TY - JOUR
T1 - Quantifying Missing Heritability at Known GWAS Loci
AU - Gusev, Alexander
AU - Bhatia, Gaurav
AU - Zaitlen, Noah
AU - Vilhjalmsson, Bjarni J.
AU - Diogo, Dorothée
AU - Stahl, Eli A.
AU - Gregersen, Peter K.
AU - Worthington, Jane
AU - Klareskog, Lars
AU - Raychaudhuri, Soumya
AU - Plenge, Robert M.
AU - Pasaniuc, Bogdan
AU - Price, Alkes L.
PY - 2013
Y1 - 2013
N2 - 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 × more heritability than GWAS-associated SNPs on average (P = 3.3 × 10-5). For some diseases, this increase was individually significant: 2.07 × for Multiple Sclerosis (MS) (P = 3.3 × 10-5) and 1.48 × for Crohn's Disease (CD) (P = 1.3 × 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 × more MS heritability than known MS SNPs (P <1.0 × 10-16) and 2.20 × more CD heritability than known CD SNPs (P =6.1 × 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 × more heritability from all SNPs at GWAS loci (P = 2.3 × 106) and 5.33× more heritability from all autoimmune disease loci (P <1 × 1016) 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. © 2013 Gusev et al.
AB - 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 × more heritability than GWAS-associated SNPs on average (P = 3.3 × 10-5). For some diseases, this increase was individually significant: 2.07 × for Multiple Sclerosis (MS) (P = 3.3 × 10-5) and 1.48 × for Crohn's Disease (CD) (P = 1.3 × 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 × more MS heritability than known MS SNPs (P <1.0 × 10-16) and 2.20 × more CD heritability than known CD SNPs (P =6.1 × 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 × more heritability from all SNPs at GWAS loci (P = 2.3 × 106) and 5.33× more heritability from all autoimmune disease loci (P <1 × 1016) 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. © 2013 Gusev et al.
U2 - 10.1371/journal.pgen.1003993
DO - 10.1371/journal.pgen.1003993
M3 - Article
C2 - 24385918
SN - 1553-7390
VL - 9
JO - PL o S Genetics
JF - PL o S Genetics
IS - 12
M1 - e1003993
ER -