Key result
Predictive genetic testing shows promise for CAD risk stratification but faces major implementation hurdles.
Why the study?
Individual risk prediction and stratification for CAD is difficult due to its multifactorial, polygenic nature and environmental components, prompting interest in genotype-based risk prediction.
Does genotype-based CAD risk prediction improve upon the discrimination and stratification offered by conventional risk factors alone?
Does genotype-based CAD risk prediction improve upon the discrimination and stratification offered by conventional risk factors alone?
While genetic testing for CAD risk variants like the 9p21.3 locus shows promise, its clinical utility and superiority over traditional risk factors remain complex and challenging to implement.
Answers are grounded in this paper and cite their sources.
Genetic CAD risk prediction shows promise but faces implementation challenges; leaves open its added value over traditional factors in clinical practice.
Coronary artery disease (CAD) is an inflammatory-metabolic disease in which atherosclerotic plaques cause stenosis of the coronary arteries, leading to acute clinical complications such as myocardial infarction. Since CAD is a multifactorial, polygenic disease with a substantial environmental component, individual risk prediction and stratification is often difficult. Recent technological advances have resulted in substantial progress elucidating the impact of common genetic variation on CAD progression. The discovery of common genetic variants, including the chromosome 9p21.3 locus as the strongest and most highly replicated independent genetic CAD risk factor, has stimulated interest in genetic testing for CAD-associated risk variants. The ultimate goal of genotype-based CAD risk prediction is to improve upon the discrimination and stratification offered by conventional risk factors alone. Genotype-based CAD risk prediction may eventually have clinical utility, but not without intrinsic complexities. Are genotype variables superior predictors of risk compared to a family history of CAD? Is a 10-year risk prediction window ambitious enough for the predictive power of genotype data? This review will outline the current state of genotype-based CAD risk prediction and highlight challenging issues integral to the successful implementation of genetic testing for CAD.
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Johansen et al. (2009) conducted a review in Coronary artery disease. Predictive genetic testing was evaluated. Predictive genetic testing for coronary artery disease may eventually offer clinical utility for risk stratification, though its successful implementation faces intrinsic complexities.
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