Genomic prediction

This recent paper gives a sense of the current state of the art in quantitative genetics. Height is one of the easiest phenotypes to measure, so almost every medical (disease) GWAS provides some additional data -- IIRC, about 200k pheno/geno-type pairs are available for analysis. With a few hundred associated variants detected (depending on how one defines the discovery threshold), one can start to construct predictors like the Weighted Allele Score (WAS) shown below (which is essentially the breeding value from population genetics). See related posts here, here and here.

It is interesting to think about what a similar figure would look like once loci accounting for 50% or 80% of total variance have been identified. (The current value is about 10%.) I would guess this will happen within 5-10 years (approx. 10^7 individuals of known height genotyped).

Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals

PLoS Genet 7(12): e1002439. doi:10.1371/journal.pgen.1002439

Abstract: Common genetic variants have been shown to explain a fraction of the inherited variation for many common diseases and quantitative traits, including height, a classic polygenic trait. The extent to which common variation determines the phenotype of highly heritable traits such as height is uncertain, as is the extent to which common variation is relevant to individuals with more extreme phenotypes. To address these questions, we studied 1,214 individuals from the top and bottom extremes of the height distribution (tallest and shortest ,1.5%), drawn from ,78,000 individuals from the HUNT and FINRISK cohorts. We found that common variants still influence height at the extremes of the distribution: common variants (49/141) were nominally associated with height in the expected direction more often than is expected by chance (p,5610228), and the odds ratios in the extreme samples were consistent with the effects estimated previously in population-based data. To examine more closely whether the common variants have the expected effects, we calculated a weighted allele score (WAS), which is a weighted prediction of height for each individual based on the previously estimated effect sizes of the common variants in the overall population. The average WAS is consistent with expectation in the tall individuals, but was not as extreme as expected in the shortest individuals (p,0.006), indicating that some of the short stature is explained by factors other than common genetic variation. The discrepancy was more pronounced (p,1026) in the most extreme individuals (height,0.25 percentile). The results at the extreme short tails are consistent with a large number of models incorporating either rare genetic non-additive or rare non-genetic factors that decrease height. We conclude that common genetic variants are associated with height at the extremes as well as across the population, but that additional factors become more prominent at the shorter extreme.