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

Nat Genet. 2019 Apr;51(4):659-674. doi: 10.1038/s41588-019-0364-4. Epub 2019 Mar 25.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • 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