Chunk #33 — Polygenic Risk Scores: A Bridge Between Population Variation and Individual Differences — PRS Practicalities — Technical Considerations. — Differences from other heritability metrics:
14–19% of the partner’s education outcomes (Hugh-Jones, Verweij et al. 2016). SNP-h2, calculated with a variety of methods [Genetic Complex Traits Analysis: GCTA (Yang et al., 2011); Linkage Disequilibrium Score Regression: LDScR; (Bulik-Sullivan et al., 2015)], may be used to examine the net effect of all genomewide variants, genotyped and imputed and is related to both twin-h2 and PRS. SNP-h2 is more similar to twin-h2 in that they harness effects of all variants, but only explain a proportion of twin-h2 (especially for behavioral traits), which are typically considered the denominator (perhaps, inaccurately) for such estimation. PRS at a threshold of p < 1.0 might reasonably be expected to approximate SNP-h2, however some have noted that the LD pruning step of PRS estimation may diminish its predictive utility (Vilhjalmsson et al., 2015), by removing correlated loci with independent effect. Nonetheless, PRS are only expected to predict variance in the same trait if SNP-h2 > 0, and in other traits if they are significantly genetically correlated (SNP-rg > 0); however, we view them to be philosophically different (although, SNP-h2 has attractive technical characteristics)2. Twin-h2 and SNP-h2 represent the total variance accounted for by latent genetic and measured common genomic variation, respectively. On
