Prediction of coronary heart disease risk using a genetic risk score: The atherosclerosis risk in communities study

Alanna C. Morrison, Lance A. Bare, Lloyd E. Chambless, Stephen G. Ellis, Mary Malloy, John P. Kane, James S. Pankow, James J. Devlin, James T. Willerson, Eric Boerwinkle

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203 Scopus citations


Recent studies have evaluated whether incorporating nontraditional risk factors improves coronary heart disease (CHD) prediction models. This 1986-2001 US study aggregated the contribution of multiple single nucleotide polymorphisms into a genetic risk score (GRS) and assessed whether the GRS plus traditional risk factors predict CHD better than traditional risk factors alone. The Atherosclerosis Risk in Communities (ARIC) cohort was followed for a median of 13 years for CHD events (n = 1,452). Individuals were genotyped for 116 single nucleotide polymorphisms associated with CHD in multiple case-control studies. Single nucleotide polymorphisms nominally predicting incident CHD in the ARIC study were included in the GRS. The GRS was significantly associated with incident CHD in Blacks (hazard rate ratio = 1.20, 95% confidence interval: 1.11, 1.29) and Whites (hazard rate ratio = 1.10, 95% confidence interval: 1.06, 1.14) as well as in each tertile defined by the traditional cardiovascular risk score (p ≤ 0.02). When receiver operating characteristic curves based on traditional risk factors were recalculated after the GRS was added, the increase in the area under the receiver operating characteristic curve was statistically significant for Blacks and suggestive of improved CHD prediction for Whites. This study demonstrates the concept of aggregating information from multiple single nucleotide polymorphisms into a risk score and indicates that it can improve prediction of incident CHD in the ARIC study.

Original languageEnglish (US)
Pages (from-to)28-35
Number of pages8
JournalAmerican journal of epidemiology
Issue number1
StatePublished - Jul 2007


  • Cardiovascular diseases
  • Genetics
  • Polymorphism, genetic
  • Risk factors

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