Blood metabolomic fingerprint is distinct in healthy coronary and in stenosing or microvascular ischemic heart disease.

BACKGROUND: The endothelium is a key variable in the pathogenesis of atherosclerosis and its complications, particularly coronary artery disease (CAD). Current evidence suggests that the endothelial status can be regarded as an integrated index of individual atherogenic and anti-atherogenic properties, and that the interaction between circulating factors and the arterial wall might be critical for atherogenesis. In organism-level investigations, a functional view is provided by metabolomics, the study of the metabolic profile of small molecules. We sought to verify whether metabolomic analysis can reveal the presence of coronary microenvironment peculiarities associated with distinct manifestations of CAD. METHODS: Thirty-two coronary blood samples were analyzed using 1H-NMR-based metabolomics. Samples collected from patients with evidence of myocardial ischemia formed the case group, and were further divided into the stenotic-disease (SD) group (N = 13) and absence of stenosis (microvascular disease; "Micro") group (N = 8); specimens of patients presenting no evidence of ischemic heart disease (dilated cardiomyopathy, valvular diseases) constituted the control group (N = 11). RESULTS: Application of an orthogonal partial least squares discriminant analysis (OPLS-DA) model to the entire dataset clearly separated the samples into 3 groups, indicating 3 distinct metabolic fingerprints. Relative to control-group members, Micro patients showed a higher content of 2-hydroxybutirate, alanine, leucine, isoleucine, and N-acetyl groups and lower levels of creatine/phosphocreatine, creatinine, and glucose, whereas SD patients showed higher levels of 3-hydroxybutirate and acetate and a lower content of 2-hydroxybutirate. Moreover, relative to SD patients, Micro patients showed higher levels of 2-hydroxybutirate, alanine, leucine, and N-acetyl groups and lower levels of 3-hydroxybutirate and acetate. CONCLUSIONS: Specific coronary microenvironments are likely associated with distinct development and pathological expression of CAD.

Metabolomic approach to profile functional and metabolic changes in heart failure.

BACKGROUND: Heart failure (HF) is characterized by a series of adaptive changes in energy metabolism. The use of metabolomics enables the parallel assessment of a wide range of metabolites. In this study, we appraised whether metabolic changes correlate with HF severity, assessed as an impairment of functional contractility, and attempted to interpret the role of metabolic changes in determining systolic dysfunction. METHODS: A 500 MHz proton nuclear magnetic resonance ((1)H-NMR)-based analysis was performed on blood samples from three groups of individuals: 9 control subjects (Group A), 9 HF patients with mild to moderate impairment of left ventricle ejection fraction (LVEF: 41.9 ± 4.0 %; Group B), and 15 HF patients with severe LVEF impairment (25.3 ± 10.3 %; Group C). In order to create a descriptive model of HF, a supervised orthogonal projection on latent structures discriminant analysis (OPLS-DA) was applied using speckle tracking-derived longitudinal strain rate as the Y-variable in the multivariate analysis. RESULTS: OPLS-DA identified three metabolic clusters related to the studied groups achieving good values for R(2) [R(2)(X) = 0.64; R(2)(Y) = 0.59] and Q(2) (0.39). The most important metabolites implicated in the clustering were 2-hydroxybutyrate, glycine, methylmalonate, and myo-inositol. CONCLUSIONS: The results demonstrate the suitability of metabolomics in combination with functional evaluation techniques in HF staging. This innovative tool should facilitate investigation of perturbed metabolic pathways in HF and their correlation with the impairment of myocardial function.