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Updated: Jun 18, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

Predictive genetic testing for coronary artery disease.

Christopher T Johansen¹, Robert A Hegele

¹Robarts Research Institute, University of Western Ontario, London, Canada.

Critical Reviews in Clinical Laboratory Sciences

|December 5, 2009

Summary

Genetic testing for coronary artery disease (CAD) shows promise for improving risk prediction beyond traditional factors. However, challenges remain in integrating genetic data for clinical use and determining its superiority over family history.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

Cardiovascular Medicine
Genetics
Preventive Cardiology

Background:

Coronary artery disease (CAD) is an inflammatory-metabolic condition characterized by atherosclerotic plaques causing coronary artery stenosis.
CAD is a complex, multifactorial disease influenced by genetics and environment, making individual risk prediction challenging.
Advances in genetic research have identified common genetic variants, such as the chromosome 9p21.3 locus, as significant CAD risk factors.

Purpose of the Study:

To review the current status of genotype-based risk prediction for coronary artery disease (CAD).
To explore the potential clinical utility of genetic testing for CAD risk assessment.
To identify and discuss the complexities and challenges in implementing genetic testing for CAD.

Main Methods:

Review of current literature on genetic variants associated with coronary artery disease (CAD).
Analysis of the role of common genetic variation in CAD progression and risk stratification.
Discussion of the comparative predictive power of genetic data versus conventional risk factors and family history.

Main Results:

Common genetic variants, notably the 9p21.3 locus, are established independent risk factors for CAD.
Genotype-based risk prediction aims to enhance the discrimination and stratification capabilities of existing risk assessment models.
The clinical utility of genotype data requires further investigation, particularly in comparison to family history and within specific prediction windows.

Conclusions:

Genotype-based risk prediction holds potential for improving cardiovascular risk assessment in coronary artery disease (CAD).
Significant challenges exist in comparing genetic predictors to family history and defining appropriate risk prediction timeframes.
Successful clinical implementation of genetic testing for CAD necessitates addressing these complexities and validating predictive models.