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Drugs that Affect Body Weight, Body Fat Distribution, and Metabolism

ABSTRACT

 

Weight gain or body fat redistribution are common side effects of many widely used drugs. Weight gain amounts varying between a few kg to an increase of 10% or more of initial body weight have been described. Often accompanying this weight gain are worsened health risks, including an increased incidence of the metabolic syndrome, type 2 diabetes, and other cardiovascular risk factors. With many drug classes, such as β-receptor antagonists, anti-psychotic drugs, corticosteroids, neurotropic drugs, and those used in the therapy of HIV, both significant weight gain and metabolic disturbances occur in susceptible patients.  In this review, we provide an overview of drugs that affect body weight, fat distribution, and metabolism. Attention is given to the possible pathogenic mechanisms underlying these effects and their metabolic consequences. Potential preventive, alternative, or therapeutic measures are suggested where applicable. For complete coverage of all related areas of Endocrinology, please visit our on-line FREE web-text, WWW.ENDOTEXT.ORG.

INTRODUCTION

 

Many widely used drugs cause weight gain that—especially in susceptible individuals—may lead to patients becoming overweight or obese. Other drugs predominately influence body fat redistribution through increases in central adiposity, including visceral fat accumulation, and/or subcutaneous fat atrophy (lipodystrophy). Accompanying these changes are increases in insulin resistance, dyslipidemia, metabolic syndrome, and risk for type 2 diabetes (T2DM), non-alcoholic steatohepatitis (NASH), cardiovascular disease, cancer, and even increased mortality. These body weight and metabolic side-effects warrant close monitoring and potentially additional therapies to minimize their health impact, thereby increasing medical costs and contributing to non-compliance, which risks worsening of the underlying condition.

 

Weight gain is consistently associated with many older agents for the treatment of diabetes and with neuropsychotropic medications, including atypical antipsychotics, antidepressants, and antiepileptic drugs (1). For other drug classes, e.g. β-blocking agents, data are less consistent or well-studied. Glucocorticoids are associated with weight gain and lipodystrophy, as are retroviral agents used in the therapy of human immunodeficiency virus (HIV). Also, drugs used to manage lipid disorders, such as MTTP inhibitors and anti-sense apo-B oligonucleotides, are associated with changes in body fat distribution, especially liver lipid accumulation.  Unfortunately, the mechanisms behind these effects on body weight and fat distribution are often poorly understood, which hampers identification of high-risk patients for prevention, development of lower risk-drugs, and possible treatments (2).

 

In this chapter, drugs affecting body weight, fat distribution, and glucometabolic outcomes will be reviewed, as well as the possible mechanisms contributing to these side effects. Recent studies will be highlighted that have been undertaken to identify predictors of weight gain and metabolic complications, and where possible, options for prevention and therapy will be discussed.

 

DRUGS ASSOCIATED WITH WEIGHT GAIN     

 

Medications for Diabetes

 

Insulin, sulfonylurea (SU), and thiazolidinediones (TZD) are medications used in the management of diabetes that may cause substantial weight gain when compared to placebo (1). Metformin and Dipeptidyl Peptidase-4 (DPP-4) inhibitors are considered to be weight neutral, whereas sodium glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 (GLP-1) receptor analogues (GLP1RA) are associated with weight loss on average (3).

 

INSULIN AND SULFONYLUREAS

 

Insulin causes weight gain by multiple mechanisms (4). Sulfonylureas cause weight gain by increasing endogenous insulin levels. Appetite stimulation, sometimes triggered by hypoglycemia and fluctuating glycemia, is probably the most important factor in body fat increase. Defensive snacking in order to prevent hypoglycemia or compensate for it, can be observed in some patients. Poor glycemic control increases metabolic rate and consequently, improving glycemic control decreases metabolism. Improving metabolic control also reduces glycosuria and retention of otherwise lost calories. Finally, the anabolic effects of insulin can increase protein synthesis and inhibit lipolysis and proteolysis, resulting in a gain of lean body mass (3,4).

 

The weight promoting properties of insulin are dose dependent and are more pronounced in injection regiments that include rapid-acting insulin compared to basal insulin only (5). The addition of metformin to insulin therapy, reduces the effects of insulin on body weight by decreasing energy intake (6).

 

The weight gain by sulfonylurea is most pronounced in the first months of therapy and then reaches a plateau. In the UKPDS and ADOPT studies a mean weight gain of this therapeutic class is approximately 4 kg during the first year of treatment (7,8).

 

THIAZOLIDINEDIONES

 

Thiazolidinediones also cause a substantial time and dose-dependent weight gain ranging from 1.5 to 4 kg in the first year of treatment (1,9). The mechanisms by which TZD’s cause weight gain include fluid retention, promotion of lipid storage, and adipogenesis through activation of peroxisome proliferator-activator receptor gamma (PPARg) (10,11). The fat accumulation is almost uniquely subcutaneous, with stable or even decreasing amounts of visceral fat (12). Thiazolidinediones also improve hepatic steatosis and inflammation in patients with non-alcoholic steatohepatitis (NASH), although safety concerns including osteoporosis and fluid retention with pioglitazone hamper their use (11,13). Newer PPAR drugs for the treatment of NASH are currently being studied in phase 3 trials (14).

 

Antihypertensive Drugs

 

Hypertension frequently accompanies obesity and T2DM. Therefore, drugs that promote weight gain and other metabolic side effects are of obvious concern in patients with obesity and hypertension (15).

 

BETA-BLOCKERS      

 

The propensity of β-blockers to cause weight gain has been known for years (16). Their use is associated with a mean weight gain of 1.2 kg compared to controls, although among β-blockers, variable effects on weight, ranging from no significant change to an increase of 4 kg or more after one year of treatment, have been described. Most weight gain occurs in the first few months, after which no further weight gain is apparent (16).

 

Mechanisms whereby β-receptor antagonists are thought to affect body weight include reductions in total energy expenditure through lowering of basal metabolic rate and thermogenic response to meals, and by inhibition of lipolysis in response to adrenergic stimulation (17). In addition, β-receptor antagonists can promote fatigue and reductions in patient activity (18-20). Polymorphisms in human genes involved in catecholamine signal transduction affecting fat cell lipolysis might partly explain individual susceptibility to β-receptor antagonist-induced weight gain (21). β-blockers may also selectively promote the accumulation of abdominal fat, which is more sensitive to catecholamines than peripheral fat (22). This preponderance of abdominal fat accumulation may be, in part, responsible for the abnormalities related to carbohydrate and lipid metabolism associated with β-adrenergic blockade (23).

 

Several large trials have linked β-receptor antagonists to dysglycemia and new onset diabetes, even without significant weight gain (24). In particular, non-vasodilating beta-blockers (atenolol, metoprolol and propranolol) are associated with a worsening of glycemic and lipid parameters. In contrast, vasodilating beta-blockers (nebivolol, labetolol and carvedilol) have more favorable effects on glucose and lipid profiles (25). Nebivolol has been shown to induce lipolysis, reduce adipocyte lipid droplet size, and promote thermogenic and mitochondrial genes through a β3 adrenergic receptor affect (26). Therefore, selective agents with a vasodilating component such as nebivolol and carvedilol should be prioritized when β-blockers are needed in a population with high risk for metabolic side effects (15).

 

CALCIUM CHANNEL BLOCKERS

 

Calcium channel blockers are considered weight neutral and do not show adverse effects on glucose and/or lipid metabolism. However, flunarizine, a calcium channel blocker used in the prophylaxis of migraine, is associated with increased appetite and weight gain up to 4 kg. These properties have been linked to its blocking effects on both the calcium channel receptor and the dopamine receptor (27,28).

 

Psychotropic Medications

 

Obesity is two to three times more common among patients with psychiatric disorders than the general population, and individuals who are obese suffer more frequently from psychiatric illnesses than those who are normal weight. Underlying causes of this interaction between obesity and psychiatric disease likely include a clustering of adverse metabolic risk behaviors, such as unhealthy eating and insufficient physical activity, as well as substance abuse that accompany many psychiatric conditions (29). But the pathophysiological neural processes that lead to psychiatric diseases also seem to share common brain pathways with those that lead to unwanted weight gain, obesity, metabolic syndrome, and cardiovascular disease risk factors, each of which can influence the risk for the others (30). Mounting evidence points to a critical role for two major pathways: inflammatory processes including related alterations of brain functions and chronic stimulation of the hypothalamic-pituitary-adrenal (HPA) axis (30,31).

 

Psychiatric disorders are often characterized by a chronic stimulation of the HPA axis and sustained cortisol elevation, which have been linked with abdominal obesity, hepatic steatosis, insulin resistance, and cardiovascular disease (31). Chronic psychosocial stress has also been linked with inflammation and metabolic alterations, including weight gain with a predominance of visceral fat accumulation and insulin resistance (30). On the other hand, increased adiposity leads to chronic low-grade activation of inflammatory processes, which have been shown to have a potent role in the pathophysiological brain alterations associated with psychiatric disease (31). It is therefore possible that adiposity-driven inflammation contributes to the development of mood disorders and their growing prevalence worldwide.

 

Medical therapies for depression, mood disorders, and other psychiatric illnesses have been associated with sometimes very large weight gain (Table 1). Epidemiologic data show a positive correlation between weight gain and the time exposed to psychotropic medication or the number of different psychotropic drugs used (32). However, the variation in mean weight gain is large between the different drug classes and even within the same class. For most psychiatric treatments, no correlation is found with weight gain and original diagnosis or severity of the underlying psychiatric condition, treatment outcome, weight at the onset of the disease or treatment, age, or sex, which impedes prediction of those patients who will or will not have metabolic side effects (32). What has been consistently shown is that weight gain in the first month after the start of treatment is a strong predictor of long-term weight gain (33). Therefore, weight should be monitored before and shortly after starting a psychotropic drug therapy and a 5% increase above baseline weight after the first month should prompt physicians to reconsider therapeutic options or to initiate weight-controlling strategies (33,34).

 

Table 1. Overview of the Psychotropic Drugs and Their Mean Effect on Weight.  (See text for abbreviation definitions).

Drug class

 

Weight loss

Weight neutral

(< 1 kg/y)

Minor weight gain

(1-5 kg/y)

Major weight gain

(> 5 kg/y)

Antidepressants

 

Tricyclic agents

 

 

amitriptylline

nortriptylline

imipramine

desipramine

dosulepine

doxepine

clomipramine

 

SSRI

 

escitalopram

paroxetine

citalopram

fluoxetine

sertraline

 

 

SNRI

 

duloxetin

venlafaxin

 

 

MAO-inhibitors

 

moclobemide

phenelzine

 

Other

bupropion

reboxetine

trazodone

nefazodone

mirtazapine

maprotiline

mianserine

 

Antipsychotics

Typical

molindone

 

haloperidol

perphenazine

 

 

Atypical

 

aripiprazol

ziprasidone

lurasidone

paliperidone

iloperidone

asenapine

amisulpiride

quietiapine

risperidone

sertindole

 

clozapine

olanzapine

Anticonvulsants

 

topiramate

zonisamide

lamotrigine

levtiracetam

Tiagabine

oxcarbazepine

gabapentine

pregabalin

valproate

carbamazepine

Mood stabilizers

 

 

 

 

lithium

 

ANTIDEPRESSANT MEDICATIONS

 

The magnitude of weight gain during antidepressant therapy differs significantly by class.

 

Tricyclic Agents

 

The greatest potential to induce weight gain has been shown with the tricyclic agents’ amitriptyline and nortriptyline. Antidepressant–induced weight gain has been clearly established in the acute and maintenance period of depression therapy and is not related to disease severity. Medications from this drug class are also associated with weight gain when used for other indications, such as neuropathic pain or anxiety. To date, no predisposing factors to weight gain resulting from these drugs has been clearly identified (35).

 

Serotonin Agents

 

During initial treatment, several selective serotonin reuptake inhibitors (SSRI’s) (citalopram, fluoxetine, sertraline) and serotonin and norepinephrine reuptake inhibitors (SNRI’s) (venlafaxine and duloxetine) are associated with a slight weight loss. However, with chronic therapy many have shown weight gain. Paroxetine is considered to be the SSRI with the greatest long-term weight gain, possibly due to its affinity for the cholinergic receptor (35,36).

 

Bupropion

 

Bupropion, a norepinephrine and dopamine reuptake inhibitor and nicotinic antagonist, reduces appetite and food cravings (37). In combination with naltrexone, bupropion is approved as an antiobesity drug in United States of America (USA) and the European Union (EU) (38).

 

LITHIUM

 

In randomized controlled trials, the incidence of significant weight gain (more than 5% of initial body weight) has been described to be as high as 60% of the patients on lithium therapy for bipolar disorder. Risk factors for weight gain are a high baseline weight, younger age, co-administration of antidepressants, and female sex (39).

