We re-estimated the p-factor model using the summary statistics from the SCZ and MDD GWASs that did not overlap with the UKB dataset, in order to predict psychiatric symptoms in UKB (Supplementary Figure 20 for phenotypic model). In order to produce a reliable set of targets for polygenic prediction, and to focus our analyses on construct validation, latent factors of psychiatric symptoms were specified as the out-of-sample targets. We compared the magnitude of out-of-sample-prediction for the p-factor PGSs predicting the phenotypic p-factor and factors of individual psychiatric domains relative to the prediction using PGSs derived from univariate summary statistics (Figure 3, Supplementary Table 9). The PGSs for the genetic p-factor predicted more variance in symptoms of depression, psychotic experiences, mania, anxiety, PTSD and a phenotypic p-factor than any univariate PGS.
