Pharmacogenetics of antipsychotic-induced weight gain

Pharmacological Research 49 (2004) 309–329

Pharmacogenetics of antipsychotic-induced weight gain Daniel J. Müller∗ , Pierandrea Muglia, Teresa Fortune, James L. Kennedy Neurogenetics Section, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ont., Canada M5T 1R8 Accepted 23 May 2003

Abstract Weight gain appears to be a serious side effect encountered during treatment with many antipsychotic drugs. Although the propensities of inducing weight gain vary considerably between antipsychotics, weight gain is mostly observed in atypical antipsychotics, increasingly prescribed for a variety of psychiatric disorders. Beside the psychological consequences weight gain may influence patients’ compliance and secondary medical comorbidities related to being overweight may arise, including diabetes, hypertonia, respiratory problems, and some types of cancer. Obesity research generally suggests that a complex system of neurotransmitters, neuropeptides, hormones and immune related factors interact in neural circuits involving at least the hypothalamus, the solitary tract and cortical structures to regulate energy homeostasis and body weight. Antipsychotics that have weight gain inducing properties may disrupt associated pathways at any of these levels, although it remains unclear what the mechanisms of action might be. Given the potential deleterious effects of weight gain, individual predictors of weight gain would be extremely helpful at the beginning of pharmacological treatment with atypical antipsychotics, allowing obesity to be avoided or for counteractive steps such as dietary restrictions to be taken in predisposed individuals. So far, only a few predictors to detect individuals at high risk have been reported and these have limited power. It is likely that genetic factors play a major role in determining individual response to antipsychotics as well as their side effect profile. In this article, we have reviewed literature related to antipsychotic-induced weight gain and have discussed the major issues, before updating the reader on current obesity research findings. Finally, we emphasize previous studies relating to the pharmacogenetics of antipsychotic-induced weight gain. © 2003 Elsevier Ltd. All rights reserved. Keywords: Antipsychotics; Neuroleptics; Weight gain; Obesity; Pharmacogenetics

1. Background—antipsychotics The discovery of antipsychotics (AP) in the 1950s initiated a revolutionary era in the pharmacotherapy of psychopathologic symptoms seen in disorders such as schizophrenia, schizoaffective disorder, or mood-related psychotic symptoms in affective disorders. Since then, many new AP have been invented and clinicians as well as their patients are faced by a remarkable number of AP in clinical practice [1]. Generally, response to AP, including their side effect profile, can rarely be foreseen, meaning that an individualised treatment cannot be achieved before the beginning of the treatment. This is particularly problematic since treatment duration might be prolonged, resulting in more health care costs as well as inducing secondary costs for potential side effect therapies. Side effects ∗ Corresponding author. Tel.: +1-416-535-8501x4421; fax: +1-416-979-4666. E-mail address: daniel [email protected] (D.J. Müller).

1043-6618/$ – see front matter © 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.phrs.2003.05.001

are a common problem resulting from the administration of AP, these may include vegetative symptoms, hormonal changes, abnormal involuntary movements (or extrapyramidal symptoms, EPS) and weight gain. Such side effects are influenced by many factors, including the type and dosage of the AP and the individual’s predisposed response to the AP. Weight gain is a frequently observed side effect with many AP treatments and seems to be underreported and underrecognized in many patients [2,3]. The joining of clozapine to the pharmacopeia of AP, has resulted in AP being formally divided into two classes: the older, conventional or ‘typical’ AP on one side and the newer, novel or ‘atypical’ AP on the other [1] (see Table 1). Whereas EPS and tardive dyskinesia (TD) are common side effects in classical AP [4], these side effects are rarely observed at doses at which atypical AP are clinically effective [5]. Although the current AP class distinction bears limitations, this classification may be helpful to illustrate specific

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Table 1 Examples of ‘typical’ and ‘atypical’ antipsychotics ‘Older’, ‘conventional’ or ‘typical’ antipsychotics

Year of release

‘Newer’, ‘novel’ or ‘atypical’ antipsychotics

Year of release

Chlorpromazine Fluphenazine Thioridazine Haloperidol

1952 1959 1959 1967

Clozapine Risperidone Olanzapine Quetiapine Ziprasidone

1975 1994 1997 1997 2001

(Europe) 1954 (US) (US) (US) (US)

features such as common side effects which are more likely to occur with typical versus atypical AP. The most common side effects caused by atypical AP in current use (e.g. clozapine, olanzapine, risperidone, and quetiapine) include sedation, metabolic side effects such as hyperglycaemia and dyslipdemia, and a considerable gain of weight when compared to most of the classical AP. The underlying pathophysiology of metabolic side effects is not clearly understood and may be related to specific neurotransmitter, endocrinologic or immune modulating systems. Since overweight and obesity also represent a common serious medical problem in the general population, many efforts have been made to unravel the complex pathway involved in energy balance, food intake, satiety and fat storage including studies related to genetic factors [6,7]. Since considerable weight gain is associated with the use of most atypical AP, studies focusing on this side effect may in turn be useful to understand the pathophysiology underlying obesity in non-AP-treated patients.

2. The application of atypical antipsychotics in clinical practice Generally, AP are the primary treatment of choice in schizophrenia, and more broadly, for psychosis. Since the fully developed symptoms of schizophrenia usually occur in the third decade of life and because schizophrenia most commonly displays a chronic course, it has to be kept in mind that affected individuals will usually undergo pharmacotherapy for years, probably decades. Of note, it has been estimated that up to 50% of AP are prescribed for diagnoses other than schizophrenia [8]. This is due to the fact that AP treat a variety of symptoms which are encountered in schizophrenia as well as in other psychiatric disorders (e.g. psychomotor agitation may be present in schizophrenia as well as in manic episodes within bipolar affective disorder, mental retardation or dementia). A current review of the literature strongly suggests that in general, atypical AP are increasingly prescribed for inpatients [9] who are most likely being treated for schizophrenic and schizoaffective disorders [10], bipolar affective disorders [11–13] or dementia [14]. Furthermore, atypical AP are recommended and prescribed to individuals meeting criteria for first psychotic episode [15]. Taken together with the

(Europe) 1990 (US) (US) (US) (US) (US)

introduction of depot formulation for atypical AP such as risperidone [16] and the recent approval for olanzapine in the indication of acute mania by the Food and Drug Administration (FDA), it is more than evident that their application will increase in the near future. Atypical AP in combination with other mood stabilizers are increasingly prescribed for schizoaffective or bipolar disorder [17–25], also for bipolar-I ‘rapid cycling’ courses [26] and treatment resistant depression [27]. Since mood stabilizers such as lithium or valproic acid are also associated with weight gain, the additional effect of weight increase related with the use of atypical AP is likely to be of greater concern. The use of atypical AP in these disorders has been extended over the past years in both schizophrenia of the elderly [28] and in child and adolescent psychiatry, where weight gain has been shown to have dramatic effects [29–33] which may not be explained by an expected gain in weight in this population. Moreover, atypical AP are prescribed in pervasive developmental disorders [34–43], mental retardation [44–46] or in individuals with a combination of these disorders [47–53]. Several studies indicate that atypical AP are used for the treatment of tic disorders [54] including Gilles-de-la-Tourette syndrome [55–57], treatment resistant obsessive compulsive disorders (OCD) [58], attention deficit hyperactivity disorder (ADHD) [59], and borderline personality disorders [60]. In neurology, atypical AP have successfully been administered to patients with Parkinson syndrome to treat l-DOPA-induced psychosis [61] and in patients displaying psychotic features suffering from juvenile neuronal ceroid lipofuscinosis (JNCL) [62]. In each of the cited studies, an atypical AP such as clozapine, risperidone, olanzapine or quetiapine was administered. All these atypical AP have the propensity to induce weight gain, an adverse reaction reported in most of the cited studies. In contrast, AP-induced weight gain is a desirable effect in eating disorders as anorexia nervosa and in palliative care medicine for cachexia [63–67]. Atypical AP have produced weight gain in anorectic patients, however, it seems unclear if weight gain was the consequence of metabolic changes or an indirect consequence caused by the reduction of a distorted body image perception. In conclusion, atypical AP are increasingly prescribed for various psychiatric disorders and/or medical conditions and therefore, the incidence of their specific side effect profile is also likely to increase.

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Table 2 Weight classification by Body Mass Index (BMI), waist circumference and associated disease risk [7] WHO classification and NHLBI terminology [7]

BMI (kg/m2 )

Underweight Normal range Preobese/overweight Obesity class 1 Obesity class 2 Obesity class 3/extreme obesity

<18.5 18.5–24.9 25.0–29.9 30.0–34.9 35.0–39.9 ≥40.0

a b

Disease riska relative to normal weight and waist circumferenceb Men ≤ 102 cm Women ≤ 88 cm

>102 cm >88 cm

– – Increased High Very high Extremely high

– – High Very high Very high Extremely high

Disease risk for type 2 diabetes, hypertension and cardiovascular disease. Increased waist circumference can also be a marker for increased risk even in persons of normal weight.

