Genetic variation in the GCG and in the GLP1R genes and antipsychotic-induced weight gain

Clinical utility of combinatorial pharmacogenomic testing in depression: A Canadian patient- and rater-blinded, randomized, controlled trial

The pharmacological treatment of depression consists of stages of trial and error, with less than 40% of patients achieving remission during first medication trial. However, in a large, randomized-controlled trial (RCT) in the U.S. ("GUIDED"), significant improvements in response and remission rates were observed in patients who received treatment guided by combinatorial pharmacogenomic testing, compared to treatment-as-usual (TAU). Here we present results from the Canadian "GAPP-MDD" RCT. This 52-week, 3-arm, multi-center, participant- and rater-blinded RCT evaluated clinical outcomes among patients with depression whose treatment was guided by combinatorial pharmacogenomic testing compared to TAU. The primary outcome was symptom improvement (change in 17-item Hamilton Depression Rating Scale, HAM-D17) at week 8. Secondary outcomes included response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. Numerically, patients in the guided-care arm had greater symptom improvement (27.6% versus 22.7%), response (30.3% versus 22.7%), and remission rates (15.7% versus 8.3%) compared to TAU, although these differences were not statistically significant. Given that the GAPP-MDD trial was ultimately underpowered to detect statistically significant differences in patient outcomes, it was assessed in parallel with the larger GUIDED RCT. We observed that relative improvements in response and remission rates were consistent between the GAPP-MDD (33.0% response, 89.0% remission) and GUIDED (31.0% response, 51.0% remission) trials. Together with GUIDED, the results from the GAPP-MDD trial indicate that combinatorial pharmacogenomic testing can be an effective tool to help guide depression treatment in the context of the Canadian healthcare setting (ClinicalTrials.gov NCT02466477).

The pharmacogenetics of treatment with olanzapine

Genetic polymorphism in olanzapine-metabolizing enzymes, transporters and drug targets is associated with alterations in safety and efficacy. The aim of this systematic review is to describe all clinically relevant pharmacogenetic information on olanzapine and to propose clinically actionable variants. Two hundred and eighty-four studies were screened; 76 complied with the inclusion criteria and presented significant associations. DRD2 Taq1A (rs1800497) *A1, LEP -2548 (rs7799039) G and CYP1A2*1F alleles were related to olanzapine effectiveness and safety variability in several studies, with a high level of evidence. DRD2 -141 (rs1799732) Ins, A-241G (rs1799978) G, DRD3 Ser9Gly (rs6280) Gly, HTR2A rs7997012 A, ABCB1 C3435T (rs1045642) T and G2677T/A (rs2032582) T and UGT1A4*3 alleles were related to safety, effectiveness and/or pharmacokinetic variability with moderated level of evidence.

Second-Generation Antipsychotics and Dysregulation of Glucose Metabolism: Beyond Weight Gain

Second-generation antipsychotics (SGAs) are the cornerstone of treatment for schizophrenia because of their high clinical efficacy. However, SGA treatment is associated with severe metabolic alterations and body weight gain, which can increase the risk of type 2 diabetes and cardiovascular disease, and greatly accelerate mortality. Several underlying mechanisms have been proposed for antipsychotic-induced weight gain (AIWG), but some studies suggest that metabolic changes in insulin-sensitive tissues can be triggered before the onset of AIWG. In this review, we give an outlook on current research about the metabolic disturbances provoked by SGAs, with a particular focus on whole-body glucose homeostasis disturbances induced independently of AIWG, lipid dysregulation or adipose tissue disturbances. Specifically, we discuss the mechanistic insights gleamed from cellular and preclinical animal studies that have reported on the impact of SGAs on insulin signaling, endogenous glucose production, glucose uptake and insulin secretion in the liver, skeletal muscle and the endocrine pancreas. Finally, we discuss some of the genetic and epigenetic changes that might explain the different susceptibilities of SGA-treated patients to the metabolic side-effects of antipsychotics.

New findings in pharmacogenetics of schizophrenia

PURPOSE OF REVIEW

This review highlights recent advances in the investigation of genetic factors for antipsychotic response and side effects.