 

The exact mechanism by which lithium exerts these adverse effects on weight is still unknown. Possible mechanisms include a direct effect on hypothalamic centers controlling appetite, increased thirst and increased intake of high caloric drinks, changes in food preference, and its influence on thyroid function with increased incidence of hypothyroidism (39,40).

 

ANTIPSYCHOTICS

 

The number of individuals in the population receiving antipsychotic drugs is surprisingly high, most commonly for psychosis, although antipsychotic drugs are also widely used to treat other psychiatric conditions like bipolar disorders, attention deficit disorder, and dementia in the elderly (41,42).

 

Typical and Atypical Antipsychotics

 

Several major chemical classes of antipsychotic drugs have been developed, mainly the phenothiazines (e.g., chlorpromazine), the butyrophenones (e.g., haloperidol), and the thioxanthines (e.g., flupenthixol). All these “conventional,” or typical, neuroleptics are effective because they are dopamine D2 receptor antagonists, but they all have major neurological side effects (43). Therefore, newer drugs, the atypical antipsychotics or second-generation antipsychotics (SGAP), are increasingly replacing the conventional neuroleptics. These atypical antipsychotics are characterized by a combined activity on both the D2 and 5-HT2a receptors. Besides their antagonistic effects on these receptors, they possess diverse pharmacologic interactions with a number of neurotransmitter receptors (44).

 

Up to 80% of patients taking antipsychotic medication experience weight gain that exceeds their ideal body weight by 20% or more (45). Weight gain variability is high in between these drugs, which has been ascribed to both a high affinity for the H1-histaminic receptor as well as, to a lesser extent, the α1-adrenergic and 5-HT2c-receptors (44). The largest weight gain is consistently associated with olanzapine and clozapine. Weight gain promoting effects of the antipsychotics seem to be more pronounced in people with a normal body weight at baseline and more in women than in men. Weight gain associated with long-term treatment is time- and dose-dependent and can be predicted by weight increases in the first weeks of treatment. Drug-naïve patients gain significantly more weight than patients exposed to antipsychotics in the past and studies in pediatric patients demonstrate greater absolute weight gain in this group than in adults. Patients who have greater treatment-emergent weight gain are more likely to benefit from treatment with antipsychotics (33,46-48).

 

Although SGAP’s influence food intake by altering neurotransmitter function in the hypothalamus, thus leading to excess caloric consumption, obesity, and insulin resistance (49), weight gain is not the only concern for patients taking antipsychotic medication (Figure 2). SGAP’s can also promote lipogenesis and enhance antilipolytic effects of insulin, thereby favoring lipid accumulation and adipocyte enlargement and inducing insulin resistance (50).  Metabolic sequela includes glucose dysregulation and an increased risk for developing metabolic syndrome and type 2 diabetes (51,52). Although an increased prevalence of metabolic syndrome has been reported in drug naïve patients with diverse psychoses, there is a significant association with longer disease duration and with the intake of clozapine in particular (51,53). In one 5-year study of clozapine-treated patients, 52% experienced one or more episodes of hyperglycemia and 30% were diagnosed as having type 2 diabetes (54). Newer SGAP appear to have fewer metabolic side effects (1,2,55,56).

 

The development of diabetes in patients taking antipsychotic has also been reported in patients without significant weight changes. SGAP’s are associated with a marked increase in insulin resistance in muscle, adipose tissue, and liver (49), possibly mediated by impaired GLUT-4 and GLUT-5 glucose transporter function (57). In addition, a direct impairment of pancreatic β-cell function and decreased insulin secretion has been linked to the affinity of these drugs for the 5HT-1a and 5HT-2 serotonin receptors of the β-cells (49).

 

Manifestations of insulin resistance, impaired glucose tolerance, metabolic syndrome (including elevations in triglyceride levels and reductions in HDL cholesterol), and type 2 diabetes contribute to the higher incidence of cardiovascular disease in patients taking these drugs. People with psychosis have a 20% shorter life expectancy than the general population, mainly driven by an increase in cardiovascular disease (53,58). In view of the high cardiometabolic risk associated with antipsychotic drug use, the American Diabetes Association and American Psychiatric Association (ADA/APA) Consensus Development Conference recommends close monitoring of weight and metabolic and cardiovascular risk factors in all patients taking SGAP’s (34).

Figure 1. Schematic representation of the central and peripheral mechanisms of antipsychotic-induced weight gain and metabolic side effects as well as current and future preventive and therapeutic options. HPA axis: hypothalamic–pituitary–adrenal axis, GLP-1: glucagon like peptide-1, GLP1RA: GLP-1 receptor agonist, RMR: resting metabolic rate, IL6: interleukin-6, TNF-α: tumor necrosis factor-α, IR: insulin resistance, PKC-βi: protein kinase C-β inhibitor, CB1R: cannabinoid receptor type 1, periph CB1Ri: peripheral cannabinoid receptor type 1 inhibitor, SREBP1c: sterol regulatory element-binding proteins type 1c, AMPK: AMP-activated protein kinase (Reprinted by permission from Springer Nature Customer Service Centr GmbH: J Endocrinol Invest. 2017;40(11):1165-1174) (2).

Therapy and Prevention of Antipsychotic Weight Gain

 

Many studies have evaluated pharmacological and non-pharmacological approaches to prevent or treat weight gain that accompanies SGAP treatment. Of non-pharmacological interventions, no significant difference was found between individual and group interventions, or cognitive-behavioral versus nutritional counselling. Adherence to the weight management program appears the best prognostic factor for achieved weight loss. To promote therapeutic alliance, weight management programs should be flexible and individualized to the patient’s needs, age and stage of their disease and incorporate daily recreational-based activities. Benefits are thought to be the greatest when delivered as early as possible, before weight gain has occurred (59).

 

Switching to another antipsychotic drug with less potential for weight and cardiometabolic side effects has been endorsed by the ADA/APA consensus guidelines in those with more than 5% weight gain or worsening of their lipid or glycemia parameters, following studies that show benefits of this strategy to limit further weight gain or reduce weight and reverse components of the metabolic syndrome (34,60) (Table 2). For example, use of the SNRI reboxetine may reduce olanzapine-induced weight gain in schizophrenia patients. Weight and metabolic benefits have also been reported by switching to, or the addition of, topiramate, amantadine, fluvoxamine, and orlistat (61-63). With metformin, attenuation or reduction of weight gain and amelioration of the metabolic side effects of SGAP therapy has been demonstrated, with greater benefits the earlier metformin was started (61,64). In a rodent study, the addition of metformin and berberine prevented the loss of brown fat induced by olanzapine and was associated with favorable changes in expression of several genes controlling energy expenditure (65).

 

Table 2. Mean Weight Reducing Effects of Switching to a Less Metabolically Active SGAP or Addition of Weight Reducing Drugs (60,63).

Action

Mean weight reduction (kg)

95 % CI

Switch to:

aripiprazole or quietiapine from olanzapine

-1.94

-3.90 to 0.08

Addition of:

Metformin

-2.94

-4.89 to -0.99

Topiramate

-2.52

-4.87 to -0.16

Reboxetine

-1.90

-3.07 to -0.72

 

In patients who are obese or with diabetes, glucagon-like protein-1 receptor agonists (GLP-1 RA) demonstrate long-lasting weight loss and benefits on glucose metabolism (1,3). Growing evidence suggests that patients who are overweight and those with psychosis exhibit similar structural brain changes, cognitive deficits, and central neuropeptide alterations, suggesting an overlap between the pathophysiological pathways of these disorders (66). GLP-1 RA’s have been shown to provide neuroprotective effects in cerebral degenerative diseases such as Parkinson’s disease, Huntington’s chorea, and Alzheimer’s dementia (66). Liraglutide, a once daily injected GLP-1 RA, reverses SGAP-induced weight gain, impaired glucose tolerance, metabolic side effects and behavioral depression (67-69).

 

Mifepristone, a glucocorticoid and progestin receptor antagonist, attenuated increases in weight and reduced the metabolic changes induced by risperidone and olanzapine, suggesting mechanistic involvement of the hypothalamic-pituitary-adrenal axis in the weight and cardiometabolic side effects of antipsychotic medications (70).  The orally effective selective protein kinase C-β (PKC- β) inhibitor ruboxistaurin, which is used in treatment of diabetes-associated retinopathy and macular edema, attenuates the effects on adipose tissue differentiation by clozapine in rodents. If this is shown to be relevant for humans, it could offer a new target for the prevention of antipsychotic-induced weight gain (71).

 

Because of the associations between inflammation, adiposity and psychiatric disease, other therapeutic options being explored to improve psychiatric symptoms without adverse metabolic sequelae include COX-2 selective non- steroidal anti-inflammatory drugs, and monoclonal antibodies against anti TNF-α and Interleukin-6 (72,73).

 

Anti-Seizure Drugs

 

Many of the anti-epileptic treatments are associated with weight change. Most prominent are valproate and carbamazepine, inducing weight gain in 71% and 43% of the patients, respectively. Pregabalin and gabapentin can also induce weight gain and are of particular importance since they are used more and more in the treatment of neuropathic pain, including in patients with diabetes. Weight neutral anti-epileptic drugs include lamotrigine, levetiracetam and phenytoin. Some others are associated with weight loss, including felbamate, topiramate, and zonisamide (74).

 

Weight-inducing effects of valproate are thought to result from interactions with appetite-regulating neuropeptides and cytokines within the hypothalamus as well as effects on energy expenditure (75). Greater weight gain is associated with longer duration of treatment with valproate, although most weight gain is observed within the first year. Specific categories of patients shown to be more susceptible to weight gain with this medication include women (vs. men), post-pubertal adolescents (vs. younger children), and those who are overweight before treatment begins. On the other hand, weight gain is not related to valproate dosage or serum levels (75).

 

Peripheral actions are thought to mediate valproates adverse effects on glucose and lipid metabolism that contribute to weight-independent worsening of insulin resistance and risk for type 2 diabetes. Directs effects in adipose tissue have been shown to increase leptin resistance, decrease adiponectin levels, as well as increase free fatty acids, all resulting in insulin resistance (76). On the other hand, valproic acid is associated with β-cell dysfunction and impaired insulin secretion by increasing oxidative stress, and direct inhibition of the GLUT-1 transporter, thereby hampering insulin secretion in an insulin resistant state, promoting hyperglycemia and type 2 diabetes (76-78).

 

Besides the increased risk for hyperglycemia and type 2 diabetes, an increased risk of other features of the metabolic syndrome (e.g., dyslipidemia) as well as endothelial dysfunction has been demonstrated. It has additionally been reported that up to 60% of the patients taking valproate also develop non-alcoholic steatohepatitis, further contributing to insulin resistance, chronic inflammation, and increased risk for cardiovascular disease (79). 

 

With the other anticonvulsants, weight gain can be considerable in susceptible patients (74). However, in contrast to valproate, metabolic side effects accompanying use of carbamazepine, pregabalin and gabapentin are thought to be secondary to the induced weight gain rather than weight-independent mechanisms (80). On the other hand, topiramate and zonisamide have been shown to decrease body weight, even when studied in populations with obesity and overweight without any seizure history. Adding topiramate to another antiepileptic, antipsychotic or antidepressant drug, or changing anticonvulsant therapy for topiramate or zonisamide can help prevent or treat weight gain that accompanies psychiatric or anticonvulsant therapy (63,81). In the USA, the combination therapy topiramate/phentermine is approved as an antiobesity drug (82).

 

DRUGS ASSOCIATED WITH WEIGHT GAIN AND LIPODYSTROPHY

 

Corticosteroids

 

Although weight gain is considered a common side-effect of long-term treatment with glucocorticoids, prospective studies examining weight gain are scarce. Self-reported data in patients using chronic corticoid therapy show substantial weight gain in up to 70% of all patients (83). The weight gain associated with glucocorticoid therapy can be massive with over 10 kg increases in approximately 20% of patients in their first treatment year of treatment. The risk of weight gain with glucocorticoids is dose dependent and significantly increases with intakes above the equivalent of oral or parenteral 5 mg prednisone per day. Inhaled corticosteroids and single epidural steroid injections have no effect on body weight.

 

Glucocorticoids may induce an increase in food intake and dietary preference for high-caloric, high-fat ‘comfort foods’ through changes in the activity of AMP-activated protein kinase in the hypothalamus (84-86). Glucocorticoids decrease thermogenesis and uncoupling protein 1 (UCP-1) expression in brown adipose tissue, thereby influencing metabolic rate (87). Chronic glucocorticoid therapy or a state of chronic hyperactivation of the hypothalamic–pituitary–adrenal (HPA) axis is associated with activation of the endocannabinoid (eCB) system, which is a potent regulator of food intake and decreases energy expenditure (88). 

