To identify approximately independent lead SNPs, we applied to the GWAS results a clumping algorithm. Our clumping algorithm begins by selecting the SNP with the lowest P value as the lead SNP in the first clump, and includes in the first clump all SNPs that have r2 greater than 0.1 with the lead SNP and that have GWAS P value less than 1×10–4. Next, the SNP with the second-lowest P value outside the first clump becomes the lead SNP of the second clump, and the second clump is created analogously but using only the SNPs outside of the first clump. This process continues until every genome-wide significant SNP (i.e., every SNP with a GWAS P value less than 5×10–8) is either designated as a lead SNPs or is clumped to another lead SNP. We also defined non-overlapping, continuous genomic loci around the lead SNPs using Ripke et al.’s46 locus definition, and we performed conditional and joint multiple-SNP analyses (COJO)13. Ripke et al. defined a locus as “the physical region containing all SNPs correlated at r2 > 0.6 with [one of
