# Coronary Artery Disease

Polygenic risk for coronary artery disease no longer collapses into a single number. Conventional scores identify who is at high risk but not which biological processes drive that risk. Decomposing 526 genome-wide significant variants by their associations with 78 CAD-related traits yielded eight latent components: cholesterol-enriched lipoproteins, triglyceride-rich lipoproteins, lipoprotein(a), metabolically unhealthy normal weight, obesity, endothelial dysfunction, coagulation and cardiac remodeling. Process-specific scores built in UK Biobank, SCAPIS and Mass General Brigham Biobank tracked clinical coronary events, subclinical atherosclerosis and distinct biomarker and comorbidity profiles.

Polygenic risk for coronary artery disease no longer collapses into a single number. Conventional scores identify who is at high risk but not which biological processes drive that risk. Decomposing 526 genome-wide significant variants by their associations with 78 CAD-related traits yielded eight latent components: cholesterol-enriched lipoproteins, triglyceride-rich lipoproteins, lipoprotein(a), metabolically unhealthy normal weight, obesity, endothelial dysfunction, coagulation and cardiac remodeling. Process-specific scores built in UK Biobank, SCAPIS and Mass General Brigham Biobank tracked clinical coronary events, subclinical atherosclerosis and distinct biomarker and comorbidity profiles.

This review surveys recent advances in coronary CT angiography (CCTA) for coronary artery disease: AI-driven plaque and stenosis quantification can cut analysis time from over 25 minutes to typically under 60 seconds per case with correlation coefficients of 0.92-0.95 against intravascular ultrasound, photon-counting detector CT (PCD-CT) reduces calcium blooming at ultra-high resolution and reclassifies some cases to lower CAD-RADS categories, and FFR-CT adds noninvasive lesion-specific physiologic assessment, so that combining the three can support more refined risk stratification for major adverse cardiovascular events and preventive therapy decisions.

This review surveys recent advances in coronary CT angiography (CCTA) for coronary artery disease: AI-driven plaque and stenosis quantification can cut analysis time from over 25 minutes to typically under 60 seconds per case with correlation coefficients of 0.92-0.95 against intravascular ultrasound, photon-counting detector CT (PCD-CT) reduces calcium blooming at ultra-high resolution and reclassifies some cases to lower CAD-RADS categories, and FFR-CT adds noninvasive lesion-specific physiologic assessment, so that combining the three can support more refined risk stratification for major adverse cardiovascular events and preventive therapy decisions.