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

CommonMind Consortium

Research output: Contribution to journalArticlepeer-review

135 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
Early online date25 Mar 2019
DOIs
Publication statusPublished - 01 Apr 2019

Keywords

  • Brain/physiopathology
  • Case-Control Studies
  • Gene Expression/genetics
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study/methods
  • Genotype
  • Humans
  • Polymorphism, Single Nucleotide/genetics
  • Quantitative Trait Loci/genetics
  • Risk
  • Schizophrenia/genetics
  • Transcriptome/genetics

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