To examine shared polygenic risk at an aggregate level between pairs of diagnoses, we used risk-score profiling as previously described.8 For each pair, we selected one disorder as a discovery dataset and the other as a target dataset and calculated the proportion of variance in the target set explained by risk scores from the discovery set with a range of statistical cutoffs for SNP inclusion in the score (appendix p 13). To assess the role of specific biological systems in the pathogenesis of the five disorders, we did pathway and eQTL analyses. Pathway analysis was by interval-based enrichment analysis (INRICH) for the full dataset consisting of linkage disequilibrium segments containing signals with association p<10−3 in the primary meta-analysis. INRICH accounts for potential genomic confounding factors, such as variable gene and pathway sizes, SNP density, linkage disequilibrium, and physical clustering of biologically related genes (appendix pp 14–16). We did eQTL enrichment analysis20 to assess whether SNPs associated with five psychiatric disorders were enriched for regulatory SNPs in post-mortem brain tissue samples compared with those with no association.21,22 To assess the specificity
