Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases
0301 basic medicine
Biomedical and clinical sciences
Epidemiology
disease architecture
Inheritance Patterns
Computer Simulation; Genetic Diseases, Inborn; Genetic Variation; Genome-Wide Association Study; Humans; Inheritance Patterns; Models, Genetic; Open Reading Frames; Regulatory Elements, Transcriptional; Genetics; Genetics (clinical)
Expression
Quantitative Genetics (incl. Disease and Trait Mapping Genetics)
Medical and Health Sciences
Genome-Wide Association
Genotype Imputation
Models
GWAS
Genetics(clinical)
Regulatory Elements, Transcriptional
genotype imputation
Genetics & Heredity
Schizophrenia Working Group of the Psychiatric Genomics Consortium
Loci
Genomics
Biological Sciences
exome chips
Dna Elements
genome-wide association studies (GWASs)
Genetic-Variation
Genetic Diseases
Transcriptional
Snps
coding variants
2716 Genetics (clinical)
Psychiatry (incl. Psychotherapy)
GWAS; schizophrenia; SNP
trait heritability
610
Open Reading Frames
03 medical and health sciences
1311 Genetics
Genetic
SDG 3 - Good Health and Well-being
Health Sciences
SWE-SCZ Consortium
Genetics
Humans
Computer Simulation
Prior Information
Gene mapping
complex-diseases
genome-wide association study
Models, Genetic
Prevention
Human Genome
Genetic Diseases, Inborn
Genetic Variation
Regulatory Elements
Large-Scale
Inborn
Schizophrenia
genotype data
Genome-Wide Association Study
DOI:
10.1016/j.ajhg.2014.10.004
Publication Date:
2014-11-06T16:45:20Z
AUTHORS (345)
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 (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.
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