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

SWE-SCZ Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, SWE-SCZ Consortium, Psychosis Endophenotypes International Consortium, Wellcome Trust Case Control Consortium

Research output: Contribution to journalArticlepeer-review

410 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)535-552
Number of pages18
JournalAmerican Journal of Human Genetics
Issue number5
StatePublished - 2014
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)


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