while additional models had been used in a total of 16 meta-analyses pertaining to random-effects (n=13), Bayesian approaches (n=1), both random-effects and Bayesian approaches (n=1), and P-value based methods (n=1). Fixed-effects models assume that there is a common true genetic effect across all studies and any variation in it is attributed to random error; on the other hand, random-effects models assume that there are different effect sizes in the included studies and any variation, i.e. heterogeneity, is due to real population differences (15, 40). In this context, the observed domination of fixed-effects synthesis is expected as this approach is more powerful than random-effects for discovery purposes, while the latter is preferable when the aim is to determine and generalize the magnitude of the genetic effect size (80). The method of weighting was reported in a total of 137 meta-analyses. Of those, 127 meta-analyses used inverse-variance weighting; 7 used sample-size weighting; 1 used both inverse-variance and sample-size; and 2 meta-analyses used the Mantel-Haenszel effect-size based method. The median number of SNPs discovered, i.e. passing the respective significance or other thresholds, in these 139 meta-analyses was 4 (IQR, 2-9). Of note, 18 meta-analyses had made no discoveries. The maximum number of discovered
