As a statistical method which allows the quantitative synthesis of results from different studies in order to estimate a common summary effect (55), the major advantage of meta-analysis is that it maximizes power, i.e. reduces the probability of false negative results (19). Additional potential advantages include the increased precision of the effect estimates for the identified associations, reduction of the extent of the winner’s curse phenomenon (when adequate power is achieved), and opportunities to evaluate and measure the degree of consistency or heterogeneity of the genetic effect across the combined studies (28, 40). Meta-analysis of GWA studies has emerged as an efficient strategy for prioritizing GWA results for further follow-up through functional analyses, or further replication efforts, cross-phenotype checks, or mendelian randomization studies (7). Meta-analysis of multiple GWA datasets is now a well-established and validated strategy for both discovery and replication of genetic association studies (7, 21, 52).
