title: Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example.
abstract: OBJECTIVE
  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.
  
  
  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.
  
  
  CONCLUSIONS
  The proposed method facilitates the standardized incorporation of a GRS in risk assessment.
authors.affiliation: Department of Medicine, Stanford University School of Medicine Stanford, CA, USA.
authors.forename: Benjamin A
authors.initials: BA
authors.lastname: Goldstein
authors.affiliation: Department of Medicine, Stanford University School of Medicine Stanford, CA, USA.
authors.forename: Joshua W
authors.initials: JW
authors.lastname: Knowles
authors.affiliation: Department of Medicine, Stanford University School of Medicine Stanford, CA, USA.
authors.forename: Elias
authors.initials: E
authors.lastname: Salfati
authors.affiliation: Department of Medicine, Stanford University School of Medicine Stanford, CA, USA ; Department of Health Research and Policy, Stanford University School of Medicine Stanford, CA, USA ; Department of Statistics, Stanford University School of Humanities and Sciences Stanford, CA, USA.
authors.forename: John P A
authors.initials: JP
authors.lastname: Ioannidis
authors.affiliation: Department of Medicine, Stanford University School of Medicine Stanford, CA, USA.
authors.forename: Themistocles L
authors.initials: TL
authors.lastname: Assimes
keywords: coronary heart disease; electronic health records; genetic risk scores; personalized medicine