subclinical-to-clinical ranges as the target phenotypes. From the UKB dataset, we chose symptoms falling within the following domains: psychosis, mania, depression, post-traumatic stress, and anxiety. We fit a confirmatory factor model (diagram shown in Supplementary Fig. 29) to the phenotypic symptom endorsements, treating them as ordered categorical variables. Analyses were run in Mplus,60 with the target phenotypes—the p-factor and each of the individual domains—specified as latent variables. PGS variables were specified to directly predict the latent phenotypes within the model (i.e., factor score estimates were not used). To construct PGSs, we removed from both the p-factor and univariate summary statistics the 5 SNPs that were identified as having genome-wide significant QSNP estimates for ML, along with SNPs that were in LD with these SNPs using an r2 threshold of 0.1 and 500-kb window. PGSs were constructed using PRSice,61 with LD clumping set to r2 > 0.25 over 250kb sliding windows. PGSs for the p-factor were based on the WLS summary statistics produced using Genomic SEM. We ran PGS analyses using a p-value threshold of 1.0 (i.e., we used all available SNPs apart from those removed due to QSNP analyses). In order to maintain comparability, PGSs for the univariate summary statistics
