Novel and Emerging Biomarkers with Risk Predictive Utility for Atherosclerotic Cardiovascular Disease

Purpose of Review: Since the release of the American Heart Association and American College of Cardiology’s 2013 pooled cohort equations and the European Cardiology Society’s 2016 SCORE, numerous studies have better characterized the predictive ability of emerging and novel biomarkers for atherosclerotic cardiovascular disease (ASCVD). Here, we review these emerging ASCVD biomarkers, with a focus on those that have been assessed using risk discrimination and reclassification performance indices in large population studies. Recent Findings: These biomarkers include genetic risk scores (GRS) based on a growing number of risk alleles, inflammatory and thrombotic markers, lipid components and functional measures, protein metabolites, microRNAs, and a variety of subclinical atherosclerosis imaging measures. While most of these markers have demonstrated some degree of association with and predictive utility for ASCVD, only coronary artery calcium (CAC) has demonstrated consistent risk prediction improvement across multiple population and risk profiles. Summary: Although CAC has garnered evidence to merit inclusion in modern risk prediction algorithms, large population studies and high-throughput genetic and protein technologies have shown promise for the risk prediction utility of several emerging biomarkers that may warrant consideration in future multimodality ASCVD risk prediction algorithms. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.