A candidate-gene association study of topiramate-induced weight loss in obese patients with and without type 2 diabetes mellitus.

OBJECTIVE: Clinical response to topiramate can vary greatly in obese patients. Identifying genetic variants associated with treatment response could help gain insight into the mechanism of action of topiramate. Little is known about the relationship between genetic variability and topiramate treatment response. We performed a large-scale candidate-gene study to identify genetic risk factors predictive of topiramate-induced weight loss. METHODS: We collected DNA samples from patients who had previously participated in clinical trials to assess the efficacy of topiramate for the treatment of obesity. A custom chip containing single nucleotide polymorphisms from ∼ 480 candidate genes was utilized to genotype a discovery cohort of 445 obese patients from a clinical study. Variants predictive of topiramate-induced weight loss were identified and further tested in an independent replication cohort of drug-naive, obese patients with type 2 diabetes (N=139). RESULTS: We identified a haplotype in INSR that may contribute to differential topiramate-induced weight loss. Carriers and noncarriers of an INSR haplotype lost 9.1 and 7.0% of body weight, respectively (P = 6.5 × 10(-6), P adj = 0.001). This finding was replicated, with carriers and noncarriers losing 9.5 and 7.3% of body weight, respectively (P Bonf=0.02), in the independent replication cohort. We also identified an SNP in HNF1A that may be associated with topiramate response and an SNP in GRIA3 that may be associated with nonpharmacologic treatment response. CONCLUSION: According to our preliminary findings, genetic variation in the INSR and HNF1A genes may differentially affect weight loss in obese individuals treated with topiramate and genes related to insulin action are implicated in modulating topiramate response. However, these findings need to be further replicated in additional larger samples.

The role of pharmacogenetics in treating central nervous system disorders.

Symptoms of central nervous system (CNS) disorders include abnormalities in both physical and psychological domains. Many drugs indicated for the treatment of CNS disorders are fraught with side effects and/or poor efficacy which impact patients' quality of life and drives non-compliance. Moreover, for many CNS drugs such as antidepressants and antipsychotics, it takes time to determine whether a particular drug is efficacious in an individual patient. To optimize drug treatment for each patient, prescribing physicians often need to raise or lower doses, switch drug classes, or prescribe additional drugs to mitigate side effects, often in a "trial and error" fashion. Pharmacogenetic (PGx) testing, particularly in the realm of CNS therapy, can reduce the unpredictability of this process. By determining a patient's genetic profile, individual therapy parameters may be predicted pre-treatment for drug efficacy, optimal drug dose, and the risk of adverse drug reactions (ADRs). The intent of this review is to highlight the power of PGx testing to predict the likelihood of ADRs and efficacy during the treatment of the following CNS disorders: epilepsy, bipolar disorder, schizophrenia and depression.

Discovery and utilization of haplotypes for pharmacogenetic studies of psychotropic drug response.

The treatment of seriously mentally ill patients is complicated by variability in individual response to psychotropic drugs. Some patients remain treatment refractory even after two to three therapeutic modalities. Other patients experience adverse events that range from mild discomfort, to poor compliance, to life threatening. Genaissance Pharmaceuticals is actively engaged in a candidate gene-based haplotype (HAP Marker) approach to the pharmacogenetics of drug response and adverse events. In the present article, we review reasons why HAP Markers are more useful than single nucleotide polymorphisms (SNPs) for discovering genetic correlations to clinical response. In addition, we review our approach to HAP Marker discovery, which involves discovering SNPs in the functional regions of genes by sequencing, organizing these SNPs into HAP Markers for an index population of ethnically diverse individuals and calculating population frequencies for these HAP Markers. For clinical correlations, HAP Markers are defined and correlated to clinical data using the in-house DecoGen Informatics System. This approach has clear implications for the discovery of psychiatric disease-associated genes as well as for the development of safer, more efficacious psychiatric drugs.

The efficacy profile of vilazodone, a novel antidepressant for the treatment of major depressive disorder.

