Modification of coronary artery disease clinical risk factors by coronary artery disease polygenic risk score

Area of Science:

• Cardiovascular Genetics
• Genomics
• Epidemiology

Background:

• The interplay between clinical risk factors and coronary artery disease (CAD) polygenic risk score (PRS) in predicting incident CAD is not fully understood.
• Investigating these interactions can refine risk prediction models for CAD.

Purpose of the Study:

• To determine if interactions between clinical risk factors and CAD PRS enhance the prediction of incident CAD.
• To assess how CAD PRS modifies the prognostic relevance of established clinical risk factors.

Main Methods:

• Utilized UK Biobank data from 357,144 European ancestry individuals without prevalent CAD.
• Applied an externally trained genome-wide CAD PRS and ascertained clinical risk factors at baseline.
• Employed Cox proportional hazards models to analyze the effects of CAD PRS, risk factors, and their interactions on incident CAD.

Main Results:

• CAD PRS was associated with a 1.35-fold increased risk per SD for incident CAD.
• High CAD PRS diminished the prognostic relevance of type 2 diabetes, increased BMI, and elevated C-reactive protein.
• High CAD PRS showed joint risk increases with elevated LDL cholesterol and total cholesterol.

Conclusions:

• CAD PRS is a significant predictor of incident CAD.
• Integrating CAD PRS with clinical risk factors improves prognostic accuracy, particularly for cholesterol levels.