 

Glucocorticoids also affect body fat distribution by increasing visceral fat mass, thereby increasing insulin resistance and the risk for impaired glucose tolerance, diabetes and cardiovascular disease (89). Although the mechanisms for this are not completely understood, glucocorticoids acutely stimulate lipolysis through the activation of hormone-sensitive lipase and an increased catecholamine responsiveness. When this disproportionately affects fat stores in the extremities, it can lead to loss of these depots, or lipodystrophy, the risk of which has been reported to be higher among females and younger patients and increases with a higher baseline body mass index (90). On the other hand, during chronic administration or exposure to high endogenous plasma corticoid concentration such as in Cushing’s syndrome, they promote both adipocyte hypertrophy by increasing synthesis and storage of lipids and adipose tissue hyperplasia by increasing differentiation of preadipocytes to mature adipocytes. Visceral adipose tissue has a higher glucocorticoid receptor density as compared with other fat depots, which might favor enhanced expansion of visceral adipose tissue (89). These differential effects on visceral and subcutaneous fat may be mediated by differential regulation of key metabolic genes including lipoprotein lipase, 11-beta-hydroxysteroid-dehydrogenase-1 (11β-HSD-1) and UCP-1 (89).

 

Glucocorticoid induced overexpression of 11β-HSD-1 in adipose tissue leads to an increase of plasma triglycerides and cholesterol levels, while 11β-HSD-1 overexpression in liver promotes insulin resistance, hepatic steatosis, and increased lipid synthesis (91,92).

In the liver, glucocorticoids act through peripheral stimulation of the cannabinoid-1 receptor (CB1R), inducing hepatic lipogenesis, steatosis and dyslipidemia. By enhancing CB1R in adipose tissue, glucocorticoids induce insulin resistance (IR) and obesity. Blocking the peripheral CB1R attenuates all aspects of metabolic dysregulation by glucocorticoids, leading the path to potential therapeutic option by selective peripheral CB1R blockers (88).  These properties make specific 11β-HSD-1 inhibitors or peripheral CB1R blockers promising candidate drugs to reverse or prevent glucocorticoid-induced side effects.

 

Hypolipidemic Drugs

 

Protein convertase subtilisin kexin type 9 (PCSK9) regulates plasma low-density lipoprotein levels and low-density lipoprotein receptor expression in several tissues. Fully human monoclonal PCSK-9 inhibitors (alirocumab and evolocumab) and small interfering RNA molecules designed to target PCSK9 messenger RNA (inclisiran) have demonstrated substantial and sustained reductions in LDL-cholesterol levels, as well as significant reductions in major cardiovascular events (93).

 

Although no obvious side effects on body weight and body fat composition or on glucose tolerance were reported in these trials, patients with genetically low PCSK9 (R46L polymorphism) have a two-fold increased prevalence of hepatic steatosis and greater epicardial fat thickness (94). PCSK9 variants associated with lower LDL cholesterol have also been associated with higher fasting glucose levels, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes (95). PCSK9 KO mice display higher visceral adipose tissue (but not subcutaneous adipose tissue), compared with wild type mice, suggesting that genetically determined PCSK9 deficiency might be associated with ectopic fat accumulation (94). It has been shown that besides the effects of LDL-R regulation in liver tissue, PCSK9 regulates VLDL-R, ApoE2 R and the CD36 receptor. PCSK9 deficiency results in reduced post-prandial lipemia and triglyceride rich lipoprotein production, while its overexpression promotes hepatic lipogenesis (96). Therefore, in genetic studies in animals and humans, PCSK9 is plays a pivotal role in fat metabolism: it regulates circulating cholesterol levels via hepatic LDL-R, but it also influences visceral adipogenesis via adipose VLDL-R regulation (97).

 

Therapies that reduce the rate of VLDL secretion represent an attractive alternative for reducing plasma concentrations of pro-atherogenic lipoproteins. Mipomersen is a second-generation anti-sense oligonucleotide that inhibits the translation of the apolipoprotein B by binding to the mRNA sequence of apolipoprotein B. Mipomersen reduces apolipoprotein B synthesis in the liver and the production of VLDL (and hence to IDL and LDL as well) and increases catabolism of VLDL. On the other hand, the hepatic production rate of triglycerides is unaffected (98). In clinical trials, mipomersen is associated with an approximately four times higher risk for hepatic steatosis. In contrast to NAFLD associated with common obesity, however, mipomersen-induced liver steatosis is not associated with an increase in inflammation or fibrosis (99).

 

Microsomal triglyceride transfer protein (MTP) is the key protein that delivers the lipid droplet to nascent VLDL and chylomicron particles during the assembly and secretion of lipoproteins in liver and intestine. MTP inhibition (e.g. lomitapide) decreases the secretion of chylomicrons and VLDL, thereby reducing the production of triglyceride rich lipoproteins and ultimately the production of LDL. Treatment with this drug also induces intra-hepatic fat accumulation, but in contrast to mipomersen, MTP inhibition is associated with greater (up to six-fold) increases in hepatic fat content and more severe increases in transaminase levels (100).

 

Acyl-CoA: cholesterol O-acyl transferase 2 (ACAT2) plays an important role in maintaining cellular cholesterol homeostasis.  When absorbed cholesterol enters the body, it is esterified by ACAT2 and directed to the liver, where it is stored within hepatocytes in lipid droplets as cholesteryl esters. Recently it was shown in high-fat fed mice that mechanisms linking accumulation of hepatic cholesteryl esters with hepatic triglyceride accumulation depend not just on de-novo triglyceride synthesis and lipogenesis secondary to hyperinsulinemia and hyperglycemia, but also on the presence of cholesteryl ester in hepatocytes limiting mobilization of triglycerides from the liver (101). Studies have shown that ACAT inhibitors are effective for the treatment of hypercholesterolemia and atherosclerosis in rodents, however data in humans have been disappointing (102). The recent data coupling lower cholesteryl esters content to higher TG mobilization, as is realized by selective ACAT2 inhibitors, needs further study not only for treating hypercholesterolemia and atherosclerosis but also for the therapy of NAFLD.

 

Antiretroviral Therapy

 

Shortly after the introduction of effective highly-active antiretroviral therapy (HAART) for the treatment of human immunodeficiency virus (HIV) disease, it became clear that patients on these medications often had disorders of fat storage and/or wasting (lipodystrophy). The term “HIV-associated lipodystrophy syndrome” was introduced to describe a typical loss of subcutaneous fat in the limbs and face (lipoatrophy) and central or truncal fat accumulation (lipohypertrophy) (Table 3). Lipohypertrophy is characterized by intra-abdominal visceral fat accumulation and localized fat accumulation in breasts, the dorsocervical region and under the skin as lipomas. While in some patients mixed patterns are observed, some patients exhibit pure lipoatrophy and others have only fat accumulation (103). The prevalence of lipodystrophy in HIV infected patients ranges from 10 to 80%. This wide range is due to differences in study population, race, age and duration of HIV infection or antiretroviral therapy, but also due to different definitions of lipodystrophy and methods of diagnosis (104).

 

 

Table 3: Classification of Antiretroviral Drugs and the Risk for Metabolic Consequences

Drug

Lipohypertrophy / weight gain

 

Lipoatrophy

Insulin resistance

Dyslipidemia

Nucleoside and nucleotide reverse transcriptase inhibitors (NRTI’s)

Abacavir (ABC)

0

0

0

+

Didanosine (ddI)

+/-

+/-

+

+

Emtricitabine (FTC)

0

0

0

0

Lamivudine (3TC)

0

0

0

+

Stavudine (d4T)

++

+++

++

++

Tenofovir (TDF)

0

0

0

0

Zidovudine (AZT or ZDV)

+

++

++

+

Non- nucleoside reverse transcriptase inhibitors (NNRTI’s)

Delavirdine(DLV)

+/-

+/-

0

+

Efavirenz (EFV)

+/-

+

+

++

Etrivirine (ETR)

+/-

0

0

0

Nevirapine (NVP)

0

0

0

++

Rilpivirine (RPV)

+

0

0

0

Protease inhibitors (PI’s)

Amprenavir (APV)

+

+

+

+

Atazanavir (ATV)

++

0

0

+

Darunavir (DRV)

+

0

+/-

+/-

Indinavir (IDV)

+

+/-

+++

+

Lopinavir (LPV)

+

+/-

+++

++

Nelfinavir (NFV)

+

+/-

+

++

Ritonavir (RTV)

+

+/-

+++

+++

Saquinavir (SQV)

+

+/-

+/-

+/-

Tipranavir (TPV)

+

+/-

+++

++

Fosamprenavir (FPV)

++

0

0

+

Fusion inhibitor

Enfuvirtide (T20)

0

0

0

0

Integrase inhibitor

Raltegravir (RAL)

+

0

0

0

Dolutegravir (DTG)

+

0

 

 

CCR5 antagonist = entry inhibitors

Maraviroc (MVC)

No or positive effects (animal data)

0

0

0

Post attachment inhibitors

Ibalizumab

No data

No data

0

0

(+ = increase; 0 = neutral: +/- = discrepant)

 

Risk factors for lipoatrophy are male gender, older age, lower weight before therapy, lower CD4 cell counts, a higher baseline viral load, and co-infection with hepatitis C. Certain mitochondrial haplotypes and nuclear genetic polymorphisms are associated with an increased risk for lipoatrophy (104,105).  In addition, there is a clear association of lipoatrophy with stavudine and zidovudine use, while switching to other retroviral drugs or using an NRTI-sparing regimen reverses lipoatrophy (106).

 

While the distribution of lipoatrophy is specific for HIV infected patients and anti-HIV therapy (Table 3), abdominal fat accumulation seems not to be associated with specific antiretroviral drugs and carries the same risk for metabolic syndrome as non-medication-associated visceral fat accumulation. Risk factors associated with fat accumulation during HAART are increasing age, female sex, weight before start of antiretroviral therapy, dietary factors, and longer duration of HIV treatment (104). In the AIDS Clinical Trial Group study (A5175), the prevalence of overweight or obesity increased from 25% to 40% after 144 weeks of HAART. In another trial a 30% increase in visceral fat mass was seen after 96 weeks of therapy (107). Whether lipohypertrophy can be directly attributed to HAART or represents the effects of treating HIV itself, is still a matter of debate. Indeed, central fat gain generally occurs at similar rates in patients randomized to different HAART regimens, is not associated with any specific antiretroviral drug or drug class, and does not reverse on switching antiretrovirals (106,108). In addition to the promotion of generalized weight gain, increases of as little as 5% of visceral adipose tissue are associated with increased metabolic risk, cardiovascular side effects, and even 5-year mortality. Stated differently, the cardiometabolic risk of weight gain in HIV patients is much higher than comparable weight gain in non-HIV infected controls (109).

 

Therefore, the European AIDS Clinical Society recommends monitoring for changes in body composition of HIV patients by using body mass index, waist circumference, waist-to-hip ratio, and to screen regularly for clinical lipodystrophy in all patients at HIV diagnosis, before starting HAART, and annually thereafter. Fat atrophy should be distinguished from general wasting associated with advanced AIDS, where besides wasting of fat mass, lean body mass is also lost. To distinguish visceral fat accumulation from simple obesity, skin fold measures can help since in HIV-induced abdominal fat accumulation, subcutaneous fat is normal or decreased, while it mostly increases in patients with simple obesity (110).

Figure 2. Major pathogenetic pathways in HIV-induced lipodystrophy and its metabolic consequences (adapted from Debarle MC et al (111))

PATHOGENETIC MECHANISMS OF HIV INDUCED LIPODYSTROPHY

 

Lipodystrophy is considered to be multifactorial, resulting from the complex interaction of host factors, HIV-related factors, and antiretroviral drug specific factors (Figure 3). While lipodystrophy is clearly linked to antiretroviral therapy, disturbances in adipose tissue gene expression are present in treatment-naïve patients with HIV, indicating that HIV-1 infection itself likely creates alterations in adipose tissue that are worsened by antiretroviral therapy (108,112).

 

When used in monotherapy, lipoatrophy is not noticed in patients using protease-inhibitors (PI). However, the co-administration of PI’s with nucleoside and nucleotide reverse transcriptase inhibitors (NRTI’s), such as stavudine and zidovudine, play an additive role in the NRTI-induced lipodystrophy (106). The older nucleoside analogues inhibit mitochondrial DNA polymerase-γ within adipocytes causing mtDNA depletion and mitochondrial dysfunction and oxidative stress in subcutaneous adipose tissue (SAT). Together with a genetic predisposition and mitochondrial dysfunction secondary to HIV itself, NRTI’s contribute in mitochondrial toxicity and increased oxidative stress, inhibiting adipogenesis and adipocyte differentiation, and promoting apoptosis, lipolysis, and dyslipidemia (105,113). Lipoatrophy is associated with inflammation, as shown by an increased macrophage number and expression of TNF-α, IL-6 and IL-8 together with increased fibrosis (114).

