An initial concern regarding GWAS meta-analysis was that increased signal from combining multiple samples would be negated by “noise” due to inter-site differences. This theoretical concern has not been borne out in practice, as illustrated above with the examples in SCZ, 58 BIP, 59 smoking behavior, 92 alcohol consumption, 100 and AD. 35,36 These meta-analyses are designed to identify risk or protective loci that have relatively similar effects across populations and that are not particularly sensitive to sample-specific factors. For example, T2DM and breast cancer loci identified in European samples tend to replicate in samples of East Asian ancestry. 150,151 It is possible that some genetic variants associated with phenotype risk are only found in certain population groups and are missed in meta-analysis; however, conclusive identification of such loci is likely to be challenging unless the effect sizes are relatively large.
