TY - JOUR

T1 - Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

AU - Huckins, Laura M.

AU - Dobbyn, Amanda

AU - Ruderfer, Douglas M.

AU - Hoffman, Gabriel

AU - Wang, Weiqing

AU - Pardiñas, Antonio F.

AU - Rajagopal, Veera M.

AU - Als, Thomas D.

AU - T. Nguyen, Hoang

AU - Girdhar, Kiran

AU - Boocock, James

AU - Roussos, Panos

AU - Fromer, Menachem

AU - Kramer, Robin

AU - Domenici, Enrico

AU - Gamazon, Eric R.

AU - Purcell, Shaun

AU - CommonMind Consortium

AU - The Schizophrenia Working Group of the PsyUniversity of Copenhagenchiatric Genomics Consortium

AU - iPSYCH-GEMS Schizophrenia Working Group

AU - Johnson, Jessica S.

AU - Shah, Hardik R.

AU - Klein, Lambertus L.

AU - Pers, Tune H.

AU - Hansen, Thomas

AU - Olsen, Line

AU - Rasmussen, Henrik B.

AU - Werge, Thomas

AU - Pedersen, Carsten Bøcker

AU - Nordentoft, Merete

AU - Bækvad-Hansen, Marie

AU - Hansen, Christine Søholm

AU - Daly, Mark J

AU - Sullivan, Patrick F

AU - O'Donovan, Michael C

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

U2 - 10.1038/s41588-019-0364-4

DO - 10.1038/s41588-019-0364-4

M3 - Journal article

C2 - 30911161

AN - SCOPUS:85063585118

VL - 51

SP - 659

EP - 674

JO - Nature Genetics

JF - Nature Genetics

SN - 1061-4036

ER -