All data analyses were carried out using R statistical software (43). First, to examine the overall level of association between the PGSs and AUBs, mean levels of CON and HED were calculated in each sample, averaging across all available waves of data per individual. Each PGS residual was used to predict mean CON and HED in a linear regression model with the lmer() or lm() functions, for cohorts with (COGA, FinnTwin12, FTC) or without (AddHealth, ALSPAC, S4S) relatives, respectively. Regression coefficient estimates were meta-analyzed using random effects inverse variance weighting with the metafor package (44).
