La Metabolomica: una nuova era in Cardiologia. Le nostre esperienze originali nei campi dell' insufficienza cardiaca, della cardiopatia ischemica e dell' ipertensione polmonare

Purpose. Metabolomics (MBS) is a “omics” science that enables the assessment of a broad range of metabolites providing a metabolic picture able to identify metabolic changes. On these basis we carried out a metabolomics on three settings of cardiovascular diseases: a) heart failure; b) Stable coronary artery disease; c) Pulmonary hypertension in systemic sclerosis. Heart Failure Heart failure (HF) is characterized by a series of maladaptive metabolic changes, which have recently been proposed as a new therapeutic target. A proton nuclear magnetic resonance (1H NMR)-based MBS analysis was performed on blood samples of 3 groups of individuals: nine control individuals (Group A); nine HF patients with mildmoderate impairment of left ventricle ejection fraction (LVEF 35-50%; Group B); fifteen HF patients with severe LVEF impairment (EF <35%; Group C). Specimens were analyzed with a 1HNMR 500MHz spectrometer. A supervised PLS-DA Projection on Latent Structures Discriminant Analysis was applied to realize a descriptive model of HF. Morevoer, we carried out an echocardiographic evaluation of whole study population, including an assessment of Longitudinal Strain (S) and Strain Rate (SR) values using Speakle Tracking Imaging. The three groups showed a progressive impairment of systolic function from Group A to Group C, with intermediate values in Group B. The application of Pattern-recognition methods to 1H-NMR spectra identified 3 metabolic clusters related to A, B and C groups, respectively. The discrimination were related to a metabolic fingerprint depending on a limited set of metabolites. Our preliminary data show that MBS is a sensitive method, which can be effectively used in association with traditional techniques for the evaluation of HF. This new tool may permit to investigate the perturbed metabolic pathways in HF and their correlation with impaired myocardial function and could lead to the identification of innovative therapeutic approaches. Stable coronary artery disease Endothelial dysfunction is a key variable in the pathogenesis and progression of atherosclerosis and its complications, particullary coronary artery disease (CAD). Current evidence suggests that endothelial status is not determined solely by the individual risk factor burden but rather, may be regarded as an integrated index of all atherogenic and atheroprotective factors present in an individual. A 1H-NMR based MBS analysis was performed on (right and left) coronary blood samples of 11 subjects (7 male, 4 female; mean age 66+/-12,87 years) enrolled after a stress echocardiography suggestive for ischemia and undergone a coronary angiography (CA). On the basis of the results of CA we classified patients in two groups: occlusive coronary atherosclerosis (OCA) and microvascular disease (MD). A supervised Orthogonal Projection on Latent Structures Discriminant Analysis (OPLS-DA) was applied to evaluate whether it is possible to realize a descriptive model of the two different expressions of CAD. CA showed an OCA in 6 patients and a MD in the other 5. OPLS-DA identified two clusters related to the CA groups, achieving good values of R2 (R2y=0.994) and Q2 (Q2=0.905); these components featured a significant separation as determined by ANOVA cross-validation (p<0.01). The metabolites of major importance in determining clustering were: Alanine, Beatine, N-N-Dimethyl-glycine, Citrate, Lactate, Malonate, Piruvate and Succinate. Afterwards, we applied an univariate statistical analysis to evaluate the differences in concentration of these metabolites between groups; this analysis showed betaine and DMG higher levels in patients with OCA when compared with those affected by MD (0.3573±0.2324 μM vs 0.1340±0.1040 μM, p<0.03, and 0.0064±0.0032 μM vs 0.0030±0.0014 μM, p<0.02, respectively). It is remarkable that these two metabolites are are related to the NO metabolism and the endothelial function. MBS seems to be a sensitive method, which can be effectively used in the study of CAD pathophysiology. The obtained results, if confirmed, could be the basis of future researches on the role of vascular microambient in determinig the evolution of atherosclerosis in the two different pathophysiological settings and could lead to the identification of innovative therapeutic approaches. Pulmonary hypertension (PH) in systemic sclerosis (SS) Pulmonary hypertension (PH) in systemic sclerosis (SS) identifies a poor prognosis subset of patients. Recent studies suggested a “metabolic theory” on the development of pulmonary arterial hypertension. On these basis we carried out a metabolomics study in order to evaluate whether in SS patients with increased Pulmonary Vascular Resistance (PVR) differences in pulmonary arterial blood metabolites were identifiable. We studied 18 SS patients (age 58,7±15,6 years) free of pulmonary fibrosis that underwent a clinical evaluation, a standard echocardiography with Tissue Doppler and Speckle tracking Imaging and a right heart catheterization (RHC). A blood sample was collected during the RHC in the distal peripheral circulation of the pulmonary arteries to perform the metabolomic analysis. Specimens were analyzed with a 1H-NMR 500MHz spectrometer. An Orthogonal Signal Correction (OSC) and a Projection on Latent Structures Discriminant Analysis (PLS-DA) were applied. Based on PVR we divided the population in Group A (N=8; PVR<1.6 uW; mean±SD = 1,16±0,23 uW) and Group B (N=10; PVR>1.6 uW; mean±SD = 2,67±0,67 uW. p<0.001 vs Group A). No significant differences were identified in terms of anthropometric, clinical, echo and terapeutic characteristics. At RHC the 2 groups showed a difference in mean pulmonary pressures values (Group A: 20±4 mmHg; Group B: 25±5 mmHg), with mild PH in group B. We applied an OSC using NMR data as the X-matrix and PVR values as the Y-matrix. A clear clusterization was observed with the PLS-DA, achieving good values of R2 (R2X=0.364; R2Y=0.889) and Q2 (0.721), with significative ANOVA cross-validation (p=0.003). The discrimination were related to a metabolic fingerprint depending on a limited set of metabolites: Group B was characterized by higher values of Lactate, Glycerol, fatty acids, Acetoacetate, Valine, Leucine, Isoleucine and VLDL/LDL, whereas Group A showed higher values of Choline, Betaine, Alanine, Glycine, Taurine, Arginine and 3-OH-butyrate; is worthy of note that all the compounds relatively higher in Group A are related to the NO metabolism and the endothelial function. Increased PVR seems to be related to specific metabolites strictly connected to the endothelial dysfunction. Moreover MBS showed to be capable to finely identify the metabolic imbalance of vasoactive factors able to determine and maintain the increased PVR. This approach could prove to be useful in better understanding the pathophysiology of this severe complication of SS.