 

Adipose tissue serves as a reservoir for HIV virus, altering adipose tissue environment and causing adipose tissue inflammation. The HIV accessory viral protein R (Vpr) inhibits PPAR-γ, impairs the expression of genes related to adipocyte metabolism including adiponectin and activates glucocorticoid target gene expression, inducing macrophage infiltration and adipose tissue hypertrophy (108). Therefore, it appears that HIV-1 infection initiates a first wave of alterations in adipose tissue that is amplified by HAART and ultimately results in lipoatrophy.

PI’s are more closely associated with lipo-accumulation (115). They interfere with adipocyte maturation and differentiation by alterations in gene expression of several transcriptase factors (SREBP-1, PPAR-γ, C/EBPα and β genes) and genes encoding for acyl coenzyme-A synthase, lipoprotein lipase, GLUT-4, leptin and adiponectin, resulting in impaired fatty acid and glucose uptake, increased lipolysis and peripheral fat loss, increased triglyceride esterification and central fat accumulation. The imbalance in the production of adipokines (adiponectin and leptin) and infiltration of immune cells into adipose tissue exacerbate the pro-inflammatory environment (114).

 

PPAR-γ expression is also reduced by NRTI’s. The non-nucleoside reverse transcriptase inhibitor (NNRTI) efavirenz decreases expression of SREBP-1c, thus decreasing intracellular stores of triglycerides, and exerts anti-adipogenic effects in cultured adipose cells (116).

Mitochondrial DNA depletion is common to both subcutaneous and visceral or dorsocervical depots in HIV lipodystrophy and mitochondrial dysfunction in visceral adipose tissue (VAT) was found to be similar to that in SAT. In SAT, mitochondrial dysfunction is linked with lipoatrophy, whereas in VAT lipohypertrophy results. These observations indicate that different responses occurring in subcutaneous and visceral fat depots during HAART treatment are likely related to intrinsic differences in physiology between these depots (114). 

 

Increases in proinflammatory cytokines, such as TNF-α and interleukin-6 further contribute to the development of lipodystrophy and their metabolic consequences. TNF-α inhibits adipocyte differentiation, increases apoptosis and mitochondrial toxicity and activates 11β-HSD-1 resulting in increased lipid accumulation in adipocytes, lipolysis and insulin resistance. In addition, increased fat tissue fibrosis and lipo-hypertrophy, are associated with ectopic lipid accumulation in liver, muscle and heart further increasing cardiometabolic complications (111).

 

Older PI‘s (indinavir, lopinavir and ritonavir) are associated with abnormalities in glucose tolerance and their use is associated with a threefold increase in the risk of diabetes compared to other treatment options. PI‘s inhibit the uptake of glucose into cells by interfering with the GLUT-4 glucose transporter and decrease insulin secretion through effects on β-cell function. Following chronic treatment, this insulin resistance leads to an inadequate suppression of lipolysis and endogenous glucose production as well as a decreased peripheral glucose uptake.  Newer PI’s like darinavir and atazanavir and Integrase inhibitors (INSTI’s) have only limited effects on glucose metabolism. Of the nucleoside analogues, stavudine and zidovudine have been associated with the greatest increase in insulin resistance (114,117).

 

Finally, the hypothalamic-pituitary-growth hormone axis may also be involved in the metabolic changes associated with lipodystrophy. Mean growth hormone levels and growth hormone pulse amplitude are reduced in HIV-infected men with body-fat changes receiving HAART, compared with men without body-fat changes and healthy control subjects (118).

 

Abnormalities of lipid metabolism in HIV-infected patients were described before the advent of HAART and are mainly characterized by increases in triglycerides by a decreased triglyceride clearance and increased hepatic VLDL synthesis and apolipoprotein-E levels. In advanced AIDS disease, reduced HDL-cholesterol and a predominance of small, dense LDL particles have been reported (119). The chronic inflammation of the HIV infection itself and the associated increase in circulating cytokines can induce dyslipidemia. With the use of HAART, these lipid abnormalities tend to increase in severity and in their prevalence, with sometimes dramatic increases in lipid concentrations, particularly triglycerides (119,120). The prevalence and severity of lipid abnormalities varies widely depending on the type of HAART, nutritional status, and HIV disease stage. Risk factors seem to be a higher viral load, a family history of lipid abnormalities, less physical activity, increasing weight, greater BMI and greater trunk-to-limb fat ratio (104,119). Lipid changes and therapy of dyslipidemia in patients on retroviral therapy are described elsewhere in Endotext (121).

 

THERAPY OF HIV ASSOCIATED LIPODYSTROPHY

 

In patients with visceral fat accumulation, combined aerobic and strength training is generally recognized to reduce visceral fat and biomarkers for inflammation (108).  Switching from a thymidine analogue NRTI (e.g. stavudine or zidovudine) to an alternative agent is considered to be a reasonable strategy to reverse or slow progression of lipoatrophy. Switching from stavudine to other NRTIs has been shown to improve mitochondrial indices, reduce fat apoptosis, and decrease some adipose tissue markers of inflammation (114,122). Switching to newer antiretroviral drugs has no effect on VAT accumulation. A switch from NRTI and NNRTI to protease inhibitors showed no weight changes whereas a switch to newer integrase inhibitors may cause even greater weight gain (123).

 

As mentioned above, pituitary growth hormone (GH) secretion is altered in HIV patients, and about one-third of patients meet criteria for GH deficiency. Growth hormone therapy in patients with ART induced lipodystrophy, reduces visceral adiposity, but is associated with supraphysiologic levels of IGF-I and symptoms of growth hormone excess. The FDA approved tesamorelin, a recombinant human GH releasing hormone, for the treatment of excess abdominal fat in HIV-infected patients. Tesamorelin decreases VAT by 15 to 18 %, with a significant improvement of triglyceride and cholesterol levels. The effects of tesamorelin appear to be highly specific for the visceral-fat compartment, with relatively little effect on subcutaneous fat. The preferential reduction in VAT is important, given the peripheral lipoatrophy. The reduction in VAT is associated with greater baseline visceral fat mass, suggesting that larger effects might be seen among patients with more accumulation of visceral fat. Tesamorelin also improves lipid profiles, triglyceride levels and the ratio of total to HDL cholesterol. Despite this reduction in VAT, a small but statistically significant increase in HbA1c is seen in subjects receiving tesamorelin. Therefore, monitoring of IGF-1 and glycemic parameters is warranted (124).

 

In patients with glucose intolerance and central obesity, metformin treatment was associated with small reductions of VAT. However, in patients with lipoatrophy, metformin should be used with caution, since a further decrease of subcutaneous fat can be induced. Doleglutavir (an integrase inhibitor) increases metformin concentration. The total daily dose of metformin should therefore not exceed 1000 mg in patients co-administrated metformin with doleglutavir (104).

 

While the therapeutic goals and the management of diabetes in patients with HIV with or without HAART is similar to the guidelines in the general population, evidence suggests that insulin sensitizers may be preferable to insulin secretagogues. A meta-analysis of all studies with thiazolidinedione therapy (pioglitazone) showed a significantly higher limb fat mass gain in patients treated with pioglitazone. However, some studies, demonstrated a lack of effect in patients on thymidine–NRTI therapy, explained by the decreased expression of PPARγ in those patients. Any benefit appears to be small, therefore pioglitazone should be reserved to patients with severe insulin resistance and /or diabetes (125,126).

 

For patients with morbid obesity and/or major obesity-related diseases, bariatric surgery can be considered. An average of 20% reduction of initial BMI, improved body composition and metabolic status was observed in patients after bariatric surgery, similarly to obese non-HIV patients. However, ART treatment should be monitored to control HIV infection and some ART doses should be adjusted following this degree of weight loss (127).

 

Lipodystrophy associated changes in adipokine concentration could be the basis of future therapeutic options. Leptin and adiponectin decreases have been demonstrated in patients with lipodystrophy. Recombinant leptin therapy increases adiponectin levels and improve insulin sensitivity, glucose tolerance and dyslipidemia and decreases VAT without any change in SAT (128). Finally, therapy with locally injected fillers or autologous fat transplantation, are cosmetic therapies with positive results on patient wellbeing and therapy compliance (129).

 

CONCLUSION

 

Many frequently used medications can cause weight gain, preferential central (visceral) fat accumulation, ectopic fat accumulation in liver and muscle, and consequently have adverse glucolipid metabolic side effects that increase patient’s risk for type 2 diabetes and cardiovascular disease. In high-risk patients, use of alternative or less metabolically-active drugs can reverse or prevent unwanted weight gain and metabolic disturbances. In those patients who need to remain on medications that induce obesity and metabolic dysfunction, frequent monitoring and management of resulting weight gain, elevated blood pressure, dyslipidemia, and type 2 diabetes using standard therapies is warranted.

 

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Metabolic Syndrome

ABSTRACT

 

Significant interest exists in understanding the shared metabolic dysregulation leading to obesity, diabetes, and cardiovascular disease (CVD).  Hence came the concept of the “metabolic syndrome” (MetS).  Reaven first described MetS in his 1988 Banting lecture as “Syndrome X”.  Reaven suggested that the syndrome hinged on the existence of insulin resistance and resulted in glucose intolerance, hypertension and dyslipidemia. The World Health Organization (WHO) produced the first formalized definition of the MetS in 1998.  Since then multiple definitions of the syndrome have been proposed, the most recent being the Harmonized Definition where 3 of the 5 risk factors are present: enlarged waist circumference with population-specific and country-specific criteria; triglycerides ≥ 150 mg/dL, HDL-C < 40 mg/dL in men and < 50 mg/dL in women, systolic blood pressure ≥ 130 mm Hg or diastolic blood pressure ≥ 85 mm Hg and fasting glucose > 100 mg/dL, with the inclusion of patients taking medication to manage hypertriglyceridemia, low HDL-C, hypertension, and hyperglycemia. The National Health and Nutrition Examination Survey (NHANES) estimated the overall prevalence of MetS in adults (aged ≥ 20 years) in the United States as 33% from 2003 to 2012.  The high prevalence is particularly alarming given that MetS also predisposes to a number of serious conditions beyond diabetes and CVD including non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), polycystic ovarian syndrome (PCOS), obstructive sleep apnea (OSA), cancer, and many other serious disease states.  Hence, early identification and intervention are warranted. Lifestyle modification is the foundational intervention in treatment of MetS.  Specifically, a healthy low-calorie, low fat diet and moderate physical activity of at least 150 minutes/week, resulting in a weight reduction of 7%.  Obesity, hypertension and dyslipidemia may also be treated pharmacologically to meet individualized patient goals. Beyond the clinic imperative around MetS are its pathophysiologic underpinnings.  This review will focus on the investigative work into the proximal origins of the MetS.  Defects in insulin signaling occur in a shared environment of pro-inflammation, untoward adipokines coming from dysregulated fatty acid metabolism, as well as novel pathways involving the gut microbiota.  Collectively, MetS continues to exist as a fertile area of research yielding significant insights into early events leading to the most prevalent cause of human morbidity and mortality. For in depth review of all related aspects of endocrinology, visit www.endotext.org.

 

HISTORY AND DEFINITIONS

 

The metabolic syndrome (MetS) is a compilation of risk factors that predispose individuals to the development of type 2 diabetes (T2DM) and cardiovascular disease (CVD).  Reaven (1) first described MetS in his 1988 Banting lecture as “Syndrome X. ” Reaven suggested that insulin resistance clustered together with glucose intolerance, dyslipidemia, and hypertension to increase the risk of CVD.  The initial definition of metabolic syndrome included impaired glucose tolerance (IGT), hyperinsulinemia, elevated triglycerides (TG), and reduced high-density lipoprotein cholesterol (HDL-C). Hyperuricemia, microvascular angina, and elevated plasminogen activator inhibitor 1 (PAI-1) were later proposed as possible additional components of the same syndrome (1,2). Obesity was not included as part of Syndrome X as Reaven believed that insulin resistance, not obesity, was the common denominator. Reaven noted that all of the elements of Syndrome X could occur in non-obese individuals, and while he acknowledged that obesity could lead to a decrease in insulin mediated glucose uptake, he stressed that obesity was only one of the environmental factors that affect insulin sensitivity (3,4).

