Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

Abstract

We introduce an approach for identifying disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified LD score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We apply our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N=169K), detecting significant tissue-specific enrichments (FDR<5%) for 34 traits. In our analysis of multiple tissues, we detect a broad range of enrichments that recapitulate known biology. In our brain-specific and immune-specific analyses, significant enrichments include an enrichment of inhibitory over excitatory neurons for bipolar disorder but 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 signal.

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

“…Systematic eQTL integration using the Summary Mendelian Randomization approach 7 prioritized 113 transcripts, 60 of which had evidence for causal or pleiotropic effects, rather than coincidental overlap of signal (as indicated by HEIDI heterogeneity test P > 0.009) (Supplementary Table 7). Second, we used LD score regression applied to specifically expressed genes (LDSC-SEG) 8 to identify tissues and cell types that are enriched for AAM heritability. Five of the 46 GTEx tissues were positively enriched for AAM-associated variants (Fig.…”

“…To identify which tissues and cell types were likely to be most relevant to genes involved in pubertal development, we applied LD score regression 39 to specifically expressed genes (LDSC-SEG) 8 . For each tissue, we ranked genes by a t statistic for differential expression, using sex and age as covariates and excluding all samples in related tissues.…”

Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets

“…Stratified LD score regression (Finucane et al, 2017) also demonstrated an enrichment of cell type expression for neuronal tissues only. Notably, genes found in the neuronal expression list of Cahoy (Cahoy et al, 2008) were significantly enriched (p=.0129; Bonferroni-corrected p=.0386), whereas negative results were obtained for genes expressed in oligodendrocytes (p=.4997) and astrocytes (p=.9057).…”

“…Summary statistics were first subjected to baseline partitioned heritability and thereafter passed through a cell type-specific functional characterization pipeline (Finucane et al, 2017). Cell type characterization includes the DEPICT tissue expression database, GTEX tissue expression, IMMGEN immune cell types, CAHOY brain level cell types, and the ROADMAP cell epigenomic marks.…”

Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis

“…Three years later, a second study utilized S‐LDSC to integrate gene expression with GWAS data, with similar goals as the study done by Hu et al in 2011. In this 2018 study, the authors assigned a tissue specificity score to each gene and subsequently defined tissue‐specific gene sets comprised of the top 10% of specifically expressed genes.…”