Association study of polymorphisms in insulin induced gene 2 (INSIG2) with antipsychotic-induced weight gain in European and African-American schizophrenia patients

Associations of the SREBF2 Gene and INSIG2 Polymorphisms with Obesity and Dyslipidemia in Thai Psychotic Disorder Patients Treated with Risperidone

Background: Patients with psychotic disorders who receive atypical antipsychotic drugs often develop metabolic abnormalities. The sterol regulatory element-binding factor 2 (SREBF2) gene and insulin-induced gene (INSIG) have important roles in lipid metabolism. A previous study indicated that risperidone stimulated both lipogenesis and cholesterogenesis through activation of SREBP2 expression and inhibition of INSIG2. The SREBF2 gene and INSIG2 polymorphisms have been reported to be associated with metabolic abnormalities. Objective: To investigate the association of the SREBF2 gene (rs1052717, rs2267439, and rs2267443) and INSIG2 (rs7566605, rs11123469, and rs17587100) polymorphisms and the presence of obesity and dyslipidemia in Thai psychotic disorder patients treated with risperidone. Methods: All 113 psychiatric patients using risperidone were evaluated for their lipid profile and screened for obesity criteria. We genotyped the SREBF2 gene and INSIG2 polymorphisms using TaqMan real-time polymerase chain reaction. Results: None of the studied SREBF2 gene and INSIG2 SNPs were associated with obesity in Thai psychotic disorder patients receiving risperidone. Nonetheless, the SREBF2 rs2267443 (G/A) A-allele carriers were at a higher risk for hypertriglyceridemia, whereas the INSIG2 rs11123469 (T/C) C-allele carriers had a lower risk for hypertriglyceridemia, after being adjusted for clinical characteristics using multiple logistic regression. Conclusions: Our findings suggest that the SREBF2 gene rs2267443 (G/A) and the INSIG2 rs11123469 (T/C) polymorphisms are associated with dyslipidemia in Thai psychotic disorder patients treated with risperidone. Further studies with prospective designs and larger patient groups are needed.

The association between BDNF levels and risperidone-induced weight gain is dependent on the BDNF Val66Met polymorphism in antipsychotic-naive first episode schizophrenia patients: a 12-week prospective study

A growing number of studies have shown that brain-derived neurotrophic factor (BDNF) is associated with weight gain during antipsychotic treatment in schizophrenia patients. However, there is still a lack of research results in the initial stage of antipsychotic treatment. This study aimed to evaluate the relationship between weight gain caused by risperidone monotherapy for 12 weeks and BDNF level in antipsychotic-naive and first-episode (ANFE) patients with schizophrenia, and we hypothesize that this may depend on BDNF Val66Met gene polymorphism. In a 12-week longitudinal trial, 225 ANFE patients were enrolled and treated with risperidone. Body weight was measured at baseline and during the 12-week follow-up. After treatment, the average weight of ANFE patients increased by 2.6 kg. Furthermore, we found that in patients with Val/Val genotype, the increase in serum BDNF levels was negatively correlated with risperidone-induced weight gain (r = -0.44, p = 0.008). Regression analysis showed that the baseline BDNF level was a predictor of weight gain after treatment (β = -0.45, t = -3.0, p = 0.005). Our results suggest that the BDNF signaling may be involved in weight gain caused by risperidone treatment. Furthermore, the negative association between weight gain and increased BDNF levels during risperidone treatment in ANFE schizophrenia depends on the BDNF Val66Met polymorphism.

Association of CNR1 and INSIG2 polymorphisms with antipsychotics-induced weight gain: a prospective nested case-control study

Weight gain is a frequent and severe adverse reaction in patients taking antipsychotics. The objective was to further investigate in a natural setting influential risk factors associated with clinically significant weight gain. An observational follow-up study was conducted. Patients when initiating treatment with whatever antipsychotic were included; a structured questionnaire was applied at baseline, 3 and 6 months later; a blood sample was obtained. In a nested case-control approach, patients with an increase ≥ 7% of their initial weight were considered as cases, the remaining, as controls. The results showed that, out of 185 patients, 137 completed the 6-month follow-up (cases, 38; controls, 99). Weight gain gradually and significantly increased in cases (baseline, 65.0 kg; 6 months, 74.0 kg) but not in controls (65.6 kg and 65.8 kg, respectively). Age (adjusted OR = 0.97, 95% CI = 0.96-0.99, p = 0.004), olanzapine (adjusted OR = 2.98, 95% CI = 1.13-7.80, p = 0.027) and quetiapine (adjusted OR = 0.25, 95% = 0.07-0.92, p = 0.037) significantly associated with weight gain. An association was also found for the CNR1 (rs1049353) and INSIG2 (rs7566605) polymorphisms. In conclusion, an increased risk of antipsychotics-induced weight gain was observed for younger age and olanzapine, and a relative lower risk for quetiapine. A potential role of CNR1 rs1049353 and INSIG2 rs7566605 polymorphisms is suggested.