 

The World Health Organization (WHO) produced the first formalized definition of the MetS in 1998. The working definition included impaired glucose tolerance (IGT), impaired fasting glucose (IFG) or diabetes mellitus and/or insulin resistance (as measured using a hyperinsulinemic euglycemic clamp study) together with two or more additional components. Additional components included hypertension (defined as a blood pressure ≥160/90 mm Hg), raised plasma triglycerides (≥150 mg/dl) and/or low HDL-C (<35 mg/dl for men and <39 mg/dl for women), central obesity (defined either as body mass index (BMI) > 30 kg/m2 or waist to hip ratio>0.90 for males and >0.85 for females) and microalbuminuria (5). Critics questioned the practicality of this definition given the need for a hyperinsulinemic clamp study. Others argued that measuring waist circumference was superior in terms of convenience to the waist to hip ratio with similar correlations to obesity. Additionally, there was a question about the value of including microalbuminuria in the definition as there was insufficient evidence of a connection with insulin resistance (5).

 

These critiques led to the first revision of the definition of the syndrome in 1999 by the European Group for the Study of Insulin Resistance (EGIR). They renamed the syndrome the “insulin resistance syndrome” (IRS) as it included non-metabolic features. They excluded patients with diabetes because of the difficulty of measuring insulin resistance in these individuals. The need for hyperinsulinemic clamp studies was obviated by defining insulin resistance as a fasting insulin level above the 75th percentile for the population. Additional criteria (elements associated with increased risk of coronary artery disease by the Second Joint Task Force of European and other Societies on Coronary Prevention) were also included, namely obesity (defined as waist circumference ≥ 94 cm (37 inches) for men and ≥ 80 cm (32 inches) for women), hypertension (now defined as a blood pressure ≥140/90 mm Hg) and dyslipidemia (with triglycerides ≥ 180 mg/dl or HDL-C ≤ 39). Additionally, microalbuminuria was omitted from the definition (6).

 

The National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) recognized that these multiple metabolic elements were cardiovascular risk factors and renamed the constellation of these metabolic risk factors as “The Metabolic Syndrome” (7). The criteria included any three of the following: obesity (defined as waist circumference ≥ 102 cm (40 inches) in males and ≥ 88 cm (35 inches) in females (based on the 1998 National Institutes of Health (NIH) obesity clinical guidelines; pediatric definitions use standardized Z-scores rather than waist circumference (8)), hypertension (defined as blood pressure ≥ 130/85 mm Hg based on the Joint National Committee guidelines), fasting glucose > 110 mg/dL, triglycerides ≥ 150 mg/dL and HDL-C < 40 mg/dL.  Additionally, in this report MetS was recognized as a secondary target of risk reduction therapy after the primary target of LDL cholesterol (7).

 

In 2003, the American Association of Clinical Endocrinologists (AACE) modified the ATP III criteria and restored the condition to the name “Insulin Resistance Syndrome,” again highlighting the central role of insulin resistance in the pathogenesis of the syndrome (9). This definition did not rely on strict diagnostic criteria. The components of the syndrome included some degree of glucose intolerance (but not overt diabetes), abnormal uric acid metabolism, dyslipidemia, hemodynamic changes (including hypertension), prothrombotic factors, markers of inflammation, and endothelial dysfunction. The AACE position statement also identified factors that increased the likelihood of developing the insulin resistance syndrome, including a diagnosis of CVD, hypertension, polycystic ovarian syndrome (PCOS), non-alcoholic fatty liver disease (NAFLD) or acanthosis nigricans, a family history of T2DM, hypertension or CVD, a personal history of gestational diabetes (GDM) or glucose intolerance, non-Caucasian ethnicity,  a sedentary lifestyle,  overweight/obesity (defined as BMI > 25 kg/m2 or waist circumference > 40 inches in men and > 35 inches in women) and age > 40 years (9).

 

The International Diabetes Federation (IDF) aimed to create a straightforward, clinically useful definition to identify individuals in any country worldwide at high risk of CVD and diabetes and to allow for comparative epidemiologic studies.  This resulted in the IDF consensus definition of MetS in 2005 (10). Central obesity, as defined as BMI> 30 kg/m2 or if ≤ 30 kg/m2 by ethnic specific waist circumference measurements) was a requisite for the syndrome. Additionally, the definition required the presence of two of the following four elements: triglycerides ≥ 150 mg/dL, HDL-C < 40 mg/dL  in men or < 50 mg/dL in women, systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 85 mmHg, fasting glucose > 100 mg/dL ( based on the 2003 ADA definition of IFG) (11) including diabetes and those with a prior diagnosis of or treatment of any of these conditions (10).

 

In 2005, the American Heart Association (AHA)/ National Heart, Lung and Blood Institute (NHLBI) also suggested criteria for diagnosis of the metabolic syndrome. Their revised definition of the metabolic syndrome was based on the ATP III criteria and required three of any of the five following criteria: elevated waist circumference ( ≥ 102 cm (40 inches) in males and ≥ 88 cm (35 inches) in females) , triglycerides ≥ 150 mg/dL and HDL-C < 40 mg/dL in men and < 50 mg/dL in women, elevated blood pressure ≥ 130/85 mm Hg and elevated fasting glucose > 100 mg/dL (12). As suggested by the IDF, ethnic-specific waist circumferences were taken into account when using this definition. Additionally, impaired fasting glucose was defined as >100 mg/dl, which was also consistent with the IDF guidelines.

 

Finally, in an effort to provide more consistency in both clinical care and research of patients with MetS, the IDF, NHBLI, AHA, World Heart Federation, and the International Association for the Study of Obesity published a joint statement in 2009 that provided a “harmonized” definition of MetS (13). According to this joint statement, a diagnosis of the MetS is made when any 3 of the 5 following risk factors are present (Table 1): enlarged waist circumference with population-specific and country-specific criteria; elevated triglycerides, defined as ≥ 150 mg/dL, decreased HDL-C, defined as < 40 mg/dL in men and < 50 mg/dL in women, elevated blood pressure, defined as systolic blood pressure ≥ 130 mm Hg or diastolic blood pressure ≥ 85 mm Hg and elevated fasting glucose, defined as blood glucose  > 100 mg/dL, with the inclusion of patients taking medication to manage hypertriglyceridemia, low HDL-C, hypertension. and hyperglycemia. This definition is frequently referred to as the current Harmonization definition.

 

Table 1. Criteria for Diagnosis of the Metabolic Syndrome

Measure

Categorical Cut-Points

        Waist circumference

Population and country specific     definitions

        Triglycerides *

          ≥ 150 mg/dL

        High Density Lipoprotein Cholesterol (HDL-C)*

Men < 40 mg/dL       Women < 50 mg/dL

        Blood Pressure*

          ≥ 130/ ≥85

        Fasting Glucose*

          ≥ 100 mg/dL

*Drug treatment for elevated triglycerides, low HDL-C, elevated blood pressure or elevated glucose are alternate indicators

 

It is important to note that in the current Harmonization definition, obesity is diagnosed using waist circumference and not BMI as waist circumference has been shown to better correlate with visceral adiposity and insulin resistance as well as the development of T2DM and CVD than does BMI (10,14,15). Subsequent to the establishment of the harmonized definition, waist to height ratio has been demonstrated to be superior to waist circumference and BMI as a screening tool for cardiometabolic risk factors (diabetes, hypertension, cardiovascular disease, and all outcomes) as well as predicting whole-body fat percentage and visceral adipose tissue mass (16,17).  It is not clear if the definition of MetS will be revised over time to reflect these new findings. Additionally, in the current Harmonization definition, ethnic-specific waist circumference cut-off values are used, as it has been shown that certain ethnic groups, especially South Asian populations, have higher degrees of visceral adiposity for given waist circumference measurements compared to Europeans (10,13,18).

 

PREVALENCE

 

The prevalence of MetS vary greatly depending on criteria used to define MetS, the age, gender, ethnicity and environment of the population being studied and obesity prevalence of the background population studied (25). Regardless of which criteria are used, however, the prevalence of MetS is high and is on the rise in many Western societies(26).

 

The National Health and Nutrition Examination Survey (NHANES) reported the overall prevalence of MetS in adults (aged ≥ 20 years) in the United States from 2003 to 2012 was 33% with the prevalence increasing with age, a finding that has been seen in other studies (24,25,27,28).  The NHANES report indicates the highest prevalence amongst Hispanics followed by non-Hispanic whites and blacks. Other studies have shown that American Indian, Hawaiian, Polynesian, and Filipino populations develop MetS more than individuals of European descent (27,29-33). Urban populations have higher rates of MetS than rural populations (34,35).  Similar to trends in Western societies, recent studies demonstrate rising rates of MetS in many developing countries (36,37). The development of these countries, bringing along a higher calorie diet and decreased physical activity, is thought to be largely responsible for the increased rate of MetS that is being observed (26,38,39). In summary, MetS affects a significant number of individuals worldwide.

 

CLINICAL UTILITY

 

The clinical utility of a diagnosis of MetS – vs. the individual components - has been studied extensively. Most recently, Pajunen and colleages compared the predictive ability of various definitions of MetS, namely the WHO, ATP III, IDF and new Harmonization definitions, found that all these definitions of MetS were significant predictors for incident CVD and T2DM. Additionally, the new Harmonization definition was found to be a better predictor of CVD endpoint than the sum of its components, as well as when compared to the Framingham risk score, but this was not the case for the prediction of T2DM (19).  Importantly, extensive, frequently conflicting literature exists examining the ability of the various definitions of MetS to predict outcomes.  Further, skeptics argue that making the diagnosis of MetS does not change the clinical management of these patients, as treatment of patients with MetS starts with diet and exercise and most physicians would offer the same recommendations to a patient with any of the individual elements of MetS (20,21).

 

In an attempt to settle some of the controversy, a WHO Expert Consultation was undertaken in November 2008. The panel concluded that MetS has limited practical utility as a diagnostic or management tool. They determined that MetS should not be applied as a clinical diagnosis, but rather should be considered a pre-morbid condition and that people with established diabetes or known cardiovascular disease should be excluded (22). They also stated that further attempts to redefine it are inappropriate in light of current knowledge and understanding (23). Despite the conclusions of the panel, the diagnosis of MetS is still commonly encountered in clinical practice as well as in the research arena and arguably applies to roughly one-third of the US adult population (24). It also predisposes to a number of serious conditions beyond diabetes and CVD including non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), polycystic ovarian syndrome (PCOS), obstructive sleep apnea (OSA), cancer, and many others.

 

PATHOGENESIS

 

There are many different factors that contribute to the development of MetS. However, as initially proposed by Reaven, insulin resistance is thought to play a central role in connecting the different components of MetS and adding to the syndrome's development (1,40). Elevated free fatty acids (FFA) and abnormal adipokine profiles can both cause and result in insulin resistance and can manifest as MetS (41). In this section, we will discuss how these factors contribute to the development of the metabolic abnormalities that characterize insulin resistance and MetS.

 

Insulin Action and Signaling

 

Through its complex signaling cascades, insulin regulates glucose and fat metabolism. Pancreatic β-cells release insulin in response to increased circulating glucose levels and subsequently decreases plasma glucose concentrations by coordinately suppressing hepatic glucose production from amino acids and other intermediates of metabolism (gluconeogenesis) and glycogen (glycogenolysis), and enhancing glucose uptake into the muscle and adipose tissue by mobilization of the insulin-responsive glucose transporter 4 (GLUT4) (Fig. 1) (42). Through actions on hormone sensitive lipase, nuclear receptor PPARγ, and fatty acid synthase, insulin inhibits lipolysis, promotes adipogenesis and adipose tissue differentiation, and under conditions of chronic hyperinsulinemia paradoxically increases fatty acid synthase(41,43).

Figure 1: Normal Insulin Action: In individuals with normal insulin sensitivity, the pancreatic β-cells release insulin in response to increased circulating glucose levels (as seen in the postprandial state). Insulin then decreases the plasma glucose concentration by suppressing hepatic glucose output and enhancing glucose uptake into adipose tissue and by skeletal muscle.

 

Insulin resistance is most simply defined by its end organ effects; a decreased ability of insulin to suppress lipolysis and hepatic glucose production, as well as facilitate glucose uptake from peripheral tissues. There are numerous factors thought to mediate insulin resistance and its adverse effects in MetS. Despite its widespread appreciation in metabolic disease, insulin resistance is still not fully understood and remains an area of intense scientific investigation. In the following section, we will review the ways in which known factors affect insulin resistance in MetS.

