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

被引:8
作者
Grotzinger, Andrew D. [1 ,2 ,13 ]
Singh, Kritika [3 ,4 ]
Miller-Fleming, Tyne W. [3 ,4 ]
Lam, Max [5 ,6 ,7 ,8 ,9 ]
Mallard, Travis T. [5 ,11 ,12 ]
Chen, Yu [6 ,10 ]
Liu, Zhaowen [5 ,11 ,12 ]
Ge, Tian [5 ,11 ,12 ]
Smoller, Jordan W. [5 ,11 ,12 ]
机构
[1] Univ Colorado Boulder, Inst Behav Genet, Boulder, CO USA
[2] Univ Colorado Boulder, Dept Psychol & Neurosci, Boulder, CO USA
[3] Vanderbilt Univ Sch Med, Dept Med, Div Genet Med, Nashville, TN USA
[4] Vanderbilt Univ Sch Med, Vanderbilt Genet Inst, Nashville, TN USA
[5] Broad Inst & Harvard, Stanley Ctr Psychiat Res, Cambridge, MA USA
[6] Massachusetts Gen Hosp, Analyt & Translat Genet Unit, Boston, MA USA
[7] Zucker Hillside Hosp, Div Psychiat Res, Northwell Hlth, Glen Oaks, NY USA
[8] Inst Mental Hlth Singapore, Res Div, Singapore, Singapore
[9] Genome Inst Singapore, Human Genet, Singapore, Singapore
[10] Cent South Univ, Ctr Med Genet, Sch Life Sci, Changsha, Hunan, Peoples R China
[11] Massachusetts Gen Hosp, Psychiat & Neurodev Genet Unit, Boston, MA USA
[12] Massachusetts Gen Hosp, Ctr Precis Psychiat, Dept Psychiat, Boston, MA USA
[13] Univ Colorado Boulder, Inst Behav Genet, 1480 30th St, Boulder, CO 80304 USA
基金
美国国家卫生研究院;
关键词
GENE-EXPRESSION; NATIONAL TRENDS; ASSOCIATION; DISEASE; IDENTIFICATION; POLYPHARMACY; COMPONENT; SYMPTOMS; GWAS;
D O I
10.1001/jamapsychiatry.2023.1808
中图分类号
R749 [精神病学];
学科分类号
100205 ;
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.
引用
收藏
页码:811 / 821
页数:11
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