Genetic Testing for Antipsychotic Pharmacotherapy: Bench to Bedside

There is growing research interest in learning the genetic basis of response and adverse effects with psychotropic medications, including antipsychotic drugs. However, the clinical utility of information from genetic studies is compromised by their controversial results, primarily due to relatively small effect and sample sizes. Clinical, demographic, and environmental differences in patient cohorts further explain the lack of consistent results from these genetic studies. Furthermore, the availability of psychopharmacological expertise in interpreting clinically meaningful results from genetic assays has been a challenge, one that often results in suboptimal use of genetic testing in clinical practice. These limitations explain the difficulties in the translation of psychopharmacological research in pharmacogenetics and pharmacogenomics from bench to bedside to manage increasingly treatment-refractory psychiatric disorders, especially schizophrenia. Although these shortcomings question the utility of genetic testing in the general population, the commercially available genetic assays are being increasingly utilized to optimize the effectiveness of psychotropic medications in the treatment-refractory patient population, including schizophrenia. In this context, patients with treatment-refractory schizophrenia are among of the most vulnerable patients to be exposed to the debilitating adverse effects from often irrational and high-dose antipsychotic polypharmacy without clinically meaningful benefits. The primary objective of this comprehensive review is to analyze and interpret replicated findings from the genetic studies to identify specific genetic biomarkers that could be utilized to enhance antipsychotic efficacy and tolerability in the treatment-refractory schizophrenia population.

The Burden of Antipsychotic-Induced Weight Gain and Metabolic Syndrome in Children

Antipsychotic medications are critical to child and adolescent psychiatry, from the stabilization of psychotic disorders like schizophrenia, bipolar disorder, and psychotic depression to behavioral treatment of autism spectrum disorder, tic disorders, and pediatric aggression. While effective, these medications carry serious risk of adverse events-most commonly, weight gain and cardiometabolic abnormalities. Negative metabolic consequences affect up to 60% of patients and present a major obstacle to long-term treatment. Since antipsychotics are often chronically prescribed beginning in childhood, cardiometabolic risk accumulates. An increased susceptibility to antipsychotic-induced weight gain (AIWG) has been repeatedly documented in children, particularly rapid weight gain. Associated cardiometabolic abnormalities include central obesity, insulin resistance, dyslipidemia, and systemic inflammation. Lifestyle interventions and medications such as metformin have been proposed to reduce risk but remain limited in efficacy. Furthermore, antipsychotic medications touted to be weight-neutral in adults can cause substantial weight gain in children. A better understanding of the biological underpinnings of AIWG could inform targeted and potentially more fruitful treatments; however, little is known about the underlying mechanism. As yet, modest genetic studies have nominated a few risk genes that explain only a small percentage of the risk. Recent investigations have begun to explore novel potential mechanisms of AIWG, including a role for gut microbiota and microbial metabolites. This article reviews the problem of AIWG and AP metabolic side effects in pediatric populations, proposed mechanisms underlying this serious side effect, and strategies to mitigate adverse impact. We suggest future directions for research efforts that may advance the field and lead to improved clinical interventions.

Exploring Biologic Predictors Response Disparities to Atypical Antipsychotics among Blacks: A Quasi-Systematic Review

Purpose

Management of schizophrenia among Blacks in the United States is affected by persistent disparities. This review explored response to atypical antipsychotics among Blacks compared with other groups to assess systematic variation that may contribute to disparities.

Methods

We conducted a quasi-systematic review of studies reporting response to atypical antipsychotics among Blacks compared with other groups, including effects of genetic variation.

Results

Of 48 identified research articles, 29 assessed differences in outcomes without inclusion of genetic variation and 20 explored effects of genetic variation; of note: one article included both types of data. Analysis of the 29 papers with clinical outcomes only suggests that while data on efficacy and risk of movement disorders were heterogeneous, findings indicate increased risk of metabolic effects and neutropenia among Blacks. Of the 20 articles exploring effects of genetic variation, allelic or genotypic variations involving several genes were associated with altered efficacy or safety among Blacks but not Whites, including risk of decreased response involving variation in DRD4 and DRD1, and improved efficacy associated with variants in DRD2, COMT, and RGS4. Others showed significant improvement in treatment response only among Whites, including variation in DTNBP1, DRD4, and GNB3.

Conclusions

The current analysis can help tailor management among Blacks using an atypical antipsychotic. Heterogeneity in genetic variation effects and response allele frequency suggests that pharmacogenetics approaches for atypical antipsychotics will need to explicitly incorporate race and ethnicity.

Molecular pathway analysis associates alterations in obesity-related genes and antipsychotic-induced weight gain

OBJECTIVE

Antipsychotics often induce excessive weight gain. We hypothesised that individuals with genetic variations related to known obesity-risk genes have an increased risk of excessive antipsychotic-induced weight gain (AIWG). This hypothesis was tested in a subset of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) trial data set.

