The methods for calculating PRS have been developed in the last 10 years as a tool to capture the cumulative effects of many genetic loci into a single quantitative metric 2, 3. This quantitative score sums the effects of individually associated single-nucleotide polymorphisms (SNPs) from an independent GWAS, enumerates how many risk alleles are carried by that individual at each locus (0, 1, or 2), and weights the risk allele at each locus by its effect size. A risk allele is defined as a gene variant that is more commonly found in cases than controls (or that is associated with more severe manifestations of a quantitative trait). Effect sizes are typically estimated as the beta-coefficient for quantitative traits and as an odds ratio for categorical binary traits (with logarithmic transformation of the odds ratios to center values around zero for use in PRS, so that PRS can be computed as a sum of weighted genotypes). An example of a population distribution of a PRS, showing a normal distribution, is illustrated in Figure 1. PRS can be calculated using different sets
