Personalization of primary prevention: Exploring the role of coronary artery calcium and polygenic risk score in cardiovascular diseases

Personalized healthcare is becoming increasingly popular given the vast heterogeneity in disease manifestation between individuals. Many commonly encountered diseases within cardiology are multifactorial in nature and disease progression and response is often variable due to environmental and genetic factors influencing disease states. This makes accurate early identification and primary prevention difficult in certain populations, especially young patients with limited Atherosclerotic Cardiovascular Disease (ASCVD) risk factors. Newer strategies, such as coronary artery calcium (CAC) scans and polygenic risk scores (PRS), are being implemented to aid in the detection of subclinical disease and heritable risk, respectively. Data surrounding CAC scans have shown promising results in their ability to detect subclinical atherosclerosis and predict the risk of future coronary events, especially at the extremes; however, predictive variability exists among different patient populations, limiting the test's specificity. Furthermore, relying only on CAC scores and ASCVD risk scores may fail to identify a large group of patients needing primary prevention who lack subclinical disease and traditional risk factors, but harbor genetic variabilities strongly associated with certain cardiovascular diseases. PRS can overcome these limitations. These scores can be measured in individuals as early as birth to identify genetic variants placing them at elevated risk for developing cardiovascular disease, irrespective of their current cardiovascular health status. By applying PRS alongside CAC scores, previously overlooked patient populations can be identified and begin primary prevention strategies early to achieve optimal outcomes. In this review, we expand on the current knowledge surrounding CAC scores and PRS and highlight the future possibilities of these technologies for preventive cardiology. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)