LD-pred242 was used to calculate the PGS of SCZ, BIP, LCU, and CUD, separately, in TOP samples using the above GWAS datasets (Supplementary Methods). For each PGS, we examined the significance and extent (PGS.R2) of association with BIP and SCZ diagnosis using a generalized logistic regression model (‘single-PGS’ models) adjusting for sex, age, genetic batch ID, and the first 20 genetic principal components. The Benjamini-Hochberg correction (q<0.05) was performed.
