Finally, we applied LD Score regression to summary statistics from GWAS representing more than 20 different phenotypes15–32 (see Table 1 and Supplementary Figures 8a–w. Metadata about the studies in the analysis are presented in Supplementary Tables 10a,b). For all studies, the slope of the LD Score regression was significantly greater than 0, and the LD Score regression intercept was substantially less than λGC (mean difference 0.11), suggesting that polygenicity significantly contributes to the increase in mean χ2 and confirming that correcting test statistics by dividing by λGC is unnecessarily conservative. As an example, Figure 2 displays the LD Score regression for the most recent schizophrenia GWAS, restricted to ~70,000 European individuals33. The low intercept of 1.07 and indicates at most a small contribution of bias, and that the mean χ2 of 1.613 results mostly from polygenicity. LD Score plots for all other GWAS included in table 1 can be found in Supplementary Figures 8a–w. As with any inference procedure that relies on a model of genetic architecture, it is possible that our results may be biased by model misspecifications other