 

It has been thoroughly documented that FFAs mediate many undesirable metabolic effects, especially insulin resistance (44). FFAs are thought to be increased in obesity secondary to increased fat mass. Additionally, under conditions of insulin resistance, insulin’s inhibitory effects on lipolysis are reduced, leading to a further increase in FFAs. Increased FFAs are not only a result of insulin resistance, but a cause as well, thus creating a vicious cycle. FFAs can lead to insulin resistance via a variety of mechanisms that include but are not limited to the Randle cycle, the accumulation of intracellular lipid derivatives such as diacylglycerol and ceramides, inflammatory signaling, oxidative stress and mitochondrial dysfunction.

 

Randle et al. first demonstrated that an elevation in FFA in the diaphragm and heart was associated with an increase in fatty acid oxidation and impaired glucose utilization (45). Via the Randle cycle effect, increased FFAs and fatty acid oxidation lead to increased intracellular glucose content and decreased glucose uptake (46). Studies in rodents and humans have demonstrated that conditions of increased FFA either via lipid infusions or secondary to T2DM lead to impaired glucose uptake and utilization in insulin sensitive tissues (47). This occurs secondary to the inhibition of the insulin signaling pathway.

 

As FFA levels increase, the capacity of the adipose tissue to take up and store FFAs can be exceeded. When this occurs, FFAs accumulate in tissues with limited ability for lipid storage, such as the liver and skeletal muscle. This phenomenon is known as ectopic fat deposition and is strongly associated with insulin resistance (48). Fatty acids accumulate in myocytes as fatty acid derivatives. Of these fatty acid derivatives, diacylglycerol (DAG), triacylglycerol, and ceramides directly correlate with insulin resistance. DAG interferes with normal insulin signaling by its interaction with a group of novel kinases, members of the protein kinase C family, that serine phosphorylate IRS, thereby impairing tyrosine phosphorylation and activation by insulin (41,48,49) Ceramide activates the enzyme protein phosphatase 2A, leading to dephosphorylation of AKT, thwarting insulin signaling and GLUT4 translocation to the cell membrane. This impairs insulin-mediated glucose uptake into the skeletal muscle (50).

 

FFAs increase inflammatory signaling pathways through direct interaction with members of the Toll-like receptor (TLR) family and indirectly through the secretion of cytokines, namely tumor necrosis factor-α (TNF-α), and interleukins (IL), IL-1β and IL-6 (49). TLR are the pathogen recognition receptors of the innate immune system that function to facilitate the detection of microbes and transmit inflammatory signaling (51,52). In vitro, FFA can signal through TLR-2 and TLR-4 on macrophages, thereby inducing pro-inflammatory gene expression (52,53). Studies in mice with a loss of function mutation of the TLR-4 receptor are protected from diet-induced obesity and saturated fatty acid-induced insulin resistance (54). Similarly, animal studies in which TLR-2 is either absent or inhibited, demonstrate a resolution of high fat diet induced insulin resistance (55,56). A recent study in humans corroborates the importance of TLR-2 and TLR-4 in the development of FFA induced insulin resistance. Jialal and colleagues studied individuals with and without MetS (according to the NCEP ATP III definition) and found that those with MetS had increased expression and activity of TLR-2 and TLR-4 (51).  TLR-4 activity leads to activation of c-Jun N- terminal kinase (JNK) and Iκβ kinase (IKK), which results in degradation of the inhibitor κβ (Iκβα) and activation of Nuclear Factor- κβ (NF- κβ).  Through JNK and IKK activation, FFA lead to Ser phosphorylation of IRS-1 and impaired insulin signaling (57,58). Ding and colleagues assessed 1628 Chinese adults and reported that levels of IL-6 and C-reactive protein were significantly associated with MetS (using the Harmonized definition) which also increased concurrent to the increased number of MetS components, further supporting that MetS is a pro-inflammatory state (59).

 

In obesity, adipose tissue infiltration by macrophages is increased. This leads to a pro-inflammatory state as macrophages produce TNF-α, IL-6 and IL-1β (60,61). Along with FFA signaling through TLR, these macrophage-derived inflammatory cytokines activate JNK and IKK to further interfere with insulin signaling and action (61). Additionally suppressor of cytokine signaling (SOCS) proteins are induced downstream of these inflammatory cytokines which terminate insulin signaling by promoting the ubiquitination and proteasomal degradation of IRS (62).

 

Reactive oxygen species (ROS) production increases with fat accumulation. FFAs activate ROS production by adipose tissue by stimulating NADPH oxidase and decreasing the expression of anti-oxidative enzymes (63). When adipose tissues is exposed to oxidative stress, there is a decrease in the anti-inflammatory adipokine, adiponectin (to be discussed in greater detail below) (64). In MetS, there is increased ROS production as a result of elevated levels of inflammatory cytokines and decreased levels of adiponectin (65). Increased levels of ROS lead to hindered insulin signaling by inducing IRS phosphorylation and impairing GLUT4 translocation and gene transcription (66).

 

It has been shown that there is a connection between mitochondrial dysfunction and insulin resistance in skeletal muscle that precedes the development of obesity and hyperglycemia. Animal studies demonstrate that mitochondrial number and function are intact, if not increased, under conditions of insulin resistance (67,68). On the other hand, studies in obese, insulin-resistant individuals as well as those with T2DM have skeletal muscle mitochondria that are fewer in size as well as number. It has also been shown that these individuals exhibit down-regulation of the genes involved in mitochondrial oxidative phosphorylation, the process by which mitochondria produce energy in the form of ATP (69-72). Studies demonstrate that PPARγ coactivator-1α (PGC-1α), a transcriptional activator involved in mitochondrial biosynthesis, has diminished expression in patients with T2DM, obesity, or a family history of T2DM (73,74). Increased FFA uptake and their incomplete oxidation have also been implicated in mediating mitochondrial dysfunction in the skeletal muscle under insulin resistant conditions (75). Furthermore, mitochondrial dysfunction leads to increased oxidative stress and the formation of ROS, which further diminishes mitochondrial mass and function.

 

As discussed above, increased FFAs in obesity and MetS are thought to lead to insulin resistance via several different mechanisms. These different mechanisms are not exclusive of one another and interact in such a way as to create a vicious cycle of insulin resistance.

 

Adipokines   

 

Adipose tissue is an active endocrine organ that releases adipokines, bioactive mediators that affect metabolism (76). It has been demonstrated that individuals with MetS have an abnormal adipokine profile that affects insulin sensitivity (77).

 

Adiponectin differs from other adipokines in that its level is inversely correlated with body adiposity and insulin resistance (78). The administration of recombinant adiponectin ameliorates insulin resistance in obese mice (78). Adiponectin transgenic mice demonstrate improvements in insulin sensitivity (79). Adiponectin increases insulin secretion in vivo and in vitro (80). In addition to its ability to improve insulin sensitivity in peripheral tissues, adiponectin has been shown to have effects on the central nervous system that affect food intake and energy expenditure (81). In humans, low levels of adiponectin have been strongly associated with insulin resistance, increased body adiposity, T2DM, and MetS (76). Genetic hypoadiponectinemia caused by a missense mutation leads to an increased propensity toward MetS (82). Longitudinal studies demonstrate that in individuals at high risk for developing T2DM, those with higher levels of adiponectin were less likely to develop T2DM than those with lower levels of adiponectin (83) . Adiponectin levels have even been proposed to be used as a cut-off for managing the risk of developing MetS in a study of male Japanese workers.  In a 3-year prospective cohort study, the risk of developing MetS, calculated by the accelerated failure-time model, demonstrated that the mean time to develop MetS declined with decreasing total adiponectin levels.

 

Adiponectin modulates glucose metabolism through its interaction with its receptors, the adiponectin receptor 1 (AdipoR1) and adiponectin receptor 2 (AdipoR2). Binding of adiponectin to AdipoR1 and AdipoR2 results in the activation of signaling pathways affecting glucose and fatty acid metabolism. As a result of adiponectin signaling, AMP-activated protein kinase (AMPK) is phosphorylated, leading to increased glucose uptake in the muscle and reduced gluconeogenesis (84). Adiponectin also has anti-inflammatory actions, suppressing TNF-α and IL-6 expression and anti-atherogenic effects, decreasing levels of pro-atherogenic small, dense low-density lipoprotein (LDL) and TG levels (76,85).

 

In patients with insulin resistance, there is reduced responsiveness of the skeletal muscle, liver and adipose tissue to insulin. Insulin levels rise in an attempt to maintain euglycemia, and the result is hyperinsulinemia. Hyperinsulinemia has been shown to down-regulate the bioactive high-molecular weight form of adiponectin (86). Thus, the hyperinsulinemia in insulin resistance may decrease adiponectin further contributing to insulin resistance (77). Aside from the direct effects of insulin, changes that characterize the metabolic milieu of insulin resistance such as inflammation, oxidative stress and mitochondrial dysfunction have been shown to suppress adiponectin (77). This relationship is observed clinically in the same study by Ding and colleagues, showing a strong inverse association between adiponectin and HOMA-IR and an inverse trend between adiponectin and an increased number of MetS components (59). Hence, the association between insulin resistance and adiponectin appears to be complex and bidirectional. Further studies are necessary to better define this complicated relationship.

 

Leptin, another important adipokine produced by adipocytes, exerts effects on appetite and energy expenditure. When leptin binds to its receptor, signaling pathways such as the Janus Kinase-Signal Transducers and Activation of Transcription (JAK/STAT) and IRS/PI3K are activated. The result is similar to what is observed when insulin binds the IR, in that anorexigenic pathways (involving POMC) are favored over orexigenic pathways (involving neuropeptides NPY and AgRP) (87). Studies suggest that leptin affects glucose metabolism independently of its effects on food intake. Studies in rodents suggest that leptin stimulated JAK/STAT signaling is important in food intake and energy expenditure while leptin mediated PI3K signaling plays a role in regulating glucose metabolism (88-90).

 

Leptin also stimulates FFA oxidation in the liver, pancreas and skeletal muscle. Leptin opposes the action of insulin by decreasing insulin’s lipogenic effect on the adipocyte and depleting the triglyceride content of adipose tissue without increasing circulating FFA (91-93). Separate from its effects on lipid and glucose metabolism, leptin affects the immune system, by enhancing the production of inflammatory cytokines and by stimulating T–cell proliferation (94).

 

While the absence of leptin leads to extreme obesity and insulin resistance, most obese individuals are not leptin deficient. Rather, they have increased levels of leptin but are immune to its appetite suppressant effects. This observation has given rise to the concept of leptin resistance in obesity (95). Similarly, elevated leptin levels have been observed in different populations with metabolic syndrome -(96-98). Decreased sensitivity to leptin leads to increased triglyceride accumulation in adipose tissue, muscle, liver and pancreas, resulting in insulin resistance (76). An alternative perspective is the concept of hypothalamic leptin insufficiency, which states that in conditions of hyperleptinemia, the blood brain barrier prevents entry of leptin into the brain resulting in insufficiencies of leptin at important sites in the CNS (99). Regardless of whether the decreased responsiveness to leptin observed in obesity is due to leptin resistance or hypothalamic leptin insufficiency, the ability of leptin to activate hypothalamic signaling is decreased in obesity and insulin resistance (99).

 

The role of resistin in MetS is not entirely understood. Resistin is an adipokine that has been seen to be increased in rodent models of obesity, leading to impaired insulin action and β-cell dysfunction (100). Resistin is highly associated with insulin resistance and T2DM in animal models (101). Resistin activates SOCS-3, which inhibits IR phosphorylation and downstream signaling proteins, leading to impaired insulin signaling (102). It also inhibits glucose uptake by skeletal muscle and the liver and enhances hepatic gluconeogenesis (101,103).  In humans, the relationship of resistin, MetS and its components are not as clear, however associations between the components of MetS have driven an interest in further understanding its potential role.  Resistin expression in humans differs from rodents in its low expression in white adipose tissue and regulation of concentration by peripheral blood mononuclear cells, macrophages and bone marrow cells (104). Its role in the inflammatory pathway has been well described, associated with upregulation of inflammatory cytokines and to induce monocyte-endothelial cell adhesions [127]. However, the role of resistin in insulin resistance has been controversial. (76). Increased resistin levels have been demonstrated in several studies with individuals with MetS but correlations have been more consistent in women than in men (105-107). Hence, more studies are necessary to better determine the role of resistin in MetS.

 

Retinol Binding Protein-4 (RBP-4) is the vitamin A (retinol) transporter and is secreted from both adipose tissue and liver.  RBP-4 has been shown to be increased in the adipose tissue of mice with an adipose-specific knockout of GLUT4 (108). RBP-4 levels are also elevated in humans with obesity, T2DM, impaired glucose intolerance and those with a strong family history of T2DM (109,110). The suggested mechanisms by which RBP4 can mediate insulin resistance include increased gluconeogenesis and impaired insulin action in the liver and muscle (108). However, there are other studies that do not support the relationship of RBP-4 with altered glucose metabolism (111,112). As with all other adipokines, further exploration is necessary to better define the role of RBP-4 in insulin resistance and MetS.