METHODS

The CATIE trial compared effects and side effects of five different antipsychotics through an 18-month period. Based on the maximum weight gain recorded, excessive weight gain was defined as >7% weight gain. Cytoscape and GeneMANIA were instrumental in composing a molecular pathway from eight selected genes linked to obesity. Genetic information on a total of 495.172 single-nucleotide polymorphisms (SNPs) were available from 765 (556 males) individuals. Enrichment test was conducted through ReactomePA and Bioconductor. A permutation test was performed, testing the generated pathway against 105 permutated pathways (p ≤ 0.05). In addition, a standard genome-wide association study (GWAS) analysis was performed.

RESULT

GWAS analysis did not detect significant differences related to excessive weight gain. The pathway generated contained 28 genes. A total of 2067 SNPs were significantly expressed (p < 0.01) within this pathway when comparing excessive weight gainers to the rest of the sample. Affected genes including PPARG and PCSK1 were not previously related to treatment-induced weight gain.

CONCLUSIONS

The molecular pathway composed from high-risk obesity genes was shown to overlap with genetics of patients who gained >7% weight gain during the CATIE trial. This suggests that genes related to obesity compose a pathway of increased risk of excessive AIWG. Further independent analyses are warranted that may confirm or clarify the possible reasoning behind.

A review of clinical pharmacogenetics Studies in African populations

Effective interventions and treatments for complex diseases have been implemented globally, however, coverage in Africa has been comparatively lower due to lack of capacity, clinical applicability and knowledge on the genetic contribution to disease and treatment. Currently, there is a scarcity of genetic data on African populations, which have enormous genetic diversity. Pharmacogenomics studies have the potential to revolutionise treatment of diseases, therefore, African populations are likely to benefit from these approaches to identify likely responders, reduce adverse side effects and optimise drug dosing. This review discusses clinical pharmacogenetics studies conducted in African populations, focusing on studies that examined drug response in complex diseases relevant to healthcare. Several pharmacogenetics associations have emerged from African studies, as have gaps in knowledge.

Progress in Genetic Polymorphisms Related to Lipid Disturbances Induced by Atypical Antipsychotic Drugs

Metabolic side effects such as weight gain and disturbed lipid metabolism are often observed in the treatment of atypical antipsychotic drugs (AAPDs), which contribute to an excessive prevalence of metabolic syndrome among schizophrenic patients. Great individual differences are observed but the underlying mechanisms are still uncertain. Research on pharmacogenomics indicates that gene polymorphisms involved in the pathways controlling food intake and lipid metabolism may play a significant role. In this review, relevant genes (HTR2C, DRD2, LEP, NPY, MC4R, BDNF, MC4R, CNR1, INSIG2, ADRA2A) and genetic polymorphisms related to metabolic side effects of AAPDs especially dyslipidemia were summarized. Apart from clinical studies, in vitro and in vivo evidence is also analyzed to support related theories. The association of central and peripheral mechanisms is emphasized, enabling the possibility of using peripheral gene expression to predict the central status. Novel methodological development of pharmacogenomics is in urgent need, so as to provide references for individualized medication and further to shed some light on the mechanisms underlying AAPD-induced lipid disturbances.

Pharmacogenetic Correlates of Antipsychotic-Induced Weight Gain in the Chinese Population

Antipsychotic-induced weight gain (AIWG) is a common adverse effect of this treatment, particularly with second-generation antipsychotics, and it is a major health problem around the world. We aimed to review the progress of pharmacogenetic studies on AIWG in the Chinese population to compare the results for Chinese with other ethnic populations, identify the limitations and problems of current studies, and provide future research directions in China. Both English and Chinese electronic databases were searched to identify eligible studies. We determined that > 25 single-nucleotide polymorphisms in 19 genes have been investigated in association with AIWG in Chinese patients over the past few decades. HTR2C rs3813929 is the most frequently studied single-nucleotide polymorphism, and it seems to be the most strongly associated with AIWG in the Chinese population. However, many genes that have been reported to be associated with AIWG in other ethnic populations have not been included in Chinese studies. To explain the pharmacogenetic reasons for AIWG in the Chinese population, genome-wide association studies and multiple-center, standard, unified, and large samples are needed.

INSIG2 polymorphism and weight gain, dyslipidemia and serum adiponectin in Finnish patients with schizophrenia treated with clozapine

Aim: To investigate INSIG2's association with obesity, weight change and serum lipid profile during clozapine treatment. Materials & methods: Subjects with schizophrenia (n = 190) were genotyped, identifying seven SNPs. Genetic risk scores (GRSs) were calculated to adiponectin, high-density lipoprotein cholesterol, triglycerides and weight gain. Results: In the model for weight gain, SNPs rs12151787, rs17047733 and rs10490626 were selected. Explanatory variables were BMI (p = 5.05 × 10-5), age (p = 0.003) and GRS (p = 2.81 × 10-5, p = 0.0002 after permutation). No GRS resulted for adiponectin or high-density lipoprotein cholesterol. Rs2161829 and rs10490620 were selected for triglycerides; this GRS was insignificant after permutation. Conclusion: INSIG2 plays a role in weight gain and obesity during clozapine treatment.

