Partitioning heritability by functional annotation using genome-wide association summary statistics

By Hilary K Finucane, Brendan K. Bulik-Sullivan, Alexander Gusev, G. Trynka, Yakir A. Reshef, Po-Ru Loh, V. Anttila, Han Xu, Chongzhi Zang, K. Farh and 12 more. Nature Genetics, 2015

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Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type–specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease–specific enrichment of heritability in FANTOM5 enhancers and many cell type–specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a29b83c3249b8b47b6d9550cc2c72abe56871d82

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Citations in the corpus

LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis (2016, background): “…the degree to which this variation represents different functional categories and/or biological pathways (Yang et al. 2011; Gusev et al. 2014; Finucane et al, 2015), and the extent to which genetic aetiologies are shared across different phenotypes (Lee et al. 2012; Lee et al. 2013;…”
Linkage disequilibrium dependent architecture of human complex traits reveals action of negative selection (2016, methodology): “Application of stratified LD score regression was performed using Finucane et al.(8) guidelines and was restricted to data sets of European ancestry.”
The GTEx Consortium atlas of genetic regulatory effects across human tissues (2019, methodology): “Next, we used S-LDSC adjusting for functional annotations (44) to confirm the .”
Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases (2020, methodology): “Based on the assumption that SNPs near causal genes should be enriched for trait heritability, Benchmarker uses stratified LD-score regression (S-LDSC) 56 to estimate the average contribution of SNPs near prioritized genes to per-SNP heritability.”