RECENT FINDINGS

Antipsychotics prescribed to treat psychotic symptoms are variable in efficacy and propensity for causing side effects. The major side effects include tardive dyskinesia, antipsychotic-induced weight gain (AIWG), and clozapine-induced agranulocytosis (CIA). Several promising associations of polymorphisms in genes including HSPG2, CNR1, and DPP6 with tardive dyskinesia have been reported. In particular, a functional genetic polymorphism in SLC18A2, which is a target of recently approved tardive dyskinesia medication valbenazine, was associated with tardive dyskinesia. Similarly, several consistent findings primarily from genes modulating energy homeostasis have also been reported (e.g. MC4R, HTR2C). CIA has been consistently associated with polymorphisms in the HLA genes (HLA-DQB1 and HLA-B). The association findings between glutamate system genes and antipsychotic response require additional replications.

SUMMARY

The findings to date are promising and provide us a better understanding of the development of side effects and response to antipsychotics. However, more comprehensive investigations in large, well characterized samples will bring us closer to clinically actionable findings.

Pharmacokinetic Pharmacogenetic Prescribing Guidelines for Antidepressants: A Template for Psychiatric Precision Medicine

Antidepressants are commonly prescribed medications in the United States, and there is increasing interest in individualizing treatment selection for more than 20 US Food and Drug Administration-approved treatments for major depressive disorder. Providing greater precision to pharmacotherapeutic recommendations for individual patients beyond the large-scale clinical trials evidence base can potentially reduce adverse effect toxicity profiles and increase response rates and overall effectiveness. It is increasingly recognized that genetic variation may contribute to this differential risk to benefit ratio and thus provides a unique opportunity to develop pharmacogenetic guidelines for psychiatry. Key studies and concepts that review the rationale for cytochrome P450 2D6 (CYP2D6) and cytochrome P450 2C19 (CYP2C19) genetic testing can be delineated by serum levels, adverse events, and clinical outcome measures (eg, antidepressant response). In this article, we report the evidence that contributed to the implementation of pharmacokinetic pharmacogenetic guidelines for antidepressants primarily metabolized by CYP2D6 and CYP2C19.

Glucagon-like peptide-1 agonists combating clozapine-associated obesity and diabetes

Clozapine is the most effective antipsychotic, but its use is tempered by adverse metabolic effects such as weight gain, glucose intolerance and type II diabetes. Current interventions do not facilitate compelling or sustained improvement in metabolic status. Recent studies suggest that glucagon-like peptide-1 (GLP-1) may play a key role in clozapine's metabolic effects, possibly suggesting that clozapine-associated obesity and diabetes are mediated independently through reduced GLP-1. As a result, GLP-1 agonists could show promise in reversing antipsychotic-induced metabolic derangements, providing mechanistic justification that they may represent a novel approach to treat, and ultimately prevent, both diabetes and obesity in patients on clozapine. GLP-1 agonists are already used for diabetes, and they provide a unique combination of glycaemic improvement and metabolically relevant weight loss in diabetic and non-diabetic patients, in the context of a currently favourable safety profile. Using GLP-1 agonists for clozapine-associated obesity and diabetes could be a potentially effective intervention that may reduce cardiometabolic morbidity and mortality in this vulnerable patient population.

Pharmacogenetics of clozapine treatment response and side-effects in schizophrenia: an update

INTRODUCTION

Clozapine (CLZ) is the most effective treatment for treatment-resistant schizophrenia (SCZ) patients, with potential added benefits of reduction in suicide risk and aggression. However, CLZ is also mainly underused due to its high risk for the potentially lethal side-effect of agranulocytosis as well as weight gain and related metabolic dysregulation. Pharmacogenetics promises to enable the prediction of patient treatment response and risk of adverse effects based on patients' genetics, paving the way toward individualized treatment.

AREA COVERED

This article reviews pharmacogenetics studies of CLZ response and side-effects with a focus on articles from January 2012 to February 2015, as an update to the previous reviews. Pharmacokinetic genes explored primarily include CYP1A2, while pharmacodynamic genes consisted of traditional pharmacogenetic targets such as brain-derived neurotrophic factor as well novel mitochondrial genes, NDUFS-1 and translocator protein.

EXPERT OPINION

Pharmacogenetics is a promising avenue for individualized medication of CLZ in SCZ, with several consistently replicated gene variants predicting CLZ response and side-effects. However, a large proportion of studies have yielded mixed results. Large-scale Genome-wide association studies (e.g., CRESTAR) and targeted gene studies with standardized designs (response measurements, treatment durations, plasma level monitoring) are required for further progress toward clinical translation. Additionally, in order to improve study quality, we recommend accounting for important confounders, including polypharmacy, baseline measurements, treatment duration, gender, and age at onset.

