype of BLTS but have only involvement of two or even one part of the syndrome. Very recently, Hermanns &co [104] described a patient affected by TD with hypoplastic thyroid gland, respiratory disease and cerebral palsy who presented mutations in both PAX8 (p.E234K) and NKX2.1 (p.A329GfsX108) genes. Functional studies demonstrated no transcriptional activity or DNA-binding of NKX2.1 mutant protein. Contrary the PAX8 mutant protein was normally located into the nucleus, and has no functional impairment. These results confirm the role of NKX2.1 mutant protein in the manifestation of the BTLS phenotype and suggest that other molecular mechanisms could be causative of the disease.

NKX2.5 was recently found mutated in patients affected by thyroid hypoplasia and no cardiovascular defects [105]. Both these mutations (c.73C>T and c.63A>G) were previously described [106, 107]. The c.73C>T was found in patients affected by thyroid ectopy and without congenital heart defects [107] and showed a deficiency in dimer formation without effects on the DNA binding capacity. The c.63A>G did is a silent mutation that determines no changes in the aminoacid sequence. It has been reported in a patients with thyroid hypoplasia [108] but also in healthy controls [105].

The involvement of PAX8 has been described in sporadic and familial cases of CH with thyroid hypoplasia [109-111]. All affected individuals are heterozygous for the mutations and autosomal dominant transmission with incomplete penetrance and variable expressivity has been described for the familial cases. In vitro transfection assays demonstrated that the mutated proteins are unable to bind DNA and to drive transcription of the TPO promoter. By NGS analysis performed in a cohort of 11 families, a heterozygous PAX8 (p.R31C) was identified in two siblings with CH and hypoplastic thyroid [112]. One of the patients also presented unilateral kidney agenesis. The mutation completely inactivates the activity of the transcription factor, as previously reported for the p.R31H [113, 114]. The frequent observation of mutation occurring in this aminoacid suggested that position 31 in the PAX8 protein can be a mutational hot spot.

TSHR belongs to the G-protein coupled receptors superfamily. The gene encoding TSHR maps to chromosome 14q31 and to mouse chromosome 12. It consists in ten exons codify for a 764 aminoacid protein. The role of the TSHR in thyroid differentiation was first identified in Tshr hyt/hyt mice, affected by primary hypothyroidism with elevated TSH and hypoplastic thyroid, as a consequence of a loss of function mutation in the fourth transmembrane domain of TSHR (pro556Leu), which abolishes the cAMP response to TSH.
Several patients with homozygous or compound heterozygous loss-of-function TSHR mutations have been reported. The disease, known as resistance to TSH (OMIM #275200) is inherited as an autosomal recessive trait, and patients are characterized by elevated serum TSH levels, absence of goiter with a normal or hypoplastic gland, and normal to very low serum levels of thyroid hormones. The clinical manifestations are very variable spanning from euthyroid hyperthyrotropinemia to severe hypothyroidism. A novel non-synonymous substitution was recently reported in the HinR of the large N-terminal extracellular domain of the TSHR gene in a patient with thyroid hypoplasia. Since this p.S304R TSHR variant does not affect the TSH binding nor the cAMP pathway activation, it was not possible to establish his role in the clinical phenotype [23].

2.4 Hemiagenesis

Thyroid hemiagenesis (THA) is a rare congenital abnormality, in which one thyroid lobe fails

to develop. Thyroid hemiagenesis is often associated with mild and/or transient hypothyroidism but several patients were found to be euthyroid.

The incidence of the disorder is estimated at 0.05–0.5% of the general population. THA occurs usually as an isolated feature, more frequently in women than in men. In the large majority of the cases, the left lobe is absent [115].

The molecular mechanisms leading to the formation of the two thyroid symmetrical lobes, which are impaired in the case of hemiagenesis, are still unclear and in humans. In contrast, Shh-/- mice embryos can display either a non-lobulated gland [116] or hemiagenesis of thyroid [117], and hemiagenesis of the thyroid is also frequent in mice double heterozygous Titf1+/-, Pax8+/- [118].

In the majority of patients with thyroid hemiagenesis, the genetic background remains unknown. Additionally, THA family members commonly present other thyroid developmental anomalies (i.e., thyroid agenesis, ectopy or thyroglossal duct cyst), suggesting a common genetic background for different thyroid developmental anomalies of the gland.

Mutations in NKX2.1, PAX8 or FOXE 1 are rarely associated with THA. novel single nucleotide substitution in exon 2 of the PAX8 gene (c.162 A>T; p.S54C) was recently identified 13/16 members of a family with hypothyroidism and variable phenotype (thyroid hemiagenesis to normal) [119].

FOXE1 contains within its coding sequence a polyalanine tract of variable length, ranging from 11 to 19 alanines [120]. Several studies have pointed to the potential role of FOXE1-polyAla length polymorphism in determining the susceptibility to TD [121-123].

Avery recent study, demonstrate the potential association between proteasome-related genes and THA. In a cohort of 34 sporadic patients and three families with THA several mutations have been identified in proteasome genes PSMA1, PSMA3, PSMD2, and PSMD3. The functional studies indicate that the mutations can lead to accumulation of undegraded protein aggregates and exert a toxic effect on the thyroid cell [124].

 

2.5 Other genetics defects

Recently, several other genes have been suggested to play a role in the pathogenesis of thyroid dysgenesis, including JAG1, GLIS3, CDCA8 or SLC26A4.

 

2.5.1 GLIS3

In a rare syndrome, CH can be associated to neonatal diabetes (NDH). These patients exhibit reduced T3 and T4 levels with elevated TSH and Tg. Patients additionally develop hyperglycemia and hypo-insulinemia. They often also presented polycystic kidney disease, hepatic fibrosis, glaucoma and mild mental retardation. Thyroid ultrasound and scintigraphy suggested athyreosis or hypoplasia. In most of the cases, the patients do not respond to conventional treatment and TSH remains elevated, despite normalization of serum T4 levels. This form has been associated to GLIS3 mutations [125, 126]. GLIS3 is a transcription factor containing five Krüppel-like zinc finger domains and sharing high homology with GLI zinc finger proteins. It has been postulated to have a critical role in the regulation of a variety of cellular processes during development [127]. GLIS3 may act as a transcriptional activator or repressor, but its precise role in thyroid development and function remains to be determined [128]. So far, few patients with syndromic CH and GLIS3 mutations have been identified [126]. Very recently, a novel GLIS3 deletion has been published in a CH girl that also presented camptodactyly, syndactyly and polydactyly [129], and mutations have been reported in patients with CH and abnormalities in external genitalia, not previously described [130].

 

2.5.2 JAG1

Studies in zebrafish suggested the involvement of Notch pathway in congenital hypothyroid phenotype [131]. In humans, heterozygous JAG1 variants are known to account for Alagille syndrome type 1 (ALGS1), a rare multisystemic developmental disorder characterized by variable expressivity and incomplete penetrance, but a recent study on a cohort of 21 young Alagille patients revealed an increased risk of non-autoimmune hypothyroidism (28%) in the presence of JAG1 heterozygous mutations [132, 133].

 

2.5.3 CDCA8

Recently, genetic variants in CDCA8 (also called BOREALIN) were identified in a study of three consanguineous families with thyroid dysgenesis [134]. The thyroid phenotypes observed in patients carrying CDCA8 variants is extensive, ranging from thyroid agenesis or ectopy to euthyroid individuals with asymmetric thyroid lobes or thyroid nodules. This variability makes the role of CDCA8 in thyroid dysgenesis still unclear and controversial.

 

2.5.4 SLC26A4

Pendrin (SLC26A4, PDS) alterations have been initially associated to Pendred syndrome (see later). Recently, NGS techniques used in patients with TD, demonstrated the frequent presence of SLC26A4 mutations also in patients with TD. The mutations were initially identified in a patient with hypoplastic thyroid tissue and severe hearing problems [135], but later the prevalence of SLC26A4 mutation was calculated to be 4% among studied Chinese CH patients [136].

 

2.5.5 DNAJC17

Studies on mouse models indicated that neither Pax8 or Nkx2.1 heterozygous null mice showed overt thyroid defects, while double heterozygous mice for both Nkx2.1 and Pax8 (DHTP) had a severe hypothyroidism characterized by thyroid hypoplasia or hemiagenesis [118]. The DHTP hypothyroid phenotype was strain specific, and the same authors identified in Dnajc17 the strain-related modifier gene for hypothyroidism. DNAJC17 belongs to the heat-shock-protein-40 type III family. DNAJC17 proteins interact, via a highly-conserved domain (J domain) with Hsp70 chaperone proteins, regulating their activity and controlling the disassembly of transcriptional complexes [137, 138].

Very recently a DNAJC17 mutational screening has been performed in a cohort of 89 CH patients. The analysis identified only one rare variant (c.610G>C) and one polymorphism (c.350A>C) in affected patients. Both variants were already reported in databases and the frequency of the alleles was not different between TD patients and controls [139].

 

3. Defects in thyroid hormone synthesis (dyshormonogenesis)

In about 15% of cases, CH is due to hormonogenesis defects caused by mutations in genes involved in thyroid hormone synthesis, secretion or recycling. These cases are clinically characterized by the presence of goiter, and the molecular mechanisms have been well defined.

In thyroid follicular cells, iodide is actively transported and concentrated by the sodium iodide symporter present in the baso-lateral membrane. Subsequently it is oxidised by hydrogen peroxide generation system (thyroperoxidase, Pendrin) and bound to tyrosine residues in thyroglobulin to form iodotyrosine (iodide organification). Some of these iodotyrosine residues (monoiodotyrosine and diiodotyrosine) are coupled to form the hormonally active iodothyronines (T4) and triiodothyronine (T3). When needed, thyroglobulin is hydrolyzed and hormones are released in the blood. A small part of the iodotyronines is hydrolyzed in the gland, and iodine is recovered by the action of specific enzymes, namely the intrathyroidal dehalogenases (Figure 1).

Defects in any of these steps lead to reduced circulating thyroid hormone, resulting in congenital hypothyroidism and goiter. In most of the cases, the mutations in these genes appear to be inherited in autosomal recessive fashion [9].

 

3.1 Sodium-iodide symporter

The sodium-iodide symporter (NIS) is a member of the sodium/solute symporter family that actively transports iodide across the membrane of the thyroid follicular cells. The human gene (SLC5A5) maps to chromosome 19p13.2-p12. It has 15 exons encoding for a 643-amino acid protein expressed primarily in thyroid, but also in salivary glands, gastric mucosa, small intestinal mucosa, lacrimal gland, nasopharynx, thymus, skin, lung tissue, choroid plexus, ciliary body, uterus, lactating mammary tissue and mammary carcinoma cells, and placenta. Only in thyroid cells iodide transport is regulated by TSH. It has been demonstrated that the δ-amino group at position 124 of NIS protein, is required for the transporter’s maturation and cell surface targeting [140].

The inability of the thyroid gland to accumulate iodine was one of the early known causes of CH, and before the cloning of NIS, a clinical diagnosis of hereditary iodide transport defect (ITD) was made on the basis of goitrous hypothyroidism and absent thyroidal radioiodine uptake. To date, 15 mutations in the SLC5A5 gene have been identified in patients with ITD [141]. Some of these, including V59E, G93R, Δ439-443, R124H, Q267E, T354P, G395R, and G543E, have been studied in detail and have provided key mechanistic information on NIS function. Since SLC5A5 mutations are inherited in an autosomal recessive manner, NIS gene defects can be detected only when both alleles are mutated and the clinical picture is characterized by hypothyroidism of variable severity (from severe to fully compensated) and goiter. Furthermore, the actual prevalence of NIS gene mutations may be higher than that reported [142].

 

3.2 Thyroperoxidase

The most frequent cause of dyshormonogenesis is thyroperoxidase (TPO) deficiency. TPO is the enzyme that catalyses the oxidation, organification, and coupling reactions. Accumulation of iodine in the thyroid gland reaches a steady state between active influx, protein binding, and efflux, resulting in a relatively low free intracellular iodide concentration in normal conditions, while increased in the presence of TPO defects. The kinetics of iodide uptake and release can be traced by administration of radioiodide. Radioiodide uptake and perchlorate inhibition gives an idea of the intrathyroidal iodide concentration in relation to the circulating iodine. Iodine organification defects can be quantified as total or partial: total iodide organification defects are characterized by discharge of more than 90% of the radioiodide taken up by the gland within 1 hour after administration of sodium perchlorate, usually given 2 hours after radioiodide. A total disappearance of the thyroid image is also observed. Partial iodide organification defects are characterized by discharge of 20% to 90% of the accumulated radioiodine [143].

Mutations in TPO gene (particularly nonsynonymous cSNPs) can lead to severe defects in thyroid hormone production, due to total or partial iodide organification defects. Based on the literature, exons 7–11 encoding the catalytic center of the TPO protein (heme binding region) are crucial for the enzymatic activity. Nonsense, splice-site, and frameshift mutations have been also described by several groups [141].

 

3.3 DUOX1 and DUOX2

The generation of H2O2 is a crucial step in thyroid hormonogenesis. DUOX1 and DUOX2 are glycoproteins with seven putative transmembrane domains. These proteins, map on chromosome 15q15.3, and their function remained unclear until a factor, named DUOXA2, which allows the transition of DUOX2 from the endoplasmic reticulum to the Golgi, was identified [144]. The coexpression of this factor with DUOX2 in HeLa cells is able to reconstitute the H2O2 production in vitro. A similar protein (DUOXA1) is necessary for the complete maturation of the DUOX1.

In murine models, only DUOX2 loss of function mutation have been associated with hypothyroidism; thus, the role of DUOX1 in thyroid biology remains unclear [145].

DUOX2 mutations usually cause transient CH or permanent CH with partial iodide organification defect. Permanent and transient CH may result from both mono- and biallelic mutations, and phenotypic heterogeneity may occur with similar mutations [146].

To date, at least 41 patients belonging to 33 families have been reported to carry mutations in DUOX2 gene [147]. Recently, a case of CH with a homozygous loss-of-function mutation in DUOX1 (c.1823-1G>C) was reported. The mutation was inherited digenically with a homozygous DUOX2 nonsense mutation (c.1300 C>T, p. R434*) [148]. Probably, the inability of DUOX1 to compensate for the DUOX2 deficiency in these kindred may underlie the severe CH phenotype.

 

3.4 Pendrin

The Pendred syndrome is characterized by congenital neurosensorial deafness and goiter. The disease is transmitted as autosomal recessive disorder. Patients have a moderately enlarged thyroid gland, are usually euthyroid and show only a partial discharge of iodide after the administration of thiocyanate or perchlorate. The impaired hearing is not constant. In 1997, the PDS gene was cloned and the predicted protein of 780 amino acids (86-kD) was called Pendrin. The PDS gene maps to human chromosome 7q31, contains 21 exons, and it is expressed both in the cochlea and in the thyroid. Pendrin has been localized in the apical membrane of thyroid follicular cell [149]. In thyroid follicular cells, and in transfected oocytes, Pendrin is able to transport iodide.

A number of mutations in the PDS gene have been described in patients with Pendred syndrome. Despite the goiter, individuals are likely to be euthyroid and only rarely present congenital hypothyroidism. However, TSH levels are often in the upper limit of the normal range, and hypothyroidism of variable severity may eventually develop.

In the last years, mutation in the PDS gene have also been associated with thyroid dysgenesis [135, 136].

 

3.5 Thyroglobulin

Thyroglobulin is a homodimer protein synthesized exclusively in the thyroid. The human gene is located on chromosome 8q24 and the coding sequence, containing 8307 bp, is divided into 42 exons [150]. Patients with disorders of thyroglobulin synthesis are moderately to severely hypothyroid and often present goiter. Usually, plasma thyroglobulin concentration is low, especially in relation to the TSH concentrations, and does not change after T4 treatment or injection of TSH. Patients classified in the category “thyroglobulin synthesis defects” often have other abnormal iodoproteins, mainly iodinated plasma albumin, and they excrete iodopeptides of low molecular weight in the urine. At least 70 distinct inactivation TG gene mutations have been described [150, 151]. Scintigraphy shows high uptake (due to induction of NIS expression by TSH stimulation) in a typically enlarged thyroid gland.

 

3.6 DEHAL1

In addition to the active transport from the blood due to NIS, iodine in the thyroid follicular cells derives also from the deiodination of monoiodotyrosine and diiodotyrosine. The gene encoding for this enzymatic activity was recently identified and named IYD (or DEHAL1) [152]. The human gene maps to chromosome 6q24-q25 and consists of six exons encoding a protein of 293 amino acids, a nitroreductase-related enzyme capable of deiodinating iodotyrosines. In the past it has been suggested that IYD mutations could be responsible for congenital hypothyroidism, but only in 2008 the first IYD mutations were described in three different consanguineous families. All the patients had homozygous IYD mutations, and presented goiter and hypothyroidism. The onset of symptoms was very variable, either at birth or later in infancy or childhood. A particular mutation of IYD, (c.658G>A, p.Ala220Thr), was reported in a heterozygous 14-yr-old boy affected by hypothyroidism and goiter, suggesting a possible dominant effect of the mutation. Very recently, a new IYD mutation was identified by genome-wide approach in a 20-yr-old patient with hypothyroidism and goiter and in his 4.5-yr-old apparently healthy sister in a consanguineous Moroccan family [153]. Since hypothyroidism is infrequent at birth, patients with biallelic IYD mutations are normally not identified as CH at the screening, but they subsequently came to medical attention between 1.5 and 8.0 years of age [141].

 

 

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  140. Paroder, V., et al., Letter to the editor: Hidden pituitary gland: implications for assessment. Am J Med Genet A, 2013. 161A(3): p. 630-1.
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Legend to figure.

 

Figure 1. Main steps involved in the biosynthesis of thyroid hormones. The picture schematizes the main enzymatic reactions involved in biosynthesis, production and release of thyroid hormones in the thyroid follicular cell. Congenital alteration in any of the reported steps can be associated to congenital hypothyroidism (dysormonogenesis).

 

Table1-
1. Clinical picture of the forms of congenital hypothyroidism with a genetic origin

 

Thyroid alteration Thyroid morphology Gene Clinical manifestations
Central hypothyroidism No goiter LHX3 and LHX4 Hypothyroidism, combined pituitary hormone deficiency, short stature, metabolic disorders, reproductive system deficits, nervous system developmental abnormalities
HESX1 Hypothyroidism, septo-optic dysplasia (SOD): hypoplasia of the optic nerves, various types of forebrain defects, multiple pituitary hormone deficiencies
TRH and TRHR Hypothyroidism, short stature
IGSF1 Hypothyroidism, prolactin deficiency, macroorchidism, delayed puberty, neurological symptoms
TBLX1 Congenital hypothyroidism and hearing defects
Thyroid dysgenesis Athyreosis PAX8 No goiter, severe hypthyroidism
NKX2-5 No goiter, severe hypothyroidism, no cardiac alterations
FOXE1 Severe hypothyroidism, Bamforth-Lazarus syndrome
Thyroid ectopy NKX2-5 No goiter, hypothyroidism, no cardiac alterations
FOXE1 Hypothyroidism, Bamforth-Lazarus syndrome
PAX8 Congenital hypothyroidism, non-syndromic
DUOX2 Congenital hypothyroidism, non-syndromic
Thyroid hypoplasia NKX2-1 No goter, variable hypothyroidism (mild to severe), choreoathetosis, pulmonary alterations
TSHR Reistance to TSH: no goiter, variable hypothyroidism (mild to severe)
PAX8 No goiter, variable hypothyroidism (moderate to severe)
Dysormonogenesis Goiter NIS Variable hypothyroidism (moderate to severe)
TPO Variable hypothyroidism (moderate to severe)
DUOX1 and DUOX2 Permanent hypothyroidism (mild to severe), transient and moderate hypothyroidism
DUOXA2 Variable hypothyroidism (mild to severe)
PDS Moderate hypothyroidism and deafness;
TG Variable hypothyroidism (from moderate to severe)
DHEAL1 Variable hypothyroidism (mild to severe)

 

 

 

Table 2. Tests used to complete the diagnosis of CH

 

  1. Imaging studies (to determine thyroid location and size)
  2. Scintigraphy (99mTc or 123I)
  3. Ultrasonography
  4. Functional studies
  5. 123I uptake
  6. Serum thyroglobulin
  7. Suspected inborn errors of thyroid hormone synthesis
  8. 123I uptake and perchlorate discharge
  9. Serum/salivary/urine iodine studies
  10. Suspected autoimmune thyroid disease
  11. Maternal and neonatal serum thyroid-antibodies determination
  12. Suspected iodine exposure (or deficiency)
  13. Urinary iodine measurement

Clinical Problems Caused by Obesity

ABSTRACT

 

Obesity constitutes a worldwide epidemic with prevalence rates which are increasing in most Western societies and in the developing world. By 2025, if this trend continues, the global obesity prevalence will reach 18% in men and exceed 21% in women. Furthermore, it is now well-established that obesity (depending on the degree, duration, and distribution of the excess weight/adipose tissue) can progressively cause and/or exacerbate a wide spectrum of co-morbidities, including type 2 diabetes mellitus, hypertension, dyslipidemia, cardiovascular disease, non-alcoholic fatty liver disease, reproductive dysfunction, respiratory abnormalities, psychiatric conditions, and even increase the risk for certain types of cancer. This chapter presents an overview of these links focusing on the most common obesity-related co-morbidities.

