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.
Highlights
Despite all improvements in prevention, diagnosis, and treatment, coronary artery disease (CAD) remains a leading cause of morbidity and mortality globally [1,2,3,4,5]
It is worth noting that, since we are in the post-genomic era, where biological studies are characterized by the rapid development and wide application portfolio of multiomic technologies, we focus our revision on the use of mass spectrometry and nuclear magnetic resonance spectroscopy as an analytical platform for metabolomics and its contributory role for the primary prevention of CAD (Figure 2)
The publications compiled in this review have shown that the application of a single biomarker may be insufficient for evaluating cardiovascular disease pathophysiology, treatment effect and prognosis, emphasizing that a combination of multiple metabolites may be more accurate in targeting risk patients
Summary
Despite all improvements in prevention, diagnosis, and treatment, coronary artery disease (CAD) remains a leading cause of morbidity and mortality globally [1,2,3,4,5]. Risk prediction plays a central role in the field of cardiovascular disease prevention, notably in a subgroup predicted to be at intermediate risk by traditional models, for which the consideration of new risk markers can help reclassify some individuals and, may influence clinical decision making [11, 13,14,15] In this context, it is essential to remember that the most commonly found cause of CAD is atherosclerosis [16] and, for decades, the traditional view that the formation of an atheroma has followed an inexorably progressive course with age playing a prominent role in disease analysis. Over the past few years, increased evidence has pointed to the role of inflammation in the atheroma development, which has forced many of us to rethink our classical views of atherosclerosis as a segmental or localized disease [17, 18]
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