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

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Pharmacogenetics of Antipsychotic Drug Treatment: Update and Clinical Implications

Numerous genetic variants have been shown to be associated with antipsychotic response and adverse effects of schizophrenia treatment. However, the clinical application of these findings is limited. The aim of this narrative review is to summarize the most recent publications and recommendations related to the genetics of antipsychotic treatment and shed light on the clinical utility of pharmacogenetics/pharmacogenomics (PGx). We reviewed the literature on PGx studies with antipsychotic drugs (i.e., antipsychotic response and adverse effects) and commonly used commercial PGx tools for clinical practice. Publications and reviews were included with emphasis on articles published between January 2015 and April 2018. We found 44 studies focusing on antipsychotic response and 45 studies on adverse effects (e.g., antipsychotic-induced weight gain, movement disorders, hormonal abnormality, and clozapine-induced agranulocytosis/granulocytopenia), albeit with mixed results. Overall, several gene variants related to antipsychotic response and adverse effects in the treatment of patients with schizophrenia have been reported, and several commercial pharmacogenomic tests have become available. However, further well-designed investigations and replication studies in large and well-characterized samples are needed to facilitate the application of PGx findings to clinical practice.

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.

Antipsychotics Promote Metabolic Disorders Disrupting Cellular Lipid Metabolism and Trafficking

Antipsychotics frequently cause obesity and related metabolic disorders that current psychopharmacological/endocrinological theories do not explain consistently. An integrative/alternative theory implies metabolic alterations happening at the cellular level. Many observations in vitro and in vivo, and pivotal observations in humans, point towards chemical properties of antipsychotics, independent of receptor binding characteristics. Being amphiphilic weak bases, antipsychotics can disrupt lysosomal function, affecting cholesterol trafficking; moreover, by chemical mimicry, antipsychotics can inhibit cholesterol biosynthesis. These two molecular adverse effects may trigger a cascade of transcriptional and biochemical events, ultimately reducing available cholesterol while increasing cholesterol precursors and fatty acids. The macroscopic manifestation of these molecular alterations includes decreased high-density lipoprotein and increased very low-density lipoprotein and triglycerides that may translate into obesity and related metabolic disorders.

Genetic Polymorphisms Associated With Constipation and Anticholinergic Symptoms in Patients Receiving Clozapine

BACKGROUND

Clozapine impairs gastrointestinal motility owing to its anticholinergic and antiserotonergic properties. This commonly leads to constipation and potentially to more severe complications such as bowel obstruction and ischemia. The aim of this study was to determine whether genetic variations in the genes encoding muscarinic and serotonergic receptors (CHRM2, CHRM3, HTR2, HTR3, HTR4, and HTR7) explain the variations in incidence of constipation and anticholinergic symptoms during clozapine treatment. Genes associated with opiate-induced constipation were also included in this analysis (TPH1, OPRM1, ABCB1, and COMT).

PROCEDURES

Blood samples from 176 clozapine-treated, Finnish, white patients with schizophrenia were genotyped. Constipation and anticholinergic symptoms were rated using the Liverpool University Neuroleptic Side Effect Rating Scale self-report questionnaire. In total, 192 single-nucleotide polymorphisms (SNPs) were detected and grouped to formulate a weighted genetic-risk score (GRS).

RESULTS

No significant associations between individual SNPs or GRSs and constipation or laxative use were observed. A GRS of 19 SNPs in CHRM2, CHRM3, HTR3C, HTR7, ABCB1, OPRM1, and TPH1 was associated with anticholinergic symptoms in a generalized linear univariate model, with body mass index, clozapine monotherapy, and GRS as explaining variables (permuted P = 0.014). Generalized linear univariate model analysis performed on the opiate-induced constipation-associated SNPs and a single CHRM3 SNP revealed an association between anticholinergic symptoms and a score of 8 SNPs (adjusted P = 0.038, permuted P = 0.002).

CONCLUSIONS

Two GRSs are able to predict the risk of anticholinergic symptoms in patients receiving clozapine and possibly an increased risk of gastrointestinal hypomotility.

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.

Genetic variants impacting metabolic outcomes among people on clozapine: a systematic review and meta-analysis

Clozapine is the gold standard medication for treatment refractory schizophrenia, but unfortunately, its use is also associated with many adverse metabolic side effects. There may be a strong genetic component to the development of these adverse effects. We undertook a systematic review to examine the evidence for genetic variation being associated with secondary metabolic outcomes in patients with schizophrenia on clozapine, under both longitudinal and cross-sectional study designs. We limited studies to those examining patients definitely taking clozapine, unlike prior reviews that have examined metabolic effects of patients taking a range of antipsychotic medications. We found associations with outcomes such as increases in BMI and metabolic syndrome for variants in genes such as LEP and HTR2C. Meta-analysis of rs381328 in HTR2C revealed that the presence of the T allele led to a 0.63 kg/m² (95% CI - 1.06 to - 0.19; p = 0.005) decrease in BMI compared to the C allele. Study and population heterogeneity and lack of statistical power among reviewed articles mean that evidence is lacking to warrant prophylactic genotyping of patients commencing clozapine to predict those at increased risk of developing adverse metabolic effects. Further efforts to establish collaborative consortia, consensus around study design and replication studies in independent populations should be encouraged.