Polygenic score

The two graphics illustrate sampling distributions of polygenic scores and the predictive ability of stratified sampling on polygenic risk score with increasing age. + The left panel shows how risk—(the standardized PRS on the x-axis)—can separate 'cases' (i.e., individuals with a certain disease, (red)) from the 'controls' (individuals without the disease, (blue)). The y-axis (vertical axis) indicates how many in each group are assigned a certain score. + At the right panel, the same population is divided into three groups according to their predicted risk, i.e., their assigned score, as high (red), middle (gray), or low (blue). The y-axis shows the observed risk amounts, where the x-axis shows the groups separating in risk as they age—corresponding with the predicted risk scores.

In genetics, a polygenic score (PGS) is a number that summarizes the estimated effect of many genetic variants on an individual's phenotype. The PGS is also called the polygenic index (PGI) or genome-wide score; in the context of disease risk, it is called a polygenic risk score (PRS or PR score[1]) or genetic risk score. The score reflects an individual's estimated genetic predisposition for a given trait and can be used as a predictor for that trait.[2][3][4][5][6] It gives an estimate of how likely an individual is to have a given trait based only on genetics, without taking environmental factors into account; and it is typically calculated as a weighted sum of trait-associated alleles.[7][8][9]

Recent progress in genetics has developed polygenic predictors of complex human traits, including risk for many important complex diseases[10][11] that are typically affected by many genetic variants, each of which confers a small effect on overall risk.[12][13] In a polygenic risk predictor the lifetime (or age-range) risk for the disease is a numerical function captured by the score which depends on the states of thousands of individual genetic variants (i.e., single-nucleotide polymorphisms, or SNPs).

Polygenic scores are widely used in animal breeding and plant breeding due to their efficacy in improving livestock breeding and crops.[14] In humans, polygenic scores are typically generated from data of genome-wide association study (GWAS). They are an active area of research spanning topics such as learning algorithms for genomic prediction; new predictor training; validation testing of predictors; and clinical application of PRS.[15][16][17][4][11] In 2018, the American Heart Association named polygenic risk scores as one of the major breakthroughs in research in heart disease and stroke.[18]

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