Replication validity of genetic association studies

The rapid growth of human genetics creates countless opportunities for stud ies of disease association. Given the number of potentially identifiable ge netic markers and the multitude of clinical outcomes to which these may be linked, the testing and validation of statistical hypotheses in genetic epi demiology is a task of unprecedented scale(1,2). Meta-analysis provides a q uantitative approach for combining the results of various studies on the sa me topic, and for estimating and explaining their diversity(3,4). Here, we have evaluated by meta-analysis 370 studies addressing 36 genetic associati ons for various outcomes of disease. We show that significant between-study heterogeneity (diversity) is frequent, and that the results of the first s tudy correlate only modestly with subsequent research on the same associati on. The first study often suggests a stronger genetic effect than is found by subsequent studies. Both bias and genuine population diversity might exp lain why early association studies tend to overestimate the disease protect ion or predisposition conferred by a genetic polymorphism. We conclude that a systematic meta-analytic approach may assist in estimating population-wi de effects of genetic risk factors in human disease.