Refining antipsychotic treatment strategies in schizophrenia: discovery of genetic biomarkers for enhanced drug response prediction

Abstract

Schizophrenia (SCZ) is a severe mental disorder affecting around 1% of individuals worldwide. The variability in response to antipsychotic drugs (APDs) among SCZ patients presents a significant challenge for clinicians in determining the most effective medication. In this study, we investigated the biological markers and established a predictive model for APD response based on a large-scale genome-wide association study using 3269 Chinese schizophrenia patients. Each participant underwent an 8-week treatment regimen with one of five mono-APDs: olanzapine, risperidone, aripiprazole, quetiapine, or amisulpride. By dividing the response into ordinal groups of “high”, “medium”, and “low”, we mitigated the bias of unclear treatment outcome and identified three novel significantly associated genetic loci in or near CDH12, WDR11, and ELAVL2. Additionally, we developed predictive models of response to each specific APDs, with accuracies ranging from 79.5% to 98.0%. In sum, we established an effective method to predict schizophrenia patients’ response to APDs across three categories, integrating novel biomarkers to guide personalized medicine strategies.