Pharmacogenetic Associations of Antipsychotic Drug-Related Weight Gain: A Systematic Review and Meta-analysis

Although weight gain is a serious but variable adverse effect of antipsychotics that has genetic underpinnings, a comprehensive meta-analysis of pharmacogenetics of antipsychotic-related weight gain is missing. In this review, random effects meta-analyses were conducted for dominant and recessive models on associations of specific single nucleotide polymorphisms (SNP) with prospectively assessed antipsychotic-related weight or body mass index (BMI) changes (primary outcome), or categorical increases in weight or BMI (≥7%; secondary outcome). Published studies, identified via systematic database search (last search: December 31, 2014), plus 3 additional cohorts, including 222 antipsychotic-naïve youth, and 81 and 141 first-episode schizophrenia adults, each with patient-level data at 3 or 4 months treatment, were meta-analyzed. Altogether, 72 articles reporting on 46 non-duplicated samples (n = 6700, mean follow-up = 25.1wk) with 38 SNPs from 20 genes/genomic regions were meta-analyzed (for each meta-analysis, studies = 2-20, n = 81-2082). Eleven SNPs from 8 genes were significantly associated with weight or BMI change, and 4 SNPs from 2 genes were significantly associated with categorical weight or BMI increase. Combined, 13 SNPs from 9 genes (Adrenoceptor Alpha-2A [ADRA2A], Adrenoceptor Beta 3 [ADRB3], Brain-Derived Neurotrophic Factor [BDNF], Dopamine Receptor D2 [DRD2], Guanine Nucleotide Binding Protein [GNB3], 5-Hydroxytryptamine (Serotonin) Receptor 2C [HTR2C], Insulin-induced gene 2 [INSIG2], Melanocortin-4 Receptor [MC4R], and Synaptosomal-associated protein, 25kDa [SNAP25]) were significantly associated with antipsychotic-related weight gain (P-values < .05-.001). SNPs in ADRA2A, DRD2, HTR2C, and MC4R had the largest effect sizes (Hedges' g's = 0.30-0.80, ORs = 1.47-1.96). Less prior antipsychotic exposure (pediatric or first episode patients) and short follow-up (1-2 mo) were associated with larger effect sizes. Individual antipsychotics did not significantly moderate effect sizes. In conclusion, antipsychotic-related weight gain is polygenic and associated with specific genetic variants, especially in genes coding for antipsychotic pharmacodynamic targets.

The brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is associated with increased body mass index and insulin resistance measures in bipolar disorder and schizophrenia

OBJECTIVES

We tested the hypothesis that a common functional variant in brain-derived neurotrophic factor (BDNF), Val66Met, which has been shown to be associated with increased body mass index (BMI) in schizophrenia (SCZ) and schizoaffective disorder (SAD), is also associated with antipsychotic-induced weight gain in bipolar disorder (BPD). Association of Val66Met with other metabolic measures, including high- and low-density cholesterol, triglycerides, total cholesterol, fasting blood glucose, and hemoglobin A1c, was also tested.

METHODS

This was a 12-month, prospective, randomized trial of two atypical antipsychotic drugs (APDs) with moderate (risperidone) or high (olanzapine) risk to cause weight gain. Subjects were diagnosed as having BPD (n = 90) and SCZ or SAD (n = 76).

RESULTS

BMI was significantly greater in all diagnoses for Met66 allele carriers at six months (p = 0.01). Met66 carriers with BPD showed a greater increase in the triglycerides/high-density (HDL) cholesterol ratio (p = 0.01), a key marker for metabolic syndrome related to insulin resistance, and log-triglycerides (p = 0.04), after three or six months of treatment. Met66 carriers had the greatest increase in log-triglycerides (p = 0.03) and triglycerides/HDL cholesterol ratio after three months of treatment with risperidone (p = 0.003), and the highest BMI at six months (p = 0.01).

CONCLUSIONS

The positive association of BNDF Val66Met with high BMI values replicates previous findings in patients with SCZ and indicates the BDNF Val66Met genotype as a potential risk factor for obesity and insulin resistance measures in patients with BPD receiving antipsychotics as well.

Association of INSIG2 polymorphism with overweight and LDL in children

Background

Dyslipidemia and overweight are common issues in children. Identifying genetic markers of risk could lead to targeted interventions. A polymorphism of SNP rs7566605 near insulin-induced gene 2 (INSIG2) has been identified as a strong candidate gene for obesity, through its feedback control of lipid synthesis.