3. Weight gain, overweight and obesity It is generally well known that the definition of ‘normal’ weight may be biased by subjective perceptions related to personal beliefs, cultural backgrounds and other factors [68]. In clinical terms, obesity is defined as an abnormally high percentage of body fat. Many techniques have been presented to measure body fat, for example, computed tomography (CT) and magnetic resonance imaging (MRI) both offer high accuracy and the advantage of measuring regional fat [69]. This is important, because abdominal fat out of proportion to total body fat is an independent predictor of health risk and morbidity [7]. However, the difficulty of use and the high costs associated with techniques such as CT and MRI strongly limits their practical use. A simpler, easier to use and economic method, which offers high accuracy when estimating body fat is the ‘Body Mass Index’ (BMI) ratio, although it has limitations as it does not measure regional fat. The BMI is widely used in clinical practice and is calculated as weight (kg)/height squared (m2 ). Overweight and obesity are defined by a BMI over 25 and 30 kg/m2 , respectively. Mortality rates are slightly elevated with a BMI between 25 and 25.9 kg/m2 , however, there is a dramatic increase of mortality in the clinically obese (BMI > 30 kg/m2 ) [7]. Since waist circumference is positively correlated with abdominal fat content, this easy to use technique may also be used to assess morbidity risks associated with abdominal fat. Additionally, the measurement of the hip circumference allows the calculation of the waist-hip-ratio (WHR), which is also used as an indicator for abdominal adipose tissue [69]. Weight classification by BMI and its associated disease risks are shown in Table 2 [7]. Most AP induce weight gain but little is known about where and how the increased mass is distributed in humans. One study addressed this question in patients following olanzapine treatment and showed that weight gain was mainly attributable to an increase in body fat and not to an increase of water content [70]. Of particular interest is the question of how body fat is distributed, due to the important implications of aforementioned disease risks. Two studies have shown that AP-induced weight gain is mainly distributed centrally as demonstrated by the WHR measurements [71,72], which were even more pronounced

in females than in males [71]. If replicated in larger studies using more sophisticated methods to measure abdominal adiposity, the effect of AP-induced weight gain may have a severe impact on cardiovascular morbidity in these patients.

4. Overweight, obesity and clinical consequences Medical conditions relating to overweight and obesity are shown in Table 3. Obesity has been most commonly associated with hypertension, type II diabetes mellitus, coronary heat disease and stroke [73]. Not surprisingly, obesity is associated with reduced life expectancy, for example, a white man aged 20–30 years with a BMI over 45 may have his lifespan reduced on average by 13 years because of obesity [74]. It has therefore been hypothesised that being overweight or obese may significantly counterbalance benefits from the medical progress which has been made in other areas [74]. For a variety of reasons, patients with schizophrenia are even more likely to experience the negative consequences of weight gain: Firstly, for unknown reasons, some AP induce diabetes mellitus, diabetic ketoacidosis or lipid abnormalities per se, regardless of prior weight gain [75–85]. In this subgroup of patients, weight gain is likely to enhance metabolic abnormalities. Secondly, patients with schizophrenia generally receive poor medical care [86]. Medical conditions associated with weight will, therefore, be less intensively treated, creating more health Table 3 Disease risk in obesity Medical conditions related to overweight and obesity Diabetes type II Hypertension Coronary artery disease Cerberovascular disease Gallstones Osteoarthritis/joint disease Respiratory dysfunction/sleep apnea Impaired fertility Menstrual abnormalities Pregnancy risks (neural tube defects) Cancer (gallbladder, colon, endometrium, breast, prostate)

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damage. Thirdly, smoking is common in patients with schizophrenia. This constitutes another serious risk factor for cardiovascular diseases [87]. Finally, with our cultural emphasis on being slender, obesity can lead to stigmatisation which in turn creates social disadvantages in obtaining employment, a residence, an education and a spouse [7]. Considering that social exclusion or stigmatisation of mental disorders is common, patients who are both mentally ill and obese are likely to encounter ‘double’ stigmatisation. By using data from the Framingham Heart Study, Fontaine et al. [88] estimated that a 10 kg weight gain induced by atypical AP would induce deleterious effects on mortality and health. The authors concluded that “. . . lives saved via the antisuicidal effects of clozapine over 10 years may essentially be offset by the deaths due to weight gain because 492 estimated suicides in 100,000 schizophrenic patients would be prevented over a period of 10 years using clozapine compared to 416 additional deaths due to AP-induced weight gain” [88].

5. Weight gain as perceived by patients It should be emphasized that AP have been clearly demonstrated to be widely beneficial to patients suffering from schizophrenia and other mental disorders treated with AP. However, there is strong evidence that patients affected by psychosis perceive weight gain and its consequences as being extremely unpleasant. A German survey of 565 schizophrenic patients indicated that after EPS and sedation, weight gain was the most distressing side effect [89]. Relatives of schizophrenic patients stated that weight gain was the second most unpleasant side effect [90]. A British survey of individuals treated with AP reported weight gain as the most distressing side effect, particularly in women [91]. Clearly, patients opposed to side effects such as weight gain are more likely to discontinue their medications and are therefore at risk of a relapse [92]. Within the era of atypical AP, EPS are less likely to occur. Therefore, weight gain is likely to become the most distressing side effect for patients who are being treated in the long term with weight inducing AP.

6. Estimating the differences in magnitude of weight gain between antipsychotics It has often been stated that some individuals don’t gain or even lose weight whereas some individuals may excessively gain weight during treatment with AP [93,94]. It seems that the variability of weight change might not only be explained by a natural interindividual predisposition across patients treated with AP, but has been shown to also depend on the type of AP used [95]. With conventional AP, weight gain was reported after the first years of chlorpromazine treatment in the 1950s [96,97] and was also reported

for depot preparations with conventional AP [2,98]. Although comparisons between distinct AP is limited by the different study designs and recruitment procedures, there is consistency in that two widely used atypical AP, clozapine and olanzapine, confer the most weight gain [95,99–101]. Data reflecting the magnitude of weight gain with atypical AP are most commonly presented as mean values expressed in kilograms (kg), while some studies report the percentage of weight gain in kg and/or BMI. In an often-cited meta-analysis by Allison et al. [100], the propensity of distinct AP to induce weight gain measured in kilograms over a time period of 10 weeks revealed the following ranking: clozapine (+3.99 kg), olanzapine (+3.51 kg), thioridazine/mesoridazine (+3.49 kg), sertindole (+2.92 kg), chlorpromazine (+2.10 kg), and risperidone (+2.0 kg) followed by other AP, whereas ziprasidone induced only very little weight gain (+0.04 kg) and placebo was associated with weight loss (−0.41 kg). Three other atypical AP (quetiapine, zotepine and amisulpride) were not included in the analyses. As for quetiapine, weight gain observed from short-term studies (up to 6 weeks) ranged from 1.8 to 5.5 kg [102–104]. In adolescent patients, quetiapine was shown on average to induce weight gain of 3.4 kg over a 8-week period after correction for expected weight gain [105]. In another review of literature focusing on the weight gain liability of AP, quetiapine was ranked in between olanzapine and risperidone [99]. For zotepine and amisulpride, few data are available. A literature review indicated that after 1 month of treatment, zotepine and olanzapine would both confer the most weight gain (+2.3 kg) followed by quetiapine (+1.8 kg) and clozapine (+1.7 kg) [106]. Furthermore, it was suggested that zotepine induced the most weight gain in an older [107] and a more recent retrospective chart analysis [108]. However, another meta analysis suggested that zotepine would induce less weight gain than clozapine, olanzapine and quetiapine [99]. Amisulpride was twice found to induce less weight gain than risperidone [109,110]. Other studies reported similar findings where amisulpride was ranked behind risperidone, zotepine and sertindole [99]. These findings suggest that quetiapine and zotepine both have a high propensity to induce weight gain that is probably only slightly inferior to that of clozapine and olanzapine. Although relatively few data are available for amisulpride, it appears that amisulpride has only a low propensity to induce weight gain. Conclusive interpretation of data is difficult because assessment of weight change has not been standardized in clinical studies that show a remarkable heterogeneity, since they differ notably in terms of demographic, clinical variables, drug dosage, co-medication, information on BMI, etc. Moreover, most of the studies were related to short-term treatment and relatively few studies measured weight gain over more than 10 weeks whereas weight tends to further increase during long-term treatment. Despite the observation that AP-induced weight gain tends to plateau after a given time [100–111], weight gain during long-term treatment

D.J. Müller et al. / Pharmacological Research 49 (2004) 309–329 Table 4 Estimating the differences in magnitude of weight gain between antipsychotics (summary) Risk of weight gain

Atypical AP

Typical AP

Very high/high

Clozapine Olanzapine

High/moderate

Quetiapine Risperidone Zotepine

Chlorpromazine

Low

Amisulpride

Haloperidol

Very low

Ziprasidone

can reach dramatic effects, demonstrated for example by case reports indicating a 40 kg weight gain after 14 months of clozapine treatment [93]. It has also to be taken into account that these data reflect mean values and that some individuals might even have lost weight upon a study trial while others might have gained much more than the mean value would suggest. For the purpose of clarity, a reference should also be made to the percentage of individuals who gained weight. The Federal Drug and Food Administration defines weight gain related to any given drug as an increase of bodyweight of more than 7% before treatment. Based on this definition, one study reports that a 7% increase in body weight was observed in 29% of patients treated with olanzapine, 25% with quetiapine, 18% with risperidone and 9.8% with ziprasidone [112]. In conclusion, a definitive picture cannot be drawn from these studies, however, they may provide approximate values of weight changes in susceptible individuals. Taking these limitations into account, we have used an ordinal scale to rank atypical AP in relation to their propensity of inducing weight gain (Table 4).

