We calculated polygenic scores (PGS) based on the SNP effect sizes of the leave-one-out meta-analyses, from which four cohorts were (separately) excluded and reserved for score validation. These included a child (GENR), young adult (S4S), and adult sample (RS). We also included the UKB-wb sample to test for validation in a very large (N = 53,576) cohort with the greatest phenotypic similarity to the largest contributor to the meta-analysis statistics (UKB-ts), in order to maximize potential predictive power. PGS were calculated on the genotype data using LDpred21, a Bayesian PGS method that utilizes a prior on effect size distribution to remodel the SNP effect size and account for LD, and PRSice20, a PLINK41-based program that automates optimization of the set of SNPs included in the PGS based on a high-resolution filtering of the GWAS P-value threshold. LDpred PGS were applied to the called, cleaned, genotyped variants in each of the validation cohorts with UK Biobank as the LD reference panel. PRSice PGS were calculated on hard-called imputed genotypes using P-value thresholds from 0.0 to 0.5 in steps of 0.001. The