 

Introduction

 

During the past few decades, the prevalence rates of obesity [defined as body mass index (BMI) over 30 kg/m2] have been increasing at a rapid pace in both Western societies and the developing world (1), reaching 641 million adults being obese in 2014 [266 million men and 375 million women], compared to 105 million adults in 1975 [34 million men and 71 million women] (2). Notably, if this trend persists, the global obesity prevalence is predicted to rise to 18% in men and surpass 21% in women by 2025 (2). Overall, obesity can be considered a chronic relapsing and progressive disease (3) and a leading risk factor for global deaths. Furthermore, alarming trends of weight gain have also been documented for children and adolescents, undermining the present and future health status of the population (4-7). To highlight the related threat to public health, the World Health Organization (WHO) declared obesity a global epidemic, also stressing that in many cases it remains an under-recognized problem of the public health agenda (1, 8, 9).

 

Depending on the degree and duration of weight gain, obesity can progressively cause and/or exacerbate a wide spectrum of co-morbidities, including type 2 diabetes mellitus (T2DM), hypertension, dyslipidemia, cardiovascular disease (CVD), liver dysfunction, respiratory and musculoskeletal disorders, sub-fertility, psychosocial problems, and certain types of cancer (Figure 1).

 

Figure 1. Co-Morbidities Associated with Overweight and Obesity.

These chronic diseases have been shown to have strong correlations with BMI, and closely follow the prevalence patterns of excessive body weight in all studied populations (10, 11). Notably, the risk of developing a number of obesity-related co-morbidities rises exponentially with increasing BMI over 30 kg/m2, which is further associated with a graded increase in the relative risk of premature death, primarily from CVD (9, 10, 12). For individuals with BMI between 25 and 29.9 kg/m2 (pre-obesity) the risk of premature mortality is weaker and appears to be influenced mainly by fat distribution (Figure 2). Indeed, fat accumulation intra-abdominally and subcutaneously around the abdomen (central, abdominal, visceral, android, upper body or apple-shaped obesity) is associated with higher risk for cardiometabolic diseases, independent of BMI (13, 14). On the other hand, fat accumulation in the subcutaneous regions of hips, thighs and lower trunk (gluteofemoral, peripheral, gynoid, lower body or pear-shaped obesity) is considered less harmful or even protective against cardiometabolic complications (13, 15-17).

 

Figure 2. Relationship Between Body Mass Index (BMI) and Mortality (data from Calle et al. NEJM 1999 (12)).

Notably, individuals of certain ethnic backgrounds, regardless of the country of residence, are predisposed to central/abdominal obesity and more vulnerable to obesity-related complications (18-21). Indeed, studies in South Asian, Japanese, and Chinese populations have demonstrated significantly higher risk for insulin resistance, T2DM and CVD compared to matched overweight/obese Caucasians (22-24). Accordingly, rigorous cut-off points have been proposed for weight management among these populations, diagnosing obesity with BMI thresholds as low as 25 kg/m2 and defining central obesity based on ethnicity specific cut-off values of waist circumference (22-27).

 

In any case, obesity should be recognized by the treating physician as a key risk factor for the health of the patient, and appropriate weight loss treatments should be offered to patients with obesity, independently of other related co-morbidities (28-30). Weight management is crucial and should be suggested promptly even when these individuals are otherwise healthy (e.g. metabolically healthy patients with obesity) to prevent and/or delay the onset of obesity-related complications. Interestingly, recent advances in treatment options for CVD risk factors and acute coronary syndromes are now offering improved cardio-protection outcomes and appear to prolong life expectancy in patients with obesity. Indeed, epidemiologic data support the notion that, in developed societies increasing numbers of these patients are expected to live more than previously predicted, despite failing to reduce their excessive body weight (31, 32). As such, it is estimated that growing and progressively ageing populations in Western societies will continue to develop an increasing burden of obesity-related disease, including complications (e.g. chronic liver disease, respiratory or mobility problems) which were previously under-diagnosed or under-expressed due to earlier mortality (expansion of obesity-related morbidity) (31, 33, 34). Subsequently, the economic impact of obesity on health care costs is profound and will continue to increase, while the additional indirect costs (e.g. absence from work, reduced productivity and disability benefits) are also substantial. National surveys in the UK have shown that obesity is directly responsible for almost 7% of the overall morbidity and mortality, with a direct cost to the Neational Health System (NHS) that currently exceeds five billion pounds per year and could potentially rise to more than nine billion pounds by 2050 (35-37).

 

Childhood obesity also poses a significant burden due to a spectrum of complications both in the short term and later in life, highlighting the need for early intervention and prevention of obesity in children and adolescents (5, 38, 39). It should be noted that the absolute BMI is not an appropriate screen index to identify children with elevated body fat mass since BMI normative values differ based on age and gender. Hence, in the pediatric population BMI should be plotted on the Centers for Disease Control and Prevention’s percentile curves to identify the corresponding BMI percentile category (www.cdc.gov/growthcharts) [obesity in children and adolescents will be reviewed in detail in the EndoText chapter dedicated to Pediatric Obesity].

 

 

Obesity and Type 2 Diabetes Mellitus

 

Diabetes mellitus constitutes a rather diverse group of metabolic disorders which are characterized by hyperglycemia (e.g. type 1 diabetes, type 2 diabetes, gestational diabetes, maturity onset diabetes of the young, drug-induced diabetes, diabetes secondary to pancreatic damage) (40). Type 2 diabetes mellitus (T2DM) comprises up to 90% of all diagnosed diabetic cases in adults and is typically associated with presence of various degrees of obesity. Depending on ethnicity, age and gender, 50-90% of T2DM patients exhibit a BMI over 25 kg/m2, while patients with BMI over 35 kg/m2 are almost 20 times more likely to develop T2DM compared to individuals with BMI in the normal range (18.5-24.9 kg/m2 for Caucasians) (40, 41). Indeed, T2DM rates have been increasing both in developed and developing countries following the documented prevalence trends of obesity (2, 42, 43); hence, the term “diabesity” has been introduced to describe this twin epidemic (43-45).

 

Large-scale population studies have shown that obesity is the most important independent risk factor for insulin resistance and T2DM (46-49). In adults, the relative risk for T2DM begins to increase even at BMI values within the normal weight range, 24 kg/m2 for men and 22 kg/m2 for women, while it rises exponentially with increasing BMI over 30 kg/m2 (Figure 3). Thus, morbid obesity is associated with markedly high relative risk for T2DM in both genders, up to 90 and 40 for women and men, respectively (46, 47). Although visceral adiposity is more prominent in men, obesity appears associated with higher T2DM risk in women compared to men (50, 51). Moreover, T2DM increases the risk of CVD by three to four times in women and two to three times in men, after adjusting for other risk factors (52). Interestingly, impaired glucose homeostasis and T2DM have been linked to X-chromosomal loci (53); however, the relative contribution of these loci to the onset of T2DM is not fully clarified yet. Overall, it appears that an interplay exists between gender, ethnicity, and certain adipose tissue characteristics which plays an important role in the association between obesity and related cardiometabolic comorbidities, including T2DM (54). Moreover, children and adolescents with obesity are now increasingly diagnosed with impaired glucose tolerance and T2DM (55-58).

 

Figure 3. Body Mass Index (BMI) and Risk of Developing Type 2 Diabetes Mellitus (T2DM) in Male and Female Adults (based on data from Colditz GA et al. Ann Intern Med. 1995 (47) and Chan JM et al. Diabetes Care 1994 (46)).

Furthermore, a strong association exists between central obesity and T2DM, beyond the impact of BMI (13, 14, 59, 60). Both insulin resistance and hyperinsulinemia correlate positively to visceral fat accumulation which constitutes an independent risk factor for T2DM. Accordingly, anthropometric indices of central obesity (e.g. waist circumference, waist-to-height ratio and the visceral adiposity index) are utilized to better assess the obesity-related risk of T2DM and CVD (61-63). The higher cardiometabolic risk associated with central fat distribution is attributed to a combination of factors, relating mainly to a more deleterious adipocyte secretory profile in these fat depots. Indeed, visceral adipose tissue is more lipolytic (decreased insulin-mediated inhibition of the hormone-sensitive lipase and increased catecholamine-induced lipolysis) causing a greater flux of free fatty acids (FFA) into the portal circulation with lipotoxic effects, primarily in the liver and skeletal muscle (64, 65). Additionally, adipocytes in visceral fat depots exhibit increased secretion of pro-inflammatory adipokines (e.g. tumor necrosis factor-α and intrerleukin-6) and decreased secretion of adiponectin, hence, leading to decreased insulin sensitivity and activation of pro-inflammatory pathways in the adipose tissue, liver, and skeletal muscle (66, 67). Hormonal changes either at the systemic level of various neuroendocrine axes (e.g. chronic mild hypercortisolemia and dysregulation of the hypothalamic-pituitary-adrenal axis, as seen in chronic stress) or at the local level of the visceral adipose tissue (e.g. increased conversion of cortisone to cortisol via type 1 11β-hydroxysteroid dehydrogenase, 11β-HSD1, in fat depots) may increase lipogenesis and thus  contribute to adverse metabolic consequences of central obesity (68-70).

 

It should be noted that, insulin resistance in patients with obesity leads to chronic compensatory hyperinsulinemia, which in turn may promote further weight gain (71). On the other hand, it is interesting that acute and short-term increases of circulating insulin levels can even reduce liver fat accumulation, at least in mice (72). This concept may contribute to the documented beneficial effects of dietary protein and certain insoluble cereal fibers which induce a short-term surge in insulin secretion (73-75). Several studies indicate that both dietary protein and cereal fiber intake are associated with beneficial effects on blood glucose regulation and body fat distribution in the long-term (76-86). With high protein diets, this appears to be mainly related to increased satiety and weight loss (86, 87). Intake of insoluble cereal fiber appears to improve insulin sensitivity and the risk of developing T2DM, with the only moderate weight loss involved unlikely being the driving factor (84, 85, 88, 89). Indeed, in an 18 week randomised controlled isoenergetic trial in 111 overweight or obese subjects, whole-body insulin sensitivity markedly improved with the intake of a diet high in cereal fiber (85). Interestingly, existing data also indicate that high protein intake in sedentary, at-risk subjects who typically fail to lose weight in the longer term regardless the diet (90) could have adverse effects on insulin resistance and T2DM risk. Of note, Wang et al. have investigated the metabolite profiles in 2,422 normoglycemic subjects who were followed for 12 years, with 201 of the subjects having developed T2DM (91). Five branched-chain and aromatic amino acids (isoleucine, leucine, valine, tyrosine, and phenylalanine) showed highly-significant associations with the future development of T2DM, with replication of the results in an independent, prospective cohort (91). The authors proposed amino acid profiling as a potential predictor for future diabetes, but a potential causal link between dietary protein intake and future diabetes cannot be excluded. Despite the widely claimed beneficial effects, there is increasing evidence that longer term high intake of both animal and total protein may have detrimental effects on insulin resistance (85, 86, 92-99), diabetes risk (100, 101) and the risk of developing CVD (102, 103). This could be especially detrimental in pre-diabetic subjects with obesity who already have impaired insulin secretion and may be resistant to the anabolic response to high protein intake (104), thus lacking several potentially important compensatory mechanisms for protein-induced worsening of insulin resistance (86). Furthermore, obese patients are typically sedentary, with potential additional unfavourable effects on protein-regulated mTOR/S6K1 signaling and the development of insulin resistance, as suggested by studies in rodents (105). Finally, whereas in elderly people low protein intake may have detrimental effects, recent studies have linked high protein intake to cancer risk and overall mortality in younger individuals (below the age of 65 years) (103). Given this evidence, further research is clearly needed before high protein diets should be widely proposed as a safe tool for weight loss in sedentary subjects with obesity that typically fail in long-term weight maintenance after an initial diet-induced weight loss and are already at high-risk of developing T2DM.

 

Overall, in chronic hyperinsulinemia a vicious cycle is formed, where fat accumulation causes generalized insulin resistance (insulin resistance in adipose tissue, liver and skeletal muscle) combined with increased insulin secretion and vice versa. Decreased insulin sensitivity in adipose tissue is crucial for initiating and fuelling this vicious cycle (106, 107). Normally, insulin-mediated inhibition of hormone-sensitive lipase in adipocytes decreases FFA release from fat depots, leading to lower FFA plasma concentrations, inhibition of hepatic glucose production and increased muscle glucose uptake. However, in T2DM uninhibited lipolysis in insulin-resistant adipocytes causes persistently increased circulating FFA levels. In turn, this leads to reduced peripheral glucose utilization, increased hepatic glucose production and decreased insulin sensitivity in the liver and skeletal muscle (108, 109). Thus, adipocytes play a crucial role in the overall regulation of glycemia in T2DM, although the adipose tissue glucose uptake is less than 5% of the total glucose disposal (107).

 

In the liver, insulin regulates the hepatic glucose production rate by activating specific enzymes which induce glycogenesis and suppressing enzymes involved in gluconeogenesis. Hepatic insulin resistance can be defined as the failure of insulin to adequately suppress hepatic glucose production and is associated with fasting hyperglycemia in T2DM (110). Notably, the lipogenic actions of insulin do not appear to be compromised in insulin-resistant states, as will be further discussed in the following section of this chapter about obesity and fatty liver disease. Under normal fasting conditions, circulating levels of insulin are low and fasting hepatic glucose production matches the basal glucose utilization (equal gluconeogenesis and glycogenolysis rates). In T2DM, the fasting glucose production in the liver is increased due to hepatic insulin resistance despite compensatory hyperinsulinemia (107). Overall, the absolute amount of hepatic glucose production is moderately increased in T2DM patients compared to that of healthy controls, but is inadequately suppressed relative to the raised concentrations of glucose and insulin (111). This increased fasting hepatic glucose production exhibits a linear correlation with the degree of fasting hyperglycemia and is caused primarily by accelerated glucose synthesis through the gluconeogenic pathway (112). On the other hand, insulin resistance in skeletal muscle fuels postprandial hyperglycemia in T2DM, since skeletal muscles are responsible for most of the glucose disposal after meals. Decreased insulin sensitivity in skeletal muscles of T2DM patients causes impaired insulin-stimulated glucose uptake which is both reduced and delayed (113). This postprandial under-utilization of glucose by skeletal muscles is superimposed on increased hepatic glucose production rates, thus, compounding the magnitude and duration of postprandial hyperglycemia.

 

Although necessary, insulin resistance alone is not sufficient for T2DM development since the pancreas has the capacity to adapt by accordingly increasing both beta-cell mass and insulin secretion. Due to these compensatory mechanisms, normoglycemia can be maintained despite reduced insulin sensitivity in the periphery. Thus, inadequate insulin secretion is a crucial component of the T2DM pathophysiology (107). Obesity contributes to beta-cell decompensation and impaired insulin secretion through the related insulin resistant state and various glucotoxic and lipotoxic effects on the pancreas. Lipotoxicity can cause beta-cell dysfunction depending on the degree of exposure to FFA and on the underlying genetic predisposition for T2DM. In vitro, prolonged exposure of beta-cells to high FFA concentrations increases FFA oxidation and causes accumulation of intracellular metabolites (e.g. citrate and ceramide) which impair glucose-stimulated insulin secretion and promote apoptosis (107, 114). Clinical studies have also confirmed that sustained high FFA plasma levels can impair insulin secretion in predisposed individuals (115). On the other hand, pharmacological inhibition of lipolysis in non-diabetic individuals with strong family history of T2DM can improve insulin secretion (116). Similarly, glucotoxicity can impair beta-cell function depending on the duration and degree of hyperglycemia. In vitro, prolonged beta-cell exposure to high glucose concentrations causes glucose desensitization, impairs insulin gene transcription and induces apoptosis (107). Clinical studies have also reported that reduced beta-cell sensitivity to glucose plays a predominant role in patients with impaired glucose tolerance (117, 118).

 

Finally, it should be emphasized that both the insulin resistant state in obesity and the related acquired beta-cell defects can be restored, at least in part, with weight loss and good glycemic control. Indeed, several studies have reported that even modest weight loss (e.g. weight loss achieved by lifestyle interventions, including diet and exercise to increase physical activity) is important for T2DM prevention, significantly reducing the risk and delaying the onset of the disease (14, 119-127).

 

 

Following the recognition of adipocytes as endocrine cells, research has further focused on studying the links between obesity-related complications and the development of a chronic low-grade inflammatory state in obesity. As such, it became evident that weight gain progressively promotes sub-clinical inflammation in patients with obesity, which is mainly attributed to secretion of various pro-inflammatory factors, including adipokines/cytokines and chemokines (e.g. leptin, TNF-α, IL-6, IL-1β) (128-140). The pro-inflammatory nature of adipose tissue is heightened in proportion to fat accumulation and exhibits positive correlations with increasing BMI and especially with visceral adiposity (65, 130-133, 141). Thus, central obesity appears to trigger and exacerbate an inflammatory cascade that initially evolves within fat depots. Over time, this exerts systemic effects, since enhanced adipose tissue secretion of pro-inflammatory adipokines persists for as long as the excess abdominal fat mass is maintained. Compiling evidence suggests that this obesity-related activation of pro-inflammatory signaling pathways is linked to key CVD risk factors (e.g. insulin resistance and T2DM), as well as to atherosclerosis and thrombosis (59, 142-146). Indeed, NLRP3 inflammasome activation appears to be a key underlying mechanism/link between obesity-related chronic inflammation and insulin resistance (129).

 

Obesity induces multiple constitutional alterations in the micro-environment and cellular content of adipose tissue depots, which collectively promote differentiation of pre-adipocytes, insulin resistance and pro-inflammatory responses (130-133). A closer look at the underlying molecular interplay unveils a vicious cycle between pre-adipocytes, mature adipocytes and macrophages, which reside in adipose tissue of patients with obesity (Figure 4).

 

Figure 4. Adipose Tissue and Low-Grade Inflammatory State in Obesity.

TNF-α: tumor necrosis factor-α, MCP-1: monocyte chemotactic protein-1, IL-8: interleukin 8, IL-1: interleukin-1, IL-6: interleukin-6.

 

Weight gain enhances both lipogenesis and adipogenesis inside fat depots, as well as secretion of pro-inflammatory adipokines and chemokines (e.g. monocyte chemotactic protein-1, MCP-1, and IL-8) into the circulation. In response to such chemotactic stimuli mononuclear cells are recruited from the circulation and transmigrate into adipose tissue depots, increasing the number of resident activated macrophages (147-149). In turn, this growing population of macrophages secretes cytokines, such as TNF-α, IL-1β and IL-6, which can potentially aggravate the pro-inflammatory and insulin resistant profile of adipocytes; although there is also a body of literature suggesting that IL-6 does not cause insulin resistance (133, 150, 151). Thus, sustained fat accumulation establishes an unremitting local pro-inflammatory response within the expanding adipose tissue. This cascade progresses to a chronic low-grade generalized inflammatory state in obesity, mediated by persistent release of pro-inflammatory adipokines of adipocyte and/or macrophage origin and coupled with decreased adiponectin secretion (130-132, 152), with deleterious effects on peripheral tissues and organs (e.g. liver, skeletal muscles, vascular endothelium). These effects promote hepatic and skeletal muscle insulin resistance, hypertension, atherosclerosis, hypercoagulability, thrombosis and enhanced secretion of acute-phase reactants (e.g. C-reactive protein, fibrinogen, haptoglobin) (130-133, 153).

 

The procoagulant state in obesity is further characterized by increased levels of fibrinogen and plasminogen activator inhibitor-1 (PAI-1), which promote atherogenic processes and increase the related CVD risk (145, 154-157). Fibrinogen is synthesized by hepatocytes and holds a pivotal role in the coagulation cascade, being a major determinant of plasma viscosity and platelet aggregation, whilst also potentially playing a pro-inflammatory role in vascular wall disease (158). Expression of fibrinogen in the liver is up-regulated by IL-6 during the acute phase reaction, and various studies have documented an association between elevated fibrinogen levels and increasing BMI (159). Interestingly, fibrinogen has also been shown to predict weight gain in middle-aged adults (160). PAI-1 regulates the endogenous fibrinolytic system and constitutes the main inhibitor of fibrinolysis by binding and inactivating the tissue plasminogen activator, thus increased PAI-1 activity leads to decreased clearance of clots. Elevated PAI-1 levels have been associated with increased BMI, visceral adiposity and obesity-related cardiometabolic complications (145, 161-165). Enhanced adipose tissue expression of PAI-1 has been reported in obesity, particularly in visceral adipose tissue (166), while an inverse relationship was also demonstrated between PAI-1 activity and adiponectin in overweight and obese women (164, 165).

