The AA discovery sample was genotyped for one million SNPs. The association results could be corrected for one million tests (α = 5×10−8) to prevent from false positive findings. However, this correction is overly conservative, because these 1 M markers are not completely independent. Instead, in the present study, we used multiple samples to replicate and confirm the discovery findings, in order to reduce the chance of false positive findings and increase the α level from 5×10−8. First, we used EAs and Australians, the most genetically distinct populations from AAs in the world, as replication groups for association analysis. This would make the replicable findings more generalizable to more other populations. Second, we aimed to detect replicable regions that were enriched with many, not a single, risk markers, which reduced the chance of false positive association findings too. Third, functional analysis as confirmation of association analysis further reduced the chance of false positive findings. Additionally, functional analysis in multiple populations with distinct ethnicity, which were also different from the populations for association analysis, would make the findings more generalizable too.