7. Which factors correlate with weight gain? Many studies addressed the question of whether or not distinct factors could be correlated with weight gain and could be used as predictors or assigned as being risk factors for AP-induced weight gain. So far, studies have mainly focused on both, factors independent of the pharmacological treatment (e.g. diagnosis, age, gender, ethnicity, cigarette smoking, or baseline BMI) as well as on treatment-dependent factors (increased appetite after treatment begins or length of exposure or dose of AP) [113]. However, for most of these factors investigated data appear either controversial or bear limitations due to the relative reduced number of studies. Furthermore, interpretation may be confounded by publication bias, since negative findings are less likely to be reported. At this point, no specific risk factor has been identified allowing individual prediction with regards to atypical AP-induced weight gain. For example, it is apparent that no conclusive data relating to dose effects exist: An

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inverse relationship was found between clozapine dosage and induced weight gain, where lower doses were correlated with more weight gain [114] contrasted by one significant positive correlation [71] while no relationship was found in other studies [108,115–117]. A positive correlation was reported for risperidone [118] but not found in another study [108]. In the case of olanzapine [111,119,120], quetiapine [121], zotepine and conventional AP [108] no dose dependency was reported with relation to weight gain. When looking for possible gender differences, animal studies suggest that female rats treated with conventional AP are at higher risk of weight gain [122,123], while other clinical studies found males treated with atypical AP (clozapine, olanzapine, risperidone) to be at higher risk for weight gain [119,124,125]. Perhaps the most consistent finding relates to low baseline weight or basal BMI, at least for clozapine [71,117] olanzapine [119,120,126] and risperidone [126,127], indicating that the thinnest patients gain the most weight as opposed to the heaviest who gain the least weight. However, a relationship between initial body weight and weight gain was not replicated in all studies [115,128], and furthermore, it has been speculated that these findings may be an artefact due to regression to the mean: regardless of any treatment, over time thin individuals are more likely to gain weight and heavy individuals are more likely to lose weight [111]. One study [71] addressed the question of whether cessation or a decrease in smoking habits could be related to weight gain in patients treated with clozapine. It had been reported previously that clozapine decreased smoking in outpatients [129], furthermore, there is a well known inverse association between tobacco smoking and body weight [130]. In fact, the study by Frankenburg et al. [71] reported that decreased smoking was significantly associated with subsequent weight gain. Although this relationship may be not surprising at first glance, it is striking that smoking habits have barely been assessed as potential risk or confounding factor when estimating the magnitude of weight gain in AP. We believe that smoking habits merit further studies in this context. As with olanzapine, other factors such as increased appetite [119,126], nonwhite ethnicity/race [119] and being of a young age [119] correlated positively with an increase in weight gain [119,126]. In conclusion, for distinct individuals receiving a specific AP, it is likely that any of these factors confer a higher risk for weight changes, however, to date these findings do not seem robust enough to confidently predict weight gain. Investigation of further risk factors has focused on the hormone leptin and the cytokine tumour necrosis factor-␣ (TNF-␣) including its soluble receptors sTNFR-1/p55 and sTNFR-2/p75 as a marker for weight gain (leptin and the TNF-␣ system will be discussed in more details in the section ‘Mechanisms of weight regulation’). In fact is has been demonstrated that weight gain with clozapine correlates with increased serum levels of TNF-␣, sTNFR-1/p55 and sTNFR-2/p75 [131,132], while weight gain with olanzapine and amitriptyline (an antidepressant with the propensity to induce weight

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gain) did not induce a significant increase of the TNF-␣ molecule. In contrast, an increase of sTNFR-1/p75 serum levels in those who gained weight has been observed with clozapine, olanzapine, amitriptyline and lithium (reviewed in [133]). Therefore, it has been suggested that the activation of the TNF-␣ system may play a major role in weight gain with psychotropic treatment and may predict the propensity of a given drug to induce weight gain. However, as no linear relationship was reported between the increases in weight/BMI and the increases in sTNFR-p75 plasma levels, the magnitude of individual weight gain does not appear to become predictable [134]. A recent study comprising 22 patients reported that an early and pronounced increase of leptin within two weeks of treatment with clozapine was associated with the lowest weight gain after 6 and 8 months of treatment [135]. If replicated in larger samples, this finding could be a promising tool for estimating the magnitude of weight gain, at least for clozapine, and possibly for other atypical AP who induce leptin expression. Finally, another interesting observation of a monozygotic twin pair revealed that both individuals treated with clozapine for treatment refractory schizophrenia, experienced extensive weight gain which tended towards the same plateau at 131 and 132 kg, or at a BMI of 35.5 and 36.2 kg/m2 , respectively [93]. This finding not only indicates that induced obesity related to atypical AP is likely to have a genetic basis, but that a positive family history might also turn out to be a highly predictive risk factor, likewise for disorders such as schizophrenia and bipolar disorder. To test this hypothesis, further and larger genetic studies on AP-induced weight gain would be required.

8. Pharmacogenetics of antipsychotic-induced weight gain: mechanisms of weight regulation Apparently, AP create an imbalance between energy intake and energy expenditure resulting in weight gain and obesity. At some point(s), the normal pathways of energy balance must be disrupted. Knowledge about the development of weight gain and obesity in otherwise healthy individuals is necessary to assess and to test for the potential risk factors (i.e. candidate genes) of AP-induced weight gain. Obesity related research over the last few decades has consistently led to a concept of energy balance comprising genetic factors, specific neuronal circuits, central and peripheral molecules (e.g. neuropeptides and hormones), as well as monoamine neurotransmitters. We will briefly illustrate what is known today about the complex interactions between these factors. 8.1. Mechanisms of weight regulation—neural circuits, central and peripheral molecules Multiple neural systems interact through neurotransmitters, peptides, hormones and other metabolites within spe-

cific brain areas (e.g. hypothalamus, brainstem, limbic and cortical structures) to integrate information from both internal nutrient sensors and the environment into behavioural, autonomic, and endocrine command signals [136,137]. Energy homeostasis is regulated through this system. It appears to be an extremely stable process in which mechanisms are precisely matched for a long period of time [138–141]. Information about body peripheral energy stores is transmitted to the brain through a variety of hormones that subsequently stimulate central neurons to secrete various neuropetides. Both forms of molecules can further be divided in anabolic (or orexigenic) and catabolic (or anorexigenic) molecules; they respectively promote weight gain or weight loss [6]. Some of these molecules will be presented here and are summarized in Table 5. Probably the most important peripheral ‘adiposity signals’ implicated in the regulation of energy or body weight homeostasis are insulin, secreted from pancreatic ␤-cells and leptin, primarily secreted by fat cells. Both hormones circulate at levels proportional to body fat content and both enter the CNS in proportion to their plasma level [138]. Thus, in the presence of an intact feedback system, elevated plasma levels of insulin or leptin induce mechanisms that induce weight loss. Their prominent role in energetic control mechanisms is supported by observations of mice lacking the CNS-specific insulin receptors (NIRKO mice). NIRKO mice demonstrated increased adipose tissue mass. Humans or mice lacking active copies of the leptin receptors showed dramatic obesity [142–144]. The mechanisms of action between insulin and leptin appear to be tightly linked since obesity occurs in NIRKO mice regardless of the catabolic counter-regulation of elevated leptin plasma levels [143]. This suggests that central insulin resistance induces central leptin resistance. Interestingly, a gradual development of insulin resistance in humans developing obesity over time leads to the same pattern of hyperphagia, obesity and hyperleptinemia with central leptin resistance associated with the development of commonly observed type II diabetes mellitus in obese individuals. The main ‘interface’ between peripheral signals and the central nervous system is located in the arcuate nucleus (ARC) of the hypothalamus, a brain area with high concentrations of leptin and insulin receptors [145], albeit both receptors are found elsewhere in rat brain tissue [146,147]. Specific neurons in the ARC which express insulin and leptin receptors act as sensors for the regulation of energy homeostasis through the initiation of downstream responses, for example, processes for energy intake (appetite) or energy expenditure (thermogenesis). Neurons that are directly regulated by leptin and insulin are referred to as ‘first-order’ neurons while peptides expressed in neurons primarily regulated by synaptic input downstream of first-order neurons are referred to as ‘secondorder’ neurons (or higher). Two different forms of first order neurons exist. They are reciprocally regulated through insulin and leptin receptor stimulation: Catabolic (anorex-

