Co-expression-based models improve eQTL predictions for transcriptome-wide association studies and highlight new schizophrenia-associated genes

Rossi, Fabiana, Sportelli, Leonardo, Kikidis, Gianluca C., Grassi, Giulia, Di Camilo, Fabio, Walters, James T. R. ORCID: https://orcid.org/0000-0002-6980-4053, O'Donovan, Michael C. ORCID: https://orcid.org/0000-0001-7073-2379, Owen, Michael J. ORCID: https://orcid.org/0000-0003-4798-0862, Escott-Price, Valentina ORCID: https://orcid.org/0000-0003-1784-5483 and Kirov, George ORCID: https://orcid.org/0000-0002-3427-3950 2026. Co-expression-based models improve eQTL predictions for transcriptome-wide association studies and highlight new schizophrenia-associated genes. Nature Genetics 58 , pp. 1559-1572. 10.1038/s41588-026-02646-3

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Abstract

Most genetic variants associated with complex heritability phenotypes lie in non-coding regions and are thought to influence disease risk by regulating gene expression. However, most transcriptome-wide association approaches primarily model local (cis) genetic effects, leaving much of gene regulation unexplained. Here, we show that incorporating distal (trans) regulatory effects improves the prediction of gene expression and the identification of disease-associated genes. Using RNA sequencing data from six human post-mortem brain regions, we developed INGENE and MODULE, two models capturing the combined influence of candidate trans-acting variants within gene coexpression networks. Integrating these models with conventional cis-based predictors improved gene expression imputation (maximum likelihood estimation, α = 0.05) for 18,744 genes across regions. Applying this framework to Psychiatric Genomics Consortium wave 3 genotypes identified 766 genes associated with schizophrenia (PFDR < 0.01), including 641 not previously reported by transcriptome-wide analyses. These findings highlight the contribution of distal regulatory mechanisms and gene network interactions to schizophrenia risk.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Medicine
Additional Information:	Full author list can be seen on the webpage - https://doi.org/10.1038/s41588-026-02646-3
Publisher:	Springer Science and Business Media LLC
ISSN:	1061-4036
Date of First Compliant Deposit:	7 July 2026
Date of Acceptance:	27 May 2026
Last Modified:	06 Aug 2026 11:44
URI:	https://orca.cardiff.ac.uk/id/eprint/188024

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