Contemporary Considerations for Constructing a Genetic Risk Score: An Empirical Approach.

Journal Article (Journal Article)

Genetic risk scores are an increasingly popular tool for summarizing the cumulative risk of a set of Single Nucleotide Polymorphisms (SNPs) with disease. Typically only the set of the SNPs that have reached genome-wide significance compose these scores. However recent work suggests that including additional SNPs may aid risk assessment. In this paper, we used the Atherosclerosis Risk in Communities (ARIC) Study cohort to illustrate how one can choose the optimal set of SNPs for a genetic risk score (GRS). In addition to P-value threshold, we also examined linkage disequilibrium, imputation quality, and imputation type. We provide a variety of evaluation metrics. Results suggest that P-value threshold had the greatest impact on GRS quality for the outcome of coronary heart disease, with an optimal threshold around 0.001. However, GRSs are relatively robust to both linkage disequilibrium and imputation quality. We also show that the optimal GRS partially depends on the evaluation metric and consequently the way one intends to use the GRS. Overall the implications highlight both the robustness of GRS and a means to empirically choose the best set of GRSs.

Full Text

Duke Authors

Cited Authors

  • Goldstein, BA; Yang, L; Salfati, E; Assimes, TL

Published Date

  • September 2015

Published In

Volume / Issue

  • 39 / 6

Start / End Page

  • 439 - 445

PubMed ID

  • 26198599

Pubmed Central ID

  • PMC4543537

Electronic International Standard Serial Number (EISSN)

  • 1098-2272

Digital Object Identifier (DOI)

  • 10.1002/gepi.21912


  • eng

Conference Location

  • United States