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

Academic Article

Abstract

  • © 2019, The Author(s), under exclusive licence to Springer Nature America, Inc. 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.
  • Authors

    Published In

  • Nature Genetics  Journal
  • Digital Object Identifier (doi)

    Author List

  • Huckins LM; Dobbyn A; Ruderfer DM; Hoffman G; Wang W; Pardiñas AF; Rajagopal VM; Als TD; T. Nguyen H; Girdhar K
  • Start Page

  • 659
  • End Page

  • 674
  • Volume

  • 51
  • Issue

  • 4