Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Huckins, Laura M., Dobbyn, Amanda, Ruderfer, Douglas M., Hoffman, Gabriel, Wang, Weiqing, Pardinas, Antonio F. ORCID: https://orcid.org/0000-0001-6845-7590, Rajagopal, Veera M., Als, Thomas D., Tan Hoang, Hoang T., Girdhar, Kiran, Boocock, James, Roussos, Panos, Fromer, Menachem, Kramer, Robin, Domenici, Enrico, Gamazon, Eric R., Purcell, Shaun, Demontis, Ditte, Borglum, Anders, Walters, James T. R. ORCID: https://orcid.org/0000-0002-6980-4053, O'Donovan, Michael C. ORCID: https://orcid.org/0000-0001-7073-2379, Sullivan, Patrick, Owen, Michael J. ORCID: https://orcid.org/0000-0003-4798-0862, Devlin, Bernie, Sieberts, Solveig K., Cox, Nancy J., Kyung Im, Hae, Sklar, Pamela, Ayumi Stahl, Eli A., The Schizophrenia Working Group of the Psychiatric Genomics Cons and iPSYCH-GEMS Schizophrenia Working Group 2019. Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. Nature Genetics 51 , pp. 659-674. 10.1038/s41588-019-0364-4

Preview

PDF - Accepted Post-Print Version Download (2MB) | Preview

Abstract

Transcriptomic imputation approaches offer an opportunity to test associations between disease and gene expression in otherwise inaccessible tissues, such as brain, by combining eQTL reference panels with large-scale genotype data. These genic associations could elucidate signals in complex GWAS loci and may disentangle the role of different tissues in disease development. Here, we use the largest eQTL reference panel for the dorso-lateral pre-frontal cortex (DLPFC), collected by the CommonMind Consortium, to create a set of gene expression predictors and demonstrate their utility. We applied these predictors to 40,299 schizophrenia cases and 65,264 matched controls, constituting the largest transcriptomic imputation study of schizophrenia to date. We also computed predicted gene expression levels for 12 additional brain regions, using publicly available predictor models from GTEx. We identified 413 genic associations across 13 brain regions. Stepwise conditioning across the genes and tissues identified 71 associated genes (67 outside the MHC), with the majority of associations found in the DLPFC, and of which 14/67 genes did not fall within previously genome-wide significant loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple pathways associated with porphyric disorders. We investigated developmental expression patterns for all 67 non-MHC associated genes using BRAINSPAN, and identified groups of genes expressed specifically pre-natally or post-natally.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Neuroscience and Mental Health Research Institute (NMHRI) Medicine MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Publisher:	Nature
ISSN:	1061-4036
Date of First Compliant Deposit:	9 July 2018
Date of Acceptance:	30 January 2019
Last Modified:	09 Nov 2023 18:12
URI:	https://orca.cardiff.ac.uk/id/eprint/113048

Citation Data

Cited 95 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item