Glucagon-like peptide 1 receptor (GLP1R) haplotypes correlate with altered response to multiple antipsychotics in the CATIE trial

Glucagon-like peptide 1 receptor (GLP1R) signaling has been shown to have antipsychotic properties in animal models and to impact glucose-dependent insulin release, satiety, memory, and learning in man. Previous work has shown that two coding mutations (rs6923761 and rs1042044) are associated with altered insulin release and cortisol levels. We identified four frequently occurring haplotypes in Caucasians, haplotype 1 through haplotype 4, spanning exons 4-7 and containing the two coding variants. We analyzed response to antipsychotics, defined as predicted change in PANSS-Total (dPANSS) at 18 months, in Caucasian subjects from the Clinical Antipsychotic Trial of Intervention Effectiveness treated with olanzapine (n=139), perphenazine (n=78), quetiapine (n=14), risperidone (n=143), and ziprasidone (n=90). Haplotype trend regression analysis revealed significant associations with dPANSS for olanzapine (best p=0.002), perphenazine (best p=0.01), quetiapine (best p=0.008), risperidone (best p=0.02), and ziprasidone (best p=0.007). We also evaluated genetic models for the two most common haplotypes. Haplotype 1 (uniquely including the rs1042044 [Leu(260)] allele) was associated with better response to olanzapine (p=0.002), and risperidone (p=0.006), and worse response to perphenazine (p=.03), and ziprasidone (p=0.003), with a recessive genetic model providing the best fit. Haplotype 2 (uniquely including the rs6923761 [Ser(168)] allele) was associated with better response to perphenazine (p=0.001) and worse response to olanzapine (p=.02), with a dominant genetic model providing the best fit. However, GLP1R haplotypes were not associated with antipsychotic-induced weight gain. These results link functional genetic variants in GLP1R to antipsychotic response.

No evidence for a role of the peroxisome proliferator-activated receptor gamma (PPARG) and adiponectin (ADIPOQ) genes in antipsychotic-induced weight gain

Antipsychotics frequently cause changes in glucose metabolism followed by development of weight gain and/or diabetes. Recent findings from our group indicated an influence of glucose-related genes on this serious side effect. With this study, we aimed to extend previous research and performed a comprehensive study on the peroxisome proliferator-activated receptor gamma (PPARG) and the adiponectin (ADIPOQ) genes. In 216 schizophrenic patients receiving antipsychotics for up to 14 weeks, we investigated single-nucleotide polymorphisms in or near PPARG (N=24) and ADIPOQ (N=18). Statistical analysis was done using ANCOVA in SPSS. Haplotype analysis was performed in UNPHASED 3.1.4 and Haploview 4.2. None of the PPARG or ADIPOQ variants showed significant association with antipsychotic-induced weight gain in our combined sample or in a refined subsample of patients of European ancestry treated with clozapine or olanzapine after correction for multiple testing. Similarly, no haplotype association could withstand multiple test correction. Although we could not find a significant influence of ADIPOQ and PPARG on antipsychotic-induced weight gain, our comprehensive examination of these two genes contributes to understanding the biology of this serious side effect. More research on glucose metabolism genes is warranted to elucidate their role in metabolic changes during antipsychotic treatment.

Antipsychotic induced weight gain: genetics, epigenetics, and biomarkers reviewed

Antipsychotic-induced weight gain (AIWG) is a prevalent side effect of antipsychotic treatment, particularly with second generation antipsychotics, such as clozapine and olanzapine. At this point, there is virtually nothing that can be done to predict who will be affected by AIWG. However, hope for the future of prediction lies with genetic risk factors. Many genes have been studied for their association with AIWG with a variety of promising findings. This review will focus on genetic findings in the last year and will discuss the first epigenetic and biomarker findings as well. Although there are significant findings in many other genes, the most consistently replicated findings are in the melanocortin 4 receptor (MC4R), the serotonin 2C receptor (HTR2C), the leptin, the neuropeptide Y (NPY) and the cannabinoid receptor 1 (CNR1) genes. The study of genetic risk variants poses great promise in creating predictive tools for side effects such as AIWG.