Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction

Area of Science:

• Genetics
• Cardiovascular Medicine
• Risk Prediction

Background:

• Standard cardiovascular disease risk calculators are crucial for managing preventative treatments.
• There is significant interest in augmenting these tools with genetic data for improved accuracy.

Purpose of the Study:

• To develop and validate an integrated risk tool (IRT) for coronary artery disease (CAD) by combining a novel polygenic risk score with existing risk calculators.
• To assess the predictive performance of the IRT compared to standard tools.

Main Methods:

• Developed a novel polygenic risk score for CAD using UK Biobank data.
• Created an IRT by integrating the polygenic risk score with the pooled cohort equations (PCE) or UK QRISK3.
• Validated the IRT in an independent cohort of 186,451 UK Biobank individuals.

Main Results:

• The novel CAD polygenic risk score demonstrated superior predictive power for CAD events.
• The IRT showed superior predictive accuracy compared to PCE and QRISK3 alone, with a net reclassification improvement of 5.9%.
• The IRT significantly improved risk classification across various age-sex subgroups, particularly in younger men.

Conclusions:

• An IRT incorporating polygenic risk outperforms current risk stratification tools, enabling enhanced early intervention opportunities.
• The integration of polygenic risk into future CAD risk tools is recommended due to its proven benefits and decreasing genetic testing costs.