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.
Gene expression imputation across multiple brain regions provides insights into schizophrenia risk / Huckins, L. M.; Dobbyn, A.; Ruderfer, D. M.; Hoffman, G.; Wang, W.; Pardinas, A. F.; Rajagopal, V. M.; Als, T. D.; T. Nguyen, H.; Girdhar, K.; Boocock, J.; Roussos, P.; Fromer, M.; Kramer, R.; Domenici, E.; Gamazon, E. R.; Purcell, S.; Commonmind, Consortium; Schizophrenia Working Group of the Psychiatric Genomics, Consortium; iPSYCH-GEMS Schizophrenia Working, Group; Demontis, D.; Borglum, A. D.; Walters, J. T. R.; O'Donovan, M. C.; Sullivan, P.; Owen, M. J.; Devlin, B.; Sieberts, S. K.; Cox, N. J.; Im, H. K.; Sklar, P.; Stahl, E. A.. - In: NATURE GENETICS. - ISSN 1546-1718. - 51:(2019), pp. 659-674. [10.1038/s41588-019-0364-4]
Gene expression imputation across multiple brain regions provides insights into schizophrenia risk
Wang W.;Kramer R.;Domenici E.;
2019-01-01
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.File | Dimensione | Formato | |
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