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Table 5 Examples for orexigenic and anorexigenic molecules Neuropeptide Y (NPY)

Pro-opiomelanocortin (POMC)

Anabolic (orexigenic) molecules (conferring weight gain) AGRP (Agouti-related peptide) Orexin A/B Melanin-concentrating hormone (MCH) Ghrelin

Catabolic (anorexigenic) molecules (conferring weight loss) Neuropeptides CART (cocaine and amphetamine-regulated transcript) ␣-Melanocyte-stimulating hormone (␣-MSH) CRH (corticotropin-releasing-hormone), TRH (thyrotropin-releasing-hormone) Peripheral molecules Leptin Insulin Peptide YY3–36 Cholezystokinin Glucagon Glucagon-like peptide-1

igenic) first-order neurons, which express proopiomelanocortin (POMC)/cocaine- and amphetamine-regulated transcript (CART) as well as anabolic (orexigenic) firstorder neurons which express neuropeptide-Y/Agouti-related protein (NPY/AgRP) [139]. Within this conceptualised system, the proportional amount of insulin and leptin (in relation to body fat content) stimulate neuropeptide circuits promoting catabolic metabolism and inhibiting those that promote anabolic metabolism downstream of the ARC such as the caudal brainstem or other brain areas [148]. For example, if the leptin level is high, POMC/CART neurons are stimulated to express POMC, which is subsequently cleaved to melanocortins including ␣-MSH. The ␣-MSH molecule in turn acts as an agonist to melanocortin-4 and melanocortin-3 receptors (MC4R and MC3R) inducing weight loss. In contrast, low leptin levels will tend to inhibit the suppression of NPY/AgRP neurons, where subsequent AgRP release antagonises MC4R and MC3R, which in turn will produce weight gain [139]. Arcuate NPY/AgRP and POMC/CART neurons project towards the lateral hypothalamic area (LHA), the adjacent perifornical area (PFA) and the hypothalamic paraventricular nucleus (PVN) [149,150]. Interestingly, LHA and PVN were formerly respectively defined as the “hunger” or the “satiety” centre, because lesions in the LHA were shown to induce anorexia and weight loss while lesions in the PVN produced hyperphagic obesity. In contrast, stimulation of these areas showed opposite effects [139]. Neurons projecting to the LHA/PF connect with neurons expressing anabolic neuropeptides, including orexins A and B [151]. An over-expression of melanin-concentrating hormones (MCH) in the LHA has been shown to induce weight gain, which suggests that MCH neurons represent an integral part of the former ‘hunger centre’ [152]. From the LHA, neurons project diffusely into the cerebral cortex where they may stimulate the conscious perception of hunger. MCH has also been hypothesised to decrease energy expenditure by suppressing the thyroid axis [139]. Of most interest is the recent development of a new drug (SNAP-7941) which acts as a MCH antagonist and has been shown to inhibit food

intake resulting in a marked decrease of body weight in rats [153]. Within the same study, this drug apparently also produced antidepressant and anxiolytic effects in rats, leading to the hypothesis that MCH might link appetite with mood regulating components. The counter regulation performed by neurons of the PVN also appears to interact with several brain areas, including hypophysiotropic neurons expressing thyrotropin-releasing hormone (TRH), corticotropin-releasing hormone (CRH) and oxytocin. The activation of the neuroendocrine axis finally leads to decreased food intake and increased energy expenditure. This might happen at least partly through the sympathetic nervous system: ␣1 - and ␤3 -adrenergic receptors are expressed in adipose tissue where stimulation results in lipolysis and subsequently frees fatty acids. These fatty acids can in turn be metabolised by mitochondrial uncoupling proteins (UCP) to produce energy and heat [138,139]. As well as insulin and leptin, many other peripheral molecules or hormones involved in energy homeostasis are expressed and secreted into the blood. They then cross the blood–brain barrier to interact with the central nervous system. Catabolic molecules, such as cholecystokinin, glucagon, glucagon-like peptide 1 appear to act as shortacting, food-stimulated satiety signals that contribute to the cessation of food intake and are supposed to target the nucleus of the solitary tract located in the brainstem [139,154]. The gut-derived hormone peptide YY3–36 has similar properties to insulin and leptin. This molecule is released postprandially in proportion to the calories ingested to interact with the Y2 receptor (Y2R) expressed on ARC NPY neurons. This inhibits NPY neurons and results in a decrease of appetite and food intake for up to 12 h in both rodents and humans [155,156]. Only recently has the first anabolic, appetite stimulating peptide, ghrelin been discovered [157]. Ghrelin is primarily implicated in short term regulation of appetite, plasma levels rise precipitously before meals and fall just as quickly after food intake, although it also takes part in the long-term regulation of appetite and body weight [139,158]. Ghrelin is secreted primarily by the stomach and in common with insulin, leptin and peptide YY3–36 , it

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interacts with the NPY/AgRP neurons in the ARC [155]. Evidence for the potency of ghrelin as an inducer of appetite and food intake is seen in another context: Humans affected by the most common form of syndromic obesity, the Prader–Willi syndrome (PWS), have been shown to display highly elevated plasma ghrelin levels when compared to controls [159]. PWS is caused by a deletion of the paternal chromosome 15 on q11-q13 and it may be that genes in that region encode factors that affect ghrelin regulation. Finally, at least some immune modulating factors also appear to be involved in body weight regulation: The aforementioned TNF-␣ system is involved in glucose, protein, and lipid metabolism [160,161]. Plasma levels of all of these molecules are increased in obese humans and decrease with weight loss, suggesting an over-expression in obese individuals [162,163]. Paradoxically, the TNF-␣ system seems to be involved in both weight loss and weight gain, probably depending on the presence of other pro-inflammatory cytokines [164], although it has also been speculated that TNF␣ may only induce weight loss at “supraphysiologic” levels [161]. The TNF-␣ system has been implicated in the development of insulin resistance [165,166] and has for example been linked to the leptin axis by inhibiting leptin production in subcutaneous and omental adipocytes in humans [167]. In summary, energy homeostasis is composed of a variety of different components, which are far more complex than outlined here, and with more, as yet undefined characteristics. It is important to notice that different, redundant, and dynamic pathways or systems are involved in body weight regulation, allowing adaptation and compensatory mechanisms to many possible circumstances. Considering the complexity of the weight regulation system it is not surprising that large-scale research on “antiobesity” drugs has not yet been successful. Indeed, when leptin was discovered, there was hope that leptin substitution might help treat obesity in a way comparable to the treatment of patients with insulin-dependent diabetes mellitus with insulin therapy. Surprisingly, most obese humans have a surfeit of leptin but then developed what many investigators deem “leptin resistance”, which is considered significant in the pathogenesis of obesity [168]. Genetic abnormalities for leptin or its receptor affects very few individuals. Only in these cases leptin treatment seem promising. Research for anti-obesity drugs is now focusing on the molecular pathways downstream of the ARC as has been illustrated for the MCH antagonist SNAP-7941 in rats. 8.2. Mechanisms of weight regulation—the monoamines Monoamines are of particular interest in energy homeostasis because they act as neurotransmitters in many areas of the CNS, have been shown to interact with hunger/satiety regulatory systems and are targeted by drugs with the ability to cause weight changes. Although the exact mechanisms are not known, a large body of evidence indicates that monoaminergic neurotransmission interacts with pathways

