2023 ACMG Annual Clinical Genetics Meeting Digital Edition: Poster Gallery-Polygenic risk scores improve 10-year risk prediction of coronary artery disease in individuals at borderline and intermediate clinical risk

Polygenic risk scores improve 10-year risk prediction of coronary artery disease in individuals at borderline and intermediate clinical risk

Back to course

Pdf Summary

Coronary artery disease (CAD) is a leading cause of death worldwide, often developing over many years before symptoms appear. The Atherosclerotic Cardiovascular Disease (ASCVD) risk estimator is commonly used to predict CAD risk and guide treatment decisions. Genome-wide association studies have identified several genetic variants associated with CAD, which can be combined into a polygenic risk score (PRS). However, most PRS are based on European cohorts, and their validity in other ancestral groups is unclear.<br /><br />A study aimed to develop and validate a PRS for CAD in diverse populations and a screening tool combining the PRS with the ASCVD risk estimator to identify individuals at high risk who may benefit from early intervention. The study found that the PRS was significantly associated with CAD risk in validation cohorts of different ancestries. The screening tool, called the IRS model, outperformed the ASCVD risk estimator alone, particularly in South Asian and European ancestry groups. The IRS model identified additional individuals at high risk among those classified as borderline or intermediate risk by the ASCVD risk estimator.<br /><br />Overall, the study showed that PRS can improve the prediction of CAD risk, especially in individuals of diverse ancestries. The IRS model combining the PRS with the ASCVD risk estimator has the potential to identify individuals who may benefit from early intervention, such as statin treatment. Future directions may include further validation of the PRS and IRS model in larger cohorts and exploring their use in clinical practice to improve CAD risk assessment and personalized treatment.

Asset Subtitle

Presenting Author - Placede Tshiaba, MS; Co-Author - Dariusz Ratman, PhD; Co-Author - Jiayi Sun, PhD; Co-Author - Tate Tunstall, PhD; Co-Author - Robert Maier, MD PhD; Co-Author - Premal Shah, PhD; Co-Author - Matthew Rabinowitz, PhD; Co-Author - Akash Kumar, MD PhD; Co-Author - Kate Im, PhD;

Meta Tag

Bioinformatics

Cardiac/circulatory disorders

Clinical History

Companion Diagnostics

Genetic Diversity

Genetic Testing

Polygenic risk scores

Population Genetics

Risk Assessment

Co-Author Dariusz Ratman, PhD

Co-Author Jiayi Sun, PhD

Co-Author Tate Tunstall, PhD

Co-Author Robert Maier, MD PhD

Co-Author Premal Shah, PhD

Co-Author Matthew Rabinowitz, PhD

Co-Author Akash Kumar, MD PhD

Co-Author Kate Im, PhD

Presenting Author Placede Tshiaba, MS

Keywords

Coronary artery disease

CAD

Atherosclerotic Cardiovascular Disease

ASCVD risk estimator

Genome-wide association studies

Polygenic risk score

European cohorts

Ancestral groups

IRS model

Early intervention