 

It is also noteworthy that a putative integration of adipocytes into the innate immune system has been suggested, thus linking metabolic and inflammatory signaling pathways. Apart from their documented reciprocal interactions inside adipose tissue depots, the inherent similarities between adipocytes and macrophages are of particular interest (133, 167, 168). Although these cells clearly belong to distinct lines, they have a common ancestral origin from the mesoderm during early embryogenesis. Mature adipocytes differentiate from pluripotent mesenchymal stem cells which, under certain conditions, become committed to the adipocyte lineage and produce pre-adipocytes. Notably, pre-adipocytes appear to have the ability to differentiate into macrophages and to function as macrophage-like cells, developing phagocytic activity against microorganisms (169, 170). Furthermore, analysis of the adipocyte gene expression profile in obesity revealed striking resemblances to that of macrophages, with adipocytes expressing specific cytokine genes (e.g. IL-6, TNF-α) which were typically associated to macrophages (171, 172). Finally, both pre-adipocytes and mature adipocytes express Toll-like receptors (TLRs) which are cardinal regulators of innate and adaptive immune responses and can be directly activated by both lipopolysacharide (LPS) and fatty acids (173). This advocates the hypothesis that the adipose tissue may also play a role as an immune organ (174), with potential implications for treatment of obesity-related complications. Identifying common initial inflammatory mechanisms could lead to therapeutic interventions that may inhibit at earlier stages the adipose-initiated pro-inflammatory cascade and, thus, prevent the onset of clinical complications. Indeed, therapeutic interventions to inhibit inflammatory pathways in obesity have shown promising results with beneficial effects on insulin sensitivity in mouse models and human trials (130).

 

Metabolic Syndrome: Definitions and Quest for a Single Set of Diagnostic Criteria

 

All the aforementioned findings support the notion that obesity-related pro-inflammatory pathways mediate deleterious cardiometabolic effects which can lead to clinical manifestations of the metabolic syndrome. In 1988, Reaven proposed the term “Syndrome X” to describe a constellation of metabolic abnormalities, including glucose intolerance, dyslipidemia and hypertension, which frequently cluster together revolving around insulin resistance (175). All these metabolic disorders are established independent CVD risk factors and their coexistence correlates with high CVD morbidity and mortality, an association that aptly led to the description of the syndrome as the “deadly quartet” (176). Since then, the term “Metabolic Syndrome” has been adopted to better illustrate this clustering of cardiometabolic risk factors, opening new opportunities for the study of their interrelationships (177, 178). Existing evidence on the prevalence of the metabolic syndrome, based on large US, European, and Australian cohorts, indicate that, depending on the applied definition, it affects over a quarter of the adult population in Western societies (179-181). Furthermore, meta-analysis data have shown that the metabolic syndrome is associated with a 2-fold increase in CVD outcomes and a 1.5-fold increase in all-cause mortality (182). Several prominent medical bodies/scientific societies, including the World Health Organization (WHO), the European Group for the Study of Insulin Resistance (EGIR), and the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III), have proposed different metabolic syndrome definitions to help identify individuals at high risk for cardiometabolic complications in clinical practice (Figure 5) (183-185).

 

However, these definitions applied diagnostic criteria that varied significantly, thus limiting comparability between studies and creating confusion regarding their use by clinicians (177). In order to address the need for widely accepted criteria that could be easily applied in different settings and ethnic populations, in 2005 the International Diabetes Federation (IDF) issued a consensus statement introducing a worldwide metabolic syndrome definition based on assessment of simple anthropometric and plasma measurements [waist circumference, blood pressure and plasma levels of triglycerides, high-density lipoprotein cholesterol (HDL-C) and fasting glucose] (Figure 5) (186). This consensus identified central obesity as the hallmark of the metabolic syndrome and the prerequisite component for its diagnosis. Furthermore, to increase the applicability in various ethnic groups, central obesity diagnosis in the IDF definition relies on waist circumference measurements, which puts into practice a set of ethnic-specific cut-off values. Thus, an approach was adopted to take into account the fact that individuals of specific ethnic origin (e.g. South Asians), regardless of their country of residence, are predisposed to central obesity and more susceptible to complications of visceral adiposity (20-24, 26). Overall, the IDF consensus was a targeted effort to offer a metabolic syndrome definition set on criteria that would be friendly to routine clinical practice and could be uniformly applied in different settings and patient groups. Moreover, the adopted rationale for this definition took into account the growing body of evidence which supported the crucial role of central obesity in the pathophysiology of insulin resistance and the metabolic syndrome.

 

Of note, the published IDF consensus statement included a recommended “Platinum standard” list of additional criteria to be included in epidemiological and other research studies regarding the metabolic syndrome (186, 187). Assessment of multiple metabolic parameters was proposed, including markers of adipocyte function (leptin, adiponectin), inflammatory markers (C-reactive protein, TNF-α, IL-6), and coagulation markers (PAI-1, fibrinogen), together with evaluation of fat distribution (visceral adiposity, liver fat), and precise measurements of insulin resistance, endothelial dysfunction, atherogenic dyslipidemia and urinary albumin. Incorporating these variables into comprehensive research on the pathophysiology of the metabolic syndrome components aimed to further advance the understanding of the underlying pathogenetic pathways/mechanisms.

 

Figure 5. Different Definitions of the Metabolic Syndrome.

It is also important to mention that, the waist circumference values in the IDF definition were proposed as initial guidelines based on available evidence and, thus, were accepted as neither complete nor definite (23, 186). Further epidemiological studies are still required in this field in order to offer additional data and contribute to identify more accurate cut-off points for waist circumference in various populations (e.g. Sub-Saharan Africans, South and Central Americans, Asian, Eastern Mediterranean and Middle East populations). Indeed, cut-off points of >85-90 cm for men and >80 cm for women have been suggested in Japan, while in China threshold values of >85 cm and >80 cm have been proposed in men and women, respectively, and slightly lower values in India (188-190).

 

Figure 6. Criteria for clinical diagnosis of the metabolic syndrome from the International Diabetes Federation (IDF) and the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) and recommended waist circumference thresholds for abdominal obesity by organization (adopted from Alberti et al. Circulation 2009 (25)).

In 2009, another attempt was made to resolve the differences between metabolic syndrome definitions, which resulted in a joint interim statement from the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) and the IDF (25). To harmonize the metabolic syndrome criteria, this statement accepted the previous five criteria of the IDF and ATP-III definitions and agreed that central obesity should not be a prerequisite for diagnosis, which instead should be confirmed by the presence of any 3 of the 5 accepted risk factors (Figure 6). In this joint definition, central obesity is defined based on population- and country-specific thresholds of waist circumference with a recommendation that the IDF cut-offs should be used for non-Europeans, while either the IDF or the AHA/NHLBI cut-offs can be used for people of European origin until more data become available (Figure 6).

 

The more recent metabolic syndrome definitions have contributed in setting more widely accepted diagnostic criteria for both research and clinical practice (25, 181, 186, 191). Despite these efforts, there has been significant debate and controversy as to whether the diagnosis of the metabolic syndrome adds more value compared to its individual components, especially in clinical decision making (177, 192-199). Indeed, based on a more recent report of a WHO Expert Consultation the metabolic syndrome is considered useful mainly as an educational concept with limited practical utility as a diagnostic or disease management tool (198, 199). However, the metabolic syndrome diagnosis and its definitions are still applied in research studies and in clinical practice, whilst both traditional and technology supported lifestyle interventions are utilized for the treatment of the metabolic syndrome and its components (200). As such, it is important to stress that, in parallel to the risk conferred by a metabolic syndrome diagnosis, additional risk factors, such as age, gender, smoking, low-density lipoprotein cholesterol (LDL-C) plasma levels and other obesity-related comorbidities (e.g. non-alcoholic fatty liver disease and obstructive sleep apnea), substantially increase the related CVD risk and must be comprehensively assessed and addressed in routine clinical practice, as will be further reviewed in the EndoText chapter dedicated to the metabolic syndrome and its treatment.

 

Obesity and Non-Alcoholic Fatty Liver Disease

 

The liver is the largest solid organ in adults, constituting 2-3% of the body weight and accounting for 25-30% of the total oxygen consumption. Normal hepatic function is essential for preserving metabolic homeostasis and a dynamic crosstalk exists between the liver and adipose tissue to regulate carbohydrate, lipid, and protein metabolism. Obesity may cause hyperinsulinemia and hyperglycemia, as well as ectopic fat accumulation and insulin resistance in the liver. In turn, this can impair hepatic function and lead to a spectrum of abnormalities, ranging from elevation of circulating liver enzyme levels and steatosis to local inflammation (steatohepatitis), cirrhosis, liver failure and even liver cancer (201-208). The term non-alcoholic fatty liver disease (NAFLD) is now applied to describe this spectrum of hepatic abnormalities.

 

The relationship between obesity and liver dysfunction has been noted in the literature since the first half of the past century (209). In 1980, the term non-alcoholic steatohepatitis (NASH) was introduced by Ludwig et al. to describe findings in 20 patients at the Mayo clinic exhibiting a non-alcohol related liver disease which was histologically similar to alcoholic hepatitis (210). Hepatocellular steatosis is the hallmark of the disease (triglyceride deposition in the liver higher than 5% of the total liver weight), and the presence of more than 5% of steatotic hepatocytes in a liver tissue section is now regarded as the minimum criterion for the histological diagnosis of NAFLD (211-213). This steatosis reflects ectopic fat deposition in the liver which is more frequently macrovesicular (one large intracellular fat droplet displacing the nucleus). Microvesicular steatosis (numerous small intracytoplasmic fat vesicles not displacing the nucleus) may also occur, but is less frequent and it can be underestimated due to limitations of routinely applied staining techniques (211-213).

 

Non-alcoholic fatty liver disease pathology extends from steatosis to steatohepatitis and fibrosis. In 1999, Matteoni et al. proposed a histologic classification of NAFLD into four distinct types (Figure 7) (214).

 

Figure 7. Natural History of Non-Alcoholic Fatty Liver Disease (NAFLD). A. Histological classification as proposed by Matteoni et al. (214). Non-alcoholic steatohepatitis (NASH) represents the most severe form of NAFLD (NAFLD types 3 and 4) and can progress to cirrhosis and hepatocellular carcinoma (HCC). B. NAFLD activity score (NAS) proposed for histological scoring and staging of NAFLD in order to consistently assess the disease and compare outcomes of therapeutic interventions (adopted from Kleiner et al. Hepatology 2005 (206, 215)).

 

Non-alcoholic steatohepatitis(NASH) corresponds to types 3 and 4 of this classification, representing the most severe histologic form of NAFLD. In addition to steatosis, NASH is characterized by various degrees of inflammation, hepatocyte injury and fibrosis which may gradually lead to cirrhosis (211-213). Subsequently, various scoring systems for grading and staging of NAFLD have been developed to assess the disease and compare outcomes of therapeutic interventions. The Pathology Committee of the NASH Clinical Research Network designed and validated a histological feature scoring system for the entire spectrum of NAFLD lesions and proposed the NAFLD activity score (NAS) which was developed as a tool to measure changes in NAFLD during therapeutic trials (Figure 7) (212, 213, 215). It must be noted that distinction between NASH and alcoholic hepatitis may be difficult at the histological level, and, thus, a detailed alcohol consumption history is always crucial when evaluating patients with suspected NAFLD in clinical practice (203). Indeed, according to the recent clinical practice guidelines for the management of NAFLD by the European Association for the Study of the Liver (EASL), the European Association for the Study of Diabetes (EASD), and the European Association for the Study of Obesity (EASO), the interaction between moderate alcohol intake and various metabolic factors in fatty liver must always be considered (216). Non-invasive scoring systems and methods have also been proposed in order to identify advanced fibrosis in NAFLD patients, including the NAFLD Fibrosis Score (NFS), the Enhanced Liver Fibrosis (ELF) panel and transient elastography which measures liver stiffness non-invasively (203, 216-218).

 

Non-alcoholic fatty liver disease is now recognized as the most common cause of chronic liver disease, with rising prevalence and worldwide distribution which follows the global trends of obesity and T2DM (201-203, 208, 219, 220). Data on NAFLD prevalence in the general adult population vary depending on the applied diagnostic criteria and the population studied. Moreover, large-scale population studies are generally hindered by the fact that this liver disease can remain asymptomatic for years, may coincide with other chronic liver diseases and requires a liver biopsy for definite diagnosis (203, 221). Non-alcoholic fatty liver disease is thought to be present in approximately 25% of the Asian population, and in 25% to over 30% of the US population with a corresponding NASH prevalence of 3-6% in the US (201, 203, 208, 219). Moreover, in the US it is estimated that the prevalent NAFLD cases will increase by 21%, from an estimated 83.1 million cases in 2015 (25.8% prevalence among all ages, and 30% prevalence among individuals aged ≥ 15 years) to 100.9 million cases in 2030, whilst, in parallel, the prevalent NASH cases will increase by 63%, from 16.52 to 27 million cases (222). Estimates of the NAFLD prevalence worldwide, based on a variety of assessment/diagnosis methods, range from 6.3% to 33%, with a median of 20% in the general adult population, whilst the estimated NASH prevalence ranges from 3% to 5% (203). Recently, the pooled overall global prevalence of NAFLD diagnosed by imaging has been estimated at 25.24% (95% CI: 22.10-28.65), with the highest prevalence rates in the Middle East and South America and the lowest in Africa (223). Particularly significant are also the reported data in cohorts with T2DM and/or obesity which consistently document very high NAFLD prevalence rates, thus suggesting strong pathogenetic links. Indeed, the majority of patients with T2DM and/or obesity appear to develop steatosis, while NASH can be diagnosed in 10-20% of these cases (203, 208, 220). Of note, NAFLD prevalence is even higher among patients with severe obesity, since the reported prevalence of NAFLD in bariatric surgery patients can exceed 90%, whilst up to 5% of these patients may have unsuspected cirrhosis (203, 220, 224, 225). It must be highlighted that NAFLD is not restricted to adults, but also exhibits increasing prevalence among the pediatric population (estimated pediatric NAFLD prevalence of 3-10%), with reported NAFLD prevalence rates of up to 80% in children with obesity based on studies from the US, Europe and Japan (203, 226).

 

Gender, age and ethnicity are associated with the prevalence of NAFLD (203, 220). As such, gender differences appear to exist, and, although the initially available data suggested female predominance, male gender is now considered a risk factor for NAFLD (220). Furthermore, several studies have shown that NAFLD prevalence increases with age, although relevant studies on individuals older than 70 years remain rather limited (203, 223, 227). Family clustering and significant ethnic variations have also been documented, supporting the role of genetic predisposition (203, 219, 228, 229). Asian populations are considered particularly susceptible to NAFLD, partly due to body composition differences, with NAFLD prevalence rates that range between 20% in China and 15-45% in South Asia and Japan (219, 230). In addition, Hispanic individuals have significantly higher, and non-Hispanic blacks have significantly lower, NAFLD prevalence, compared to non-Hispanic whites (203, 229).

 

Studies on the natural history of NAFLD have shown that the underlying histologic stage dictates the prognosis of the disease, which appears to rely crucially on the presence of fibrosis (Figure 7) (201, 203, 208, 218, 220, 231-233). It is generally accepted that simple steatosis with absence of inflammation and fibrosis is associated with a benign and stable long-term course in the vast majority of the cases, exhibiting no or very slow histological progression (203, 218, 220). On the other hand, patients with NASH can exhibit histological progression to cirrhotic-stage disease (203, 218, 220). Indeed, NASH is associated with an increased risk for developing cirrhosis, liver failure and even hepatocellular carcinoma (HCC), with studies indicating that 3-15% of NASH cases can progress to cirrhosis over 10-20 years (234, 235). The prognosis is poor once NASH-related cirrhosis is established and a high proportion of these cases will require liver transplantation. Furthermore, HCC has been reported to develop at an annual rate of 2-5% in NASH patients with cirrhosis (236, 237). In a study with long-term follow-up of a small cohort with biopsy-proven NAFLD (129 patients followed for 13.7 years) NASH patients had significantly reduced survival due to liver-related and CVD causes (238). Overall, the age and gender adjusted mortality rate in NAFLD patients is significantly higher compared to the general population (both for overall and liver-related mortality) (203, 232, 239). A meta-analysis by Musso et al. reported that NAFLD has a 2-fold risk of T2DM and an increased overall mortality (OR: 1.57, 95% CI: 1.18-2.10) due to liver-related problems and CVD, with the odds ratio of liver-related mortality in the presence of advanced fibrosis being 10.06 (95% CI: 4.35-23.25; p=0.00001) compared with less advanced fibrosis stages (218). Non-alcoholic fatty liver disease severity tends to increase with age, but regression is also possible if prompt and effective weight loss interventions are applied before the stage of cirrhosis. However, signs of regression can be misleading, particularly in older patients, since progressing fibrosis may be silent or even associated with normalization of aminotransferases levels and improvement of steatosis and inflammation features. This often reflects a transition of NASH to cryptogenic cirrhosis which is associated with high HCC risk (203, 233, 240, 241).

 

The pathogenesis of NAFLD has been the subject of intense research in recent years (201). Initially, Day et al. first proposed a two stage hypothesis/model in order to provide a pathophysiological rationale (“two-hit” model), describing steatosis (reversible intracellular deposition of triacylglycerols) as the initial stage (first “hit”) that sensitizes the liver to the “second hit” (generation of free radicals, oxidative stress and cytokine-induced hepatic injury) which induces progression to fibrosis (242). This model offered an initial framework to study NAFLD pathogenesis; however, it is now regarded that progression to steatohepatitis is not limited to a “two-hit” process, but rather involves multiple interacting mechanisms occuring in parallel (208, 233, 243). Indeed, the pathogenesis of NAFLD appears to involve a complex interplay between genetic predisposition, environmental factors (e.g. diet composition, sedentary lifestyle, smoking), metabolic dysregulation (e.g. dyslipidemia, lipotoxicity and hyperglycemia) and other contributors, such as dysbiosis of the gut microbiota (201, 207, 208, 228, 233, 243-247).

 

In the context of this chapter, we will briefly highlight crucial pathophysiologic processes linking obesity (especially central/visceral obesity) and obesity-related insulin resistance with NAFLD and its progression to NASH. Fat accumulation in adipose tissue depots is typically followed by ectopic fat deposition in the liver and skeletal muscle and by insulin resistance in these tissues. Although hepatic insulin resistance can develop independently as a result of increased hepatocyte triglyceride content, growing evidence indicates that this usually follows insulin resistance in adipose tissue (207, 208, 245). Thus, obesity-related insulin resistance can cause fatty liver and, vice versa, excessive intrahepatic fat accumulation may promote insulin resistance and weight gain (110). However, the lipogenic actions of insulin appear to remain uncompromised in insulin-resistant states; hence, de novo fatty acid synthesis is undeterred even in the presence of marked insulin resistance (e.g. hepatic transcription of the gene encoding SREBP-1c remains stimulated by both insulin and glucose; Figure 8). Insulin resistance induces decreased inhibition of lipolysis in adipocytes, as well as decreased inhibition of gluconeogenesis and increased lipogenesis in the liver. Thus, steatosis is closely associated with an overall enhanced hepatic influx of circulating FFA that have been released by insulin resistant adipocytes. Importantly, in central obesity visceral fat depots exhibit a higher lipolysis turnover creating an amplified direct supply of FFA to the liver via the portal vein, which can account for 20-30% of the total hepatic FFA influx (248). Moreover, there is also evidence that hepatic accumulation of previously stored body fat and saturated dietary fat may induce hepatic insulin resistance (249).

Figure 8. Signaling Pathways Leading to Hepatic Triglyceride Accumulation in Insulin-Resistant States. In insulin sensitive states, insulin binds to its receptor and activates IRS1 and IRS2 which, via PKB/Akt, block gluconeogenesis (FOXO1) and fatty acid oxidation (FOXA2). In insulin resistance, the FOXA2 pathway may remain responsive to insulin when inhibition of FOXO1 is impaired, resulting in decreased fatty acid oxidation. In turn, elevated glucose activates both SREBP-1c and ChREBP, enhancing pancreatic insulin secretion (compensatory hyperinsulinemia). SREBP-1c blocks IRS2 signaling in the liver, further promoting hepatic glucose production, and probably counteracting the suppressive effect of SREBP-1c on gluconeogenic genes. Insulin, ChREBP and SREBP-1c also induce FASN and ACAC, leading to increased production of fatty acids. Thus, in insulin-resistant states hepatic triglycerides accumulate as a result of both reduced fatty acid oxidation and increased fatty acid production. Red arrows indicate the direction of changes in insulin-resistant states. ACAC: Acetyl-CoA carboxylase; ChREBP: carbohydrate response element-binding protein; FASN: fatty acid synthase; FOX: forkhead transcription factor; PKB: protein kinase B/Akt; SREBP: sterol response element-binding protein (adopted from Weickert et al. Diabetologia 2006 (110)).

 

On the other hand, newly produced fat by the liver, as well as mono- and poly-unsaturated dietary fat are likely to have less deleterious or even beneficial effects, suggesting compartmentalization of fatty acid metabolism in hepatocytes (249). In the context of hepatic insulin resistance, hyperinsulinemia and hyperglycemia can further increase the intrahepatic triglyceride content by stimulating de novo lipogenesis (DNL), impaired hepatic fatty acid oxidation and decreased VLDL efflux, while dietary fatty acids also contribute to steatosis (Figure 9) (250, 251). Indeed, it has been shown that of the triacylglycerol accounted for in the liver of NAFLD patients approximately 60% originates from serum FFA, 26% from DNL, and 15% from the diet (250). Moreover, a positive correlation is reported between the degree of insulin resistance and steatosis (252).