Objective

To identify polymorphisms in INSIG2 which are associated with overweight (BMI ≥ 85% for age) and dyslipidemia in children. Hypothesis: The C allele of rs7566605 would be significantly associated with BMI and LDL.

Design/Methods

We genotyped 15 SNPs in/near INSIG2 in 1,058 healthy children (53% non-Hispanic white (NHW), 37% overweight) participating in a school based study. Genotype was compared with BMI and lipid markers, adjusting for age, gender, and puberty.

Results

We found a significant association between the SNP rs12464355 and LDL in NHW children, p < 0.001. The G allele is protective (lower LDL). A different SNP was associated with overweight in NHW: rs17047757. SNP rs7566605 was not associated with overweight or lipid levels.

Conclusions

We identified novel genetic associations between INSIG2 and both overweight and LDL in NHW children. Polymorphisms in INSIG2 may be important in the development of obesity through its effects on lipid regulation.

Association between SREBF2 gene polymorphisms and metabolic syndrome in clozapine-treated patients with schizophrenia

BACKGROUND

Patients with schizophrenia using antipsychotics often develop metabolic side effects, especially with clozapine. Previous studies indicated that antipsychotics could activate the pathway of the sterol regulatory element-binding protein (SREBP). The sterol regulatory element binding transcription factor 2 (SREBF2) gene mainly regulates the cholesterol biosynthetic gene. Therefore, we hypothesized that the SREBF2 gene would be a candidate gene for interindividual variation in drug-induced metabolic syndrome (MetS). In this genetic case-control study, we examined the SREBF2 gene polymorphisms in the risk of MetS patients treated with clozapine.

METHODS

Ten single nucleotide polymorphisms (SNPs) of SREBF2 were genotyped in a CHB (Han Chinese in Beijing, China) population, a sample of 621 schizophrenia patients treated with clozapine. Patients were evaluated for metabolic parameters and screened for the MetS criteria.

RESULTS

The incidence of MetS among all subjects was 41.8% (260/621). Two markers of SREBF2 were associated with MetS induced by clozapine after False Discovery Rate (FDR) correction (rs1052717, corrected Pallele=0.010, corrected Pgenotype=0.022; and rs2267443, corrected Pgenotype=0.015). Patients who received clozapine and carried the A-allele of rs2267443 or rs1052717 had an increased risk of MetS (rs2267443, odds ratio (OR)=1.67, 95% confidence interval (CI): 1.20-2.34; and rs1052717, OR=1.81, 95% CI: 1.15-1.98), adjusted by logistic regression for clinical characteristics.

CONCLUSION

The results suggest that the genetic polymorphisms of SREBF2 gene may be associated with MetS in patients treated with clozapine.

Pharmacogenetics in schizophrenia: a review of clozapine studies

OBJECTIVES

Clozapine is quite effective to treat schizophrenia, but its use is complicated by several factors. Although many patients respond to antipsychotic therapy, about 50% of them exhibit inadequate response, and ineffective medication trials may entail weeks of unremitted illness, potential adverse drug reactions, and treatment nonadherence. This review of the literature sought to describe the main pharmacogenetic studies of clozapine and the genes that potentially influence response to treatment with this medication in schizophrenics.

METHODS

We searched the PubMed database for studies published in English in the last 20 years using keywords related to the topic.

RESULTS AND CONCLUSIONS

Our search yielded 145 studies that met the search and selection criteria. Of these, 21 review articles were excluded. The 124 studies included for analysis showed controversial results. Therefore, efforts to identify key gene mechanisms that will be useful in predicting clozapine response and side effects have not been fully successful. Further studies with new analysis approaches and larger sample sizes are still required.

Pharmacogenetics of antipsychotics

OBJECTIVE

During the past decades, increasing efforts have been invested in studies to unravel the influence of genetic factors on antipsychotic (AP) dosage, treatment response, and occurrence of adverse effects. These studies aimed to improve clinical care by predicting outcome of treatment with APs and thus allowing for individualized treatment strategies. We highlight most important findings obtained through both candidate gene and genome-wide association studies, including pharmacokinetic and pharmacodynamic factors.

METHODS

We reviewed studies on pharmacogenetics of AP response and adverse effects published on PubMed until early 2012. Owing to the high number of published studies, we focused our review on findings that have been replicated in independent studies or are supported by meta-analyses.

RESULTS

Most robust findings were reported for associations between polymorphisms of the cytochrome P450 system, the dopamine and the serotonin transmitter systems, and dosage, treatment response, and adverse effects, such as AP-induced weight gain or tardive dyskinesia. These associations were either detected for specific medications or for classes of APs.

CONCLUSION

First promising and robust results show that pharmacogenetics bear promise for a widespread use in future clinical practice. This will likely be achieved by developing algorithms that will include many genetic variants. However, further investigation is warranted to replicate and validate previous findings, as well as to identify new genetic variants involved in AP response and for replication of existing findings.