 

Apelin, omentin and visfatin are other adipokines have been implicated in the pathogenesis of insulin resistance and MetS. However further study is necessary to better define the part they play in this process. Individuals with insulin resistance and MetS exhibit atypical adipokine profiles that not only result from insulin resistance but further contribute to its development and pathogenesis.

 

Though there are many different factors that contribute to the development of MetS. Insulin resistance, via augmented FFA levels and irregular adipokine patterns, is largely responsible for the pathogenesis of the syndrome.

 

Gut Microbiota

 

There has been considerable interest in the gut microbiota and its relationship with inflammation and metabolism.  With limited ability to digest polysaccharides, the gut microbiota in mammals represents an important system significant influence on energy harvest and efficiency(113-115).

 

In fact, mice raised in a germ-free environment, compared to conventionally raised mice, had lower body fat content and, following colonization with intestinal flora, there was an increase in body fat and hepatic triglyceride synthesis as well as the development of insulin resistance, independent of food intake and energy expenditure (113). Beyond alterations in energy harvest, the gut microbiota composition can also drive low level inflammation which has also been found to be a contributor to obesity and the metabolic syndrome (116,117). Interventional experiments with Roux en Y gastric bypass versus sham surgeries with subsequent microbiota transplant have further underscored the relationship of the microbiota with obesity (118). Observational human studies have noted differences in the microbial diversity in lean and obese subjects as well as in those with differences in microbial diversity based upon diet composition (119-121). Similar differences in microbiota composition have been seen in those with and without type 2 diabetes mellitus (122). Furthermore, infusion of microbiota via gastrointestinal probe have demonstrated alterations in insulin sensitivity (123).

 

The metabolic syndrome is a product of the complex intertwining of inflammation and insulin resistance; with its relationship to both of these, the gut microbiota has been demonstrated to have a strong influence on metabolic diseases. From observational to experimental data, the microbiota not only offers important insight into pathophysiology but also has the potential as a therapeutic target.

 

TREATMENT

 

Lifestyle modification is the foundational intervention in treatment of MetS. The Diabetes Prevention Program demonstrated that lifestyle intervention reduced the incidence of MetS by 41% compared with placebo. The intensive lifestyle intervention involved a healthy low-calorie, low fat diet and moderate physical activity of at least 150 minutes/week, resulting in a weight reduction of 7% (124). The recommended diet should include < 200 mg/day of cholesterol, < 7% saturated fat, with total fat comprising 25-35% of calories, low simple sugars and increased fruits, vegetables and whole grains (12). Smoking cessation should be instituted in all patients with MetS. Additionally, low dose aspirin is recommended in cases of moderate to high cardiovascular risk where no contraindication to aspirin therapy exists (12). For those patients in whom lifestyle intervention is not sufficient to treat their MetS, pharmacotherapy for the treatment of many of the components of MetS is available.

 

Historically, many of the medications aimed to treat obesity have failed to gain approval or have been removed from the market by the FDA due to side effects and marginal success in weight reduction (125). However, in the last decade, an increasing number of pharmacotherapies have become FDA approved.  Currently available FDA-approved pharmacotherapy for obesity includes phentermine, orlistat, phentermine/topiramate, locaserin, buproprion/naltrexone and liraglutide 3.0 mg.  Further, individuals with morbid obesity (BMI> 40 kg/m2 or >35 kg/m2 with comorbidities) may be candidates for bariatric surgery (126). Bariatric surgery has been demonstrated to be an effective treatment of obesity with improvements in weight, T2DM, hypertension, hyperlipidemia, and sleep apnea.  Resolution rates of each component reported in the literature are variable, the type of surgery highly influential on the resolution of comorbidities (127). Some studies demonstrate superiority of surgical to nonsurgical treatment in weight loss and MetS (128).     

 

There are no pharmacologic agents specifically approved for prediabetes or the prevention of T2DM. In the Diabetes Prevention Program, metformin was shown to lead to weight loss and a 31% decrease in the incidence of T2DM compared to patients receiving placebo (124). It has been suggested that GLP-1 receptor agonists, agents now commonly used in the treatment of established T2DM, may have a role in prevention of T2DM, but more studies are needed. The American Diabetes Association recommends lifestyle modification over medication for the prevention of diabetes. However, they state that metformin therapy may be considered for the prevention of T2DM in individuals with IGT, IFG or HgA1c 5.7-6.4%, especially for those individuals with BMI> 35 kg/m2, those aged < 60 years, and those with a prior diagnosis of GDM (129,130).

 

Elevated blood pressure is first approached with lifestyle modification. If this fails to bring the blood pressure to goal range <140/90 or <130/80 in patients with diabetes or CKD, medication should be added. First line medications include thiazide diuretics in uncomplicated individuals, angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) in those with diabetes, congestive heart failure or CKD, or beta blockers in individuals with angina (131).

 

Drug therapy for dyslipidemia is generally approached with the use of HMG Co-A reductase inhibitors (statins). The primary objective in CVD risk reduction is to lower LDL-C values and the drug of choice for this purposes is statins, which have been shown not only to lower LDL-C, but also to modestly raise HDL-C and lower triglycerides (132). The second targets in lipid improvement to reduce CVD risk are HDL-C and triglycerides. Niacin is effective at raising HDL-C as well as lowering triglycerides and LDL-C. Fibrates are effective at lowering triglycerides but do not have the beneficial effects on HDL-C and LDL-C. Omega-3 polyunsaturated fatty acids (n-3 PUFA) in fish oil can also be used to lower triglycerides with recent data from the REDUCE-IT trial demonstrating a reduced risk of ischemic events in patients with elevated triglycerides despite statin therapy receiving icosapent ethyl.  

 

CONCLUSION

 

The metabolic syndrome is a collection of related risk factors that predispose an individual to the development of T2DM and CVD. It affects a large number of people worldwide and its prevalence is increasing. The diagnostic criteria for MetS have been harmonized for the purpose of providing more consistency in clinical care and research of patients with MetS. Insulin resistance remains at the core of the syndrome, as it did when it was first introduced by Reaven in 1988, and appears to contribute to the development of MetS, via elevated FFA levels and abnormal adipokine profiles. Insulin resistance has both metabolic and mitogenic effects and can result in the development of hyperglycemia and T2DM, hypertension, dyslipidemia, NAFLD, PCOS, OSA, sexual dysfunction, and cancer. In patients with MetS, lifestyle modification is imperative in decreasing the risk of CVD and treating many of the associated conditions. Treatment of the individual conditions is often also required.

 

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Hypothyroidism in Pregnancy

CLINICAL RECOGNITION

The prevalence of overt and subclinical hypothyroidism in pregnancy is 0.3-0.5% and 2-3% respectively. Overt hypothyroidism in pregnancy may present classically but is often subtle and difficult to distinguish from the symptoms of normal pregnancy. A high index of suspicion is therefore required, especially in women with a predisposition to thyroid disease such as a personal or family history of thyroid disease, the presence of goiter or the co-existence of other autoimmune disorders like type 1 diabetes. Subclinical hypothyroidism (high TSH with normal FT4) accounts for the majority of cases. Isolated hypo-thyroxinemia (FT4 below the trimester specific reference range without elevation of TSH) occurs in about an equal number of cases.

PATHOPHYSIOLOGY

Although endemic iodine deficiency (areas where the ambient urinary iodine concentration is less than 50µg/liter) is the most common cause of hypothyroidism worldwide, the main cause in iodine-replete populations is chronic autoimmune thyroiditis. Other causes include post-surgical or post-radioiodine ablation. Adverse effects on mother and child range from anemia in pregnancy to miscarriage, or if pregnancy is continued, preterm birth with its consequences (table 1). Even in an iodine sufficient area maternal thyroid dysfunction (hypothyroidism, subclinical hypothyroidism or hypothyroxinemia) during pregnancy results in neuro-intellectual impairment of the child; hence maternal thyroid hormones are required through gestation for proper fetal brain development. Specific effects will depend on when maternal hormone deficiency occurs during pregnancy. Low maternal thyroid hormone concentrations in early gestation can be associated with significant decrements of IQ of young children. A significant decrement in IQ has also been reported in children born to euthyroid mothers with circulating anti TPO antibodies, but this is not an established association as yet.

 

Table 1. Adverse Outcomes of Pregnancy with Maternal Hypothyroidism

Infertility

Miscarriage

Increased fetal death rate

Anemia in pregnancy

Preeclampsia

Abruptio placenta

Postpartum hemorrhage

Preterm birth

Low birth weight

Increased neonatal respiratory distress

Impaired neurointellectual child development

 

DIAGNOSIS AND DIFFERENTIAL

 

Hypothyroidism is diagnosed on the basis of a low FT4 or TT4 and high TSH. In pregnancy there are changes in the ranges of both these hormones requiring the use of gestational trimester-specific reference ranges. Thyroid antibody testing (thyroid peroxidase antibody) confirms the autoimmune nature of hypothyroidism and may also identify antibody positive women who are at risk of postpartum thyroiditis. Subclinical hypothyroidism is diagnosed when TSH is above the reference range while the T4 level is normal. The TSH level is difficult to interpret during the 1st trimester due to the weak thyromimetic action of hCG. Isolated hypothyroxinemia occurs most frequently in the 3rd trimester. The clinical significance is not clear as it may arise due to hemodilution.

 

Table 2. Etiology and Diagnosis of Hypothyroidism During Pregnancy

Autoimmune thyroiditis:  Positive thyroid antibody test (TPOAb)

Iodine deficiency: Low urinary iodine, Goiter

Post-surgical: History of Graves’ disease, toxic nodular goiter, thyroid cancer, benign goiter

 

Table 3. Patients at Risk of Thyroid Dysfunction (American Thyroid Association Case Finding Criteria)

1.         Age >30 years

2.         History of thyroid dysfunction or positive thyroid antibodies

3.         Type 1 diabetes or other autoimmune disorders

4.         Head or neck radiation

5.         Use of drugs that affect thyroid function

6.         Administration of iodinated contrast materials

7.         Goiter or symptoms or signs of thyroid dysfunction

8.         Residents in areas of moderate to severe iodine deficiency

9.         Multiple prior pregnancies (> 2)

10.       Previous pregnancy loss, preterm delivery, or infertility

11.       Family history of thyroid disease

12.       Morbid obesity (BMI > 40 kg/m2)

 

THERAPY

 

Women with overt hypothyroidism in pregnancy should be treated with levothyroxine, but there is no consensus regarding treatment for women with subclinical hypothyroidism or isolated hypothyroxinemia. Treatment should be considered in women with subclinical hypothyroidism if they have TSH concentrations above 10 mU/L, positive thyroid antibodies, or other risk factors for thyroid disease such as goiter, personal or family history of thyroid autoimmunity, or type 1 diabetes (table 3). Women with infertility or recurrent pregnancy loss could also be treated on the basis that treatment could potentially improve live delivery rates. Treatment of isolated hypothyroxinemia is controversial and is probably not indicated in the 3rd trimester.

 

In women not receiving T4 who may have risk factors for thyroid disease (e.g. personal or family history of an autoimmune disorder, positive thyroid antibodies, Type 1 DM, prior pre-term delivery, possible iodine deficiency, or neck irradiation) thyroid function should be measured pre-conception. If the TSH is above the laboratory reference range, the test should be confirmed, and supplemental thyroxine therapy should be considered, especially if thyroid antibodies or other risk factors for thyroid disease are present (table 3). Women with thyroid autoimmunity who are euthyroid in the early stages of pregnancy are at risk of developing hypothyroidism and should be monitored for elevation of TSH above the normal range for pregnancy.

 

Women receiving T4 for hypothyroidism before pregnancy should have thyroid function checked to maintain TSH levels not higher than 2.5mIU/L in the first trimester and not higher than 3.0mIU/L in subsequent trimesters. As soon as pregnancy is confirmed T4 dose should be increased by 30-50% and TFTs checked every 4 weeks. Note that TSH level is difficult to interpret in the 1st trimester due to HCG action. Not all women require an increase in T4 dosage in pregnancy. Women who are newly diagnosed to be hypothyroid in pregnancy should receive 100µg T4 daily and the dose adjusted after 4 weeks to the optimal level. In summary, women with overt hypothyroidism or with subclinical hypothyroidism who are TPO antibody positive should be treated with oral levothyroxine.

Screening

Because of the proven adverse effects of hypothyroidism on pregnancy, and the failure of testing only women at “high risk” of hypothyroidism (defined above) to detect more than 50% of thyroid problems, a case can be made for screening all women for thyroid function in early pregnancy with administration of levothyroxine in women with subnormal thyroid function. Another recommended approach is to screen only women at “high risk”. However, the issue remains unsettled.

