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Updated: Mar 26, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Genome-wide association analysis to predict optimal antipsychotic dosage in schizophrenia: a pilot study
Arthur T Koga1,2, John Strauss1, Clement Zai1
1Department of Psychiatry, University of Toronto, Toronto, Canada.
Abstract:
In recent years, several studies have investigated genetic polymorphisms of antipsychotic drug-metabolizing enzymes and receptors. However, most studies focused on drug response and very few have investigated the genetic influence on antipsychotic dosage. The aim of the present study is to test the association between antipsychotic dosages at genome-wide level. The current dosage of antipsychotic medications was collected from 79 schizophrenia patients. The dosage was standardized using three different methods: chlorpromazine equivalent (CPZe), defined daily dose (DDD), and percentage of maximum dose (PM %). The patients were then genotyped using the Illumina HumanOmni2.5-8 BeadChip Kit. All markers were screened for significance using linear regression, and the p values were visualized using a Manhattan plot. The genome-wide analysis showed that the top Single-Nucleotide Polymorphisms (SNPs) associated with dosage variation were rs981975 on chromosome 14 for CPZe, rs4470690 on chromosome 4 for PM %, and rs79323383 on chromosome 8 for DDD. However, no genome-wide significantly associated SNPs were identified. In this pilot sample, we found promising trends for pharmacodynamic targets associated with antipsychotic dosage. Therefore, studies combining large prescription databases may identify genetic predictors to adjust the dose of antipsychotic medication.
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