AUTHOR=Martins Aline M. A. , Paiva Mariana U. B. , Paiva Diego V. N. , de Oliveira Raphaela M. , Machado Henrique L. , Alves Leonardo J. S. R. , Picossi Carolina R. C. , Faccio Andréa T. , Tavares Marina F. M. , Barbas Coral , Giraldez Viviane Z. R. , Santos Raul D. , Monte Guilherme U. , Atik Fernando A. TITLE=Innovative Approaches to Assess Intermediate Cardiovascular Risk Subjects: A Review From Clinical to Metabolomics Strategies JOURNAL=Frontiers in Cardiovascular Medicine VOLUME=8 YEAR=2021 URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2021.788062 DOI=10.3389/fcvm.2021.788062 ISSN=2297-055X ABSTRACT=

Current risk stratification strategies for coronary artery disease (CAD) have low predictive value in asymptomatic subjects classified as intermediate cardiovascular risk. This is relevant because not all coronary events occur in individuals with traditional multiple risk factors. Most importantly, the first manifestation of the disease may be either sudden cardiac death or acute coronary syndrome, after rupture and thrombosis of an unstable non-obstructive atherosclerotic plaque, which was previously silent. The inaccurate stratification using the current models may ultimately subject the individual to excessive or insufficient preventive therapies. A breakthrough in the comprehension of the molecular mechanisms governing the atherosclerosis pathology has driven many researches toward the necessity for a better risk stratification. In this Review, we discuss how metabolomics screening integrated with traditional risk assessments becomes a powerful approach to improve non-invasive CAD subclinical diagnostics. In addition, this Review highlights the findings of metabolomics studies performed by two relevant analytical platforms in current use–mass spectrometry (MS) hyphenated to separation techniques and nuclear magnetic resonance spectroscopy (NMR) –and evaluates critically the challenges for further clinical implementation of metabolomics data. We also discuss the modern understanding of the pathophysiology of atherosclerosis and the limitations of traditional analytical methods. Our aim is to show how discriminant metabolites originated from metabolomics approaches may become promising candidate molecules to aid intermediate risk patient stratification for cardiovascular events and how these tools could successfully meet the demands to translate cardiovascular metabolic biomarkers into clinical settings.