Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases
AU - Gusev, Alexander
AU - Lee, S. Hong
AU - Trynka, Gosia
AU - Finucane, Hilary
AU - Vilhjálmsson, Bjarni J.
AU - Xu, Han
AU - Zang, Chongzhi
AU - Ripke, Stephan
AU - Bulik-Sullivan, Brendan
AU - Stahl, Eli
AU - Kähler, Anna K.
AU - Hultman, Christina M.
AU - Purcell, Shaun M.
AU - McCarroll, Steven A.
AU - Daly, Mark
AU - Pasaniuc, Bogdan
AU - Sullivan, Patrick F.
AU - Neale, Benjamin M.
AU - Wray, Naomi R.
AU - Raychaudhuri, Soumya
AU - Price, Alkes L.
AU - Knight, Jo
AU - Schizophrenia Working Group of the Psychiatric Genomics Consortium
N1 - Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
PY - 2014/11/6
Y1 - 2014/11/6
N2 - 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 (hg(2)) 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 hg(2) from imputed SNPs (5.1× enrichment; p = 3.7 × 10(-17)) and 38% (SE = 4%) of hg(2) 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 hg(2) 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.
AB - 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 (hg(2)) 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 hg(2) from imputed SNPs (5.1× enrichment; p = 3.7 × 10(-17)) and 38% (SE = 4%) of hg(2) 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 hg(2) 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.
KW - Computer Simulation
KW - Genetic Diseases, Inborn
KW - Genetic Variation
KW - Genome-Wide Association Study
KW - Humans
KW - Inheritance Patterns
KW - Models, Genetic
KW - Open Reading Frames
KW - Regulatory Elements, Transcriptional
U2 - 10.1016/j.ajhg.2014.10.004
DO - 10.1016/j.ajhg.2014.10.004
M3 - Journal article
C2 - 25439723
VL - 95
SP - 535
EP - 552
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
SN - 0002-9297
IS - 5
ER -