responsible for body weight regulation [169]. The binding properties and intrinsic activities of different CNS active drugs (e.g. AP and antidepressants) vary considerably, however, the following monoaminergic systems have been implicated as key systems related to weight regulation: dopamine (DA), norepinephrine (NE), epinephrine (E), serotonin (5HT or 5-hydroxytryptamine), and histamine (H). Many atypical AP achieve their therapeutic efficacy by modulating dopaminergic, histaminergic, adrenergic and serotonergic neurotransmission, suggesting that these effects may be linked to their propensity to induce weight gain. There is a large body of evidence that dopamine is involved in feeding behaviour, however, the mechanisms are not clear yet. Studies with dopamine-deficient mice showed that they became gradually aphagic after birth, dying of starvation soon afterwards and that leptin-deficient mice did not become obese if they were dopamine-deficient at the same time [170,171]. The double mutants mouse (i.e. deficient for dopamine and leptin) do not initiate feeding unless l-DOPA is administered (although they retain the capacity for movement), suggesting that DA is necessary to the leptin–melanocortin pathway in controlling feeding [172]. Hunger, palatability, and conditioned reward all contribute to the motivation to eat. At least two separate processes regulate food intake, one involving the dorsal striatum which maintains caloric requirements and a second involving the nucleus accumbens (NAC) which mediates the rewarding properties of food [173]. In particular, sweet and fatty foods potentiate the release of DA, induce more pleasurable subjective feelings, and are more rewarding both to humans and to animals [174,175]. Almost any mammal, including human beings, will eat beyond their homeostatic caloric needs if presented with highly palatable food [176]. This most likely occurs because the brain taste pathways interface with the brain reward system. Whether dopamine is more important for the prediction of reward rather than the receipt of reward per se is not completely clear. Schultz [177] proposed that the DA response to rewarding stimuli habituates (because the reward is predictably available), and subsequently DA responses transfer to cues that predict or anticipate future rewards. Further animal studies have shown that eating increases dopamine metabolism in the brain [178]. Dopamine released in the NAC has been associated with pleasurable and rewarding events and has been primarily implicated in drug addiction and intracranial self-stimulation, suggesting that it may be involved in the hedonic mechanisms for regulating feeding behaviour. The NAC is strongly connected to the LHA (lateral hypothalamic area) where it is believed to stimulate feeding (reviewed in [176]). Nearly all AP share antidopaminergic activities at least at the dopamine D2 receptors (DRD2) and it may therefore be possible that AP modulate dopaminergic activities in systems regulating appetite, satiety or feeding behaviour. There is evidence that an overdrive of antidopaminergic effects are likely to be perceived as unpleasant to patients since they drive ‘anhedonic feelings’, meaning that primary needs such as emotions,

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sexuality or motivation are negatively affected. Food intake may partly stimulate dopaminergic turnover in specific human brain areas and thus counteracting antidopaminergic effects induced by the application of AP. This is consistent with a finding of decreased availability of (DRD2) in otherwise healthy subjects which has been associated with obesity by PET studies. The same authors speculated that dopamine deficiency might perpetuate pathological eating to compensate for decreased activation of these circuits [173]. Another explanation may be that the rewarding nature of food intake may become more sensitive than normal through the application of AP. Of note, there are case reports of patients with AP-induced weight gain whose eating behaviour increased such that it resembled binge-eating behaviour. This has been observed with both atypical AP [93] and typical AP, as Planansky [96] reported in 1958 that some patients became “voracious” for food. Increased food intake up to binge eating (or ‘eating attacks’) may be the end of an APinduced spectrum of increased appetite or food intake and may be related to the rewarding properties. The involvement of the dopamine pathways in eating behaviour is evident, however, the mechanism between reward and dopamine is complex. Non-dopaminergic systems also contribute importantly to the reward value of food, such as the serotonergic, cannabinoid or opioid system [176,179–181]. In summary, strong evidence exists that dopamine is required for feeding, albeit the exact mechanisms of (inter-) actions are currently speculative. The question, whether there might be a distinct relationship between the affinity of AP for dopamine receptors and the magnitude of weight gain, was raised. However, there is no clear evidence supporting this relationship either for typical or for atypical AP but results do point to another neurotransmitter: An exponential relationship was seen between the maximum weight gain and the relative receptor affinities for the histamine H1 receptor antagonism in AP [101]. This is consistent with another study which found the highest in vitro binding affinities for H1 receptors for olanzapine and clozapine, while the lowest affinities are found for ziprasidone and haloperidol [182]. The administration of l-histidine, which penetrates the blood brain barrier and is subsequently converted into histamine, results in a decreased food intake thus indicating a role for histamine in feeding behaviour. In contrast, weight gain is a well known side effect in antihistamines, for example H1 receptor antagonists that are usually used for treatment of allergic rhinitis or asthma [183]. The same effects were observed in animal studies; H1 antagonists increased food intake, and H1 agonists decreased food intake. It should be noted that these effects were dependent on the brain area in which these agents were injected (reviewed in [184]). The role of the H2−4 receptors in AP appears to be of minor importance, but they also appear to modulate weight gain. In one case study, the H2 antagonist nizatidine was reported to successfully reduce olanzapine-induced weight gain [185]. Animal studies, however, did not indicate a major role for the H2 receptor in

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food intake. As for the H3 receptors, these results are controversial [184] and no data are available on this topic for the recently discovered H4 receptors. Mice studies indicate that the mechanism of action of histamine might be mediated through hypothalamic histamine neurons. These neurons may be directly targeted by leptin and an increase of histamine result in suppressed food intake [186]. In leptin-resistant obese mice central histamine infusion led to suppression of fat deposition in visceral fat and an increase of energy expenditure through the activation of the adrenergic system via uncoupling proteins in brown and white adipose tissue [187]. In conclusion, the histamine H1 receptor appears to be a good candidate for pharmacogenetic studies of AP-induced weight gain. The role of the peripheral adrenergic ␣1 and ␤3 -adrenergic receptors (AR) was briefly discussed earlier. Generally, epinephrine is the key hormone by which the sympathetic nervous system (SNS) targets ␣1,2 and ␤1–3 -AR. The ␤AR are involved in thermogenesis while ␤1–3 -AR and the ␣1 -AR are involved in lipolysis and lipid oxidation. SNS activity has been shown to be decreased in times of starvation [188]. In contrast, the CNS activates the SNS-mediated norepinephrine release in response to food and to cold environments which in turn leads to thermogenesis either through an increase of ATP consumption or to an increase of mitochondrial oxidation of food substrates through the ␤3 AR expressed in brown adipose tissue. However, through ␤3 -AR-mediated expression of the uncoupling protein 1 (UCP-1), the oxidative phosphorylation will be uncoupled and no ATP is synthesized and energy will be entirely converted into heat. This process is named ‘diet-induced thermogenesis’ (DIT) and varies considerably from individual to individual, depending on the genetic make up and the composition of the diet (for review see [189,190]). The power to prevent obesity through activation of the DIT has recently been demonstrated in a study with ‘␤-less mice’ (mice lacking all three ␤-AR). On a chow diet, these mice had a decrease in metabolic rate and developed mild obesity. In contrast, on a high-fat diet, ␤-less mice developed massive obesity compared to wild-type mice. Furthermore, it has been observed that brown adipose tissue, which is mainly involved in DIT, showed a different morphology than in wild type mice [191]. The central stimulation of ␤1 - and ␤2 -adrenergic receptors in the hypothalamic perifornical area has been shown to decrease feeding behaviour in rats [192]. Within the paraventricular nucleus, activation of ␣2 -AR increases food intake, whereas activation of ␣1 -AR suppresses food intake (reviewed in [193]). Of interest, ␣1 -adrenergic agents enhance the leptin transport through the blood–brain barrier in rats, while leptin in turn may increase the tone of the SNS through POMC products [194,195]. Hence, although results are mainly driven by animal studies, it seems likely that the SNS and the adrenergic receptors are involved in human body weight regulation as well. As for patients treated with atypical AP, a recent case report reported that a 6 kg weight

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increase after four weeks of olanzapine treatment was associated with a 4% decrease in daily basal energy expenditure [196]. More studies are needed to elucidate the role of the SNS in humans and in AP-induced weight gain as well. Finally, it has been proven that the serotonergic system is involved in appetite/body weight regulation with some early findings highlighting the considerable interindividual variation in response to drugs targeting the serotonergic system [197]. The serotonin receptor subtype(s) receiving the most attention in previous studies included the 5-HT2A 5-HT2C , and 5-HT1A receptors (e.g. [198,199]). Serotonin agonists or drugs that increase the activity of central serotonin have been used as appetite suppressants. The most prominent drug in this field was d-fenfluramine until it was withdrawn from the market in 1997 due to cardiopulmonary side effects. The mechanism of action comprises serotonergic dorsal raphe nucleus neurons which target POMC neurons in the hypothalamus. Consistent with that, it has been shown in animal studies that POMC neurons are stimulated either through d-fenfluramine or through the 5-HT2C/1B agonist 1-(m-chlorophenyl)piperazine (mCPP). The stimulation is likely to be mediated through 5-HT2C receptors expressed on POMC neurons, which in turn activate the melanocortin pathway through ␣-MSH release along with its subsequent effects on the MC4R and MC3R [200]. Animal studies have shown that antagonism at the 5-HT2A and 5-HT2C increase appetite in rats, while knockout mice for the 5-HT2C receptor became obese due to increased feeding [201,202]. Agonism at the 5-HT1A receptor has been associated with increased food intake [203]. However, generally little is known about where and how serotonergic receptor subtypes are specifically involved in the CNS to regulate appetite. Some evidence suggests that serotonin 5-HT2A receptors are located within the paraventricular nucleus where they are supposed to modulate the orexigenic effects of NPY on food intake [204]. Another study found that an interaction might exist with the leptin axis since leptin has been shown to increase the serotonin turnover [205]. Furthermore, leptin seems to activate serotonergic neurons of the dorsal raphe which in turn project to the hypothalamus in the rat [206]. Altogether, serotonergic metabolism is involved in appetite regulation most likely involving at least the 5-HT2C , 5-HT2A and the 5-HT1A receptors. There is evidence that the role of the monoaminergic transmitters in energy homeostasis is complex and perhaps they are not the major targets in adiposity signals [138]. Atypical AP such as clozapine or quetiapine act as potent 5-HT2A and 5-HT2C antagonists which might explain their propensity to induce weight gain. However, in evidence against this hypothesis is ziprasidone, which induces very little weight gain although it is a potent 5HT2A /5HT2C antagonist. Furthermore, like clozapine and quetiapine, ziprasidone is a partial 5HT1A agonist [207]. It has been speculated that these agents may act either as antagonist or as agonists on the 5-HT1A receptors, depending on their intrinsic activity, receptor density and the synaptic concentration of 5-HT. Thus, ziprasidone might exert the opposite

effect on 5-HT1A receptors compared to clozapine and quetiapine and by this action, prevent weight gain. It has also been pointed out that ziprasidone has a relatively unique high affinity to 5-HT1D receptors, although the role of this receptor in weight regulation is not known at present [208]. The combined antagonism of the H1 , 5-HT2A , 5-HT2C , as well as the partial agonism of the 5-HT1A receptors may be one key feature of atypical AP-induced weight gain [115].

