Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example

Abstract

Purpose: Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers.Materials and Methods: We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.Results: The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. Results are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider.Conclusion: The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

Genetics: Implications for Prevention and Management of Coronary Artery Disease

“…The most practical way to currently integrate genetics into risk prediction models, such as the Framingham Risk Score or the ACC/AHA pooled cohorts calculator, is through the calculation of a genetic risk score (GRS) for individuals (122). A GRS is a single variable that summarizes one's exposure to variants that increase risk for CAD (123).…”

“…A GRS is a single variable that summarizes one's exposure to variants that increase risk for CAD (123). A GRS is typically calculated by summing the product of the number of high-risk variants inherited by each individual for each susceptibility variant and the log of the odds ratio previously determined in a GWAS for the same variant (122). Family history would intuitively serve as a substitute for genetic risk.…”

The Foundation of Precision Medicine: Integration of Electronic Health Records with Genomics Through Basic, Clinical, and Translational Research

“…Developing prediction models for common complex diseases such as type 2 diabetes mellitus, stroke and inflammatory arthritis has been more challenging and the results have been disappointing. This was also evident in the third paper of this group (Goldstein et al, 2014) in which coronary heart disease was investigated in the NIH-funded Atherosclerosis Risk in Communities (ARIC) cohort. The authors combined a genetic risk score derived from 45 SNPs with a clinical risk score, but received only minimal improvement in discrimination and calibration statistics of the risk score.…”

“…The fourth group of papers (Goldstein et al, 2014;Kullo et al, 2014b;Schrodi et al, 2014;Sleiman et al, 2014) belonging to this special issue discusses the use of genetic data together with EHRderived clinical data in clinical settings. The first one of these papers used imputed GWAS data to study two loss-of-function variants in the PCSK9 gene.…”

Sports genetics moving forward: lessons learned from medical research

“…Much work is being done to develop valid methodology in the application of genetic knowledge to the prediction of multifactorial, polygenic diseases and traits (29). To get a comprehensive picture large studies are needed to find common variants, in combination with family studies to discover rare variants.…”