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

  • Laura M. Huckins (Corresponding Author)
  • , Amanda Dobbyn
  • , Douglas M. Ruderfer
  • , Schizophrenia Working Group of the Psychiatric Genomics Consortium, SWE-SCZ Consortium
  • , Liene Nikitina-Zake (Member of the Working Group)

Research output: Contribution to journalArticlepeer-review

146 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)659-674
Number of pages16
JournalNature Genetics
Volume51
Issue number4
DOIs
Publication statusPublished - 1 Apr 2019
Externally publishedYes

Field of Science*

  • 3.2 Clinical medicine

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database

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