Polygenic score

A polygenic score, also called a polygenic risk score, genetic risk score, or genome-wide score, is a number based on variation in multiple genetic loci and their associated weights (see regression analysis). It serves as the best prediction for the trait that can be made when taking into account variation in multiple genetic variants.

Polygenic scores are widely employed in animal, plant, and behavioral genetics for prediction and understanding genetic architectures. In a genome-wide association study (GWAS), polygenic scores having substantially higher predictive performance than the genome-wide statistically-significant hits indicates that the trait in question is affected by a larger number of variants than just the hits and larger sample sizes will yield more hits; a conjunction of low variance explained and high heritability as measured by GCTA, twin studies or other methods indicates that a trait may be massively polygenic and affected by thousands of variants. Once a polygenic score explaining at least a few percent of variance has been created which effectively identifies most of the genetic variants affecting a trait, it can be used as a lower bound to test whether heritability estimates may be biased, measure the genetic overlap of traits (genetic correlation) which might indicate eg shared genetic bases for groups of mental disorders, used to measure group differences in a trait such as height, examine changes in a trait over time due to natural selection indicative of a soft selective sweep such as intelligence (where the changes in frequency would be too small to detect on each individual hit but the polygenic score declines), used in Mendelian randomization (assuming no pleiotropy with relevant traits), detect & control for the presence of genetic confounds in outcomes (eg the correlation of schizophrenia with poverty), and investigate gene–environment interactions.

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