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Transcriptome-Wide Structural Equation Modeling of 13 Major Psychiatric Disorders for Cross-Disorder Risk and Drug Repurposing

药物重新定位 共病 精神分裂症(面向对象编程) 双相情感障碍 转录组 心理干预 基因 遗传学 生物 精神科 生物信息学 计算生物学 心理学 医学 药品 基因表达 认知
作者
Andrew D. Grotzinger,Kritika Singh,Tyne W. Miller‐Fleming,Max Lam,Travis T. Mallard,Yu Chen,Zhaowen Liu,Tian Ge,Jordan W. Smoller
出处
期刊:JAMA Psychiatry [American Medical Association]
卷期号:80 (8): 811-811 被引量:31
标识
DOI:10.1001/jamapsychiatry.2023.1808
摘要

Importance: Psychiatric disorders display high levels of comorbidity and genetic overlap, necessitating multivariate approaches for parsing convergent and divergent psychiatric risk pathways. Identifying gene expression patterns underlying cross-disorder risk also stands to propel drug discovery and repurposing in the face of rising levels of polypharmacy. Objective: To identify gene expression patterns underlying genetic convergence and divergence across psychiatric disorders along with existing pharmacological interventions that target these genes. Design, Setting, and Participants: This genomic study applied a multivariate transcriptomic method, transcriptome-wide structural equation modeling (T-SEM), to investigate gene expression patterns associated with 5 genomic factors indexing shared risk across 13 major psychiatric disorders. Follow-up tests, including overlap with gene sets for other outcomes and phenome-wide association studies, were conducted to better characterize T-SEM results. The Broad Institute Connectivity Map Drug Repurposing Database and Drug-Gene Interaction Database public databases of drug-gene pairs were used to identify drugs that could be repurposed to target genes found to be associated with cross-disorder risk. Data were collected from database inception up to February 20, 2023. Main Outcomes and Measures: Gene expression patterns associated with genomic factors or disorder-specific risk and existing drugs that target these genes. Results: In total, T-SEM identified 466 genes whose expression was significantly associated (z ≥ 5.02) with genomic factors and 36 genes with disorder-specific effects. Most associated genes were found for a thought disorders factor, defined by bipolar disorder and schizophrenia. Several existing pharmacological interventions were identified that could be repurposed to target genes whose expression was associated with the thought disorders factor or a transdiagnostic p factor defined by all 13 disorders. Conclusions and Relevance: The findings from this study shed light on patterns of gene expression associated with genetic overlap and uniqueness across psychiatric disorders. Future versions of the multivariate drug repurposing framework outlined here have the potential to identify novel pharmacological interventions for increasingly common, comorbid psychiatric presentations.
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