Year: 2018
Type: article
Abstract: LD Score Regression (LDSC) has been widely applied to the results of genome-wide association studies. However, its estimates of SNP heritability are derived from an unrealistic model in which each SNP is expected to contribute equal heritability. As a consequence, LDSC tends to over-estimate confounding bias, under-estimate the total phenotypic variation explained by SNPs, and provide misleading estimates of the heritability enrichment of SNP categories. Therefore, we present SumHer, software for estimating SNP heritability from summary statistics using more realistic heritability models. After demonstrating its superiority over LDSC, we apply SumHer to the results of 24 large-scale association studies (average sample size 121 000). First we show that these studies have tended to substantially over-correct for confounding, and as a result the number of genome-wide significant loci has under-reported by about 20%. Next we estimate enrichment for 24 categories of SNPs defined by functional annotations. A previous study using LDSC reported that conserved regions were 13-fold enriched, and found a further twelve categories with above 2-fold enrichment. By contrast, our analysis using SumHer finds that conserved regions are only 1.6-fold (SD 0.06) enriched, and that no category has enrichment above 1.7-fold. SumHer provides an improved understanding of the genetic architecture of complex traits, which enables more efficient analysis of future genetic data.
Source: Nature Genetics
Authors: Doug Speed, David J. Balding
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: G1085576015, eMERGE Coordinating Center, G1180809207, G1192516092, EHR-based Genomic Discovery and Implementation, G1610637519, G1678063915, G1766209448, G2277351001, Integrative Analysis of a GWAS Repository with EMRs from over 40,000 Children, Creating a National Resource for Genetic Research in Behavioral & Health Sciences, Expanding a National Resource for Genetic Research in Behavioral & Health Science, Genetic Discovery and Application in a Clinical Setting Continuing a Partnership, Biorepository for Genomic Medicine in diverse Communities, G6975713648, Geisinger eGenonic Medicine (GeM) Program, Better Outcomes for Children: GWAS & PheWAS in eMERGEII., G7163342664, Improved methodology for understanding the genetics of complex traits, with particular application to epilepsy., G7635268731, Vanderbilt Genome Electronic Records Project, G8058148303, A Personalized Genomic Medicine Pilot Program Using the NJgene eMERGE Experience, G8257054342, IRIS: Incorporating Research Into Sight, Health and Retirement Study: Yrs 35-40
OpenAlex ID: W2901957554