 

Furthermore, progression from steatosis to NASH and cirrhosis also appears connected to a diffusion of detrimental effects from adipose tissue depots to the hepatic cellular level (203-208). Indeed, NASH development in the steatotic liver involves increased hepatic insulin resistance and lipid peroxidation, in combination with local pro-inflammatory, oxidative stress, and endoplasmic reticulum stress responses. In obesity-related insulin resistance these pathways are triggered and fuelled by hyperleptinemia, hypoadiponectinemia and increased circulating concentrations of adipose-derived cytokines (e.g. TNF-α and IL-6). Intermittent exposure of the steatotic liver to this adverse adipokine profile increases hepatic insulin resistance and leads to mitochondrial dysfunction, inflammation, cell injury, apoptosis and fibrosis (203-208). Hepatocytes are also stimulated to locally secrete pro-inflammatory cytokines and factors (e.g. TNF-α, IL-6, IL-1β). In addition, hepatic stellate cells and Kupffer cells are activated, while circulating inflammatory cells are chemo-attracted and infiltrate the liver (253, 254). The outcome of these processes is a chronic pro-inflammatory state inside the liver, which bears resemblance to the low-grade inflammation within adipose tissue depots in obesity. Further research in the pathophysiology of NAFLD is required to fully clarify these underlying pathogenetic mechanisms, and lead to targeted therapeutic interventions which could either prevent steatosis or stop/delay progression to steatohepatitis.

Figure 9. Free Fatty Acid (FFA) Circulation Through the Liver (adopted from Roden et al. Nat Clin Pract Endocrinol Metab 2006 (251) with data from Nielsen et al. J Clin Invest 2004 (248). Adipose tissue delivers approximately 80% of circulating FFA in the fasted state, reduced to 60% postprandially. In normal-weight persons dietary fat is responsible for the bulk of the portal supply to hepatic FFA, with the remaining proportion being derived mainly from subcutaneous fat. The contribution of FFA supplied from visceral adipose tissue increases in individuals with obesity, whereas a lower percentage of FFA is supplied from both subcutaneous fat depots and dietary fat. This could be important given that the source of FFA might be relevant for metabolic effects of hepatic lipid accumulation (reviewed in Weickert et al. Diabetologia 2006 (110)). FACoA: long-chain fatty acids bound to coenzyme A.

 

Detailed description of the treatment options for NAFLD is beyond the scope of this chapter. Various position papers and clinical practice guidelines have been published by international and national scientific societies (216, 255). As such, EASL, EASD, and EASO have recently issued clinical practice guidelines for the management of NAFLD (216). It must be noted that, while several clinical trials are exploring the safety and efficacy of various agents for the treatment of NASH and hepatic fibrosis, no agent is specifically approved by regulatory agencies for NASH treatment (201, 216). Thus, weight loss remains vital for the management of NAFLD patients with obesity. Evidence suggests that weight loss of at least 3-5% of the body weight appears necessary to improve steatosis, while greater weight loss (up to 10%) may be required to improve necroinflammation (203). Therefore, pragmatic approaches should be discussed with NAFLD patients with overweight/obesity in order to adhere to lifestyle modifications combining dietary interventions and increased physical activity (e.g. aerobic exercise or resistance training), aiming to achieve and maintain a meaningful weight loss (201, 216). In addition to weight loss interventions, appropriate treatment for any coexisting metabolic syndrome manifestation (e.g. for T2DM, dyslipidemia and hypertension) should be also offered in order to both improve the underlying liver pathology, and to further address the associated high CVD morbidity and mortality.

 

Obesity and Gallbladder Disease

Gallbladder disease is a common gastrointestinal disorder in Western countries and cholelithiasis represents the most frequent hepatobiliary pathology, primarily with gallstones composed of cholesterol (approximately 80% of gallstones are cholesterol stones) (256, 257). The prevalence of gallstones reaches 10-20% in the adult population in developed countries and it is estimated that in the US alone more than 700,000 cholecystectomies are performed per year with annual costs of approximately 6.5 billion US dollars (257, 258). Female gender, increasing age, and family history are typical risk factors for gallstones, while the main modifiable risk factors include obesity, metabolic syndrome, and high caloric intake (257-260). Overall, cholelithiasis is strongly associated with being overweight and obese and a classic medical textbook mnemonic for gallstone risk factors is known as the "4 Fs" (“fat, female, fertile, and forty”) (41, 260-265). The relative risk of gallstone formation rises as body weight increases, exhibiting a positive correlation with increasing BMI which is more pronounced when BMI exceeds 30 kg/m2 (41, 261-263). In the Nurses’ Health Study women with BMI over 30 kg/m2 had twice the risk of gallstones compared to non-obese women, while a 7-fold excess risk was noted in women with BMI over 45 kg/m2 compared to those with BMI less than 24 kg/m2 (263). Obesity and female gender remain risk factors for gallstone disease even in children and adolescents (266-268). Higher prevalence of cholelithiasis with increasing BMI is also reported in men; however, this association appears less potent and appears to depend more on abdominal fat accumulation than on body weight alone (262, 269, 270). Indeed, large prospective studies among US adults of both genders indicate that indices of central obesity (e.g. waist circumference and waist-to-hip ratio) can predict the risk of gallstones and cholecystectomy independent of BMI (271, 272).

 

In addition to a higher prevalence of cholesterol gallstones, a study on gallbladder pathology in morbidly obese individuals has further documented significantly increased prevalence of cholecystitis and cholesterolosis (273). Interestingly, obesity may be also associated with inflammation and fatty infiltration of the gallbladder (fatty gallbladder disease, including cholecystosteatosis and steatocholecystitis), which results in abnormal wall structure and decreased gallbladder contractility (274, 275). Of note, it has been reported that NASH prevalence in patients with morbid obesity and gallbladder disease can be as high as 18%, with insulin resistance being more common in concurrent NASH and gallbladder disease (276). Moreover, another study reported cholelithiasis as an independent risk factor of NAFLD (277). Finally, obesity appears to increase both the risk of hospital admission and the length of hospital stay for gallbladder disease (278), as well as the conversion rate from laparoscopic cholecystectomy to open surgery in patients with symptomatic gallstone disease (279).

 

Several mechanisms have been proposed to explain the association between excess body weight and formation of cholesterol gallstones, focusing primarily on secretion of supersaturated bile and gallbladder stasis (256, 280-284). Thus, obesity is characterized by a high daily cholesterol turnover which is proportional to the total body fat mass and can result in elevated biliary cholesterol secretion (256, 280-282). This leads to supersaturation of the bile which becomes more lithogenic with high cholesterol concentrations relative to bile acids and phospholipids. Notably, in patients with obesity the bile also remains supersaturated for much longer periods of time and not only during the fasting state. Furthermore, obesity is associated with gallbladder hypomotility and stasis which predispose to gallstones formation. Increased fasting and residual volumes, as well as decreased fractional emptying of the gallbladder have also been reported in patients with obesity (285-288). Interestingly, hyperinsulinemia may cause both increased cholesterol supersaturation and gallbladder dysmotility (289-292).

 

Rapid weight loss in patients with obesity is also associated with increased risk of gallstone formation (293-300). Of note, weight cycling has been also shown to increase the risk of cholecystectomy, independent of BMI (301). Increased bile lithogenicity during weight loss is potentially attributed to an enhanced flux of cholesterol through the biliary system, while low intake of dietary fat may further impair gallbladder motility and cause stasis (293, 294, 300). Thus, diets with moderate levels of fat may reduce cholelithiasis risk by triggering gallbladder contractions and maintaining an adequate gallbladder emptying (293). A meta-analysis has also indicated that use of ursodeoxycholic acid can also prevent gallstone formation after surgical weight loss interventions (302).

 

The increased risk of gallstone formation with rapid weight loss is of particular significance following bariatric surgery. It is suggested that patients with severe obesity undergoing bariatric surgery should be considered at high risk for developing gallstone disease independently of other risk factors (295-299). Indeed, a retrospective study regarding predictors of gallstone formation after bariatric surgery reported that weight loss exceeding 25% of the initial body weight was the only postoperative factor that helped in selecting patients for postoperative ultrasound surveillance and subsequent cholecystectomy once gallstones were identified (296). Another study comparing cholecystectomy cases after Roux-en-Y gastric bypass, sleeve gastrectomy, and gastric banding reported that the frequency of symptomatic gallstones did not differ significantly between the first two procedures, while it was significantly lower after gastric banding potentially due to lower and slower weight loss (298). Concomitant prophylactic cholecystectomy with bariatric procedures has been suggested in order to prevent postoperative gallstone formation (303, 304). However, there is no clinical consensus on this point, while a growing body of evidence suggests that concomitant cholecystectomy should not be routinely performed during bariatric surgery, but only in bariatric patients with symptomatic gallbladder disease or at a second stage after the bariatric operation in patients who had or developed asymptomatic gall stones (305-310).

 

Gallstones are the major risk factor for biliary tract cancers and particularly for gallbladder cancer; however, gallbladder cancer is rare in Europe and North America reflecting the widespread and earlier adoption of cholecystectomy (high-risk areas remain mainly in South America and India where access to gallbladder surgery is still inadequate) (311-313). Subsequently, studies on the relationship between obesity and gallbladder cancer are limited. However, the available data are consistent in indicating that obesity is indeed associated with increased risk of gallbladder cancer, potentially attributed to higher risk of cholelithiasis and chronic inflammation (305, 311). Meta-analysis data that included eleven studies (three case-control and eight cohort studies with a total of 3288 cases) have also confirmed that excess body weight could be considered a risk factor for gallbladder cancer (314). In this meta-analysis, compared to normal weight individuals, the summary relative risk of gallbladder cancer for overweight and obese subjects was 1.15 (95% CI, 1.01-1.30) and 1.66 (95% CI, 1.47-1.88), respectively. Notably, the documented association with obesity was stronger for women (relative risk of 1.88; 95% CI, 1.66-2.13) than for men (1.35; 95% CI, 1.09-1.68). Accordingly, the 2016 working group of the International Agency for Research on Cancer (IARC) has concluded that there is sufficient evidence to support that excess body fatness causes gallbladder cancer (315, 316).

 

Obesity and Reproduction

 

Obesity can cause dysfunction of the hypothalamic-pituitary-gonadal (HPG) axis in both genders (317-319) (see also corresponding chapter in EndoText on Endocrine Consequences of Obesity). Reproductive disorders are more frequent in obese women, presenting with a wide range of manifestations that extend from menstrual abnormalities to infertility, while obese men can exhibit decreased libido, erectile dysfunction, sub-fertility and more rarely hypogonadism (318, 320-324). Despite recent progress in understanding the role of adipose tissue in multiple neuro-endocrine networks, the exact pathogenetic mechanisms linking excess fat accumulation to HPG dysfunction have not been fully elucidated. As such, current research is focused on interactions between adipokines and the HPG (325), with leptin being the prototype adipokine which plays a vital role as a pleiotropic modulator of energy homeostasis and reproduction (318, 319, 326-331). Furthermore, increased metabolism of sex steroids within adipose tissue depots can lead to abnormal plasma levels of androgens and estrogens, thus, potentially affecting the reproductive axis in obesity (332-335). Sex hormone binding globulin (SHBG) is also implicated in obesity-related reproductive dysfunction by regulating the bio-availability of sex steroids (336). Patients with obesity tend to exhibit decreased circulating SHBG levels, with higher bio-available sex-steroid levels and increased sex-steroid clearance. This results from direct suppression of SHBG synthesis in the liver by insulin, which is apparently more potent in central obesity due to more pronounced insulin resistance and compensatory hyperinsulinemia (332-334, 337). Finally, it must be noted that a psychological component may also frequently be present, with reciprocal relationships between obesity and psychological comorbidities, especially anxiety and depression. This can significantly contribute to male and female impairment in sexual functioning, which may manifest as decreased sexual desire, lack of sexual activity enjoyment, difficulties in sexual performance and avoidance of sexual encounters (338-340).

 

Female Reproductive System and Obesity:

 

In 1952, Rogers et al. first published a study documenting the relation of obesity to menstrual abnormalities (341). Since then it has become evident that, a close link exists between body weight and reproductive health in females from menarche to menopause and beyond (Figure 10).

 

Figure 10. Hormonal Changes and Clinical Manifestations of Hypothalamic-Pituitary-Gonadal (HPG) Axis Dysfunction in Females with Obesity.

 

From an evolutionary perspective, menarche marks the beginning of the reproductive potential, which requires sufficient energy stores to facilitate pregnancy and lactation. Thus, it is not surprising that the onset of menstruation is closely related to the presence of a critical body fat mass (342-344). Of note, leptin links energy homeostasis to female reproductive function and appears to act as a metabolic gate to gonadotropin secretion, with minimum critical leptin levels and/or receptor signally being necessary to initiate and maintain the menstrual cycle (318, 319, 325, 328, 342, 345). Indeed, in female patients with anorexia nervosa low leptin levels are associated with amenorrhea and decreased LH and FSH, while regain of fat mass stimulates LH and FSH leading to resumption of menstrual function (345). Several epidemiological studies report a clear correlation between obesity and earlier puberty onset in girls with increased BMI (346-348). In Western societies, the age of pubertal maturation appears to be decreasing among girls in relation to increased prevalence rates of childhood and adolescent obesity (349, 350). However, this is often linked to decreased reproductive performance later in life and growing evidence suggests that weight gain can also lead to earlier ovarian failure and menopause (351, 352).

 

Menstrual disturbances are the most common manifestation of HPG dysfunction in women with obesity, extending from dysmenorrhea and dysfunctional uterine bleeding to amenorrhea (318, 323, 353, 354). The degree of clinical manifestations is reported to have a strong correlation with BMI and appears related to body fat distribution, since central obesity commonly leads to more severe symptoms (323, 324, 353-355). Abnormal menstrual patterns in women with obesity are primarily attributed to altered androgen, estrogen and progesterone levels (Figure 10), whilst weight loss can restore menstrual regularity, in part, by decreasing androgen aromatization to estrogens in adipose tissue depots (318, 353, 354). Women with obesity and polycystic ovary syndrome (PCOS) constitute a distinct category characterized by (i) polycystic ovaries; (ii) oligo- or anovulation; and (iii) clinical and/or biochemical signs of hyperandrogenism (2 out of 3 criteria according to the Rotterdam consensus for PCOS) (356). Notably, PCOS women with obesity exhibit higher risk of menstrual abnormalities compared to BMI matched women without PCOS, attributed to worse endocrine/metabolic profiles involving various degrees of hyperinsulinemia accompanying insulin resistance that lead to enhance ovarian-stimulated hyperandrogenism (134, 137, 357).

 

Female obesity is additionally associated with decreased fertility due to chronic anovulation (318, 324, 353, 354). Several studies have reported higher risk of anovulatory infertility with increasing BMI (358-362). Central fat distribution is considered to play a crucial role in this association through hyperinsulinemic hyperandrogenemia that disrupts ovulation, as also documented in PCOS (353, 354, 363). Interestingly, prehistoric statuettes that are presumed to be fertility idols, including the famous “Venus of Willendorf”, depict women with obesity characterized by pronounced buttocks and thighs (364, 365). Furthermore, obesity can also decrease the success rate of assisted conception methods such as in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) (366-371). Although additional data are still required, women with obesity appear to require higher doses of ovarian stimulation drugs and have increased risk of cycle cancellation and fewer oocytes collected, as well as lower pregnancy and live birth rates compared to normal-weight women (353, 354, 366, 371-375). Thus, weight loss (even modest weight loss of 5-10%) is advised for women with obesity that seek fertility treatment in order to increase the chances of a favorable outcome (376, 377). However, despite good evidence supporting the role of diet, physical activity/exercise, and behavior changes regarding optimal weight gain during pregnancy (378), there is clearly a need for further research into preconception weight loss interventions in order to study the effects of these interventions on key related outcomes (e.g. on live birth rates and the health of both the infant and the mother) and establish better evidence-based guidelines (321). Overall, pregnant women with obesity can be classified as having a high-risk pregnancy associated with increased rates of miscarriage, in addition to a spectrum of both maternal (e.g. gestational diabetes, hypertension and pre-eclampsia, urinary tract infections, thromboembolism, increased incidence of operative delivery, anesthetic risks and postpartum hemorrhage) and fetal (e.g. macrosomia, neural-tube defects and stillbirth) complications (379, 380).

 

Finally, obesity is also a risk factor for endometrial, postmenopausal breast and ovarian cancer (315, 316, 381-383). The higher risk of these hormone-sensitive gynecologic malignancies in women with obesity is attributed to elevated endogenous estrogen levels that persist even after menopause (adipose tissue consists the major source of postmenopausal estrogen production from androgens) (384, 385). Hyperinsulinemia appears to independently contribute to carcinogenesis, as will be reviewed in the following section of this chapter on obesity and cancer (384-386).

 

Male Reproductive System and Obesity:

 

Clinical manifestations of obesity-related HPG axis dysfunction exist also in men, although these appear to be less frequent compared to those in women (320, 323, 325). However, research has been focused mainly on the impact of obesity on the female reproductive health. Thus, it is plausible that the adverse effects of obesity on reproduction in men have been underestimated. Indeed, in recent years, following the increasing availability of assisted conception methods, a growing body of evidence indicates that obesity can significantly impair the male reproductive health, leading to decreased libido, erectile dysfunction, and sub-fertility/infertility (Figure 11) (318, 320, 323-325, 333, 351).

 

Figure 11. Hormonal Changes and Clinical Manifestations of Hypothalamic-Pituitary-Gonadal (HPG) Axis Dysfunction in Male Patients with Obesity.

 

Data on secular trends of pubertal maturation in boys and potential relationships to obesity are less clear and partly conflicting (346, 348-350, 387). As such, various studies have reported that increasing BMI and adiposity can be associated with either earlier or later pubertal onset in boys, while lack of correlation has also been documented (348, 387-391). Furthermore, assessing male puberty can be more subjective and unreliable due to lack of a landmark pubertal event similar to menarche in girls. Thus, further data are required to clarify the impact of childhood obesity on male sexual maturation.

 

Impaired male fertility is also associated with increasing BMI, especially in men with severe obesity when BMI exceeds 40 kg/m2 (318, 323, 324, 392-394). Semen quality can be significantly affected, and it is reported that both overweight and obese men exhibit markedly higher incidence of oligozoospermia and asthenospermia compared to normal-weight men (320, 323, 325, 392, 395-397). This is primarily attributed to decreased circulating testosterone levels due to higher aromatization of androgens to estrogens in adipose tissue depots, thus suppressing gonadotrohin levels; while SHBG levels can also be decreased (Figure 11) (333, 334, 337, 351, 398). In addition to hormonal changes, men with obesity are predisposed to elevated scrotal temperature, since the scrotum remains in close contact with surrounding tissues, which can potentially increase the risk of altered semen parameters and infertility (318, 323, 399). Finally, severe and longstanding obesity is associated with other comorbidities (e.g. T2DM and macrovascular disease), which further increase the risk of sexual dysfunction in men and can lead to sub-fertility.

 

In addition, both epidemiologic and mechanistic evidence indicates that there is an association between obesity and prostate cancer, although the data are relatively limited and have been inconsistent (315, 400-406). Large prospective studies link obesity with an increased risk of aggressive (high-grade) prostate cancer, while, on the other hand, obesity is inversely associated with indolent (low-grade) tumors (407-409). Of note, early data also suggest that obesity may be more closely linked to prostate cancer depending on race and molecular subtyping (e.g. in African American patients and in patients with TMPRSS2-ERG-positive tumors) (402). However, it must be highlighted that epidemiologic data on prostate cancer incidence should be interpreted with caution because men with obesity tend to have larger prostate size and lower circulating prostate-specific antigen (PSA) levels (lower PSA due to either lower androgen levels or hemodilution effects); parameters affecting the sensitivity and specificity of both prostate needle biopsy and PSA screening in this population (403-405, 410, 411). Interestingly, it has been reported that the accuracy of PSA in predicting prostate cancer did not change by BMI category in Asian men (411, 412). More consistently obesity has been associated with a higher risk of prostate cancer-specific mortality (401, 404, 405, 413). For the clinical practice, it has been suggested that men with obesity and prostate cancer should continue to be offered active surveillance as a management option, since their risk of competing mortality is higher compared to normal-weight men (402). Overall, the underlying pathophysiologic mechanisms for the associations between obesity and prostate cancer are considered multifactorial, including changes in androgen levels, increased circulating adipokines, hyperinsulinemia and the low-grade chronic inflammation state in obesity (403, 405, 406, 414).

 

Obesity, Stress and Psychiatric Co-Morbidities

 

A growing body of evidence indicates that common psychological disorders, such as depression, anxiety and chronic stress, constitute risk factors for developing obesity, metabolic syndrome manifestations, and CVD (415-419). Indeed, prospective data from the Whitehall II cohort documented that common mental disorders increase the risk of obesity in a dose-dependent manner (more episodes of the disorder correlated with higher future obesity risk) (420). Moreover, the odds of obesity in the presence of mental disorders tend to increase with age (421). As such, in a large community-based cohort of elderly persons that was followed for 5 years, baseline depression was associated with increased abdominal fat accumulation independent of overall obesity, suggesting pathogenetic links between depression and central obesity (422). In addition, existing evidence indicates that prolonged and/or intense stress can lead to subsequent weight gain. In the Hoorn Study, enhanced visceral adiposity and higher probability of previously undiagnosed T2DM were associated to the number of major stressful life events during a 5-year preceding period (423). Chronic work-related stress has also been identified as an independent predictive factor for general and central obesity during midlife (424, 425). Interestingly, weight gain in female UK students during their first year at university was related to higher levels of perceived stress (426).

