Inverse variance weighted meta-analysis was conducted on 28 European cohorts using METAL98. Weighting was based on standard error primarily to account for the large case/control imbalances in cohorts that used linear mixed model approaches in their primary GWAS. Heterogeneity was assessed with Cochran’s Q statistic and I2 statistic99,100 (see Supplementary Note 5 for details). The genomic control factor lambda (λ) was calculated for each individual GWAS and for the overall meta-analysis to identify residual population stratification or systematic technical artifact. GWAS summary statistics were subjected to linkage disequilibrium (LD) score regression (LDSC) analyses on high-quality common SNPs (INFO score > 0.9) to examine the LDSC intercept to distinguish polygenicity from other types of inflation, and to estimate the genetic heritability from the meta-analysis and genetic correlations between cohorts. The genomic inflation factor lambda (λ) was estimated at 1.330 with an λ1000 of 1.033, while the LDSC intercept was 1.0155 (s. e. = 0.0085), indicating that the inflation was mostly due to polygenic signal and unlikely to be significantly confounded by population structure. The genome-wide significance threshold for the GWAS was
