학술논문
Gene expression imputation across multiple brain regions provides insights into schizophrenia risk
Document Type
article
Author
Huckins, Laura M; Dobbyn, Amanda; Ruderfer, Douglas M; Hoffman, Gabriel; Wang, Weiqing; Pardiñas, Antonio F; Rajagopal, Veera M; Als, Thomas D; T. Nguyen, Hoang; Girdhar, Kiran; Boocock, James; Roussos, Panos; Fromer, Menachem; Kramer, Robin; Domenici, Enrico; Gamazon, Eric R; Purcell, Shaun; Demontis, Ditte; Børglum, Anders D; Walters, James TR; O’Donovan, Michael C; Sullivan, Patrick; Owen, Michael J; Devlin, Bernie; Sieberts, Solveig K; Cox, Nancy J; Im, Hae Kyung; Sklar, Pamela; Stahl, Eli A
Source
Nature Genetics. 51(4)
Subject
Language
Abstract
Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.