 

On the other hand, epidemiologic data further support positive correlations between obesity and both depression and anxiety disorders risk (427, 428). These associations appear primarily concentrated among individuals with severe obesity and among females (429-434). The level of existing evidence on these associations is considered relatively moderate, since gender differences and multiple obesity-depression covariations (moderating/mediating factors) are probable, while a limited number of high-quality prospective studies have been published (435-439). However, the “jolly fat” hypothesis, associating obesity with decreased depression risk, should be revisited (440-443). Of note, a U-shaped quadratic relationship between BMI and depression can be proposed (444). In accord with epidemiologic data, there is also an increasing number of prospective, controlled studies reporting remission of depressive symptoms and improved psychological functioning following weight loss through bariatric procedures (445-450). Thus, reversibility is noted regarding adverse effects of obesity on mental health. Conversely, it must be also highlighted that depressive and anxiety disorders are shown to have strong predictive value for reduced weight loss in patients with obesity even when surgical interventions are applied (451).

 

Overall, obesity can be considered to hold a bi-directional association with psychological well-being, especially with chronic stress and mood disorders (416, 429, 435). This reciprocal relationship is complex and the underlying pathogenetic interplay has not been fully elucidated. Several mechanisms have been proposed to explain links between obesity and mental health in both directions, mainly focusing on over-activation of the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic nervous system (SNS), as well as on the role of health risk behaviors (Figure 12) (452-457).

 

Figure 12. Reciprocal Relations Between Obesity (Mainly Visceral) and Stress. Chronic stress, manifested with depressive and/or anxiety symptoms, can induce prolonged activation of the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic nervous system (SNS) which, together with health risk behaviors, can progressively lead to visceral obesity and vice versa (adopted from Kyrou et al. Curr Opin Pharmacol. 2009 (457)).

 

As aforementioned, particularly central obesity induces an unremitting low-grade inflammatory state that is characterized by high plasma levels of pro-inflammatory adipokines (131, 132). This adverse adipokine profile (decreased adiponectin and increased TNF-α, IL-6, and leptin levels) can act as a persistent stress stimulus, leading to chronic hypercortisolemia and SNS activation which predispose to depression and anxiety (454, 458). Conversely, chronic stress and depression, associated with mild hypercortisolemia and increased sympathoadrenal activity, favor visceral fat accumulation and obesity (e.g. favoring enhanced appetite, insulin resistance and increased adipogenesis) (459-463). Interestingly, sleep disorders (e.g. chronic insomnia, inadequate sleep or poor sleep quality) are also shown to exhibit associations with dysregulated energy balance, obesity and T2DM, mediated through SNS activation and changes in circulating adipokines (e.g. leptin, TNF-α and IL-6) and gut hormones (e.g. ghrelin, glucagon) (464-467). Thus, a deleterious vicious cycle appears to be formed, where weight gain causes prolonged stress system activation (manifested with depression and/or anxiety and/or sleep disorders) and vice versa, mediated through hormonal and adipokine effects on multiple endocrine axes and the central nervous system (457, 461, 462). Furthermore, obesity is associated with sedentary lifestyle and socioeconomic disadvantage which increase the risk of depression (468). In turn, over-nutrition, comfort eating, alcohol abuse, and low physical activity are common features of depression and anxiety disorders, promoting the development of obesity. Moreover, patients with obesity often experience obesity-related stigma and discrimination, which further contribute to clinical manifestations of depression and low self-esteem (427, 469). The aforementioned associations highlight the importance of assessing and treating psychiatric co-morbidity as part of weight management interventions (431, 451). In the context of a multidisciplinary approach, clinicians should also take into consideration that several widely prescribed antidepressants and antipsychotic agents can induce weight gain (e.g. tricyclic antidepressants, paroxetine, mirtazapine, monoamine oxidase inhibitors, lithium, clozapine, olanzapine, risperidone) (470, 471).

 

Obesity and Cancer Risk

 

Compelling evidence over the past years indicates that obesity and obesity-related diabetes are associated with higher incidence of certain types of cancer (315, 316, 472-484). Indeed, excess adiposity is now considered a key cancer risk factor, so that obesity and physical inactivity are currently recognized among the most important modifiable risk factors for primary cancer prevention, together with tobacco use (316, 484, 485). In 2016, a working group of the International Agency for Research on Cancer (IARC) reassessed the preventive effects of weight control on cancer risk, reviewing the existing epidemiological evidence, as well as mechanistic data and studies in experimental animal models (315, 316). The special report on the findings of this IARC working group concluded that there is sufficient evidence that excess body fatness causes cancer of the esophagus (adenocarcinoma), gastric cardia, colon and rectum, liver, gallbladder, pancreas, breast (postmenopausal), corpus uteri (endometrium), ovary, kidney (renal-cell), meningioma, thyroid, and multiple myeloma (315, 316) (Figure 13). Moreover, according to this IARC working group, currently there is limited evidence to support this link for male breast cancer, fatal prostate cancer, and diffuse large B-cell lymphoma, whilst inadequate relevant evidence exists for squamous-cell carcinoma of the esophagus, and cancer of the gastric noncardia, extrahepatic biliary tract, lung, skin (cutaneous melanoma), testis, urinary bladder, and brain or spinal cord (glioma) (Figure 13).

 

In accord with what is noted for the majority of obesity-related co-morbidities, central obesity is identified as an independent, at least in part, predictor of increased cancer risk. Waist circumference correlates primarily with cancer of the endometrium, breast, colon, pancreas and liver, suggesting pathogenetic links between visceral adiposity and carcinogenesis at these sites/organs (486-488). Overall, the risk of cancer in adults appears to increase when BMI exceeds 22 kg/m2, and, thus, there is a cancer prevention recommendation regarding body adiposity from the World Cancer Research Fund (WCRF) and the American Institute for Cancer Research (AICR) to stay as lean as possible within the normal BMI range (recommended public health goal for a median BMI between 21 and 23 kg/m2 in adults, depending on normal ranges for different ethnic populations) (489-491). Moreover, emphasis must also be placed on the increasing evidence supporting the impact of weight loss in reducing the obesity-related cancer risk (492-495). Of note, gender and ethnic differences appear to exist regarding the impact of obesity and weight gain on certain types of cancer. Thus, significantly stronger association is documented between BMI and colon cancer in males, whilst correlations between BMI and breast cancer risk appear more potent in the Asia-Pacific region compared to Europe, North America, and Australia (496, 497). Furthermore, the prospective, controlled Swedish Obese Subjects (SOS) study showed that bariatric surgery was associated with a reduction in the cancer incidence among women by 42%, while there was no effect on the cancer incidence among men (492, 494). In addition, the duration of obesity appears to be another significant parameter in the association between increased BMI and cancer risk, with data from the Women’s Health Initiative showing that a longer duration of overweight/obesity is associated with higher risk of developing several types of cancer (e.g. the risk of endometrial cancer increased by 17% for every 10-year increase in the duration of overweight in adulthood) (498). Accordingly, childhood obesity may also be associated with increased cancer risk and is suggested to have long-term consequences (e.g. increased risk of death from colon cancer), although further research is required to clarify the exact links between childhood obesity and different types of cancer (39, 499, 500).

 

Figure 13. Level of evidence regarding the cancer-preventive effect of the absence of excess body fatness according to cancer site/type, based on the special report of the 2016 working group of the International Agency for Research on Cancer (IARC).

[Adopted from: International Agency for Research on Cancer Handbook Working Group. N Engl J Med. 2016 Aug 25;375(8):794-8. (315)].

 

In general, overweight and obesity also constitute adverse prognostic factors among cancer survivors (individuals who are living with a diagnosis of cancer or have recovered from the disease), associated with worse survival rates and increased recurrence risk for several types of cancer (489-491). Indeed, existing evidence links increased BMI with recurrence and compromised survival in women with breast cancer (501, 502). Furthermore, data on colon cancer survival suggest that patients with obesity have greater overall mortality and shorter disease-free survival intervals, although more evidence is required (503-506). Finally, as aforementioned, obesity appears associated to higher prostate cancer-specific mortality and risk of aggressive prostate cancer (403-409, 413).

 

It is also interesting to note that, various studies have suggested an association between obesity and delayed cancer detection in clinical practice. This may be attributed either to weight-related barriers and patient delay (the period from first onset of symptoms to first medical consultation) or to greater difficulty in performing clinical examinations (e.g. examination of larger breasts in women with obesity or abdominal examination in central obesity) and diagnostic procedures (e.g. less accurate biopsy detection of prostate cancer in men with obesity due to larger size of the prostate) (404, 507-510). Furthermore, it is important to emphasize that the disease burden may be higher in patients with obesity and cancer due to increased risk for both cardiometabolic co-morbidity (e.g. T2DM and ischemic heart disease) and post-chemotherapy or postoperative complications.

 

In addition to environmental factors and genetic predisposition, multiple mechanisms have been proposed to explain the epidemiologic associations between obesity and cancer (511-514). Insulin resistance and chronic compensatory hyperinsulinemia appear to play a crucial role in the pathophysiology of obesity-related carcinogenesis, which may vary depending on the cancer type/site (Figure 14) (386, 483, 515-518).

 

Figure 14. Overview of Proposed Mechanisms that Link Obesity and Increased Cancer Risk.

 

Obesity, particularly central/visceral, causes insulin resistance and chronic compensatory hyperinsulinemia. Increased insulin levels have been shown to induce mitogenic effects and contribute to tumorigenesis through activation of both the insulin receptor and the insulin-like growth factor 1 (IGF-1) receptor.  Hyperinsulinemia can also suppress the synthesis of insulin-like growth factor binding protein 1 (IGFBP-1) in the liver and locally in other tissues, while is also associated with reduced plasma IGFBP-2. In turn, this decrease in IGFBP-1 and IGFBP-2 levels leads to increased bio-availability of IGF-1 which promotes cellular proliferation and inhibits apoptosis through its receptor in several tissues (386, 483, 515, 519, 520). Increased levels of estrogens and androgens are also considered to mediate carcinogenic effects, particularly for endometrial and post-menopausal breast cancers. Circulating SHBG levels are markedly decreased in patients with central obesity and hyperinsulinemia due to suppression of SHBG synthesis in the liver by insulin. Thus, higher free sex-steroid levels are present in the circulation increasing the risk for hormone-sensitive gynecologic malignancies (333, 334, 337, 515). Enhanced metabolism of sex steroids within adipose tissue depots can further contribute to increased plasma levels of androgens and estrogens in obesity (Figure 14) (332-334). Finally, existing evidence suggests that changes in circulating adipokines (e.g. hypoadiponectinemia and hyperleptinemia) and the chronic low-grade inflammatory state in obesity may also directly promote carcinogenesis (386, 483, 511-514, 517, 521).

 

 

The aforementioned co-morbidities are closely related to adipose tissue secretion of multiple adipokines, hormones and factors that induce deleterious autocrine, paracrine and endocrine effects. A second principal mechanism leading to obesity-related disease reflects increased physical burdens imposed by excess fat mass to various body sites (522). Indeed, enhanced local biomechanic stress due to accumulated fat and increased body weight (e.g. on the joints, respiratory tract, blood vessels or within the abdominal compartment) causes and/or exacerbates several co-morbidities which are common in patients with obesity, such as knee osteoarthritis, back pain, restrictive lung disease, obstructive sleep apnea, gastroesophageal reflux disease, hernias, and chronic venous insufficiency. Of note, even these complications are further aggravated by the adverse metabolic profile and chronic inflammatory state in obesity, amplifying the overall burden of the disease and creating a vicious cycle which can be effectively broken only by sustained weight loss.

 

Obesity and Osteoarthritis

 

Osteoarthritis (OA) is the most frequent joint disorder worldwide and one of the leading causes of chronic pain and disability in the adult population of Western societies, particularly among the elderly (523). Obesity is a major risk factor for knee OA, with available data indicating that weight gain can precede the disease onset by several years and that this increased risk begins as early as the third decade of life (524-530). Indeed, a systematic review by Blagojevic et al. reported obesity as one of the main factors consistently associated with knee OA (pooled odds ratio of 2.63, 95% CI: 2.28-3.05) (525). Moreover, a prospective population-based study in Finland with a follow-up of 22 years documented a strong association between BMI and risk of knee OA, with relative odds ratio of 7.0 (95% CI: 3.5-14.10; adjusted for age, gender and other covariates) for individuals with obesity compared to those with BMI less than 25 kg/m2 (531). Overall, the lifetime risk of symptomatic knee OA increases with increasing BMI and it is suggested that each additional BMI unit above 27 kg/m2 can lead to a 15% increase of this risk, with the association being more prominent in women compared to men and for bilateral than for unilateral disease (529, 530, 532-534).

 

Obesity appears to also increase the risk of hip and hand osteoarthritis, although these associations are less consistent (523, 535-540). Furthermore, excess body weight is an important predictor of progressive knee and hip OA with patients with obesity exhibiting higher risk for deteriorating disease and development of disability (522, 523, 529, 530). Of note, it has been shown that weight loss of approximately 5.1 kg over a 10-year period can reduce the odds of developing symptomatic knee OA by more than 50% (541). Functional disability in patients with obesity diagnosed with knee OA may also be improved with weight loss over 5% or at the rate of more than 0.25% per week within a 20 week-period (542). Finally, a growing body of evidence indicates that bariatric surgery may benefit patients with obesity and knee or hip OA, although further high-quality randomized studies assessing the impact of bariatric surgery and subsequent weight loss on these conditions are still required (543, 544).

 

The association of obesity with OA of weight-bearing joints is primarily attributed to repetitive over-loading during daily activities, which progressively causes cartilage destruction and damage to ligaments and other support structures (529, 530, 533, 545, 546). Abnormal gait, muscle weakness and alignment disorders may be further contributing factors for development of OA in patients with obesity. It is important to note that, increasing BMI is also associated with higher injury rates, including those related to falls, sprains/strains, joint dislocations and lower extremity fractures (547). In turn, joint injuries (e.g. meniscal ligament tears in the knee, fractures and dislocations) increase the risk of later developing OA in the injured joint (548). However, OA in non-weight-bearing joints (e.g. in the hand) and increased frequency of OA in women with obesity indicate that a metabolic/hormonal component may also link obesity to OA, in addition to biomechanic causes (549-551). Current evidence suggests that adverse hormonal and metabolic profiles in obesity (e.g. changes in leptin, adiponectin, TNF-α and IL-6, as well as hyperglycemia, lipid abnormalities and chronic inflammation) can play a role in the pathogenesis of OA. Indeed, increasing attention is now focused on the effects of leptin and the local dysregulation of adipokine production in osteoarthritic joints, while adipokines are also suggested as surrogate biomarkers for the severity of OA (529, 530, 533, 549-556).

 

Obesity and the Skin

 

Obesity is associated with several dermatologic conditions (557-562). Striae distensae (striae or stretch marks) is a common dermatosis in patients with obesity, representing linear atrophic plaques which are created due to tension and skin stretching from expanding fat deposits (557, 560, 561). Obesity-related striae are distributed primarily in the abdomen, breasts, buttocks, and thighs and pose more of a cosmetic problem. Clinically, these striae appear to be lighter, narrower, and less atrophic compared to striae in Cushing’s syndrome which are characterized by more intense (purple) color and inordinate breadth (> 1 cm) and depth. Acanthosis nigricans can be also noted in patients with obesity and hyperinsulinemia due to insulin resistance and is manifested with hyperpigmented, velvety, irregular plaques often in the folds of the back of the neck, axilla and groin, as well as on knuckles, extensor surfaces, and face (558, 560, 561). Skin tags are also commonly associated with hyperinsulinemia and acanthosis nigricans (557). Of note, women with obesity may also exhibit hirsutism and acne vulgaris as a result of both hyperandrogenism and hyperinsulinemia. Furthermore, weight gain is also associated with cellulite due to changes in the epidermis and dermis mostly in women and in areas such as the thighs, buttocks and abdomen. Due to excessive sweating and increased friction between skin surfaces, a number of skin infections are more frequent in obesity including oppositional intertrigo (inflammation-rash in body folds), candidiasis, candida folliculitis, folliculitis and less often cellulitis, erysipelas or fasciitis. Moreover, obesity is a risk factor for lower limb lymphedema, chronic venous insufficiency and stasis pigmentation, while wound healing tends to be slower in patients with obesity (557). Growing evidence also indicate that patients with obesity are at increased risk of inflammatory dermatoses, such as psoriasis (557, 560). Finally, although the currently available evidence has been regarded as inadequate by the 2016 IARC working group (315), there are data indicating the obesity may also be associated with increased risk of skin cancer (particularly malignant melanoma) (557, 560, 563).

 

Obesity and the Respiratory System

 

Increased body weight and fat accumulation in the abdomen and chest wall can have a significant impact on respiratory physiology leading to deterioration of pulmonary function, attributed primarily to increased mechanical pressure on the thoracic cage and trunk (564-567). Although the detrimental effects on conventional respiratory function tests are often modest until BMI exceeds 40 kg/m2, patients with obesity may exhibit reductions in lung volumes and respiratory compliance, as well as in respiratory efficiency (566-568). Severe obesity is associated with decreased total lung capacity (TLC), expiratory reserve volume (ERV) and functional residual capacity (FRC), as a result of mass loading, splinting and restricted decent of the diaphragm (564-568). Reduced FRC impairs the capacity to tolerate periods of apnea and represents the most consistently documented effect of obesity on respiratory function (568-570). Functional residual capacity can be reduced even in overweight individuals and declines exponentially with increasing BMI to the extent that it may approach residual volume (RV) (568, 570). On the other hand, RV is usually within the normal range in patients with obesity but can also be increased, suggesting concurrent obstructive airway disease and gas trapping (568-570). Forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) are also modestly affected in obesity and, thus, these spirometric variables frequently remain within normal limits in otherwise healthy adults and children with increased BMI (571, 572). However, both FEV1 and FVC exhibit a tendency to decrease with weight gain and improvements have been reported following weight loss (572-575). Longitudinal studies have aslo demonstrated an inverse association between BMI and FEV1 (576, 577). It is important to note that FEV1 is regarded as an independent predictor of all-cause mortality and a risk factor for CVD (e.g. ischemic heart disease and stroke) and lung cancer (578, 579). Furthermore, increasing BMI is related to an exponential decline in respiratory compliance, which is attributed primarily to reduced lung compliance due to increased pulmonary blood volume and to reductions in chest wall compliance due to local fat accumulation (580, 581). Decreased respiratory compliance is associated with FRC reductions and impaired gas exchange (569, 582). Conversely, total respiratory resistance is increased in severe obesity mainly due to increases in lung resistance (580, 581). These changes in respiratory compliance and resistance are more marked in the supine position and can affect the breathing pattern which becomes shallow and rapid. Overall, the work of breathing is enhanced and can lead to restricted maximum ventilatory capacity and respiratory muscle inefficiency with heightened demand for ventilation and relative hypoventilation during activity (566). The impact of obesity on respiratory function is generally greater in men compared to women, probably attributed to gender-related differences in fat distribution, highlighting the crucial role of central obesity (583-585). Indeed, indices of central/visceral adiposity are considered better predictors of respiratory function than body weight or BMI, whilst an inverse association exists between waist circumference and both FEV1 and FVC (585, 586). Data show that, on average, an increase in waist circumference of 1 cm is associated with reductions of 13 ml and 11 ml in FVC and FEV1, respectively, after adjustment for gender, age, height, weight and pack-years of smoking (585, 586). Adverse effects on the lungs caused by circulating adipokines and chronic inflammation in central obesity are also considered to mediate these heighten associations with respiratory dysfunction (567, 568).

 

Obesity is further associated with a spectrum of distinct respiratory conditions, including obstructive sleep apnea, obesity hypoventilation syndrome, asthma, and chronic obstructive pulmonary disease (564, 587-592).  Obstructive sleep apnea (OSA) is a prevalent respiratory disorder in the general population, and is shown to be particularly common in men and women with obesity (593). Obstructive sleep apnea is characterized by recurrent episodes of temporary airflow cessation (apnea) or reduction (hypopnea) during sleep, which are caused by total or partial upper airway collapse and result in decreased oxygen saturation (repeated episodes of hypoxemia and hypercapnia) (587, 594). Airflow is restored with arousal, thus disrupting the normal sleep pattern and adversely affecting sleep quality. Subsequently, OSA can lead to various clinical manifestations including snoring, choking episodes during sleep, nocturia, restless and un-refreshing sleep, daytime fatigue and hypersomnolence, impaired concentration, hypertension, decreased libido, irritability and personality changes, while it is also distinctly associated with increased incidence of motor vehicle accidents. Screening for OSA can be performed through validated questionnaires (e.g. the Epworth Sleepiness Scale and the Berlin Questionnaire) (587, 595, 596), and is particularly important for the clinical practice in patients with obesity and/or other obesity-related cardiometabolic disease (e.g. in patients with T2DM or PCOS) (597, 598), while the diagnosis of OSA relies on polysomnography which remains the “gold standard” diagnostic method (587, 595, 596). By consensus, an apnea is defined as airflow cessation for at least 10 seconds and is classified as obstructive or central based on presence or absence of respiratory effort, respectively (599). Accordingly an episode of hypopnea is defined based on the presence of either (i) reduced airflow by ≥30% from baseline for at least 10 seconds with ≥4% desaturation from baseline or (ii) reduced airflow by ≥50% for at least 10 seconds with ≥3% desaturation or an arousal (599). OSA severity is usually defined by the apnea-hypopnea index (AHI) which represents the number of apneas plus hypopneas per hour of documented sleep (mild OSA: AHI of 5 to 15; moderate OSA: AHI of more than 15 to 30; and severe OSA: AHI of more than 30 (600) However, it must be noted that AHI does not necessarily reflect the severity of clinical symptoms and use of other indices has also been suggested (e.g. based on hypoxemia) (601, 602). Of note, a long-term consequence of OSA is alterations in the central control of breathing, with episodes of central apnea due to progressive desensitization of respiratory centers to hypercapnia. These episodes are initially limited during sleep, but eventually can lead to the obesity-hypoventilation syndrome (Pickwickian syndrome), which is characterized by obesity, sleep disordered breathing, alveolar hypoventilation, chronic hypercapnia and hypoxia, hypersomnolence, right ventricular failure, and polycythemia (603).

