We used GCTA-COJO analysis7,8 to select the top associated SNPs. This method uses the summary statistics from the meta-analysis and LD correlations between SNPs estimated from a reference sample to perform a conditional association analysis7. The method starts with an initial model of the SNP that shows the strongest evidence of association across the whole genome. It then implements the association analysis conditioning on the selected SNP(s) to search for the top SNPs one-by-one iteratively via a stepwise model selection procedure until no SNP has a conditional P-value that passes the significance level. Finally, all the selected SNPs are fitted jointly in the model for effect size estimation. We used 6,654 unrelated individuals from the ARIC cohort as the reference sample for LD estimation. There were ~3.0M SNPs included in the original meta-analysis. We included in this analysis only the SNPs (~2.48M) on HapMap2 and with sample size > 50,000. We used the genome-wide significance level P<5×10−8 (as reported in Supplementary Table 1).
