We performed analyses to quantify the variance explained by SNPs in close physical proximity to the top associated SNPs in 9,500 unrelated individuals (pairwise genetic relatedness < 0.025) from a combined dataset of the QIMR and TwinGene cohorts. As in previous analyses, to avoid sample overlap between discovery and validation studies, we repeated the discovery meta-analysis excluding the QIMR and TwinGene cohorts, and identified 643 genome-wide significant SNPs from the GCTA-COJO analysis of the summary statistics using ARIC data for LD estimation. We used GCTA-GREML analysis4,8 to quantify the phenotypic variance explained by all the common SNPs (MAF > 0.01) within 100Kb, 500Kb or 1Mb of the 643 genome-wide significant SNPs. We show in Supplementary Figure 6a that there are 104K, 423K and 745K SNPs within 100Kb, 500Kb and 1Mb of the top associated SNPs, which explain 20.8% (s.e. = 1.3%), 25.7% (s.e. = 1.8%) and 29.5% (s.e. = 2.2%) of phenotypic variance, respectively. We then applied a regression-based approach28 to adjust for LD between SNPs. The estimates of variance explained after LD-adjustment were slightly higher than those without adjustment,
