Genomic Risk Stratification Predicts All-Cause Mortality After Cardiac Catheterization

Area of Science:

• Cardiovascular Genetics
• Genomic Risk Prediction
• Public Health Genomics

Background:

• Coronary artery disease (CAD) is influenced by genetic factors and traditional risk factors.
• Polygenic risk scores (PRS) can identify individuals at elevated risk for CAD before traditional risk factors develop.
• Genome-wide PRS for CAD has shown potential in predicting mortality.

Purpose of the Study:

• To evaluate if a genome-wide PRS for CAD can predict all-cause mortality.
• To determine if PRS adds predictive value beyond traditional risk factors and angiographic CAD.
• To assess the mortality risk associated with high PRS in individuals with and without angiographic CAD.

Main Methods:

• A genome-wide PRS was calculated for 1503 participants undergoing coronary angiography.
• Participants were categorized into high PRS (hiPRS) and low-PRS groups.
• All-cause mortality after the index coronary angiogram was the primary outcome, with adjustments for traditional risk factors and CAD severity.

Main Results:

• Individuals with hiPRS had a significantly increased risk of all-cause mortality (HR, 1.6; P=0.004) after adjusting for traditional risk factors and angiographic CAD.
• The risk of all-cause mortality was highest in individuals with hiPRS but without angiographic CAD (HR, 2.4; P=0.04).
• Adding hiPRS to traditional risk assessment improved the prediction of 5-year all-cause mortality (AUC 0.70 vs 0.66; P=0.001).

Conclusions:

• A genome-wide PRS enhances risk stratification for all-cause mortality when combined with traditional risk factors and coronary angiography findings.
• Individuals without angiographic CAD but with a high PRS face a significantly elevated risk of mortality.
• PRS offers valuable prognostic information for cardiovascular risk assessment.