Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases

Gusev, Alexander, Lee, S. Hong, Trynka, Gosia, Finucane, Hilary, Vilhjálmsson, Bjarni J., Xu, Han, Zang, Chongzhi, Ripke, Stephan, Bulik-Sullivan, Brendan, Stahl, Eli, Kähler, Anna K., Hultman, Christina M., Purcell, Shaun M., McCarroll, Steven A., Daly, Mark, Pasaniuc, Bogdan, Sullivan, Patrick F., Neale, Benjamin M., Wray, Naomi R., Raychaudhuri, Soumya, Price, Alkes L., Escott-Price, Valentina, Carrera, Noa, Hamshere, Marian L., Holmans, Peter ALan, Kirov, George, Legge, Sophie, Li, Meng, O'Donovan, Michael Conlon, Owen, Michael John, Pocklington, Andrew, Richards, Alexander, Walters, James Tynan Rhys and Williams, Nigel Melville 2014. Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. American Journal of Human Genetics 95 (5) , pp. 535-552. 10.1016/j.ajhg.2014.10.004

Full text not available from this repository.

Abstract

Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (View the MathML sourcehg2) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of View the MathML sourcehg2 from imputed SNPs (5.1× enrichment; p = 3.7 × 10−17) and 38% (SE = 4%) of View the MathML sourcehg2 from genotyped SNPs (1.6× enrichment, p = 1.0 × 10−4). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained <10% of View the MathML sourcehg2 despite having the highest enrichment. We replicated these findings but found no significant contribution from rare coding variants in independent schizophrenia cohorts genotyped on GWAS and exome chips. Our results highlight the value of analyzing components of heritability to unravel the functional architecture of common disease.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Neuroscience and Mental Health Research Institute (NMHRI)
Medicine
Advanced Research Computing @ Cardiff (ARCCA)
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Systems Immunity Research Institute (SIURI)
Subjects: R Medicine > R Medicine (General)
Publisher: Elsevier (Cell Press)
ISSN: 0002-9297
Date of Acceptance: 2 October 2014
Last Modified: 23 Aug 2019 12:04
URI: http://orca.cf.ac.uk/id/eprint/75918

Citation Data

Cited 224 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item