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 ORCID: https://orcid.org/0000-0003-1784-5483, Carrera, Noa ORCID: https://orcid.org/0000-0003-0739-0382, Hamshere, Marian L. ORCID: https://orcid.org/0000-0002-8990-0958, Holmans, Peter ALan ORCID: https://orcid.org/0000-0003-0870-9412, Kirov, George ORCID: https://orcid.org/0000-0002-3427-3950, Legge, Sophie, Li, Meng, O'Donovan, Michael Conlon ORCID: https://orcid.org/0000-0001-7073-2379, Owen, Michael John ORCID: https://orcid.org/0000-0003-4798-0862, Pocklington, Andrew ORCID: https://orcid.org/0000-0002-2137-0452, Richards, Alexander, Walters, James Tynan Rhys ORCID: https://orcid.org/0000-0002-6980-4053 and Williams, Nigel Melville ORCID: https://orcid.org/0000-0003-1177-6931 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

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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:	Advanced Research Computing @ Cardiff (ARCCA) Medicine Neuroscience and Mental Health Research Institute (NMHRI) 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:	16 Nov 2022 07:34
URI:	https://orca.cardiff.ac.uk/id/eprint/75918

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