OBJECTIVE: Vilazodone is a novel serotonin reuptake inhibitor and serotonin 1A receptor partial agonist approved for the treatment of major depressive disorder (MDD). This evaluation presents side-by-side efficacy data from two randomized, double-blind, placebo-controlled, short-term 8-week trials (referred to as randomized controlled trial [RCT]-1 [N = 410] and RCT-2 [N = 481]); efficacy data for demographic and clinical subgroups (derived from pooled RCT data); and effectiveness data from a 52-week, open-label, long-term study (N = 616). The objective is to summarize the efficacy profile of vilazodone at its approved dose of 40 mg/day. METHODS: The main assessment in individual pivotal trials and pooled subgroup analyses was the change from baseline to end of treatment (EOT, 8 weeks) in the Montgomery-Åsberg Depression Rating Scale (MADRS) total score. Mixed-effects repeated-measures analyses were conducted in the placebo-controlled trials. Effectiveness analyses in the long-term study included mean MADRS score change over time. RESULTS: Vilazodone-treated patients in both short-term studies showed greater improvement from baseline to EOT in mean MADRS scores than placebo-treated patients (least-squares mean [LSM] treatment difference: -3.2 [p = 0.001], RCT-1; -2.5 [p = 0.009], RCT-2). Clinical Global Impressions-Improvement mean scores at EOT reflected greater improvement with vilazodone compared with placebo in both studies (LSM treatment difference: -0.4 [p = 0.001], RCT-1; -0.3 [p = 0.004], RCT-2). MADRS response rates were significantly greater among patients receiving vilazodone versus those receiving placebo (RCT-1: 40.4% versus 28.1%, respectively [p = 0.007]; RCT-2: 43.7% versus 30.3%, respectively [p = 0.002]). The greater efficacy of vilazodone versus placebo was consistent for the majority of demographic and MDD characteristic subgroups. In the long-term study, the mean MADRS score improved from 29.9 (baseline) to 11.4 (week 8), 8.2 (week 24), and 7.1 (week 52). CONCLUSION: Vilazodone 40 mg/day resulted in clinically meaningful, statistically significant improvement in MDD symptoms in two placebo-controlled, 8-week studies. Findings are supported by subgroup analysis and open-label, long-term effectiveness data. TRIAL REGISTRATION: Randomized controlled trial 1: ClinicalTrials.gov identifier: NCT00285376, http://ClinicalTrials.gov/ct2/show/NCT00285376 ; randomized controlled trial 2: ClinicalTrials.gov identifier: NCT00683592, http://ClinicalTrials.gov/ct2/show/NCT00683592 ; open-label, long-term study: ClinicalTrials.gov identifier: NCT00644358, http://ClinicalTrials.gov/ct2/show/NCT00644358 .

Candidate gene analysis identifies a polymorphism in HLA-DQB1 associated with clozapine-induced agranulocytosis.

OBJECTIVE: Clozapine is considered to be the most efficacious drug to treat schizophrenia, although it is underutilized, partially due to a side effect of agranulocytosis. This analysis of 74 candidate genes was designed to identify an association between sequence variants and clozapine-induced agranulocytosis (CIA). METHOD: Blood and medical history were collected for 33 CIA cases and 54 clozapine-treated controls enrolled between April 2002 and December 2003. Significant markers from 4 genes were then assessed in an independently collected case-control cohort (49 CIA cases, 78 controls). RESULTS: Sequence variants in 5 genes were found to be associated with CIA in the first cohort: HLA-DQB1, HLA-C, DRD1, NTSR1, and CSF2RB. Sequence variants in HLA-DQB1 were also found to be associated with CIA in the second cohort. After refinement analyses of sequence variants in HLA-DQB1, a single SNP (single nucleotide polymorphism), 6672G>C, was found to be associated with risk for CIA; the odds of CIA are 16.9 times greater in patients who carry this marker compared to those who do not. CONCLUSIONS: A sequence variant (6672G>C) in HLA-DQB1 is associated with increased risk for CIA. This marker identifies a subset of patients with an exceptionally high risk of CIA, 1,175% higher than the overall clozapine-treated population under the current blood-monitoring system. Assessing risk for CIA by testing for this and other genetic variants yet to be determined may be clinically useful when deciding whether to begin or continue treatment with clozapine.