9. Pharmacogenetic findings in antipsychotic-induced weight gain Thus far, pharmacogenetic studies have mainly focused on the relationship between clozapine-induced weight gain and monoamine receptor gene polymorphisms. Furthermore, polymorphisms were tested for association with APinduced weight gain in drug metabolizing genes (CYP1A2 and CYP2D6) and in the TNF-␣ gene. Other drugs included in previous studies other than clozapine were olanzapine, chlorpromazine, risperidone, fluphenazine, and sulpiride. Polymorphisms are common variations of the DNA sequence, which can be located in regulatory regions (e.g. promoter), in non-coding or in coding regions. Polymorphisms may alter the activity or the conformation of the encoded protein which may contribute to the phenotype including the subjective predisposition to AP-induced weight gain. Furthermore, a polymorphism may alter the mRNA stability, thus modulating the translation process. Finally, the possibility remains that the investigated polymorphism is ‘linked’ to another, phenotype-associated variant (meaning that polymorphisms co-occur in the same allele and are in ‘linkage disequilibrium’). Thus, an association with a given polymorphism to a distinct disorder may be not of functional relevance itself but represent a marker for a true genetic variant linked to the disorder or to the phenotype. Table 6 provides an overview of pharmacogenetic studies performed in this field grouped by single studies in chronological order. Here, findings will be summarized and categorized by gene variants according to their pharmacodynamic, pharmacokinetic or immunological profile. 9.1. Pharmacodynamic factors 9.1.1. The dopaminergic system Among the five known dopamine receptors (DRD1–5 ), only the DRD4 receptor gene has been analysed with regards to AP-induced weight gain [209]. Rietschel et al. attempted to test for an association between four of the polymorphisms of the DRD4 gene and clinical response to clozapine as well as numerous side effects including weight gain. The rationale to investigate the DRD4 gene was based on findings that clozapine has a 10-fold higher affinity for DRD4 compared to DRD2 . The study sample consisted of 149 patients of German descent affected with schizophrenia or schizoaffective disorders according to DSM-IV criteria. The

Table 6 Pharmacogenetic studies and antipsychotic induced weight gain Medication

Sample size (n)

Diagnoses

Ethnicity

Period of weight assessment

Polymorphisms

Results

Rietschel et al. [209]

Clozapine

149

Scizophrenia/schizoaffective disorder (DSM-IV)

German

At least 28 days

Non-significant

Rietschel et al. [212] Hong et al. [213]

Clozapine

152

German

At least 28 days

Clozapine

93

Scizophrenia/schizoaffective disorder (DSM-IV) Schizophrenic disorders (DSM-IV)

Four in the DRD4 receptor gene (48-bp repeat in exon 3, 12-bp repeat in exon 1, 13-bp deletion in exon 1, Gly11Arg substitution) One in the 5-HT2C receptor: (Cys23Ser)

Chinese

Monthly, for 4 months

Basile et al. [210]

Clozapine

80

Schizophrenia (DSM-III-R)

Caucasian (58), African American (22)

6 weeks

Ellingrod et al. [220]

Olanzapine

11

Schizophrenia (DSM-III-R and DSM-IV)

Caucasian

Weekly for up to 47 weeks

Hong et al. [211]

Clozapine

88

Schizophrenic disorders (DSM-IV)

Han Chinese

4 months

Reynolds et al. [214]

Chlorpromazine (69) Risperidone (46) Clozapine (4) Fluphenazine (3) Sulpiride (1) Clozapine

123

Schizophrenia (DSM-IV)

Han Chinese

Weekly for up to 10 weeks

One in the 5-HT2C gene (−759C/T)

80

Schizophrenia (DSM-III-R)

6 weeks

One in the 5-HT2C gene (−759C/T)

80

Scizophrenia/schizoaffective disorder

Caucasian (58), African American (22) Han Chinese

4 months

One in the 5-HT2C gene (−759C/T)

Basile et al. [215] Tsai et al. [216]

Clozapine

Four in the serotonergic system: 5-HTT (short/long allele), 5-HT2A (102T/C), 5-HT2C (Cys23Ser), 5-HT6 (267C/T) Four in serotonergic receptors: 5-HT1A (CA-repeat), 5-HT2A (102T/C), 5-HT2A (His452/Tyr), 5-HT2C (Cys23Ser); two in histaminergic receptors: H1 (promoter), H2 (G-1018A); one in the CYP1A2 gene (C → A in the first intron); two adrenergic receptor ADR␣1 (Arg347Cys), ADR␤3 (Trp64Arg); one in the TNF␣ gene (G-308A) Two in the CYPD26 gene (allele 1∗ represents the wild type whereas allele 3∗ and 4∗ represent two distinct polymorphisms) Two in the H1 receptor (Glu349Asp, Leu449Ser)

Non-significant Non-significant

Non-significant (trends for 5-HT2C , ADR␣1 , ADR␤3 , and TNF␣)

Heterozygous (1∗ /3∗ , 1∗ /4∗ ) gained more weight (P = 0.0097) Non-significant for Glu349Asp; all patients were homozygotes for Leu449 Less weight gain with −759T allele (P = 0.003)

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Authors

Hemizygous men with T allele gained more weight (P = 0.047) Non-significant

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investigated DRD4 polymorphisms comprised two repeat polymorphisms, a 12-base pair (bp) repeat (n = 1–3) in exon 1 and a 48 bp repeat unit in exon 3 (n = 2–10), where n is indicative of the number of repeating units present. Other DRD4 polymorphisms included a single nucleotide polymorphism (G31C) resulting in an amino acid substitution at position 11 (Gly11Arg) and one 13-bp deletion in exon 1 at position 235–247. Rietschel et al. [209] found the longer alleles (6–9) of the 48-bp repeat to be over-represented in the subgroup of non-responders (as categorised by “worsening, unchanged or slightly improved” condition) and who received clozapine for a minimum of 56 days (X2 = 13.1, d.f. = 6, P = 0.04). A genotypic association was found for nausea (P = 0.03), another side effect of medication. However, these results lost their level of significance after correction for multiple testing. No association was detected between weight gain (observed in 23.5% of the patients) or with any other side effect and DRD4 polymorphisms. Further analysis between DRD4 polymorphisms with respect to treatment duration, clinical diagnoses, and medication doses revealed negative results. The relatively large sample (n = 149) used in the study [209] suggests that a polymorphism exerting a major effect on AP-induced weight gain should have been detected if present. However, this may not be the case for the 13-bp deletion and the Gly11Arg substitution where observed allele frequencies were very low in this sample (only 6 deletions and only 3 amino acid substitutions were observed). As the authors note, one weakness of the study was that data were collected retrospectively over a time period of 16 years. Furthermore, the vast majority (n = 122) received other AP prior to their treatment with clozapine, therefore, confounding effects on weight gain due to previous AP treatment cannot be ruled out. Finally, the duration of treatment varied considerably (mean 69.3 days, S.D. = 40.2) while only patients receiving clozapine for a minimum of 28 days were included in the analyses which may not be long enough to detect significant weight changes. In conclusion, a relationship between DRD4 polymorphisms and weight gain cannot be excluded at this point despite these negative findings. More research focusing on other polymorphisms within the dopaminergic system and using larger samples are warranted. 9.1.2. The histaminergic system Two different studies have investigated the polymorphisms of the histamine receptors [210,211]. Basile et al. [210] studied the role of a single polymorphism in the promoter region of the histamine 1 receptor (H1 ) gene and the G-1018A polymorphism of the H2 gene. The weight changes in 80 patients with DSM-III-R diagnoses of schizophrenia and who were treated with clozapine were assessed prospectively for a time period of 6 weeks. However, no association could be detected between any of the polymorphisms and weight changes (F = 0.60, d.f. = [2, 71], P = 0.55, n = 73 for the H1 gene and

