title: Genetic Risk Scores.
abstract: The generation of genome-wide variation data has become commonplace. However, the potential for interpretation and application of these data for clinical assessment of outcomes of interest, and prediction of disease risk, is currently not fully realized. Many common, complex diseases now have numerous, well-established "risk" loci, and likely harbor many genetic determinants with effects too small to be detected at genome-wide levels of statistical significance. A simple and intuitive approach for converting genetic data to a predictive measure of disease susceptibility is to aggregate the risk effects of these loci into a single genetic risk score. Here, some common methods and software packages for calculating genetic risk scores, with focus on studies of common, complex diseases, are described. The basic information needed as well as important considerations for constructing genetic risk scores, including specific requirements for phenotypic and genetic data, and limitations in their application is reviewed. © 2016 by John Wiley & Sons, Inc.
authors.affiliation: Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio.
authors.forename: Jessica N
authors.initials: JN
authors.lastname: Cooke Bailey
authors.affiliation: Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio.
authors.forename: Robert P
authors.initials: RP
authors.lastname: Igo
mesh_terms: D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D010641:Phenotype; D018570:Risk Assessment / Q000379:methods*; D012984:Software
keywords: auc; complex diseases; complex traits; disease prediction; genetic risk score