T-SEM of 11 Major Psychiatric Disorders: Identification of Gene Expression Patterns for Cross-Disorder Risk and Drug Repurposing

Abstract

Structured AbstractImportancePsychiatric 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.ObjectiveTo identify gene expression patterns underlying genetic convergence and divergence across psychiatric disorders along with existing pharmacological interventions that target these genes.DesignThis genomic study applied a multivariate transcriptomic method, Transcriptome-wide Structural Equation Modeling (T-SEM), to investigate gene expression patterns associated with four genomic factors indexing shared risk across 11 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. Public databases describing drug-gene pairs were used to identify drugs that could be repurposed to target genes found to be associated with cross-disorder risk.Main Outcomes and MeasuresGene expression patterns associated with genomic factors or disorder-specific risk and existing drugs that target these genes.ResultsIn total, T-SEM identified 451 genes whose expression was associated with the genomic factors and 41 genes with disorder-specific effects. We find the most hits for a Thought Disorders factor defined by bipolar disorder and schizophrenia. We identify 39 existing pharmacological interventions that could be repurposed to target gene expression hits for this same factor.Conclusions and RelevanceThe 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.