Strong Genes: Insights Into Polygenic Risk and Coronary Artery Calcium in Older Individuals
Year: 2024
Type: editorial
Abstract: cardiovascular disease; risk factors; computerized tomography (CT); genetics Coronary artery calcium (CAC) and polygenic scores (PGS) represent two valuable methods for enhancing understanding and prediction of cardiovascular risk across age groups.Measured through non-invasive computed tomography (CT) scans, coronary artery calcium quantifies the amount of calcified plaque in the coronary arteries, providing a direct assessment of subclinical atherosclerosis.Studies have shown that CAC helps accurately reclassify risk, with individuals with higher CAC scores having significantly increased risk for future cardiovascular events and individuals with a CAC of zero being largely protected from developing events.[1][2][3] Polygenic scores -which quantify inherited risk by summing information from many common sites of DNA variation -hold considerable promise for improving upon available clinical risk estimators.4 Risk estimation by PGS is available early in life, and genotyping data from a single blood test can facilitate PGS calculation for numerous conditions, including coronary artery disease (CAD).5 Advances in genome-wide association studies and statistical methods have led to more accurate risk prediction across diverse populations.6 Both CAC and CAD PGS provide informative and independent risk prediction beyond that of traditional clinical risk factors.7- 10 Similarly, very high values of CAC or CAD PGS are associated with equivalent risk of atherosclerotic cardiovascular disease events as those with established coronary artery disease or familial hypercholesterolemia. 6,[11][12][13] Although several observational studies have outlined the potential of CAC and PGS in predicting CAD risk in the general population, their relevance and applications in older individuals are less understood.
Author: Aniruddh P. Patel
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4404332781
