Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease

Abstract

Association studies offer a potentially powerful approach to identify genetic variants that influence susceptibility to com- mon disease1-4, but are plagued by the impression that they are not consistently reproducible5,6. In principle, the inconsis- tency may be due to false positive studies, false negative stud- ies or true variability in association among different populations4-8. The critical question is whether false positives overwhelmingly explain the inconsistency. We analyzed 301 published studies covering 25 different reported associations. There was a large excess of studies replicating the first positive reports, inconsistent with the hypothesis of no true positive associations (P <1 0 -14). This excess of replications could not be reasonably explained by publication bias and was concentrated among 11 of the 25 associations. For 8 of these 11 associations, pooled analysis of follow-up studies yielded statistically signif- icant replication of the first report, with modest estimated genetic effects. Thus, a sizable fraction (but under half) of reported associations have strong evidence of replication; for these, false negative, underpowered studies probably con- tribute to inconsistent replication. We conclude that there are probably many common variants in the human genome with modest but real effects on common disease risk, and that stud- ies using large samples will convincingly identify such variants. From 166 frequently studied associations between common vari- ants and common diseases9, we selected a subset of 25 associa-