Our primary analyses were performed using the LDSC software (https://github.com/bulik/ldsc; B. Bulik-Sullivan et al. 2015). Briefly, this set of tools can be used with existing GWAS summary data in order to distinguish polygenicity from confounding caused by uncontrolled population stratification or cryptic relatedness among samples (B. K. Bulik-Sullivan et al. 2015), to estimate the heritability of a given phenotype (B. Bulik-Sullivan et al. 2015), and to estimate the genetic correlation between two phenotypes based on two separate or related sets of summary statistics (B. Bulik-Sullivan et al. 2015). In the latter application, the minimal requirements for each set of summary statistics include columns of data indicating SNP ID, the identities of reference and non-reference alleles, association p-value, effect size, test statistic (e.g., odds ratio, regression β, or Z-score), and sample size (per SNP or for all SNPs). For each pair of phenotypes, this tool compares the strength and direction of association signal at each locus while correcting for the correlation that would be expected based on genetic linkage alone, and it provides an estimate of the genetic correlation between phenotypes.