Exploratory study on association of genetic variation in TBC1D1 with antipsychotic-induced weight gain

BACKGROUND

Previous studies have shown that antipsychotics with high propensity for antipsychotic-induced weight gain (AIWG) influence glucose transporter type 4 (GLUT4) mediated glucose intake. Variation in the gene encoding TBC1 domain family member 1 (TBC1D1), a Rab-GTPase activating protein regulating GLUT4 trafficking, has been associated with obesity. Therefore, we investigated the impact of TBC1D1 polymorphisms on AIWG.

METHODS

We analyzed rs9852 and rs35859249 in TBC1D1 in 195 schizophrenia subjects treated mostly with clozapine or olanzapine for up to 14 weeks. Association was tested using analysis of variance and analysis of covariance with change (%) from baseline weight as the dependent variable.

RESULTS

Analysis of covariance showed a non-significant trend for lower weight gain in carriers of the T-allele of rs9852 than in C-allele homozygotes (p = 0.063). This effect was more pronounced in the subgroup of patients treated with clozapine or olanzapine (p = 0.024). For rs35859249, no significant association with AIWG could be detected.

CONCLUSIONS

This is the first study examining the association between TBC1D1 and AIWG. The moderate association of rs9852, located in the 3'UTR near a miRNA binding site, indicates an influence of TBC1D1 on AIWG. Further investigations remain necessary to elucidate the role of this gene in AIWG.

Pharmacogenetic Aspects of Antipsychotic Drug-induced Weight Gain - A Critical Review

Treatment with several antipsychotic drugs can result in weight gain, which may lead to further morbidity such as type 2 diabetes and cardiovascular disease via the development of metabolic syndrome. These important and problematic metabolic consequences of antipsychotic drug treatment probably reflect a pharmacological disruption of the mechanisms involved in control of food intake and body weight. The extent of weight gain following antipsychotic drug treatment shows substantial variability between individuals, due in part to genetic factors. Common functional polymorphisms in many candidate genes implicated in the control of body weight and various aspects of energy and lipid metabolism have been investigated for association with weight gain in subjects receiving antipsychotic drug treatment, and with metabolic pathology in chronic schizophrenia. Perhaps the strongest and most replicated findings are the associations with promoter polymorphisms in the 5-HT2C receptor and leptin genes, although many other possible genetic risk factors, including polymorphisms in the fat mass and obesity associated (FTO) gene and genes for the alpha2A adrenoceptor and melanocortin4 receptor, have been reported. Genome-wide association studies (GWAS) have also addressed antipsychotic-induced weight gain and other indicators of metabolic disturbances. However there is as yet little consistency between these studies or between GWAS and classical candidate gene approaches. Identifying common genetic factors associated with drug-induced weight gain and its metabolic consequences may provide opportunities for personalized medicine in the predictive assessment of metabolic risk as well as indicating underlying physiological mechanisms.

Pharmacogenetics of antipsychotic-induced weight gain: review and clinical implications

Second-generation antipsychotics (SGAs), such as risperidone, clozapine and olanzapine, are the most common drug treatments for schizophrenia. SGAs presented an advantage over first-generation antipsychotics (FGAs), particularly regarding avoidance of extrapyramidal symptoms. However, most SGAs, and to a lesser degree FGAs, are linked to substantial weight gain. This substantial weight gain is a leading factor in patient non-compliance and poses significant risk of diabetes, lipid abnormalities (that is, metabolic syndrome) and cardiovascular events including sudden death. The purpose of this article is to review the advances made in the field of pharmacogenetics of antipsychotic-induced weight gain (AIWG). We included all published association studies in AIWG from December 2006 to date using the Medline and ISI web of knowledge databases. There has been considerable progress reaffirming previous findings and discovery of novel genetic factors. The HTR2C and leptin genes are among the most promising, and new evidence suggests that the DRD2, TNF, SNAP-25 and MC4R genes are also prominent risk factors. Further promising findings have been reported in novel susceptibility genes, such as CNR1, MDR1, ADRA1A and INSIG2. More research is required before genetically informed, personalized medicine can be applied to antipsychotic treatment; nevertheless, inroads have been made towards assessing genetic liability and plausible clinical application.

The pharmacogenetics of antipsychotic treatment

There is substantial interindividual variability in the effects of treatment with antipsychotic drugs not only in the emergence of adverse effects but also in symptom response. It is becoming increasingly clear that much of this variability is due to genetic factors; pharmacogenetics is the study of those factors, with the eventual goal of identifying genetic predictors of treatment effects. There have been many reported associations of single nucleotide polymorphisms (SNPs) in candidate genes with the consequences of antipsychotic drug treatment. Thus variations in dopaminergic and serotoninergic genes may influence positive and negative symptom outcome, respectively. Among the adverse effects, tardive dyskinesia and weight gain have been the most studied, with some consistent associations of functional SNPs in genes relating to pharmacological mechanisms. Technological advance has permitted large-scale genome-wide association studies (GWAS), but as yet there are few reports that replicate prior findings with candidate genes. Nevertheless, GWAS may identify associations which provide new clues relating to underlying mechanisms.