 

Obstructive sleep apnea prevalence is increasing in Western societies and appears to be higher in men and among the elderly (593, 604). US data from the Wisconsin Sleep Cohort Study reported that the estimated population prevalence of OSA (AHI of 5 or more) in middle-aged men and women (30-60 years old) was 24% and 9%, respectively, with 4% of men and 2% of women also presenting daytime hypersomnolence (605). Obesity, especially central, is recognized as a major risk factor for OSA (587, 594, 604, 606, 607). Several studies have reported a consistent association between increased BMI and OSA risk, with an extremely high OSA incidence among subjects with severe obesity (55-100% in patients evaluated for bariatric surgery) (594, 608-610). Notably, a prospective population-based study documented that even moderate weight gain can increase the risk of OSA, with a 10% weight gain predicting a 6-fold (95% CI, 2.2-17.0) increase in the odds of developing moderate to severe sleep-disordered breathing, while a 10% weight loss predicted a 26% (95% CI, 18%-34%) decrease in the AHI (611). Neck circumference, reflecting central obesity and fat deposition around the upper airways, is regarded as a better predictor of OSA risk compared to body weight and BMI (612, 613). Indeed, it has been shown that neck circumference is associated with the severity of OSA independently of visceral obesity, especially in non-obese patients (614). Finally, available data also suggest that waist circumference can exhibit a stronger association with OSA risk compared to BMI, highlighting the role of upper body fat distribution in the pathophysiology of OSA (615).

 

Multiple mechanisms appear to mediate the association between obesity and OSA (587, 594, 606, 607). Existing evidence suggests both direct genetic contribution to OSA susceptibility, as well as indirect genetic contribution implicated through obesity, craniofacial structure features, regulation of sleep and circadian rhythms, and neurological control of upper airway muscles (616). Overall, contributing factors for development of sleep-disordered breathing include older age, male gender, anatomically narrow upper airways, increased tendency for upper airway collapse, and variations in neuromuscular control of upper airway muscles and in ventilatory control mechanisms (587). Cervical fat deposition in obesity with fat deposits in the lateral wall of the pharynx may decrease the caliber of the upper airways and increase their collapsibility, mainly due to increased thickness of the lateral pharyngeal muscle wall (617-619). Furthermore, in patients with obesity impairment of the upper airway dilator muscles has been also suggested, with data showing increased genioglossus fatigability (620). Abdominal fat accumulation also leads to decreased longitudinal upper airway tension and increased upper airway collapsibility due to the aforementioned changes in respiratory function and lung volumes (564-568). Chronic intermittent hypoxia in OSA appears to increase reactive oxygen species (ROS) production and oxidative stress (Figure 15). In addition, insulin resistance, circulating adipokines (e.g. leptin), pro-inflammatory cytokines (e.g. IL-6 and TNF-α), are also considered to further aggravate OSA, particularly in central obesity (594, 606, 621-624). Finally, research has been recently focused on the role of increased SNS activity, which is thought to result from chronic intermittent hypoxia and disruption of normal sleep patterns (sleep fragmentation and recurrent arousals), on insulin resistance and HTN.  In turn, insulin resistance promotes further central fat accumulation and CVD risk, which aggravate OSA, thereby forming a vicious cycle (625-627).

 

Figure 15. Potential mechanisms linking weight gain, insulin resistance, cardiovascular disease (CVD) and hypertension in patients with obesity and obstructive sleep apnea (OSA) (adopted from Arnarsdottir et al. Sleep 2009 (623)).

 

Sustained weight loss (e.g. by lifestyle modification with diet and exercise) can significantly reduce the AHI and improve the clinical manifestations of OSA (594, 628). Promising results have been also reported from studies exploring the impact of bariatric surgery on OSA (628), with meta-analysis data showing that up to 85% of OSA patients may exhibit remission and complete resolution of sleep-disordered breathing (629). However, it is important to note that although weight reduction improves OSA, patients with severe obesity undergoing bariatric surgery should not necessarily expect to be cured of OSA following weight loss. Indeed, another meta-analysis regarding the effect of bariatric-induced weight loss on measures of OSA demonstrated that the mean AHI after weight loss with bariatric procedures was consistent with moderately severe OSA (a pooled baseline AHI of 54.7 events per hour was reduced to a final value of 15.8 events per hour) (630). Nevertheless, a more recent systematic review performed to determine which of the common available bariatric procedures (i.e. Roux-en-Y gastric bypass, sleeve gastrectomy, gastric banding or biliopancreatic diversion) is the most effective for the treatment of OSA reported that all these procedures had significant beneficial effects on OSA (over 75% of the bariatric patients exhibited at least improvement), with biliopancreatic diversion being the most successful and gastric banding being the least successful in improving or resolving OSA (631). Interestingly, recurrence of OSA has been reported following initial improvements with weight loss even without concomitant weight regain (632). This can be attributed to variation in fat loss from different body sites with persisting fat deposition in the neck, and to other mechanisms which contribute to increased upper airway collapsibility independent of body weight (607).

 

In clinical practice, physicians should also be reminded that the link between OSA and obesity is bi-directional, with untreated OSA predisposing to weight gain and obesity. Short sleep duration predicts future obesity and newly diagnosed OSA patients often experience a history of recent weight gain in the period preceding the diagnosis (633, 634). Finally, a significant proportion of OSA patients remains undiagnosed and this potentially poses an additional risk to bariatric surgery candidates, since OSA appears associated with higher risk of adverse outcomes occurring within 30 days after surgery (e.g. death, deep-vein thrombosis or venous thromboembolism, reintervention with percutaneous, endoscopic or operative techniques and failure to be discharged from the hospital within 30 days after surgery) (609, 635-638). Of note, it has been reported that OSA screening prior to bariatric surgery identifies an additional 25% of patients as having OSA; although, in this study, unscreened patients with severe obesity did not exhibit an increased incidence of cardiopulmonary complications after surgery compared to screened patients (639). To address this point for the clinical practice, in 2016 a consensus meeting was held in Amsterdam that issued a consensus guideline that, based on the existing evidence, comprehensively addressed the issue of perioperative management of OSA in bariatric surgery (640).

 

Conclusion

 

In this chapter, we have discussed major disorders/diseases that are associated with obesity and are caused, at least in part, by adipose tissue accumulation. These include disturbances of glucose metabolism, manifestations of the metabolic syndrome, non-alcoholic fatty liver disease, gallbladder disease, osteoarthritis, obstructive sleep apnea, and various types of cancer, as well as unfavorable outcomes regarding reproduction, stress levels, and psychiatric disorders.

 

In clinical practice it should be noted that individuals with obesity often vary significantly regarding clinical manifestations of obesity-related morbidity, and it appears that patterns of lipid partitioning are a major determinant of their metabolic profile (65). Distribution of body fat plays an important role in this context (65, 641). As such, visceral accumulation of excess body fat is shown to be strongly associated with most of the obesity-related disorders including insulin resistance (642), and T2DM (643), as well as with all-cause mortality (644). On the other hand, increased subcutaneous fat depots can even have protective metabolic effects (645-647). Although not all previous studies have shown an independent effect of the subcutaneous abdominal fat on insulin sensitivity (646) and controversial findings have also been reported (648), data suggest that an expanded fat mass, particularly of subcutaneous adipose tissue, may function as a sink for glucose uptake and triglyceride accumulation resulting in compensatory improvement of insulin sensitivity (647). In agreement with this hypothesis, it has been shown that enabling a massive expansion of the subcutaneous adipose tissue mass in the ob/ob mouse model potently counteracts the development of insulin resistance associated with excess caloric intake (649). Importantly, evidence from rodent models of obesity and research into the genetic basis of human obesity have started to provide novel insight into the predisposition to weight gain and the pathophysiology of obesity-associated co-morbidity [rodent models of obesity and the genetics of obesity in humans will be reviewed in detail in the corresponding EndoText chapters].

 

In conclusion, obesity constitutes a complex, multifactorial disease associated with a wide spectrum of comorbidities due to both a deleterious endocrine/metabolic profile of the expanded/accumulated adipose tissue, and an increased physical burden imposed on various body sites/organs. Thus, even in cases of “metabolically healthy” obese individuals (presenting with a predominantly female type of fat distribution and absence of metabolic abnormalities) multiple other parameters and the risk of long-term adverse outcomes (e.g. risk of CVD, osteoarthritis, disability, psychological comorbidity) need to be seriously considered when discussing the benefits of various weight management interventions (28, 650, 651).

 

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Pheochromocytoma and Paraganglioma

ABSTRACT

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors arising from chromaffin cells of the adrenal medulla or neural crest progenitors located outside of the adrenal gland, respectively. These tumors are derived from either sympathetic tissue in the adrenal or extra-adrenal abdominal locations (sympathetic PPGLs) or from parasympathetic tissue in the thorax or head and neck (parasympathetic PPGLs). The clinical presentation is so variable that a PPGL has been described as "the great masquerader". The varied signs and symptoms of PPGLs are attributed to hemodynamic and metabolic actions of the catecholamines produced and secreted by these tumors. For a better understanding of clinical symptomatology of PPGLs, one needs to be aware of the tumor physiology, biochemistry, and molecular biology, which were discussed in detail in this chapter. While most PPGLs are benign, about 10% of pheochromocytomas and 25% of PGL are malignant. The newer targeted therapies for metastatic PPGLs are likely to be based on our understanding of tumor biology and the design of new highly specific compounds with fewer side effects. There has been an extensive research in the field of PPGLs in the last decade that shed light on genetic etiology and multiple possible metabolic pathways that lead to these tumors. In this article, we detail the current literature on diagnosis and management of PPGLs with a special focus on recent advancements in the field.  For complete coverage of this and related areas of eendocrinology, please see WWW.ENDOTEXT.ORG.

INTRODUCTION

Pheochromocytomas and paragangliomas (PPGLs) are highly vascular neuroendocrine tumors that arise from chromaffin cells of the adrenal medulla or their neural crest progenitors located outside of the adrenal gland, respectively1. PPGLs are estimated to occur in about 2–8 of 1 million persons per year and about 0.1% of hypertensive patients harbor a PPGL. About 10% of patients with PPGL present with adrenal incidentaloma2. Per 2017 – WHO classification of tumors (fourth edition), based on their location/origin, these neuroendocrine tumors are classified as tumors of the adrenal medulla and extra-adrenal paraganglia3. These tumors are derived either from sympathetic tissue in adrenal or extra-adrenal abdominal locations (sympathetic PPGLs) or from parasympathetic tissue in the thorax or head and neck (parasympathetic PPGLs)4. Sympathetic PPGLs frequently produce considerable amounts of catecholamines, and in approximately 80% of patients, they are found in the adrenal medulla1,4. Remaining 20% of these tumors are located outside of the adrenal glands, in the prevertebral and paravertebral sympathetic ganglia of the chest, abdomen, and pelvis. Extra-adrenal PPGLs in the abdomen most commonly arise from a collection of chromaffin tissue around the origin of the inferior mesenteric artery (the organ of Zuckerkandl) or aortic bifurcation. In contrast, most parasympathetic PPGLs are chromaffin-negative tumors mostly confining to the neck and at the base of the skull region along the glossopharyngeal and vagal nerves, and only 4% of these tumors secrete catecholamines4. These head and neck PGLs were formerly known as glomus tumor or carotid body tumors. Most PPGLs represent sporadic tumors and about 35% of PPGLs are of familial origin with about 20 known susceptibility genes making them most strongly hereditary amongst all human tumors5,6. Based on these genetic mutations and pathogenetic pathways, PPGLs can be classified into three broad clusters- cluster 1, cluster 2 and cluster 3. Cluster 1 includes mutations involving in overexpression of vascular endothelial growth factor (VEGF) (due to pseudohypoxia) and impaired DNA methylation leading to increased vascularization. Cluster 2 includes activating mutations of Wnt-signaling pathway (Wnt receptor signaling and Hedgehog signaling). This activation of Wnt and Hedgehog signaling is secondary to somatic mutations of CSDE1 (Cold shock domain containing E1) and MAML3 (Mastermind like transcriptional coactivator 3) genes7. Abnormal activation of kinase signaling pathways like PI3Kinase/AKT, RAS/RAF/ERK, and mTOR pathways account for cluster 3 mutations3,8. On the other hand, based on biochemical secretory patterns, PPGLs can be characterized into three different phenotypical categories – noradrenergic phenotype (predominant norepinephrine secreting), adrenergic phenotype (predominant epinephrine secreting) and dopamine secreting. These biochemical phenotypes of PPGL lead to a constellation of symptoms (based on the predominant hormone secreted) leading to different clinical manifestations.

CLINICAL FEATURES:

The clinical presentation is so variable that a PPGL has been termed as "the great masquerader". The varied signs and symptoms of PPGLs mainly reflect the hemodynamic and metabolic actions of the catecholamines produced and secreted by the tumors5,9. Although the presence of signs and symptoms of catecholamine excess remains the principal reason for initial suspicion of PPGLs, this does not imply that all PPGLs exhibit such manifestations. Increasing proportions of these tumors are now being discovered incidentally during imaging procedures for unrelated conditions or during routine periodic screening in patients with identified mutations that predispose to the tumor. In such patients, the clinical presentation may differ considerably (based on the biochemical phenotype) from those in whom the tumor is suspected based on signs and symptoms.

Hypertension is the most common sign and may be sustained or paroxysmal, with the latter more usual presentation occurring on a background of normal blood pressure or sustained hypertension. PPGL may also present with hypotension (excessive stimulation of beta adrenoreceptors by elevated levels of epinephrine), postural hypotension or alternating episodes of high and low blood pressure10. Headache occurs in up to 90% of patients with PPGL. In some patients’ catecholamine-induced headache may be similar to tension headache. Excessive, most commonly, truncal sweating occurs in approximately 60-70% patients. A typical sign of catecholamine excess is also pallor seen in approximately 27% of patients whereas only a few patients can present with flushing11. The presence of 3 Ps triad including headache (pain), palpitations and generalized inappropriate sweating (perspiration) in patients with hypertension should lead to immediate suspicion for a PPGL. Other common (but non-specific) complaints are severe anxiety, tremulousness, nausea, vomiting, weakness, fatigue, dyspnea, weight loss despite normal appetite (caused by catecholamine-induced glycogenolysis and lipolysis), visual problems during an attack and profound tiredness and polyuria most commonly experienced after an attack. Most patients also present with severe episodes of anxiety, nervousness, or panic attacks. Attacks (spells) of signs and symptoms may occur weekly, several times daily, or as infrequently as once every few months. Most last less than an hour, but rarely more than several days. Attacks may be precipitated by palpitation of the tumor, postural changes, exertion, anxiety, trauma, pain, ingestion of foods or beverages containing tyramine (certain cheeses, beers, and wines), use of certain drugs (histamine, glucagon, tyramine, phenothiazine, metoclopramide, adrenocorticotropic hormone), intubation, induction of anesthesia, chemotherapy, endoscopy, catheterization, and micturition or bladder distention (with bladder tumors). Less frequent clinical manifestations include fever of unknown origin (hypermetabolic state) and constipation12. Due to sustained hypertension secondary to 1- adrenoceptor mediated vasoconstriction, patients with noradrenergic phenotype can have hypertensive encephalopathy sometimes leading to ischemic attack/stroke, intestinal ischemia leading to intestinal necrosis followed by sepsis, renal failure, muscle necrosis and myoglobinuria13,14. In contrary, patients with adrenergic phenotype can present with hypotension resulting in tachycardia and even cardiogenic shock due to the vasodilatory effects of epinephrine, mediated through prominent β2-adrenoceptor overstimulation15,16. Patients with dopaminergic phenotype may have some very non-specific manifestations as described above in this section, e.g. nausea and vomiting (possibly due to some D2 receptor stimulation in brain), diarrhea (stimulation of D1 receptors in gut) and hypotension (due to vasodilatory effects of dopamine)17. Except for clinical signs and symptoms as described thus far, patients with malignant PPGL can, in up to 54% of cases, present with tumor related pain due to large primary tumors or due to metastatic lesions, most often bone metastases18.

Highly variable symptomatology in patients with PPGL may reflect variations in nature and types of catecholamines secreted, as well as co-secretion of neuropeptides: vasoactive intestinal peptide, corticotrophin, neuropeptide Y, atrial natriuretic factor, growth hormone-releasing factor; somatostatin, parathyroid hormone-related peptide, calcitonin, and adrenomedulin. The classic example is the PPGL with ectopic secretion of corticotrophin or corticotrophin-releasing factor, resulting in the presentation of Cushing’s syndrome19,20. PPGLs have also been described that secrete excessive amounts of vasoactive intestinal peptide, this resulting in presentation of watery diarrhea and hypokalemia21.

As described above, neglecting the secretory status of these tumors predisposes patients to serious and potentially life threatening cardiovascular complications due to catecholamine excess, including severe hypertension, acute myocardial infarction, cardiac arrhythmias, pulmonary edema, heart failure due to aseptic cardiomyopathy, and shock22.

DIAGNOSIS OF PPGLs:

The diagnosis is based on documentation of catecholamine excess by biochemical testing and localization of the tumor by imaging. Both are of equal importance, although the rule of endocrinology applies to the diagnostic algorithm of PPGL as well, making biochemical diagnosis as initial step followed by localizing studies. Moreover, biochemical analysis helps us in understanding the biochemical phenotype of the tumor so that further genetic and imaging studies can be tailored accordingly.

BIOCHEMICAL TESTING:

Missing a PPGL can have a detrimental outcome. Therefore, biochemical evaluation should include highly sensitive tests to safely exclude a PPGL. PPGLs can secrete all, none, or any combination of catecholamines (epinephrine, norepinephrine, dopamine) depending upon their biochemical phenotype. As the secretion of catecholamines from a PPGL is episodic; a single estimation of plasma or urinary epinephrine and norepinephrine most likely misses the biochemical diagnosis in about 30% of cases. In contrast, the metabolites of catecholamines (epinephrine is metabolized to metanephrine and norepinephrine is metabolized to normetanephrine) are constantly released into circulation23. This intra-tumoral process occurs independently of catecholamine release, which can occur intermittently or at low rates. In line with these concepts, numerous independent studies have confirmed that measurements of fractionated metanephrine (i.e. normetanephrine and metanephrine measured separately) in urine or plasma provide superior diagnostic sensitivity over measurement of the parent catecholamines24. Consequent to the above considerations, current US Endocrine Society guidelines recommend plasma free metanephrine or urinary fractionated metanephrine as initial screening tests25. These results, in addition to dopamine and plasma 3-methoxytyramine (3-MT as the dopamine metabolite), can be used to accurately establish the biochemical phenotype of a tumor26,27. A high diagnostic sensitivity for the detection of these tumors is achieved if blood measurements are collected in the supine position especially after an overnight fast and after a patient has been recumbent in a quiet room for at least 20 to 30 minutes before sampling28 . Fractionated urinary metanephrine, with measurement of urinary creatinine for verification of collection, can be used as alternative options especially in centers where supine blood sampling is not feasible. Caffeine, smoking, and alcohol intake as well as strenuous physical activity should be withheld for approximately 24 hours prior to testing to avoid false-positive results. Certain medications like tricyclic antidepressants, monoamine oxidase inhibitors can cause a false elevation in catecholamine and metanephrine levels11. A detailed list of medications that can interfere with testing is listed in Table 1. One should consider withholding these medications (only if patient’s clinical condition permits) that can lead to false-positive test results. A 3-4- fold increase in metanephrine levels above the upper limit of the age-adjusted reference is rarely a false-positive result, except when patients are on antidepressants. Metanephrine levels within the reference range typically exclude the tumors, while equivocal results (<3-4-fold above the upper limit) require additional tests if reference intervals are appropriately established and measurement methods are accurate and precise29,30. False-negative metanephrine could be observed in tumors that are smaller than 1 cm, dopamine-secreting head and neck tumors (recommend measuring 3-MT), or nonfunctional tumors5. Also, it is important to note that urine dopamine levels should never be used in the diagnostic work up as most of the dopamine present in mammalian urine is formed in renal cells, rendering this test unacceptable for evaluation of PPGLs27.

Table 1: Medications That Interfere With Testing of Fractionated Plasma or Urinary Metanephrines

Adapted from Hannah-Schmouni et al (11) with permission.

