Inverse-variance-weighted meta-analysis was conducted on 28 European cohorts using METAL97. 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 the I2 statistic98,99 (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 artifacts. GWAS summary statistics were subjected to 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 λ was estimated at 1.330 with a 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 substantially confounded by population structure. The genome-wide significance threshold for the GWAS was set at a P value of \documentclass[12pt]{minimal} \usepackage{amsmath}
