To investigate the loci identified in the individual GWAS further, we performed a phenome-wide scan considering 4,082 traits assessed in up to 361,194 participants from the UK Biobank using previously generated GWAS association summary data23. Details regarding QC criteria and GWAS methods of this previous analysis are available at https://github.com/Nealelab/UK_Biobank_GWAS/tree/master/imputed-v2-gwas. Briefly, the association analyses for all phenotypes were conducted using regression models available in Hail (available at https://github.com/hail-is/hail) including the first 20 ancestry principal components, sex, age, age2, sex×age, and sex×age2 as covariates. We applied a false discovery rate (FDR) multiple testing correction (q<0.05) to account for the number of variants and phenotypes tested. Additionally, we investigated the associations of the loci we identified here with respect to 27 non-duplicated traits related to mental and behavioral disorders attributable to use of alcohol, cannabis, and tobacco (Supplementary Table 3). This information was derived from large-scale summary association data collected by the GWAS Atlas (available at https://atlas.ctglab.nl/)24. We also conducted a gene-based phenome-wide scan across 4,756 available datasets in the GWAS Atlas. A Bonferroni correction accounting for the number of traits tested was applied to this gene-based analysis (p<1.05×10−5).
