Chunk #15 — Polygenic Risk Scores: A Bridge Between Population Variation and Individual Differences — PRS Practicalities — STEP 1: Identify a well-powered discovery GWAS in which your sample is not included and obtain summary statistics from that analysis.
The remarkable popularity of PRS is in part attributable to the increasing availability of full summary statistics from discovery GWAS, a data-sharing approach spearheaded by the PGC (https://www.med.unc.edu/pgc/results-and-downloads), who not only share the summary statistics of their GWAS but also do so prior to formal publication and host results files from other consortia and investigators. PRS are derived by applying the “effect” alleles and their corresponding effect sizes (odds-ratios or beta coefficients) from a discovery GWAS to an independent, target sample (Figure 1). Because the effect size is used to weight allelic risk, its reliability is critically important. Hence, the better powered the discovery GWAS is, which is undoubtedly related to sample size, but also, arguably, to phenotypic relevance and strength of assessment, as well as sample composition (CONVERGE, 2015), the greater the confidence we might have in the resulting effect sizes. In Figure 1, we use the example of the current largest GWAS of Schizophrenia which includes 36,989 cases and 113,075 controls (Schizophrenia Working Group of the Psychiatric Genomics, 2014). While it is not necessary for the discovery GWAS