 

FOLLOW-UP

 

In women with previously treated Graves’ hyperthyroidism who are receiving thyroxine for post ablative hypothyroidism the Thyroid Stimulating Hormone Receptor Antibodies (TRAbs) assay may be positive even many years later. The woman should be counselled if another pregnancy is planned to guard against fetal or neonatal hyperthyroidism due to transplacental passage of maternal TRAb. Before a further pregnancy thyroid function should be checked in order to keep the TSH less than 2.5mIU/l. When first pregnant the woman should increase T4 dose by 25-50% (usually by 50 micrograms per day) and then have a further thyroid function test 4 weeks later and at least in every trimester thereafter. About 25% do not require an increase in T4 dose.

 

GUIDELINE

 

Alexander EK, Pearce EN, Brent GA, Brown RS, Chen H, Dosiou C, Grobman WA, Laurberg P, Lazarus JH, Mandel SJ, Peeters RP, Sullivan S. 2017 Guidelines of the American Thyroid Association for the Diagnosis and Management of Thyroid Disease During Pregnancy and the Postpartum. Thyroid. 2017 Mar;27(3):315-389.

REFERENCES

 

Teng W, Shan Z, Patil-Sisodia K, Cooper DS. Hypothyroidism in pregnancy.

Lancet Diabetes Endocrinol. 2013;1:228-237.

 

Krassas GE, Poppe K, Glinoer D. Thyroid function and human reproductive health. Endocr Rev 2010;31:702-755

Lazarus J. Thyroid dysfunction and pregnancy. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, editors. Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000-2016 Jul 21.

 

Okosieme OE, Khan I, Taylor PN. Preconception management of thyroid dysfunction. Clin Endocrinol (Oxf). 2018 Sep;89(3):269-279.

 

 

 

 

 

Hyperthyroidism in Pregnancy

CLINICAL RECOGNITION

 

Hyperthyroidism occurs in approximately 0.2-1.0% of all pregnancies. Most cases are due to Graves’ disease. The clinical recognition of Graves’ disease may prove challenging in pregnancy since the features of normal pregnancy overlap with symptoms of hyperthyroidism. Specific features which may point to Graves’ hyperthyroidism include the presence of a diffuse goiter, ophthalmopathy, or pre-tibial myxedema (Table 1).

 

Table 1. Features of Graves’ Disease

Past history of autoimmune thyroid disease

Family history of autoimmune thyroid disease

Features of hyperthyroidism such as weight loss and heat intolerance

Diffuse goiter

Ophthalmopathy

Pre-tibial myxedema

Proximal myopathy

Nail changes: onycholysis

 

DIAGNOSIS AND DIFFERENTIAL DIAGNOSIS

 

Hyperthyroidism is diagnosed on the basis of elevated trimester specific serum levels of free thyroxine (FT4) or free triiodothyronine (FT3) (or comparable measures of total thyroxine or FTI) and low thyroid stimulating hormone (TSH). In subclinical hyperthyroidism FT4 and FT3 are normal but TSH is low or suppressed to undetectable levels. Treatment is generally not required for subclinical hyperthyroidism in pregnancy. In fact, most instances of a low TSH in early pregnancy are not pathological and are due to TSH suppressive effects of β-human chorionic gonadotrophin (β-HCG). Detection of thyroid stimulating hormone receptor antibodies (TRAbs) in serum is diagnostically helpful in distinguishing Graves’ disease from other pathological and non-pathological causes of a low TSH. Most cases of hyperthyroidism in pregnancy are due to Graves’ disease. Other causes include single or multiple toxic nodules and thyroiditis (Table 2).

 

Table 2. Causes of Hyperthyroidism in Pregnancy

Graves’ disease

Gestational thyrotoxicosis

Single toxic nodule

Toxic multinodular goiter

Subacute thyroiditis

Silent thyroiditis

Thyrotoxicosis factitial

 

It is important to distinguish hyperthyroidism in pregnancy from gestational transient thyrotoxicosis (GTT) which occurs as a result of the thyroid stimulatory actions of β–HCG. GTT is more common than Graves’ disease being diagnosed in about 1-3% of all pregnancies. It may be associated with hyperemesis gravidarum, choriocarcinoma, or hydatiform mole and in rare instances may result from functional mutations which increase TSH receptor hypersensitivity to β-HCG. GTT is typically mild in presentation, self-limiting and rarely requires specific treatment with antithyroid medications (Table 3). While GTT may be difficult to distinguish from Graves’ disease, features such as goiter, ophthalmopathy, or pretibial myxedema are suggestive of Graves’ disease.

 

Table 3. Clinical Differences Between Graves’ Disease in Pregnancy and Gestational Transient Thyrotoxicosis

Graves’ Disease

Gestational Thyrotoxicosis

Past history of thyroid autoimmunity

Family history of thyroid autoimmunity

May exhibit overt hyperthyroid features

Goiter may be present

Ophthalmopathy may be present

TRAb positive

TPOAb positive

No past history of thyroid autoimmunity

No family history of thyroid autoimmunity

May present with hyperemesis, dehydration and   electrolyte imbalance

No goiter

No ophthalmopathy

TRAb negative

TPOAb negative

 

Thyroid Stimulating Hormone Receptor Antibodies (TRAbs)

 Measurement of TRAbs is useful for monitoring for the risk of fetal and neonatal hyperthyroidism (Table 4). The management of such patients can be considered in three categories.

 

Table 4. Measurement of Thyroid Stimulating Hormone Receptor Antibodies (TRAbs)

Patients with active hyperthyroidism

Patients previously treated with radioiodine or surgery

Patients with high TRAb levels require serial fetal monitoring with ultrasonography

 

PATIENTS IN REMISSION FROM HYPERTHYROIDISM

 

Patients who have successfully completed treatment for hyperthyroidism who become pregnant while in remission require close monitoring since there is a risk of relapse in pregnancy. Such patients may continue to harbor TRAbs with the risk of transplacental transfer. This risk is lowest for patients who were treated with antithyroid drugs and it is recommended that TRAbs are checked in early pregnancy in patients who were treated with surgery or radioiodine. If TRAbs are positive in early pregnancy, then fetal monitoring is indicated with repeated measurement of TRAbs at 18-22 weeks, and again at 30-34 weeks if TRAbs continue to be positive.  TRAb levels >5 IU/L or more than 3 times the upper limit of normal is an indication for close fetal or neonatal monitoring due to the high risk of fetal/neonatal hyperthyroidism from transplacental TRAb transfer.

 

PATIENTS CURRENTLY UNDERGOING TREATMENT FOR HYPERTHYROIDISM

 

Women who conceive while on antithyroid treatment should have TRAbs level checked in early pregnancy and again at 18-22 weeks, and at 30-34 weeks if TRAbs continue to be positive. Women of child bearing age with Graves’ disease should be counselled against becoming pregnant until a euthyroid state is achieved.

 

PATIENTS WHO DEVELOP HYPERTHYROIDISM DURING PREGNANCY

 

Patients who develop hyperthyroidism for the first-time during pregnancy are at particular risk of adverse fetal and maternal adverse effects and should be controlled promptly and monitored carefully. TRAB levels should also be checked in late pregnancy to assess the risk of neonatal hyperthyroidism.

 

PATHOPHYSIOLOGY

 

Uncontrolled hyperthyroidism is associated with adverse feto-maternal effects including pre-eclampsia, maternal congestive cardiac failure, miscarriages, premature birth, still-birth, and low birth weight. Furthermore, neonates of hyperthyroid mothers with Graves’ disease are at risk of developing fetal hyperthyroidism and goiter due to the transplacental transfer of TRAbs. Fetal hypothyroidism may also develop due to transplacental transfer of maternal antithyroid drugs or in rare instances from transplacental transfer of maternal blocking TRAbs.

 

THERAPY

 

The natural course of Graves’ disease in pregnancy should be borne in mind during therapy. Due to the immune tolerant state of pregnancy there is a tendency for Graves’ disease to remit towards the latter stages of gestation.

 

Anti-Thyroid Drugs

 

Anti-thyroid drugs are the treatment of choice for hyperthyroidism in pregnancy (Table 5). The lowest effective dose should be used. Treatment should be monitored with FT4 and TSH. These should be measured every 2-4 weeks initially and then 4-6 weekly once thyroid hormone levels are stabilized. FT4 levels should be maintained at or just above the upper limit of the trimester specific reference range.

 

Dose reductions or even cessation of therapy with careful monitoring may be necessary in late pregnancy. The thionamides, propylthiouracil (PTU), methimazole (MMI), and its pro-drug derivative, carbimazole are the antithyroid drugs of choice. Both propylthiouracil and methimazole exhibit similar placental transfer kinetics, have similar effects on fetal and neonatal thyroid function, and are equally safe in lactation. Methimazole has greater efficacy than propylthiouracil and is associated with better compliance since it can be administered once daily whereas propylthiouracil needs to be taken twice or thrice daily. More so a growing number of reports have highlighted the association of propylthiouracil with fatal liver failure. However, methimazole is associated, rarely, with the occurrence of aplasia cutis and methimazole embryopathy in the neonate. Although this risk is slight it is most likely with methimazole administration in early pregnancy during embryogenesis. For the above reasons it is recommended that propylthiouracil is used in the first trimester and that consideration should be given to switching to methimazole in later pregnancy.

 

Table 5. Guidelines for Anti-Thyroid Drugs (ATD) in Pregnancy

PTU is recommended in first trimester

Consider switching to MMI from second trimester

Use lowest effective dose of ATD

Consider reducing dose or stopping ATD in later pregnancy

Monitor treatment with FT4 and TSH: Initially 2-4 weekly, later 4-6 weekly.

Aim for FT4 at or just above the upper end reference range

 

Beta-blocking agents such as propranolol may be used to control severe adrenergic symptoms but should be discontinued once symptoms begin to improve, usually within 2-4 weeks. The combination of thionamides with levothyroxine i.e. block and replace therapy is not recommended in pregnancy as this may lead to fetal hypothyroidism due to disproportionately greater transplacental transfer of antithyroid drugs than levothyroxine. Radioactive iodine is absolutely contraindicated in pregnancy. Adverse effects of radioiodine on fetal thyroid function include fetal hypothyroidism and this is more likely in later pregnancy since the fetal thyroid only starts to actively concentrate iodide from about 12 weeks gestation.

Surgery

 

Thyroidectomy is an option in patients with significant problems with compliance or severe adverse reactions to antithyroid medications. Surgery is best undertaken in the second trimester of pregnancy.

FOLLOW UP

Newborn

Following delivery, the infant of hyperthyroid mothers should be monitored for thyroid dysfunction. Transient neonatal hyperthyroidism due to transplacental transfer of maternal TRAbs is seen in 1-5% of neonates of mothers with Graves’ disease. The presentation may be more obvious after the first few days of life since TRAbs are cleared from the neonatal circulation at a slower rate than maternal antithyroid drugs.

Mothers

Mothers with a past history of hyperthyroidism require regular thyroid function tests after delivery since Graves’ disease may relapse in the postpartum period. Anti-thyroid drugs are safe in lactation and if indicated should be used at the lowest effective dose, preferably administered after breast feeds in divided doses. Women with risk factors for autoimmune thyroid dysfunction may develop postpartum thyroiditis (PPT).  This occurs in 5-9% of pregnancies and is characterized by a transient hyperthyroid phase followed by a hypothyroid phase before return to euthyroidism. The hyperthyroid phase will usually not require treatment but levothyroxine may be given to symptomatic women in the hypothyroid phase. Long term follow-up is necessary due to the risk of permanent hypothyroidism.

GUIDELINES

Alexander EK, Pearce EN, Brent GA, Brown RS, Chen H, Dosiou C, Grobman WA,

Laurberg P, Lazarus JH, Mandel SJ, Peeters RP, Sullivan S. 2017 Guidelines of the

American Thyroid Association for the Diagnosis and Management of Thyroid Disease During Pregnancy and the Postpartum. Thyroid. 2017 Mar;27(3):315-389.

 

REFERENCES

 

Cooper DS, Laurberg P. Hyperthyroidism in pregnancy. Lancet Diabetes

Endocrinol. 2013;1:238-249.

 

Krassas GE, Poppe K, Glinoer D. Thyroid function and human reproductive health. Endocr Rev 2010;31:702-755. 

 

Lazarus J. Thyroid dysfunction and pregnancy. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, editors. Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000-2016 Jul 21.

 

Okosieme OE, Khan I, Taylor PN. Preconception management of thyroid dysfunction. Clin Endocrinol (Oxf). 2018 Sep;89(3):269-279.