 

As the underlying genetic mutation leads to variable expression of biosynthetic enzymes (due to mutation-dependent differentiation of progenitor cells), there is a profound difference in the types and amount of catecholamines produced by these tumors31. Moreover, regulatory and constitutive secretory pathways, which are also genotype dependent, contribute to variations in the catecholamine content displayed by tumors31. Hence, greater understanding of the genetic background will allow physicians for further advancements in diagnostic approaches (and thus treatment options). Approaching genetic testing using an individual patients’ clinical presentation is considered cost-effective, timely and valuable for early and effective treatment of patients, especially with hereditary PPGLs. For a better understanding of tailoring of biochemical analysis based on the clinical presentation, we briefly describe biochemical phenotype correlations in this section. As described above in the section 1, PPGLs can be broadly classified into three biochemical phonotypes – noradrenergic, adrenergic and dopaminergic. Tumors can be classified to non-secretary type if they are not making any hormones (usually seen in parasympathetic PPGLs).

Noradrenergic Phenotype:

This phenotype comprises of PPGLs that predominantly produce norepinephrine and are therefore characterized by elevated norepinephrine and normetanephrine levels32. PPGLs of cluster 1 (pseudohypoxia-related tumors) belong to this biochemical phenotype. A typical noradrenergic phenotype is suggestive of mutations in the tumor suppressor von Hippel-Lindau (VHL) in VHL syndrome, succinate dehydrogenase (SDH) type A, B, C, or D, fumarate hydratase (FH), malate dehydrogenase type 2 (MDH2), and endothelial pas domain protein 1 (also known as hypoxia-inducible factor type 2A) (EPAS1/HIF2A) genes. Genetic mutations of SDHAF2 are also included in this cluster though there is limited evidence exists on their biochemical nature (Table 2). Krebs cycle (SDHx, FH, MDH2) and hypoxia signaling pathway (VHL, HIF2A, PHD1, PHD2) PGL-related gene mutations cause HIF-2α stabilization, promoting chromaffin/paraganglionic cell tumorigenesis33. A summary of the clinical characteristics of patients with each genetic mutation is presented in Table 2. Patients with elevated normetanephrine levels (and/or normal 3-methoxytyramine levels) should undergo genetic screening for mutations in the above-mentioned genes, especially if other syndromic features are absent. The location of PPGLs with the noradrenergic phenotype is typically extra-adrenal; however, they may also be limited only to the adrenal glands, especially in the VHL syndrome. They also often present as multifocal, recurrent, or metastatic.

 

Table 2: Genotype-biochemical phenotype correlation of PPGLs

Adapted from Gupta et al (5) with permission.

 

Adrenergic Phenotype:

PPGLs predominantly secreting metanephrines are included in this phenotype. PPGLs of cluster 2 (kinase signaling-related tumors) belong to this biochemical phenotype. These tumors are usually well differentiated, and contain phenylethanol-N-methyltransferase (PNMT) enzyme that regulates the conversion of norepinephrine to epinephrine. The enzymatic activity is typically located in adrenal medulla and so location of a tumor with this phenotype is typically adrenal, however, they may also be seen in extra-adrenal locations, especially in TMEM127 mutation34. Patients presenting with predominantly elevated levels of metanephrine should usually undergo genetic screening for RET and NF1 mutations first5,32. Nevertheless, most often patients with these mutations are usually first diagnosed based on other syndromic features of the disease and may only require biochemical and genetic testing to confirm the suspicion. Genetic screening for TMEM127 may be considered for adrenergic PPGLs once mutations in NF1 and RET are ruled out35. Other mutation that can be considered under this category is MAX mutation, which is intermediate between the adrenergic and noradrenergic phenotype and hence, targeted genetic screening for this gene may be considered in cases of adrenal PPGLs when other susceptibility genes have been ruled out36.

Dopaminergic Phenotype:

PPGLs that predominantly secrete dopamine with or without mild increase in norepinephrine (normetanephrine) are classified under the dopaminergic phenotype. The dopaminergic phenotype is common with head and neck PPGLs (carotid body tumors), though adrenal tumors have also been reported37. The dopamine produced by these tumors is metabolized to 3-MT and so increased 3-MT levels are of an important diagnostic value, especially in cases with normal dopamine levels38. The dopaminergic phenotype is typically seen in metastatic disease, especially related to SDHB and SDHD mutations, though there are a few case reports of the dopaminergic phenotype in NF1, VHL, and MEN2A. The common presence of the dopaminergic phenotype in metastatic disease may be attributed to proliferation of poorly differentiated progenitor cells leading to decrease dopamine decarboxylase activity.

LOCALIZATION STUDIES:

Tumor localization should usually only be initiated once the clinical evidence and a biochemical proof of a PPGL is established. In patients with a hereditary predisposition, a previous history of a PPGL, or other PPGL syndromic presentations where the pre-test probability of a PPGL is relatively high, less-compelling biochemical evidence might justify the use of imaging studies. Imaging also plays a key role in a screening process for patients with genetic predispositions to PPGL development. For carrier screening, along with biochemical evaluations, a CT or MRI is often recommended every few years to detect tumors in early stages, if at all. Adding whole-body imaging is particularly important for SDH mutation carriers, as these tumors are sometimes missed by only biochemical evaluations39.

Either computed tomography (CT) or magnetic resonance imaging (MRI) are recommended for initial PPGL localization (more than 95% of PPGLs are found)1,40. Compared to MRI, CT has a better spatial resolution and hence used as first choice imaging modality. Though both CT and MRI have equal sensitivity in localizing PPGLs, use of T2-weighted MRI imaging is recommended especially in patients with metastatic PPGL, for detection of skull base and neck PGLs, patients with surgical clips, in patients with an allergy to CT contrast and for patients in whom radiation exposure should be limited (children, pregnant women, patients with known germline mutations, and those with recent excessive radiation exposure).

On CT, adrenal pheochromocytomas typically have a heterogeneous appearance, often with some cystic areas. Depending upon the composition of PPGL, calcifications and/or hemorrhage may be seen. On dual-phase contrast-enhanced CT, pheochromocytomas can also be distinguished from other adrenal masses due to higher intensity during the arterial phase, with enhancement levels greater than 10 HU (usually more than 20 HU is diagnostic) and washout less than 50% at the end of 10 minutes (it is important to note that adrenal cancers also have limited washout)41. However, in case of high fat content, adrenal pheochromocytoma may also resemble adrenal adenomas. If the adrenal PPGL is less than 3 cm and the patient is younger than 40 years and has no family history of PPGL, no further imaging workup needs to be performed before proceeding to definitive management42. On T2-weighted MRI, adrenal pheochromocytoma typically appear as bright lesions (compared to that of liver), although cystic or necrotic components may affect this classic appearance. If imaging of the adrenal glands is normal, imaging of additional areas of the body should be performed. Imaging should be completed of the abdomen, followed by the pelvis, chest, and neck and extremities should be included in case of metastatic disease (to evaluate for bone metastasis).

Although CT and MRI have almost equal and excellent sensitivity for detecting most PPGLs, these anatomical imaging approaches lack the specificity required to unequivocally identify a mass as a PPGL. The higher specificity of functional imaging modalities offers an approach that overcomes the limitations of anatomical imaging, providing justification for the coupling of the two approaches. Upon CT or MRI lesion confirmation, a patient’s biochemical phenotype, tumor size, family history, syndromic presentation, and metastatic potential plays a key role to determine the need of functional imaging. The patients with a single, epinephrine or metanephrine secreting adrenal tumor that is less than 5 cm, will most likely not benefit from additional functional imaging, since these tumors are almost always confined to the adrenal gland and present with a small likelihood of metastases, even if hereditary component is present43. On the contrary, functional imaging is necessary for lesions that secrete norepinephrine or normetanephrine and are larger than 5 cm, or associated with a hereditary tumor syndrome (as these characters determine the metastatic potential). Functional imaging also allows determination of the extent of disease, including the presence of multiple tumors or metastases, information that can be important for appropriately guiding subsequent management and treatment44.

Historically, functional imaging has been performed with 123I- or 131I-metaiodobenzylguanidine (MIBG) scintigraphy. Though 123I-MIBG SPECT has high sensitivity for detection of adrenal pheochromocytoma, it has unacceptably low sensitivity for the detection of extra-adrenal PGLs (56% to 75%) and metastases, especially in the presence of SDHx mutations45. Moreover, certain medications, such as opioids, tricyclic antidepressants, and anti-hypertensives like labetalol, can also affect MIBG uptake, leading to less intense or false-negative scans. Nonetheless, 123I-MIBG is useful to identify patients with metastatic PPGL because MIBG avid lesions indicate that these patients may benefit from treatment with therapeutic doses of 131I-MIBG. Given the low sensitivity of MIBG imaging, US Endocrine Society Guidelines recommend using 18F-FDG PET scan as a preferred modality of functional imaging in patients with metastatic disease25. However, many recent studies have shown that metastatic lesions were missed on 18F-FDG PET scan46,47. As PPGLs express somatostatin receptors (SSTRs), imaging modalities based on SSTR (DOTA peptides, particularly 68GaDOTA(0)-Tyr(3)-octreotate (68Ga-DOTATATE) are emerging as gold standard functional tests.

The first functional imaging specific to neuroendocrine tumors, including PPGLs developed was 18F-fluorodopa (18F-FDOPA), an amino acid analog and catecholamine precursor that is taken up by the amino acid transporter. Initially lower sensitivity was now improved by inhibiting DOPA decarboxylase by pretreatment with carbidopa, which enhances the tracer uptake by the tumor48. From all PPGLs, 18F-FDOPA PET is extremely sensitive for patients with head and neck PGLs, sometimes identifying small tumors missed by all other imaging techniques. This technique also appears to be particularly effective for patients with SDH mutations or biochemically silent PHEO/PGL or both and may be valuable as a screening technique, particularly for patients with SDHD mutations. 18F-fluorodopamine (18F-FDA), which is similar to dopamine and taken up by norepinephrine transporters. 18F-FDA PET is another PPGL specific tracer that offers excellent diagnostic sensitivity and spatial resolution, and appears particularly useful for localization of some primary and metastatic PPGLs, but this imaging modality is not use often these days since it has been surpassed by 68Ga-DOTATATE and 18F-FDOPA PET. A prospective study demonstrated the superiority of 68Ga-DOTATATE in a cluster of 22 patients, in which DOATATE could localize 97.6% metastatic lesions whereas 18F-FDG PET/CT, 18F-FDOPA PET/CT, 18F-FDA PET/CT, and CT/MRI showed detection rates of 49.2 %, 74.8 %, 77.7 %, and 81.6 % respectively (p<0.01)49. King et al50 and recently Janssen et al46 reported that 18F-FDOPA as well as 68Ga-DOTATATE PET are equally good in the localization of head and neck SDHx-related and non-hereditary PPGLs. However, a recent prospective analysis by Archier et al51 concluded that 68Ga-DOTATATE is superior to 18F-FDOPA in localizing small head and neck PPGLs especially caused by SDHD mutation making it a preferred modality of imaging in head and neck PPGLs. On the contrary, the study showed that small adrenal pheochromocytomas (usually seen with MEN2 and NF1 syndromes) are better detected with 18F-FDOPA51. This might be secondary to high physiological uptake of 68Ga-DOTATATE in adrenal gland, compared to 18F-FDOPA. Table 3 summarizes the current proposed PET radiopharmaceuticals for PPGL imaging according to genetic background52.

Table 3: Current proposed PET radiopharmaceuticals for PPGL imaging based on genetic background

Adapted from Taïeb et al (52) with permission.

 

MALIGNANT PPGL

While most PPGLs are benign, about 10% of pheochromocytomas and 25% of PGL are malignant. The prediction of malignant behavior of PPGL is not straight-forward and is often challenging. Several markers (Ki-67 index, expression of heat-shock protein 90, activator of transcription3, pS100 staining, increased expression of angiogenesis genes, and N-terminal truncated splice isoform of carboxypeptidase E)53-57 and a scoring system (pheochromocytoma of adrenal gland scaled score)58 were developed, which were later found to have suboptimal correlation to malignant behavior showing that these techniques may not be sufficient for distinguishing between benign and malignant tumors and that larger studies including various hereditary and non-hereditary PPGLs are definitely needed to confirm some initial findings59.  Having said that, several independent risk factors for metastatic disease were established, including the presence of SDHB mutations, extra-adrenal location, size of primary tumor > 5 cm (in SDHB-related PPGLs over 3.5 cm), younger age of initial diagnosis of PPGL and elevated 3-MT levels18,49,60-63.

PPGL typically metastasize to lungs, liver, bones, and lymph nodes and patients with metastatic disease suffer from diminished quality of life due to localized pain caused due to metastasis, consequences of catecholamine excess and of course, treatment side effects64. Though bone metastases are thought be less aggressive with a better survival (compared to non-skeletal metastases), they are associated with complications not limiting to bone pain, spinal cord compression, bone fractures, and hypercalcemia65. Irrespective of site of metastases, the 5-year overall survival for malignant PPGL is about 60%63.

MANAGEMENT OF PPGLs:

The definitive treatment of PPGL is surgical excision of the tumor. Laparoscopic surgery is commonly the technique of first choice for resection adrenal and extra-adrenal PPGLs when oncologic principles can be followed66. Exposure to high levels of circulating catecholamines during surgery may cause hypertensive crises and arrhythmias, which can occur even when patients are preoperatively normotensive and asymptomatic. All patients with PPGL should therefore receive appropriate preoperative medical management to block the effects of released catecholamines25. Hence, it is of utmost importance that preparation of the patient for surgery requires adequate preoperative medical treatment to minimize operative and postoperative complications. Exceptions to this rule include endocrine emergencies like necrotic PPGL leading to severe hypotension, other surgical emergencies67 or the tumors that secrete high amounts of dopamine or epinephrine.

Pre-Operative Medical Management (Blockade):

As described above, once diagnosed with PPGL, patients should be placed on antihypertensive medications, preferentially a- followed by b-adrenoceptor blockade1. Table 4 summarizes the list of available drugs and suggested doses. The first choice should be an α-adrenoceptor blocker.  A b-adrenoceptor blocker may be used for preoperative control of arrhythmias, tachycardia or angina. However, loss of b-adrenergic-mediated vasodilatation in a patient with unopposed catecholamine-induced vasoconstriction via a-adrenoceptors can result in dangerous increases in blood pressure sometimes hypertensive crisis. Therefore, b-adrenoceptor blockers usually should not be employed without first blocking α-adrenergic mediated vasoconstriction. Labetalol (more potent b than a antagonistic activities with a:b of 1:5) should not be used as the initial therapy because it can result in paradoxical hypertension due to its high affinity to b-adrenoceptors. Phenoxybenzamine, a long-acting α-adrenoceptor blocker is commonly preferred drug in patients who have elevated blood pressures. Short acting α-adrenoceptor blockers like prazosin, terazosin, and doxazosin are used when phenoxybenzamine is not available or when not available or when a patient's hypertension is not severe enough to warrant the use of a long-acting α-adrenoceptor blocker68. As there is a high chance that these medications can cause orthostatic hypotension, they should be started at night68. The doses should be titrated to achieve normo-tension or mild tolerable hypotension. The patients should also be advised to maintain adequate water and salt intake to maintain adequate intravascular volume. Calcium channel blockers (CCBs) can be added if a goal blood pressure control is not achieved with adequate α- and β-adrenoceptor blockade. CCBs can also be used as initial agents of choice in patients who have normo-tension/mild hypertension, and/or who could not tolerate α-blocker due to hypotension (usually seen in PPGLs that secrete dopamine predominantly). Patients with non-secreting head and neck tumors with normal blood pressure may not be placed on pre-procedural blockade69.

Table 4: Medications used for symptom management and preoperative blockade for PPGLs

Adapted from Martucci et al (42) with permission.

 

In patients who did not achieve adequate blood pressure control despite being on optimized doses of α- and β-adrenoceptor blockade, metyrosine (competitive inhibitor of tyrosine hydroxylase) can be added to prevent catecholamine synthesis. Metyrosine acts by decreasing the catecholamine synthesis and its main side effects include depression, anxiety, and sleepiness due to its effects on central nervous system (as it can cause blood brain barrier)69.

In some patients’, blood pressure can reach very high values and such a situation is termed a hypertensive crisis when it is life-threatening or compromises vital organ function. The hypertensive crises are the result of a rapid and marked release of catecholamines from the tumor. Patients may experience hypertensive crises in different ways. Some report severe headaches or diaphoresis, while others have visual disturbances, palpitations, encephalopathy, acute myocardial infarction, congestive heart failure, or cerebrovascular accidents. Therefore, it is crucial to start proper antihypertensive therapy immediately. Treatment of a hypertensive crisis due to PPGL should be based on administration of phentolamine. It is usually given as an intravenous bolus of 2.5 mg to 5 mg at 1 mg/min. If necessary, phentolamine’s short half-time allows this dose to be repeated every 5 minutes until hypertension is adequately controlled. Phentolamine can also be given as a continuous infusion (100 mg of phentolamine in 500 mL of 5% dextrose in water) with an infusion rate adjusted to the patient’s blood pressure during continuous blood pressure monitoring. Alternatively, control of blood pressure may be achieved by a continuous infusion of sodium nitroprusside (preparation similar to phentolamine) at 0.5 to 10.0 µg/kg per minute (stop if no results are seen after 10 minutes)69.

Certain medications are to be avoided in patients with PPGLs. Effects of some drugs are more obvious due to their mechanism of action, such as dopamine D2 receptor antagonist metoclopramide. More recently, peptide and corticosteroid hormones, including corticotropin, glucagon and glucocorticoids (intravenous) have been shown to have adverse reactions in this patient population. Other classes of drugs contraindicated in patients with PPGL are tricyclic anti-depressants, anti-depressants that are serotonin or norepinephrine reuptake inhibitors like Cymbalta and Effexor. Displacement of catecholamines from storage can have devastating sequelae. Many drugs for obesity management fall in this category such as phentermine (Adipex, Fastin and Zantryl), phendimetrazine (Bontril, Adipost, Plegine), sibutramine (Meridia), methamphetamine (Desoxyn) and phenylethylamine (Fenphedra). Other over the counter medications such as nasal decongestants containing ephedrine, pseudoephedrine, or phenylproanolamine can also lead to drug interference.

1.1 SURGERY:

As described earlier, surgical resection is the treatment of choice. The risks of operative mortality are extremely low if performed by an experienced surgical team including a skilled anesthesiologist to monitor for intra-operative hypertensive crises69. Laparoscopic procedure is the preferred technique when feasible and has similar outcomes as open-surgery. Surgery can also be used as a curative treatment for recurrent, or limited metastatic tumors; it can also be used as a debulking technique for patients with extensive metastatic disease to reduce symptoms and imminent complications from tumor size. However, the long-term benefits of debulking procedures for patients with metastatic disease may be limited70.

Post-Operative Management:

Although a few patients suffer from hypotension in the immediate post-operative period, most require treatment, which is best remedied by administration of fluids. Hypoglycemia in the period immediately after tumor removal is another problem that is best prevented by infusion of 5% dextrose started immediately after tumor removal and continuing for several hours thereafter. Post-operative hypoglycemia is transient, whereas low blood pressure and orthostatic hypotension may persist for up to a day or more after surgery and require care with assumption of sitting or upright posture42.

The long-term prognosis of patients after operation for PPGL is excellent, although nearly 50% may remain hypertensive after surgery. Biochemical testing should be repeated after about 14-28 days from surgery to check for remnant disease. Importantly, normal postoperative biochemical test results do not exclude remaining microscopic disease so that patients should not be misinformed that they are cured and that no further follow-up is necessary. On long-term follow-up, about 17% of tumors recur, with about half of these showing signs of malignancy. Although follow-up is especially important for patients identified with mutations of disease-causing genes, there is currently no method based on pathological examination of a resected tumor to rule out potential for malignancy or recurrence. Thus, long-term periodic follow-up is recommended for all cases of PPGL5,42.

Radiofrequency Ablation (Rfa), External Beam Radiation And Radiotherapy:

RFA, external radiation and radiotherapy with 131I-MIBG therapy can be used in patients with metastatic disease in whom surgery may not be feasible. RFA has been successfully used in liver and bone metastases71,72. External beam radiation is a common treatment modality in patients with inoperable head and neck paragangliomas73. Radiation therapy with gamma knife, or cyber knife have begun to replace traditional external-beam radiation for glomus jugulare tumors, owing to their more precise targeting of radiation and increased dose capability74. For patients with a positive MIBG uptake, therapy with 131I MIBG can be a valuable treatment modality. It is important to note that the patients should be taken off medications (labetalol, tricyclic antidepressants, and certain calcium antagonists) that can block MIBG uptake by the tumors. In some patients, radiotherapy targeting somatostatin receptors (DOTA peptides (DOTATATE, DOTATOC, and DOTANOC), radio labeled with lutetium (177Lu), yttrium (90Y), orindium (111In) has been successfully used and is currently an emerging modality of therapy for metastatic inoperable PPGLs75-78.

