Abstract Regulatory and coding variants are known to be enriched in associations identi_ed by genome-wide association studies (GWAS) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance components methods to partition the heritability explained by genotyped SNPs (h2g ) across functional categories (while accounting for shared variance due to linkage disequilibrium) to imputed genotype data for 11 common diseases. Extensive simulations show that that the variance components approach partitions heritability accurately under a wide range of complex disease architectures, in contrast to current estimates from GWAS summary statistics. Across the 11 diseases, DNaseI Hypersensitivity Sites (DHS) from 217 cell types, spanning 16% of imputed SNPs (and 24% of genotyped SNPs), explained an average of 79% (s.e. 8%) of h2g from imputed SNPs (5:1_ enrichment; P = 3:7 _ 1017) and 38% (s.e. 4%) (1:6_, P = 1:0 _ 104) of h2g from genotyped SNPs. Further enrichment was observed at enhancer DHS elements and cell-type speci_c DHS regions. In contrast, coding variants, which span 1% of the genome, explained <10% of h2g despite having the highest enrichment. We replicated these _ndings but found no signi_cant 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.