Brain and behavior · 2026
Multi-Trait Genetic Insights Into Schizophrenia Across Ancestries: Genome-Wide Association Meta-Analyses, Machine Learning, and Drug Repurposing Study.
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Yan Ping, Wang Haili, Shu Ye, Xie Rui, Reyidan Ainiwaner, Fu Songnian
Аннотация
BACKGROUND: Schizophrenia is a psychiatric disorder characterized by a wide range of symptoms and a complex interplay between genetic and environmental factors. Despite advances in genomics, the genetic underpinnings of SC and its relationship with drug use remain poorly understood.
METHODS: This study utilized genome-wide association data from 53,386 SC patients and 77,258 controls of mainly European ancestry, and 22,778 patients and 35,362 controls of mainly East Asian ancestry, alongside GWAS summary data for 23 types of drug use. Genetic correlation analysis was conducted using linkage disequilibrium score regression, followed by meta-analysis of genome-wide association studies across multiple traits related to SC. Independent risk loci were identified, and their biological significance was explored using molecular methodologies. Machine learning techniques were employed to develop predictive models for SC diagnosis, and drug repurposing opportunities were investigated.
RESULTS: We found significant genetic correlations between SC and drug use in both ancestries, uncovering 24 previously unidentified loci associated with SC. Through various analytical strategies, we highlighted novel genes linked to SC and developed diagnostic models. Drug repurposing analysis identified ten drug classes with potential therapeutic relevance for SC, including cannabinoid receptor antagonists, which have shown promise in alleviating symptoms.
CONCLUSION: Our findings reveal a common genetic foundation linking susceptibility to schizophrenia with drug use, providing new insights into the genetic architecture of SC across ancestries. The identification of novel loci and genes associated with SC enhances our understanding of its biological underpinnings and offers potential targets for therapeutic intervention. Additionally, our study opens avenues for drug repurposing as a promising strategy for SC treatment, underscoring the importance of integrating genetic and pharmacological research in psychiatry.
METHODS: This study utilized genome-wide association data from 53,386 SC patients and 77,258 controls of mainly European ancestry, and 22,778 patients and 35,362 controls of mainly East Asian ancestry, alongside GWAS summary data for 23 types of drug use. Genetic correlation analysis was conducted using linkage disequilibrium score regression, followed by meta-analysis of genome-wide association studies across multiple traits related to SC. Independent risk loci were identified, and their biological significance was explored using molecular methodologies. Machine learning techniques were employed to develop predictive models for SC diagnosis, and drug repurposing opportunities were investigated.
RESULTS: We found significant genetic correlations between SC and drug use in both ancestries, uncovering 24 previously unidentified loci associated with SC. Through various analytical strategies, we highlighted novel genes linked to SC and developed diagnostic models. Drug repurposing analysis identified ten drug classes with potential therapeutic relevance for SC, including cannabinoid receptor antagonists, which have shown promise in alleviating symptoms.
CONCLUSION: Our findings reveal a common genetic foundation linking susceptibility to schizophrenia with drug use, providing new insights into the genetic architecture of SC across ancestries. The identification of novel loci and genes associated with SC enhances our understanding of its biological underpinnings and offers potential targets for therapeutic intervention. Additionally, our study opens avenues for drug repurposing as a promising strategy for SC treatment, underscoring the importance of integrating genetic and pharmacological research in psychiatry.