F = 1.11, d.f. = [2, 48], P = 0.34, n = 50 for the H2 gene). Basile et al. [210] concluded that positive results may have been missed because of the limited sample size and because weight gain was only assessed for a relatively short time period, 6 weeks, yet weight changes are known to continue for a longer period. Although the authors were aware of the heterogenous ethnicity of their sample (58 Caucasians and 22 African Americans) and accounted for it using ethnicity as a covariate in their analysis, this factor may have weakened the results. The patient sample proved to be treatment resistant, meaning that they did not respond sufficiently to prior medication. This implies that the patient sample has been skewed towards individuals with a more severe form of psychosis and also that weight gain may have already occurred as a consequence of earlier medication, resulting in a possible bias to the result of the study. Hong et al. [211] tested two polymorphisms in the H1 polymorphism which results in amino acid changes in the encoded protein; at the Glu349Asp and the Leu449Ser codons. The study sample comprised 88 Taiwanese Han Chinese with DSM-IV diagnoses for schizophrenic disorders who were treated with clozapine. Weight changes were assessed at baseline and after four months. All patients were homozygous for the wild-type (449Leu) polymorphism, resulting in only the Glu349Asp variant being entered in to the analyses. Only five patients were heterozygous for the 349Asp allele and nobody was homozygous. No significant association was detected between the 349Asp allele and weight changes. However, given the low frequency and that the sample size was relatively small for a study of a complex phenotype, any conclusions should be regarded as preliminary unless replicated in larger samples. In summary, both studies failed to detect an association between the H1 and H2 gene and weight changes during AP treatment. However, it seems that neither a positive nor a negative relationship should be excluded at this point, due to the limitations of both studies. 9.1.3. The adrenergic system Basile et al. [210] analysed two adrenergic receptor polymorphisms, one in the ␣-1 and one in the ␤-3 receptor. Both polymorphisms are known to change an amino acid within the receptor protein and therefore may alter the protein function. The polymorphism in the ␣-1 receptor changes the amino acid arginine in position 374 to cystein (Arg374Cys). In the same sample as described above, however, no association with weight change could be detected in 60 subjects (F = 1.58, d.f. = [2, 58], P = 0.22). Similarly, no association could be detected between the ␤-3 receptor polymorphism Trp64Arg, and weight change. Of the 73 subjects, the Arg allele was only observed 11 times among the 146 alleles which were studied. However, a tendency toward weight gain with the Trp allele was observed. It might be that this will become significant in replicated studies using larger sample sizes.

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9.1.4. The serotonergic system In 9 published articles focussing on AP-induced weight gain, 6 articles have presented 12 analyses of 4 different serotonin receptor genes and the serotonin transporter gene (5-HTT) [210,212–216]. These 6 articles were published by 4 research groups who used 4 different ‘core’ samples. In total, 216 Chinese, 210 Caucasians and 22 African Americans were included in these studies. Beside 119 patients receiving other drugs [214], the remaining 329 patients were treated with clozapine. All patients were treated for schizophrenic or schizoaffective disorders (see Table 6). However, heterogeneity exists in the clinical course of the patients disorders: Reynolds et al. [214] examined entirely first-episode schizophrenic patients while the other groups performed their analyses with treatment resistant schizophrenics. Further, the duration of the assessment periods varied from a minimum of 28 days [212] to a maximum of 4 months [213,216]. Finally, analyses of weight gain were not homogeneous among studies as the use of covariates varied among studies. Keeping the heterogeneity of the studies in mind, we first try to summarise the findings on the 5-HT2C receptor polymorphisms: By testing for an association with clozapine response Rietschel et al. [212] were the first to analyse the X-linked Cys23Ser polymorphism for clozapine-induced weight gain. The patient sample (n = 152) for the Cys23Ser polymorphism was based on the same sample as in the previous study focussing on the DRD4 gene polymorphisms [209]. It was noted that 25% of the patients gained at least 5% to their baseline weight and that 14.5% gained at least 10% of their original weight after being treated with clozapine. The Ser23 polymorphism has been shown to increase the receptor affinity for m-CPP [217] and has been chosen as a good candidate for the study of clozapine effects. However, no significant association with clinical response or weight gain could be identified. It has been concluded that an existing effect could be too small to be detected within this study sample size. The same Cys23Ser polymorphism was also analysed in the studies of Basile et al. [210] and Hong et al. [213]. The patient sample of Basile et al. [210] comprised 77 patients of the aforementioned study regarding histaminergic and adrenergic polymorphisms. Similarly, the 93 Han Chinese patients treated with clozapine in the sample of Hong et al. [213] was almost the same sample as described for histaminergic polymorphisms (n = 88) [211]. Both studies analysing the Cys23Ser polymorphism failed to detect an association with this polymorphism (F = 0.63, d.f. = [2, 75], P = 0.54 (n = 77) for Basile et al. [210] and P = 0.66 for Hong et al. [213]). Basile et al. [210] did not detect an effect although they corrected for confounding effects including covariates such as sex, ethnicity, pre-treatment baseline weight, and responder/non-responder status. As for Hong et al. [213], only one Han Chinese was carrier of the Cys23Ser polymorphism, precluding meaningful analyses and suggesting a possible ethnicity related variance in the frequency of this polymorphism.

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More recently, Reynolds et al. [214] tested the −759C/T variant of the promoter region of the 5HT2C gene for APinduced weight gain. This followed a report on promoter variants which were shown to be of functional relevance and associated to obesity as well as type II diabetes [218]. The study sample of Reynolds et al. [214] was composed of 123 Han Chinese who were admitted after the first psychotic episode without previous AP treatment and fulfilled the criteria for schizophrenia according to DSM-IV. Subjects with a positive family history for diabetes and eating disorders were excluded. Furthermore, most patients (n = 117) were followed for up to 10 weeks which represents an adequate time period to assess significant weight changes according to the meta analysis of Allison et al. [100]. The sex-specific distribution revealed 16 heterozygous women and 11 hemizygous men for the −759T allele. After 6 weeks of treatment, patients with the −759T variant allele were found to gain less weight than patients with the −759C (or ‘wild-type’) allele (BMI mean increase for the T allele = −0.01 (±0.60) and for the C allele = 0.85 (±0.96); P < 0.0001). Similar results, though moderately less significant, were obtained after 10 weeks (BMI mean increase for the T allele = 0.41 (±1.02) and for the C allele = 1.38 (±1.21); P = 0.0003). A substantial weight gain of more than 7% to the baseline was observed after ten weeks for the −759C allele carriers in 50 subjects, whereas 77 subjects gained less than 7%. For these analyses, similar significant results were obtained after 6 weeks of treatment. Since the 5-HT2C gene is X-linked the impact of a genetic variant may be more pronounced in one of the sexes. Reynolds et al. [214] found that the significance level between men and women was similar after 6 weeks of treatment (P = 0.004 and P = 0.002, respectively), whereas after 10 weeks of treatment the significant effect seemed to be most robust in the male group (P = 0.005 and P = 0.018, respectively). Analyses were not adjusted for the various AP used in this study (see Table 6), however, the authors did consider or adjust for other confounding variables, e.g. initial body-mass index, age, duration of illness and drug dose (in chlorpromazine equivalents). These adjusted analyses revealed no significant association between the variant and women treated for 10 weeks (P = 0.055). Finally, the authors did analyses in various subgroups of patients after six weeks and found significant results for patients with an initial BMI of 17–26 (P = 0.001), and those receiving either chlorpromazine (P = 0.003) or risperidone (P = 0.014) as initial treatment, although these values were not corrected for multiple testing. Nonetheless, these findings support the idea that regulation of the 5-HT2C gene may be involved in AP-induced weight gain. Basile et al. [215] and Tsai et al. [216] attempted to replicate the findings of Reynolds et al. [214]. Basile et al. [215] performed their analyses with their previously described sample (n = 73). Additionally, patients were classified in the gain of weight group according to the 7% threshold used in the study of Reynolds et al. [214]. However, neither anal-

