We used bivariate LD Score regression9 (link) to estimate genetic correlations between general risk tolerance and various phenotypes. We used the scores computed by Finucane et al.50 , which are based on genotypic data from the European-ancestry samples in the 1000 Genomes Project and only HapMap3 SNPs. As is common in the literature, we restricted our analyses to SNPs with MAF > 0.01. We used the summary statistics of the meta-analysis combining our discovery and replication GWAS of general risk tolerance to estimate genetic correlations with general risk tolerance, and we used the summary statistics of our GWAS of adventurousness, our four main risky behaviors, and their first PC to estimate genetic correlations with those phenotypes. For most other phenotypes, we used published GWAS results. We obtained the summary statistics from the GWAS of lifetime cannabis use25 (link) and of ADHD51 from the International Cannabis Consortium and the Psychiatric Genomics Consortium, respectively. We conducted our own GWAS using the first release of the UKB data for five phenotypes: age first had sexual intercourse (n = 98,956), teenage conception among females (n = 40,077), use of sun protection (n = 111,560), household income (n = 97,059), and Townsend deprivation index score (n = 112,192). The sex-specific GWAS of general risk tolerance used to estimate the genetic correlation between males and females were conducted in the full release of UKB data, separately for males and females, following the same methodology and QC protocol as for our other GWAS in the full release of UKB data. The Supplementary Note and Supplementary Tables 9, 31 provide additional details. Also, the Supplementary Note, Supplementary Table 32, and Supplementary Fig. 15 report the results of proxy-phenotype analyses in which we examined whether the general-risk-tolerance lead SNPs tend to also be associated with related phenotypes.