Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types.
Hilary K FinucaneYakir A ReshefVerneri AnttilaKamil SlowikowskiAlexander GusevAndrea ByrnesSteven GazalPo-Ru LohCaleb LareauNoam ShoreshGiulio GenoveseArpiar SaundersEvan MacoskoSamuela Pollacknull nullJohn R B PerryJason D BuenrostroBradley E BernsteinSoumya RaychaudhuriSteven McCarrollBenjamin M NealeAlkes L PricePublished in: Nature genetics (2018)
We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.
Keyphrases
- gene expression
- genome wide
- dna methylation
- bipolar disorder
- genome wide association study
- body mass index
- electronic health record
- single cell
- spinal cord
- big data
- cell therapy
- major depressive disorder
- stem cells
- small molecule
- spinal cord injury
- mesenchymal stem cells
- drinking water
- bone marrow
- weight gain
- hiv infected
- white matter
- genome wide identification
- genome wide analysis