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PLoS Genet. 2013;9(12):e1003993. doi: 10.1371/journal.pgen.1003993. Epub 2013 Dec 26.

Quantifying missing heritability at known GWAS loci.

Author information

1
Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America ; Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America ; Medical and Population Genetics Program, Broad Institute, Cambridge, Massachusetts, United States of America.
2
Medical and Population Genetics Program, Broad Institute, Cambridge, Massachusetts, United States of America ; Harvard-Massachusetts Institute of Technology (MIT) Division of Health, Science and Technology, Cambridge, Massachusetts, United States of America.
3
Department of Medicine Lung Biology Center, University of California San Francisco, San Francisco, California, United States of America.
4
Medical and Population Genetics Program, Broad Institute, Cambridge, Massachusetts, United States of America ; Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America ; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
5
The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America.
6
Arthritis Research UK Epidemiology Unit, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom.
7
Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden.
8
Medical and Population Genetics Program, Broad Institute, Cambridge, Massachusetts, United States of America ; Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America ; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America ; Arthritis Research UK Epidemiology Unit, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom.
9
Department of Pathology and Laboratory Medicine, Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.

Abstract

Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain 1.29 x more heritability than GWAS-associated SNPs on average (P=3.3 x 10⁻⁵). For some diseases, this increase was individually significant: 2.07 x for Multiple Sclerosis (MS) (P=6.5 x 10⁻⁹) and 1.48 x for Crohn's Disease (CD) (P = 1.3 x 10⁻³); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained 7.15 x more MS heritability than known MS SNPs (P < 1.0 x 10⁻¹⁶ and 2.20 x more CD heritability than known CD SNPs (P = 6.1 x 10⁻⁹), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of > 20,000 Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with 2.37 x more heritability from all SNPs at GWAS loci (P = 2.3 x 10⁻⁶) and 5.33 x more heritability from all autoimmune disease loci (P < 1 x 10⁻¹⁶ compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.

PMID:
24385918
PMCID:
PMC3873246
DOI:
10.1371/journal.pgen.1003993
[Indexed for MEDLINE]
Free PMC Article
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