While we have dense SNP coverage across the genome, the SNPs may not be in complete linkage disequilibrium (LD) (i.e. perfectly correlated) with all common causal variants. We therefore adjusted the variance estimates explained by our SNPs for incomplete LD with causal variants, under the assumption that the causal variants have the same allelic spectrum as the genotyped SNPs. This adjustment procedure is based on a formula empirically established by Yang et al. (2010) and is described in detail in their paper. The adjustment is implemented in the GCTA program. In this way we tested to what extent the variance explained by the SNPs captured the variance explained by all common variants (including common structural variants e.g. copy number variants). Additionally, we tested whether including more SNPs in our analyses (all SNPs that were genotyped for at least a third of our sample, N=532,030 SNPs) would affect the variance accounted for.