Chemotherapy And Molecular Targeted Therapies:

Traditional chemo-therapy with cyclophosphamide, vincristine, and dacarbazine (CVD) has been used most extensively with progressive and widely metastatic PPGLs79,80. CVD chemotherapy is usually well tolerated for long periods, with and increased time between the doses can be tried in patients who develop toxicities. Clinicians using the chemotherapy, should be aware of potentially fatal complications arising from excessive catecholamine release as tumor cells are destroyed (usually within the first 24 hours) and patient should be closely monitored, preferentially in intensive care unit, especially in patients who have extensive disease and high baseline catecholamine levels. Experience with other chemotherapy agents such as temozolomide; streptozotocin with other agents; ifosfamide; cyclophosphamide and methotrexate; cisplatin and 5-flurouracil is limited to case reports81,82. Molecular targeted therapies such as sunitinib (tyrosine kinase inhibitor) and everolimus (mTOR inhibitor) have been tried with mixed results83-85. As we gradually progress in understanding the pathophysiology of PPGLs, newer modalities of targeted therapies can be explored (e.g., HIF pathway and mTOR pathway antagonists)33,86.

 

TAKE HOME POINTS:

  1. PPGLs are neural crest-derived tumors, and currently more than 40% have a known genetic cause. Thus, all patients with PPGLs should be considered for genetic testing. Recently new syndromes were described associated with these tumors: Carney-Stratakis and Pacak-Zhuang syndromes.
  2. Genetic testing should be based on several considerations: syndromic features, family history, age at diagnosis, multifocal and metastatic presentation, tumor location, and a specific biochemical phenotype.
  3. PPGLs are tumors that are mainly diagnosed based on the measurement of plasma or urinary metanephrine and 3-MT since 30% of these tumors do not secrete catecholamines.
  4. Patients with metastatic disease should undergo appropriate genetic testing based on the biochemical profile and tumor location.
  5. Computed tomography (CT) is the first-choice imaging modality. Magnetic resonance imaging (MRI) is recommended in patients with metastatic PPGL, for detection of skull base and neck PGLs, in patients with surgical clips that cause artifacts when using CT, in patients with an allergy to CT contrast, and in patients in whom radiation exposure should be limited (children, pregnant women, patients with known germline mutations and those with recent excessive radiation exposure).
  6. 18F-FDOPA or 68Ga DOTATATE scanning is preferred functional modality in patients with primary solitary or metastatic disease.
  7. 123I-MIBG scintigraphy as a functional imaging modality in patients with metastatic PPGL detected by other imaging modalities when radiotherapy using 131I-MIBG is planned.
  8. All patients with a hormonally functional PPGL should undergo preoperative blockade with α-adrenoceptor blockers followed by β-adrenoceptor blockade as the first choice to prevent perioperative cardiovascular complications for 7-14 days.
  9. Minimally invasive adrenalectomy is recommended for most adrenal PPGLs and open resection for large or invasive PPGLs to ensure complete resection and avoid local recurrence.
  10. Multidisciplinary teams at centers with appropriate expertise to ensure favorable outcome should treat all patients with PPGL.

 

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The Genetics of Obesity in Humans

ABSTRACT

 

Over the past twenty years a growing number of genes have been described in which loss of function mutations are consistently associated with the development of severe obesity beginning in early childhood.  Whilst individually these disorders are rare, cumulatively at least 10% of children with severe obesity have rare chromosomal abnormalities, nonsense mutations, or missense mutations that strongly drive the carrier’s risk of becoming obese.  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 some cases, the finding of a genetic cause for a patient’s obesity can lead to specific therapeutic interventions.

 

INTRODUCTION

 

The rising prevalence of obesity is driven by an increase in the intake of easily available, energy-dense highly palatable foods and a decrease in energy expenditure at school/work and in leisure time.  However, there is considerable variation in body weight and fat mass between individuals within a population.  Estimates of the heritability (the proportion of the phenotypic variance of a trait that is attributable to genetic variation) of body mass index (BMI: weight in kg/height in meters squared) range between 40% and 70%, suggesting that this variation in BMI is largely influenced by genetic factors (1, 2).  The findings from twin, family, and adoption studies are supported by recent studies in twins born after the recent increase in the prevalence of obesity, which have estimated the heritability of BMI at 77% (3).  Whilst the influence on body weight of the shared environment cannot be distinguished from the genetic contribution in most studies, comparable estimates of heritability have been derived from studies of adopted children, whose weights correlate better with that of their biological parents than with that of their adoptive parents (4).  Genetic factors may modulate the response to changes in energy intake as evidenced by classical overfeeding studies in monozygotic twins, which showed that the amount of weight gained was similar between members of a twin pair but differed across sets of identical twins (5).

 

COMMON OBESITY ASSOCIATED VARIANTS IDENTIFIED BY GENOME WIDE ASSOCIATION STUDIES  

        

Different approaches have been used to identify genetic factors that contribute to the heritability of increased BMI and obesity.  One such approach involves Genome-wide association studies (GWAS’s), which examine thousands of common genetic variants spanning the genome, often in large population-based cohorts in whom BMI data is available (6).  Altogether, GWAS analyses of BMI levels as a continuous quantitative trait or of obesity as a categorical variable have led to the discovery of over 200 associated loci (7, 8).  These common variants uncovered in GWAS’s are characterized by modest effect sizes (per-allele odds ratios between 1.1. and 1.5), and the proportion of total variability explained by GWAS-identified loci to date remains relatively modest.  Many of the genes within these loci are expressed in the brain and some have been shown to modulate body weight in experimental studies in animals (9).  Importantly, gene burden scores for obesity risk alleles are significantly associated with validated childhood eating behaviour scores for satiety and food responsiveness, which themselves predict obesity, reinforcing the conclusion that most of these genes are exerting their obesogenic effects through the brain and the control of food intake (10).

 

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 at least 10% of children with severe obesity have chromosomal abnormalities or other penetrant rare variants that drive their obesity (11).  The assessment of severely obese children and adults should be directed at screening for endocrine, neurological, and genetic disorders (12).  Useful information can be obtained from a detailed family history to identify potential consanguineous relationships, the presence of other family members with severe obesity or who have had bariatric surgery, and the ethnic origin of family members.  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.

 

OBESITY SYNDROMES WITHOUT DEVELOPMENTAL DELAY     

 

Some genetic obesity syndromes are associated with learning difficulties and clinical disorders which mean that children come to medical attention at a young age.  However, there is a large and increasing group of genetic disorders where severe obesity itself is the presenting feature.  Severe obesity can result from a multiplicity of defects involving the leptin-melanocortin pathway.

 

Briefly, leptin is an adipocyte-derived hormone whose circulating levels correlate closely with fat mass (13). Its clearest role is to defend against starvation (14).  A fall in leptin levels (as seen in weight loss, acute caloric restriction or congenital leptin deficiency) leads to a set of physiological responses that act to restore energy homeostasis by driving an increase in energy intake and a reduction in daily energy expenditure (15).

 

Many of the physiological effects of leptin are mediated through the long isoform of the leptin receptor, which is widely expressed in the hypothalamus and other brain regions involved in energy homeostasis (16).  Leptin stimulates the expression of pro-opiomelanocortin (POMC) in primary neurons located in the arcuate nucleus of the hypothalamus.  POMC is extensively post-translationally modified to generate the melanocortin peptides, which activate the melanocortin receptors to modulate diverse functions in the central nervous system, adrenal glands, and skin.  In the hypothalamus, activation of the melanocortin receptors suppresses food intake.  In addition, leptin inhibits orexigenic pathways mediated by neurons expressing the melanocortin antagonist, Agouti-related protein, and neuropeptide Y (NPY); in turn, NPY has been shown to suppress the expression of POMC.  These two sets of primary leptin-responsive neurons project to second-order neurons expressing the melanocortin 4 receptor (MC4R).  Targeted genetic disruption of MC4R in mice leads to not only increased food intake and adiposity, but also increased lean mass and linear growth (17).  These hypothalamic pathways interact with other brain centres to coordinate appetite control with modulation of efferent signals in peripheral organs regulating intermediary metabolism and energy expenditure.

 

Leptin and Leptin Receptor Deficiency

 

Congenital leptin (LEP) and leptin receptor (LEPR) deficiency are rare, autosomal recessive disorders associated with severe obesity from a very young age (before 2 years) (18, 19).  Homozygous frameshift, nonsense, and missense mutations involving LEP and LEPR have been identified in 1% and 2-3% of severely obese patients from consanguineous families, respectively (20-22).  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 is highly suggestive of a diagnosis of congenital leptin deficiency.  Very rare mutations that result in a detectable but bio-inactive form of leptin have also been described (23).  Serum leptin concentrations are appropriate for the degree of obesity in leptin receptor deficient patients and as such an elevated serum leptin concentration is not necessarily a predictor of leptin receptor deficiency (21).  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 (18).

 

The clinical phenotypes associated with congenital leptin and leptin receptor deficiencies are similar. Patients are born of normal birth weight but exhibit rapid weight gain in the first few months of life resulting in severe obesity.  Affected subjects are characterized by intense hyperphagia with food seeking behaviour and aggression when food is denied (20).  While measurable changes in resting metabolic rate or total energy expenditure have not been demonstrated, abnormalities of sympathetic nerve function suggest that defects in substrate utilisation may contribute to the phenotype observed (24).  Children with leptin deficiency have profound abnormalities of T cell number and function (20), consistent with high rates of childhood infection and a high reported rate of childhood mortality from infection (24).

 

Patients are hyperinsulinemic consistent with the severity of obesity and some adults develop type 2 diabetes in the 3rd to 4th decade.  Leptin and leptin receptor deficiency are associated with hypothalamic (secondary) hypothyroidism characterized by low free thyroxine levels and inappropriately normal or high-normal levels of serum thyroid stimulating hormone (TSH) (18, 19).  Typically, normal pubertal development does not occur in adults with leptin or leptin receptor deficiency, with biochemical evidence of hypogonadotropic hypogonadism.  However, there is some evidence for the delayed but spontaneous onset of menses in a small number of leptin and leptin receptor deficient adults (18-20). 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 that result in beneficial effects on hyperphagia, fat mass and hyperinsulinemia, reversal of the immune defects, and permissive effects on the development of puberty (20, 25).  Such treatment is currently available to patients on a compassionate-use or individual patient basis.

 

The major effect of leptin administration is on food intake, with normalization of hyperphagia and enhanced satiety.  Leptin is also involved in mediating food reward.  In the leptin-deficient state, images of food (compared to non-food images) were associated with a marked increase in neuronal activation in the ventral striatum an area associated with pleasure and reward, visualised using functional MRI (26).  This response was normalized after seven days of leptin treatment.  On the other hand, leptin administration does not result in a change in energy expenditure.  However, given that weight loss by caloric restriction is associated with an adaptive decrease in basal and daily energy expenditure, the absence of this adaptive thermogenic response is notable as demonstrated in obese volunteers in whom  the fall in energy expenditure seen after 10% weight loss is blunted by the administration of leptin (27).

 

Leptin administration also permits progression of appropriately-timed pubertal development, suggesting that leptin is a permissive factor for the development of puberty in humans (20).  In adults with leptin deficiency, leptin induced the development of secondary sexual characteristics and pulsatile gonadotrophin secretion (24).  Leptin may exert these effects on the reproductive system through a number of molecules including kisspeptin, which signals through GPR54, to modify the release of gonadotrophin-releasing hormone.

 

Pro-opiomelanocortin Deficiency

 

Leptin suppresses food intake in part by acting on hypothalamic neurons expressing POMC.  People who are homozygous or compound heterozygous for loss of function mutations in the pro-opiomelanocortin gene, POMC, are hyperphagic and develop early-onset obesity due to loss of melanocortin signalling at the MC4R in the hypothalamus (28).  The clinical features are comparable to those reported in patients with mutations in the receptor for POMC-derived ligands, MC4R (see below).  In the pituitary, POMC is the precursor for adrenocorticotrophin (ACTH).  As such, POMC deficiency presents in neonatal life with findings of secondary adrenal insufficiency:  hypoglycaemia, cholestatic jaundice, or other features of adrenal crisis requiring long-term corticosteroid replacement therapy (29).  Such children have pale skin, and white Caucasians have red hair, due to the lack of melanocortin function at melanocortin 1 receptors in the skin (28).  POMC deficiency may also impair the central control of reproduction through mechanisms that are as yet unclear.  Children from different ethnic backgrounds may have a less obvious phenotype such as dark hair with red roots.  A number of heterozygous point mutations affecting POMC peptides and POMC processing have been described (30).  These variants significantly increase obesity risk but are not invariably associated with obesity.

 

The marked weight loss seen in adults with POMC deficiency studied in a recent trial of a selective melanocortin receptor agonist (setmelanotide) holds considerable promise for the treatment of this group of patients in the future (31).

 

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 hypoglycaemia due to impaired processing of proinsulin to insulin as well as severe, early onset obesity (32, 33).  Elevated plasma levels of proinsulin and 32/33 split proinsulin in the context of low levels of mature insulin provide the basis for a diagnostic test for this disorder.

 

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).  The prevalence of pathogenic MC4R mutations varies from 0.5 -2.5% of people with a BMI > 30 kg/m2 in UK and European populations to 5% in patients with severe childhood obesity (34, 35).  As MC4R deficiency is the most common genetic form of obesity (35, 36), assessment of the sequence of the MC4R is increasingly seen as a necessary part of the clinical evaluation of the severely obese child.

 

Given the large number of potential influences on body weight, it is perhaps not surprising that both genetic and environmental modifiers have important effects on the severity of obesity associated with MC4R mutations in some pedigrees.  Taking account of all of these observations, co-dominance, with modulation of expressivity and penetrance of the phenotype, is the most appropriate descriptor for the mode of inheritance.

 

The clinical features of MC4R deficiency include hyperphagia, which often starts 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, thus they often appear “big-boned” (35).  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 (37).  Despite this early hyperinsulinemia, obese adult subjects who are heterozygous for mutations in the MC4R gene have a comparable risk of developing impaired glucose intolerance and type 2 diabetes compared to controls of similar age and adiposity.

 

Further studies have established that MC4R plays a role in fat oxidation and nutrient partitioning.  These effects are also seen in rodents and appear to be mainly mediated by the sympathetic nervous system.  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 (38).  Thus, central melanocortin signalling 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 Roux-en-Y-bypass surgery, which can be considered in adults (39).  As most patients are heterozygotes with one functional allele intact, it is possible that small molecule MC4R agonists (36) or pharmacological chaperones which improve receptor trafficking to the cell surface, might become appropriate treatments for this disorder.

 

Albright’s Hereditary Osteodystrophy

 

Albright hereditary osteodystrophy (AHO) is an autosomal dominant disorder due to germline mutations in GNAS1, an imprinted gene that encodes the G alpha s protein that mediates signalling by multiple G-protein coupled receptors (GPCRs).  Classically, heterozygous loss-of-function mutations in GNAS lead to AHO, a disorder characterized by short stature, obesity, skeletal defects, and impaired olfaction.  Maternal transmission of GNAS1 mutations leads to AHO plus resistance to several hormones (e.g., parathyroid hormone) that activate Gs in their target tissues (pseudohypoparathyroidism type IA), while paternal transmission leads only to the AHO phenotype (pseudopseudohypoparathyroidism) (40).  Studies in both mice and humans demonstrate that GNAS1 is imprinted in a tissue-specific manner, being expressed primarily from the maternal allele in some tissues and biallelically expressed in most other tissues.  Thus, multi-hormone resistance occurs only when Gs (alpha) mutations are inherited maternally.  Recent studies have suggested that rare variants in GNAS may lead to obesity without short stature and some of the other clinical features associated with AHO (11), suggesting that this diagnosis should be considered in a broader group of patients with severe early-onset obesity.

 

SRC Homology 2B (SH2B1) 1 Deficiency

 

Deletion of a 220-kb segment of 16p11.2 is associated with highly penetrant familial severe early-onset obesity and severe insulin resistance (41).  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) signalling.  These patients gain weight in the first years of life, with hyperphagia and fasting plasma insulin levels that are disproportionately elevated compared to age- and obesity-matched controls.  Loss of function mutations in the SH2B1 gene have also been reported in association with early-onset obesity, severe insulin resistance, and behavioural abnormalities in some patients (42).

 

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.  The clinical features of Prader-Willi syndrome (PWS) include diminished fetal activity, hypotonia in infancy, obesity, mental retardation, short stature, hypogonadotropic hypogonadism, and small hands and feet. Diagnostic criteria arrived at by a consensus group refer to five major criteria, such as feeding problems and failure to thrive in infancy and seven minor criteria, such as hypopigmentation, which can be added together to give a score used to make a clinical diagnosis of PWS.

 

Chromosomal abnormalities are principally responsible for PWS either through deletion of an imprinted region on the paternal chromosome 15q11.2-q12 or through loss of the entire paternal chromosome 15 with presence of 2 maternal homologues (uniparental maternal disomy).  Maternal deletion of the same imprinted region (or paternal uniparental disomy), causes another characteristic phenotype known as Angelman syndrome.  Within the 4.5Mb PWS region in 15q11-q13, where there is a lack of expression of paternally imprinted genes, several candidate genes have been studied and their expression shown to be absent in the brains of PWS patients.  These transcripts include SNURF-SNRPN and multiple small nucleolar RNAs (snoRNAs), in particular the HBII-85 snoRNAs. Small deletions encompassing only this family of snoRNAs have been reported in association with the cardinal features of PWS including obesity (43, 44), suggesting that these noncoding sequences may play a critical role in the development of this syndrome.

 

Some features of PWS distinguish this diagnosis from other genetic obesity syndromes.  There is mild prenatal growth retardation with a mean birth weight of about 6 lbs (2.8 kg) at term, hyporeflexia and poor feeding in neonatal life due to diminished swallowing and sucking reflexes; infants often require assisted feeding for about 3 to 4 months.  Feeding difficulties generally improve by the age of 6 months.  From 12 to 18 months onward, uncontrollable hyperphagia becomes a dominant feature resulting in severe obesity (45). One suggested mediator of the obesity phenotype in PWS patients is the stomach-derived hormone ghrelin, which is implicated in the regulation of meal-time hunger in rodents and humans and is a potent stimulator of growth hormone secretion.  Fasting total plasma ghrelin levels are 4.5-fold higher in PWS patients than in equally obese patients without PWS and patients with other genetic obesity syndromes (46).  However suppression of ghrelin with octreotide appears to have no impact on the hyperphagia seen in adults with Prader Willi syndrome (47).  As such, the clinical relevance of this finding has not as yet been established.  Additionally, histopathological studies on post-mortem brain samples from PWS patients have demonstrated reduced levels of oxytocin expression in the hypothalamus (48) and trials of intranasal administration in PWS are ongoing (49).

 

Children with Prader-Willi syndrome (PWS) display diminished growth, reduced lean body mass and increased fat mass, body composition abnormalities which can be explained in part by growth hormone (GH) deficiency.  Growth hormone treatment in these children decreases body fat and increases linear growth, lean mass, fat oxidation, and energy expenditure.  These improvements are most dramatic during the first year of GH therapy, although prolonged treatment does not completely normalize these parameters.

 

Bardet Biedl Syndrome

 

Bardet-Biedl syndrome (BBS) is a rare (prevalence <1/100,000), autosomal recessive disease characterized by obesity, mental retardation, dysphormic extremities (syndactyly, brachydactyly or polydactyly), retinal dystrophy or pigmentary retinopathy, hypogonadism, and structural abnormalities of the kidney or functional renal impairment (50). The differential diagnosis includes Biemond syndrome II (iris coloboma, hypogenitalism, obesity, polydactyly, and mental retardation) and Alstrom syndrome (retinitis pigmentosa, obesity, diabetes mellitus and deafness).

 

Bardet-Biedl syndrome is a genetically heterogeneous disorder with multiple genes identified to date.  Although BBS is usually transmitted as a recessive disorder, some families have exhibited tri-allelic inheritance where clinical manifestation of the syndrome requires two mutations in one BBS gene plus an additional mutation in a second, unlinked BBS gene. To date, BBS proteins are all involved in basal body and centrosomal function and impact on ciliary development and transport (51).

 

 

Brain-derived neurotrophic factor (BDNF) is one of several nerve growth factors which activate signalling by the tyrosine kinase receptor tropomycin-related kinase B (TrkB), which may lie distal to MC4R signalling.  Rare chromosomal rearrangements and heterozygous point mutations in BDNF and TrkB are associated with speech and language delay, hyperphagia and impaired pain sensation (52-54).  Disordered behaviours including hyperactivity, fearlessness, anxiety, and aggression are also features of these disorders, which can often present as de-novo genetic abnormalities.

 

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 cause severe obesity (55-57).  Clinical features of these patients resemble those seen in MC4R deficiency with, in addition, a variable phenotype of developmental delay with some autistic like features noted in some, but not all, patients.

 

Carboxypeptidase E

 

Later steps of prohormone processing (see above under PCSK1 deficiency) are undertaken by a range of carboxy and amino peptidases, one of which, carboxypeptidase E (CPE), has long been known to cause obesity when disrupted in mice. The first human homozygous nonsense mutation in CPE was recently reported.  In addition to obesity and hypogonadism, the affected proband showed severe developmental delay suggesting a broader role for CPE in CNS development and function (58).

 

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, where the persistence of severe obesity despite medical advice has been considered a reason to invoke parental neglect, the making of a genetic diagnosis has prevented children from being taken into care by social services. 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 regarding the use of bariatric surgery (feasible in some, high risk in others). Importantly, some genetic obesity syndromes are treatable.

 

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