Pharmacogenetics of response to antipsychotics in patients with schizophrenia

This review presents the findings of pharmacogenetic studies exploring the influence of gene variants on antipsychotic treatment response, in terms of both symptom improvement and adverse effects, in patients with schizophrenia. Despite numerous studies in the field, replicating findings across different cohorts that include subjects of different ethnic groups has been challenging. It is clear that non-genetic factors have an important contribution to antipsychotic treatment response. Differing clinical, demographic and environmental characteristics of the cohorts studied have added substantial complexity to the interpretation of the positive and negative findings of many studies. Pharmacogenomic genome-wide investigations are beginning to yield interesting data although they have failed to replicate the most robust findings of candidate gene studies, and are limited by the sample size, especially given the need for studying homogeneous cohorts. Most of the studies conducted on cohorts treated with single antipsychotics have investigated clozapine, olanzapine or risperidone response. These studies have provided some of the most replicated associations with treatment efficacy. Serotonergic system gene variants are significantly associated with the efficacy of clozapine and risperidone, but may have less influence on the efficacy of olanzapine. Dopamine D3 receptor polymorphisms have been more strongly associated with the efficacy of clozapine and olanzapine, and D2 genetic variants with the efficacy of risperidone. Serotonin influences the control of feeding behaviour and has been hypothesized to have a role in the development of antipsychotic-induced weight gain. Numerous studies have linked the serotonin receptor 2C (5-HT2C) -759-C/T polymorphism with weight gain. The leptin gene variant, -2548-G/A, has also been associated with weight gain in several studies. Pharmacogenetic studies support the role of cytochrome P450 enzymes and dopamine receptor variants in the development of antipsychotic-induced movement disorders, with a contribution of serotonergic receptors and other gene variants implicated in the mechanism of action of antipsychotics. Clozapine-induced agranulocytosis has been associated with polymorphisms in the major histocompatibility complex gene (HLA).

Pharmacogenetic testing to predict antipsychotic-induced weight gain: a systematic review

Weight gain is an important side effect of antipsychotic drugs. Since the high interindividual difference in weight gain suggests that genetic factors play a role in this weight gain, studies have tried to identify these factors. Most of these studies were carried out in the past few years and focussed largely on receptor polymorphisms, although some tried to explain the variation in weight gain by differences in pharmacokinetics. Unfortunately, the results of these association studies are often conflicting, which makes it hard to apply this genetic knowledge in daily clinical practice. This article summarizes the findings of these association studies and focuses on differences in study methodology in an attempt to explain why study results could have been conflicting. Furthermore, the feasibility of genetic testing in today’s clinical practice is discussed, using a model that consists of four components; analytical validity, clinical validity, clinical utility and ethical, legal and social issues.

Antipsychotic switching for people with schizophrenia who have neuroleptic-induced weight or metabolic problems

BACKGROUND

Weight gain is common for people with schizophrenia and this has serious implications for a patient's health and well being. Switching strategies have been recommended as a management option.

OBJECTIVES

To determine the effects of antipsychotic medication switching as a strategy for reducing or preventing weight gain and metabolic problems in people with schizophrenia.

SEARCH STRATEGY

We searched key databases and the Cochrane Schizophrenia Group's trials register (January 2005 and June 2007), reference sections within relevant papers and contacted the first author of each relevant study and other experts to collect further information.

SELECTION CRITERIA

All clinical randomised controlled trials comparing switching of antipsychotic medication as an intervention for antipsychotic induced weight gain and metabolic problems with continuation of medication and/or other weight loss treatments (pharmacological and non pharmacological) in people with schizophrenia or schizophrenia-like illnesses.

DATA COLLECTION AND ANALYSIS

Studies were reliably selected, quality assessed and data extracted. For dichotomous data we calculated risk ratio (RR) and their 95% confidence intervals (CI) on an intention-to-treat basis, based on a fixed-effect model. The primary outcome measures were weight loss, metabolic syndrome, relapse and general mental state.

MAIN RESULTS

We included four studies for the review with a total of 636 participants. All except one study had a duration of 26 weeks or less. There was a mean weight loss of 1.94 kg (2 RCT, n = 287, CI -3.9 to 0.08) when switched to aripiprazole or quetiapine from olanzapine. BMI also decreased when switched to quetiapine (1 RCT, n = 129, MD -0.52 CI -1.26 to 0.22) and aripiprazole (1 RCT, n = 173, RR 0.28 CI 0.13 to 0.57) from olanzapine.Fasting blood glucose showed a significant decrease when switched to aripiprazole or quetiapine from olanzapine. (2 RCT, MD -2.53 n = 280 CI -2.94 to -2.11). One RCT also showed a favourable lipid profile when switched to aripiprazole but these measures were reported as percentage changes, rather than means with standard deviation.People are less likely to leave the study early if they remain on olanzapine compared to switching to quetiapine or aripiprazole.There was no significant difference in outcomes of mental state, global state, and adverse events between groups which switched medications and those that remained on previous medication. Three different switching strategies were compared and no strategy was found to be superior to the others for outcomes of weight gain, mental state and global state.

