Notwithstanding the increase of effect size of the PRS, and calculations yielding a more precise estimate, the variance explained by the PRS was still relatively small, which was expected in light of the low SNP heritability. Given the highly polygenic architecture of ASB, contributing SNPs have low average effect sizes, thus leading to limited predictive power in independent samples. New PRS methods along with further increasing sample sizes will likely further increase the amount of variance accounted for by the PRS. Moreover, the association may be enhanced by improving the quality of phenotype measurements, which is reflected by our PRS results demonstrating the most robust association with high-quality measurement of ASB (using a factor score based upon multiple assessments). Aggregating data from measurements across ages, as opposed to the measures assessed at a single time point, can lead to more reliable trait measures and to better prediction [46]. Phenotypically, adding more extreme ASB phenotypes to the GWAS meta-analysis might also lead to more explained variance. In addition, the inclusion of clinical samples displaying extreme ASB phenotypes (e.g., [multiple] homicide, sexual
