Innovative Approaches to Assess Intermediate Cardiovascular Risk Subjects: A Review From Clinical to Metabolomics Strategies

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.

Keywords: atherosclerosis; cardiovascular prevention; coronary artery disease (CAD); metabolomics; risk stratification.

Figure 1

Limitations of current non-invasive techniques for re-stratification of intermediate risk patients. The management of asymptomatic subjects with intermediate risk is considered uncertain and challenger. The ability to re-stratify these patients as either low or high risk would confer important benefits. Limitations of the non-invasive techniques considered as risk modifiers to improve risk prediction and decision making include cost, accuracy, overtreatment, and radiation exposure. CV, Cardiovascular; CAC, Coronary Artery Calcium score; hs-CRP, high-sensitivity C-Reactive Protein; CIMT, Carotid Intima-Media Thickness; CAD, Coronary Artery Disease.

Figure 2

Metabolomics approaches in CAD risk stratification. Inaccurate stratification using current models is a challenge to be overcome, particularly in the group of asymptomatic individuals at intermediate risk for CAD. Current tools for cardiovascular risk assessment usually fail to accurately predict CAD asymptomatic subjects. Discriminant metabolites originated from metabolomics approaches may become promising candidate molecules to aid CAD risk stratification. Prospective studies with metabolomic's biomarkers usually apply MS instruments and/or NMR as main analytical techniques. Once the effectors from the plaques (possible lipid droplets and/or exosomes) that are carried in plasma are extracted and injected in those analytical instruments. Abundant metabolite ions are detected and identified after data processing and chemometrics approach. This molecular signature could be integrated to clinical and laboratorial data to restratify intermediate subjects. CAD, Coronary Artery Disease; CIMT, Carotid Intima-Media Thickness; CAC, Coronary Artery Calcium score; hs-CRP, high-sensitivity C-Reactive Protein; MS, mass spectrometry; NMR, nuclear magnetic resonance spectroscopy.

Figure 3

The formation of the atheroma and susceptibility to rupture. The formation of the atheroma derives from an insidious sequence of events starting with entry and accumulation of LDL particles within the sub endothelial space, more specifically in the intima. Once trapped by molecules of the extracellular matrix, those particles are more susceptible to biochemical modifications, including oxidation, which turn them pro-inflammatory. While LDL can accumulate in the intima, a dysfunctional endothelium facilitates the entry of circulating inflammatory cells. Indeed, the exposure of the endothelial monolayer to risk factors unbalances several of its properties, resulting in reduced production of endogenous vasodilators, and expression of adhesion molecules and chemo attractants, which lead to inflammatory cell accumulation in the embryonary atheroma. Distinct inflammatory cells can participate in atherogenesis. Macrophages can internalize local accumulated lipids and become foam cells. Upon cell death, lipids and debris from dead cells can form the atheroma lipid necrotic core. The susceptibility of the plaque to rupture depends on the size of the necrotic lipid, the amount of plaque macrophages, presence of positive remodeling, spotty calcification, and predominance of IFN, TNF-rich Th1 cells (thin fibrous plaque). LDL, low-density lipoprotein cholesterol; IFN, interferon; TNF, tumor necrosis factor; Th1: Type 1 T helper.

Figure 4

Schematic view of subclinical CAD metabolomic-signature by high-performance analytical tool. Prospective studies of metabolomic biomarkers usually apply MS instruments coupled with chromatography systems as the main analytical technique. In these protocols, once the components extracted from the plaque are injected, abundant metabolite ions are detected in specific regions of the chromatogram, and compared to a database for identification, on the mass-to-charge ratio and fragmentation patterns. Statistical analysis and network modeling complement the refinement of patients analytical data, discriminating samples from different stages and identifying metabolic pathways and biomarkers that could lead to acute coronary syndromes (angina and myocardial infarction). CAD, Coronary Artery Disease; MS, mass spectrometry.