AUTHORS' CONCLUSIONS

Evidence from this review suggests that switching antipsychotic medication to one with lesser potential for causing weight gain or metabolic problems could be an effective way to manage these side effects, but the data were weak due to the limited number of trials in this area and small sample sizes. Poor reporting of data also hindered using some trials and outcomes. There was no difference in mental state, global state and other treatment related adverse events between switching to another medication and continuing on the previous one. When the three switching strategies were compared none of them had an advantage over the others in their effects on the primary outcomes considered in this review. Better designed trials with adequate power would provide more convincing evidence for using medication switching as an intervention strategy.

Association study of polymorphisms in cholecystokinin gene and its receptors with antipsychotic induced weight gain in schizophrenia patients

Cholecystokinin (CCK) gene and its receptors play an important role in several biological processes including satiety signaling. Administration of exogenous or endogenously secreted CCK leads to decreased food intake in both rats and humans. Similarly, in rats pretreated with intraperitoneal CCK, antagonists of the CCKA receptor prevent decrease in food intake. The CCKB receptor plays an important role in anxiety and gastric acid secretion. We investigated the role of polymorphisms in the CCK gene (2 SNPs) and its receptors CCKA (4 SNPs) and CCKB (4SNPs, 1 microsatellite, CTn) in antipsychotic induced weight gain (n=215). Weight change (%) from baseline was compared across genotypic groups using analysis of covariance. In the European ancestry patients treated with clozapine or olanzapine a trend of association was observed with the SNP rs2929183 (p=0.10) in CCKBR gene. Carriers of the genotype AA (3.23%±4.8) gained less weight than the AG and GG genotypes (6.50%±6.5; p=0.035). A similar trend was observed for the CTn repeat, where carriers of the LL genotype gained less weight (3.73%±5.41) than the S allele carrying genotypes (6.29%±6.2, p=0.05). In the subjects of African ancestry we observed similar marginal association although with the opposite allele. However, none of these observations would survive corrections for multiple testing. None of the other polymorphisms in either CCK or CCKA receptor genes was associated with weight change (%). In conclusion, CCKB receptor gene may play a role in antipsychotic induced weight gain. However, these observations need to be replicated in a larger and independent sample set.

Insulin-induced gene: a new regulator in lipid metabolism

Insulin-induced genes (Insigs) including Insig-1 and Insig-2, are proteins that mediate sterol regulation of sterol regulatory element-binding protein (SREBP) cleavage-activating protein (SCAP) and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMG-CoA reductase). Insigs perform distinct tasks in the regulation of these effectors: they promote the endoplasmic reticulum (ER) retention of SCAP, but ubiquitin-mediated degradation of HMG-CoA reductase. Through these activities, Insig-1 and Insig-2 influence cholesterol metabolism, lipogenesis, and glucose homeostasis in diverse tissues such as adipose tissue and liver. In this article, we focus on the functions, expression and regulation, gene polymorphisms of Insigs, and their deficiency with diseases.

Physical health care monitoring for people with serious mental illness

BACKGROUND

Current guidance suggests that we should monitor the physical health of people with serious mental illness and there has been a significant financial investment over recent years to provide this.

OBJECTIVES

To assess the effectiveness of physical health monitoring as a means of reducing morbidity, mortality and reduction in quality of life in people with serious mental illness.

SEARCH STRATEGY

We searched the Cochrane Schizophrenia Group Trials Register (October 2009) which is based on regular searches of CINAHL, EMBASE, MEDLINE and PsycINFO.

SELECTION CRITERIA

All randomised or quasi-randomised clinical trials focusing on physical health monitoring versus standard care or comparing i) self monitoring vs monitoring by health care professional; ii) simple vs complex monitoring; iii) specific vs non-specific checks iv) once only vs regular checks or v) comparison of different guidance.

DATA COLLECTION AND ANALYSIS

The authors (GT, AC, SM) independently screened search results and identified three studies as possibly fulfilling the review's criteria. On examination, however, all three were subsequently excluded.

MAIN RESULTS

We did not identify any randomised trials which assessed the effectiveness of physical health monitoring in people with serious mental illness.

AUTHORS' CONCLUSIONS

There is no evidence from randomised trials to support current guidance and practice. Guidance and practice are based on expert consensus, clinical experience and good intentions rather than high quality evidence.