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Updated: Jun 29, 2025
Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Genetic testing in cardiovascular disease
Michael P Gray1,2, Diane Fatkin3, Jodie Ingles4
1University of Sydney, Sydney, NSW.
Insights
Genetic testing is advancing cardiovascular disease (CVD) risk prediction. Polygenic risk scores offer new avenues for personalized prevention strategies, moving beyond traditional genetic testing for inherited CVDs.
Area of Science:
- Genetics
- Cardiology
- Bioinformatics
Background:
- Cardiovascular disease (CVD) is a major global health burden, causing significant mortality and morbidity.
- Advances in technology and bioinformatics enable identification of genetic variants linked to specific inherited CVDs like familial hypercholesterolaemia.
- Genetic testing for CVD is becoming more accessible and affordable.
Purpose of the Study:
- To explore the role of genetics in common cardiovascular diseases.
- To discuss the application of polygenic risk scores for complex CVDs.
- To highlight the potential of genetic insights for personalized cardiovascular risk prediction and prevention.
Main Methods:
- Review of current literature on genetic contributions to cardiovascular diseases.
- Explanation of polygenic risk scores as a tool for complex genetic traits.
- Discussion of direct-to-consumer genetic testing accessibility.
Main Results:
- Monogenic inheritance patterns are common in specific CVDs, identifiable through genetic testing.
- Common CVDs like coronary artery disease and atrial fibrillation are influenced by numerous small-effect genetic variants.
- Polygenic risk scores mathematically integrate these variants for comprehensive risk assessment.
Conclusions:
- Understanding the genetic architecture of CVD is crucial for advancing personalized medicine.
- Polygenic risk scores represent a significant development in predicting risk for common cardiovascular diseases.
- Genomic insights hold promise for tailoring preventive therapies and improving clinical management of CVD.
Abstract:
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally and is responsible for an estimated one-third of deaths as well as significant morbidity and health care utilisation. Technological and bioinformatic advances have facilitated the discovery of pathogenic germline variants for some specific CVDs, including familial hypercholesterolaemia, cardiomyopathies and arrhythmic syndromes. Use of these genetic tests for earlier disease identification is increasing due, in part, to decreasing costs, Medicare rebates, and consumer comfort with genetic testing. However, CVDs that occur more commonly, including coronary artery disease and atrial fibrillation, do not display monogenic inheritance patterns. Genetically, these diseases have generally been associated with many genetic variants each with a small effect size. This complexity can be expressed mathematically as a polygenic risk score. Genetic testing kits that provide polygenic risk scoring are becoming increasingly available directly to private-paying consumers outside the traditional clinical setting. An improved understanding of the evidence of genetics in CVD will offer clinicians new opportunities for individualised risk prediction and preventive therapy.
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