Abstract:
: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.
journal_name
Nat Genetjournal_title
Nature geneticsauthors
Finucane HK,Reshef YA,Anttila V,Slowikowski K,Gusev A,Byrnes A,Gazal S,Loh PR,Lareau C,Shoresh N,Genovese G,Saunders A,Macosko E,Pollack S,Brainstorm Consortium.,Perry JRB,Buenrostro JD,Bernstein BE,Raychaudhuri S,Mdoi
10.1038/s41588-018-0081-4subject
Has Abstractpub_date
2018-04-01 00:00:00pages
621-629issue
4eissn
1061-4036issn
1546-1718pii
10.1038/s41588-018-0081-4journal_volume
50pub_type
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