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

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 This 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 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 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 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. ### Competing Interest Statement J.W.S. is a member of the Leon Levy Foundation Neuroscience Advisory Board, the Scientific Advisory Board of Sensorium Therapeutics (with equity), and PI of a collaborative study of the genetics of depression and bipolar disorder sponsored by 23andMe for which 23andMe provides analysis time as in-kind support but no payments. ### Funding Statement The work presented here was supported by a gift from the Tommy Fuss Fund. ADG was supported by NIH Grants R01MH120219 and RF1AG073593. KS is supported by AHA827137. The dataset(s) used for the BioVU analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by numerous sources: institutional funding, private agencies, and federal grants. These include the NIH funded Shared Instrumentation Grant S10RR025141; and CTSA grants UL1TR002243, UL1TR000445, and UL1RR024975. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962, R01HD074711; and additional funding sources listed at . We add that the current analyses would not have been possible without the enormous efforts put forth by the investigators and participants from ENIGMA, the Psychiatric Genetics Consortium, iPSYCH, and UK Biobank. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The data that support the findings of this study are all publicly available or can be requested for access. Specific download links for various datasets are directly below are reported in the Data Availability Statement. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The data that support the findings of this study are all publicly available or can be requested for access. Specific download links for various datasets are directly below. Summary statistics for data from the Psychiatric Genomics Consortium (PGC) can be downloaded or requested here: Summary statistics for the Anxiety phenotype can be downloaded here: Links to the LD-scores, reference panel data, and the code used to produce the current results can all be found at: Links to the functional reference weights from GTEx version 8 and CMC can be found here: Links to the functional reference weights from PsychENCODE can be found here: The DGIdb database can be found here (results were downloaded on March 4th, 2022) The C-MAP Repurposing database can be found her (results were downloaded on March 4th, 2022):