We assessed the predictive power of polygenic scores of general risk tolerance in six different validation cohorts: Add Health, HRS, NTR, STR, UKB-siblings, and Zurich. (The UKB-siblings cohort comprised all individuals with at least one full sibling in the UKB.) We constructed three polygenic scores. Our first two polygenic scores were constructed with the LDpred28 method, which accounts for the linkage disequilibrium (LD) between SNPs. The first used the summary statistics from the meta-analysis of the discovery and replication GWAS of general risk tolerance, while the second used the MTAG summary statistics. (The LDpred method relies on a Gaussian mixture weight that corresponds to the assumed fraction of SNPs that are causal. For each of our first two polygenic scores, we first generated LDpred scores for each of the following mixture weights: 1, 0.3, 0.1, 0.03, 0.01, 0.003, 0.001, 0.0003, and 0.000153. The LDpred-score results we present in this paper for our first two polygenic scores are for the scores based on a Gaussian mixture weight of 0.3 (our “preferred score”), which consistently performed well across cohorts and phenotypes.) Our