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ysis detected significant findings (P = 0.21 and 0.41, respectively). Sex-specific analysis revealed a trend for men (n = 45) to gain more weight with the −759T allele (7.2 kg versus 3.6 kg; P = 0.047), a result opposite to the finding of Reynolds et al. [214], where patients gained less weight with the −759T allele. Although the frequencies of the −759T allele (28%) was comparable to the study of Reynolds et al. (21%), both studies varied in sample size, ethnicity, medication, phenotypic assessment, and patients ascertainment. Patients in the study of Basile et al. [215] suffered from treatment resistant schizophrenia and received other AP prior to the beginning of the study. Therefore, mixed results may be due to these factors. Tsai et al. [216] included 80 Han Chinese (52 men, 28 females) with schizophrenia and schizoaffective disorder treated with clozapine for 4 months who gained on average 2.1 kg (±4.7). The −759T variant was observed in 13 patients. No significant differences could be detected between genotypes and magnitude of weight gain. Sex-specific analysis revealed no different effects. The authors claim that false positive or false negative findings between them and Reynolds et al. [214] may have arisen or that other factors related to the medication used may represent the most plausible explanation for the failure to replicate their findings. The 5-HT2A gene has been studied for association with clozapine-induced weight gain with the 102T/C variant in two studies [210,213] and for the His452Tyr polymorphisms in [210]. In the study of Hong et al. [213], 93 Chinese patients were genotyped for the 102T/C variant. The 102C allele was observed in 42 heterozygotic and 15 homozygotic patients. Patients carrying at least one copy of the C allele gained less weight than patients carrying the T allele, however, the finding was not significant (P = 0.59). In the study of Basile et al. [210] (n = 77) patients revealed more weight gain in presence of the C allele (42 heterozygotes, 21 homozygotes), although the association was not significant (F = 0.29 d.f. = [2, 75], P = 0.75). The His452Tyr genotypes of 78 patients deriving from the study of Basile et al. [210] detected less weight gain in carriers of the His allele, however, only ten were heterozygous and two homozygous for the His allele. The finding was not significant (F = 0.05, d.f. = [2, 76], P = 0.95). The same study also investigated the potential role of the CA-repeat within the 5-HT1A gene in 73 patients. Five different forms of alleles were observed (1/1, n = 6; 1/2, n = 3; 2/2, n = 60, 2/3, n = 2 and 3/3, n = 2) but no association with weight change was detected. Finally, Hong et al. [213] did analyses on a biallelic polymorphism (short and long allele) in the 5 regulatory region of the serotonin transporter (5HTT) gene and on the 267C/T variant of the 5HT6 receptor gene. The observed frequency of the long allele of the 5HTT gene was 19% and for the 267T allele of the 5HT6 gene 27%. In either analysis, body weight changes were more pronounced in the heterozygotes. No significant weight changes in the analysis of variance were detected for any of the given genotypic combinations.

9.2. Pharmacokinetic factors Basile et al. [210] were the first to analyse a variant in a gene which encodes a protein involved in the metabolism or degradation of clozapine. They assessed the potential role of the C/A polymorphism located in the first intron of the CYP1A2 gene. Carriers of the C-allele have shown less inducibility of the CYP1A2 enzyme in smokers [219]. After genotyping 70 patients, 12 patients were homozygotes for the C allele, 35 were homozygous for the A-allele and 23 were heterozygous [210]. The C homozygotes gained an average of 5.1 kg (±4.1). The A homozygotes gained on average 3.3 kg (±4.4), while 23 heterozygotes gained 2.9 kg (±4.2). The observed differences could not be explained by other than random factors (F = 1.58, d.f. = [2, 68], P = 0.22) [210]. Ellingrod et al. [220] reported a significant association between variants of the CYP2D6 gene and 11 male Caucasian subjects treated with olanzapine for up to 47 weeks. Patients were genotyped for the 1∗ , 3∗ and 4∗ allele variants as described elsewhere [221]. Six patients were homozygous for allele 1∗ and 5 were heterozygous for the 1∗ allele and either the 3∗ or 4∗ allele, while no subjects were homozygous for the 3∗ or 4∗ genotype. Neither of the groups differed significantly for other variables (age, baseline or endpoint BMI, dose or duration of treatment) and no relationship was found between percent change in BMI and smoking or baseline BMI. The mean baseline BMI for patients homozygous for allele 1∗ was 28 (±4.2) and 31.8 (±4.1) at endpoint, while subjects heterozygote for allele 1∗ /3∗ or 1∗ /4∗ had a mean baseline BMI of 24.4 (±4) and a mean endpoint BMI of 31.4 (±6.9). Linear regression analysis including age, smoking status, baseline BMI/weight, olanzapine dose, duration of treatment and interactions as factors in addition to the genotype as independent variable revealed that hetrozygotes (with a 1∗ /3∗ or 1∗ /4∗ genotype) experienced a larger BMI change than those with a 1∗ /∗ 1 genotype (F = 10.69, d.f. = [1, 9], P < 0.0097). Study limitations named by Ellingrod et al. [220] include the retrospective nature of the study, as well as the non assessment of olanzapine serum levels. Furthermore, dietary or activity monitoring was not performed likewise no monitoring was performed for other physiological aspects. The mean duration of treatment and the standard deviation for the groups appears relatively high (15.7±15.4 and 11.6±10.5 months for 1∗ /1∗ and 1∗ /3∗ , 4 allele carriers, respectively). In contrast to other studies, individuals enrolled in the study were exclusively out-patients (personal communication). Ellingrod et al. [220] suggests that being non-homozygous for the 1∗ allele may lead to an increased concentration of olanzapine in the serum, which in turn confers weight gain. This argument is intriguing, however, a relationship between olanzapine levels and weight gain could not be detected in a study by Rao et al. [222]. In conclusion, despite those mentioned limitations, this study indicates that pharmakokinetic factors such as the CYPD26 variants might influence AP-induced

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weight gain. However, this finding should be replicated with a larger patient sample. 9.3. Immunological factors Since immunological factors may also be involved in APinduced weight gain, Basile et al. [210] investigated a polymorphism (G-308A) in the TNF-␣ gene for association with weight change in 74 patients treated with clozapine. The polymorphism was shown to be functionally relevant, that is, carriers of the G/G or G/A genotype were associated with a three-fold reduction in TNF-␣ expression [223]. Theoretically, the A allele would be associated with higher TNF-␣ expression which in turn may cause more weight gain. Analyses revealed that A/A homozygotes (n = 3) gained 7.4 kg (±3.9), G/G homozygotes 3.9 kg (±4.5) and A/G heterozygotes gained only 2.3 kg (±4.1). However, no significant association could be detected (F = 1.94 [d.f. = 2.72], P = 0.15). Future studies investigating genetic factors relating to the immune system and their possible involvement in AP associated weight change are needed.

10. Conclusions and outlook We have reviewed the role of AP in weight gain and observed that most weight gain is induced by some, but not all atypical or novel AP. Atypical AP are increasingly prescribed in clinical practice for a broad range of symptoms and disorders. Although these drugs have many beneficial components patients are also likely to become overweight or obese with a serious impact on general health. Obesity can create psychological distress and stigmatisation in patients who already have to cope with devastating disorders like schizophrenia. Effective long-term treatment preventing obesity is not yet available and it requires further research efforts. Although the field of obesity research is rapidly evolving and promising findings have been made, including the discovery of leptin, the melanocortin pathways or the neuronal circuits involved in weight and energy regulation, little is known about the pathophysiology of either general or AP-induced weight gain. Genetic effects are known to influence obesity and are thus implicated in drug-induced side effects including weight gain. Pharmacogenetics seeks to identify distinct risk factors based on the genetic makeup of the person. Pharmacogenetic studies of AP-induced weight gain have generated mostly negative or controversial results as described in this review. This may point to the complexity of the phenotype where it is likely that many risk factors each with small contribution to the phenotype exist. Therefore, we assume that study findings up to now are limited by the following factors: • Only relatively few samples have been analysed and most studies were originally not designed for the purpose to

• •

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•

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assess AP-induced weight gain. Therefore, many important factors could retrospectively not be included in the analyses (e.g. regular assessments of weight, BMI, dietary controls, previous medication, etc.). Ascertainment strategies varied considerably between studies (e.g. medication, duration of treatment, inpatient versus outpatient status, etc.). Most candidate genes were chosen based on pharmacological properties related to AP. Many genes have not been investigated yet (e.g. polymorphism of melanocortin receptor genes, etc.) and require further investigation. Many polymorphisms analysed in previous studies have low minor allele frequencies. Therefore, statistical power is limited and effects may only become significant in larger sample sizes. In complex traits, many genes contribute to the phenotype with possible interaction among predisposing genes, so that combined effects of different genes have to be considered. So far, the effect of gene interactions has not been considered. Nonetheless, an interesting and significant finding was obtained (P < 0.0001) in AP-induced weight gain for a regulatory variant of the 5-HT2C gene [214]. A recent metaanalysis of association studies have demonstrated that P < 0.001 has a strong predictive power to be replicated in future studies [224], however, the size of the sample has to be large enough to detect the effect.

In conclusion, there is a need of larger and well characterised samples that are specifically assessed for AP-induced weight gain. These samples can only be obtained by collaborative efforts among several research groups. The use of DNA chips capable of testing thousands of different gene variants, typically single nucleotide polymorphisms (SNP), will hopefully detect polymorphisms involved in response and side effects of a given medication. It may take a considerable amount of time and energy until prediction of AP induced weight gain is achieved, however, the first steps toward an individualized treatment have been made. We would like to encourage more research and collaboration in the field of psychiatric pharmacogenetics.

Acknowledgements This work was supported by the Canadian Institutes of Health Research (CIHR) and D.J.M. is recipient of a CIHR postdoctoral fellowship award.

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