Analysis of urinary exosomal metabolites identifies cardiovascular risk signatures with added value to urine analysis.

BACKGROUND: Subclinical atherosclerosis may result in fatal cardiovascular (CV) events, but the underlying mechanisms and molecular players leading to disease are not entirely understood. Thus, novel approaches capable of identifying the factors involved in pathological progression and providing a better understanding of the subjacent mechanisms are needed. Extracellular vesicles (EVs) have been shown to have numerous biological functions, and their metabolome has recently generated interest as a source of novel biomarkers. The metabolic content of the exosomes has been so far unexplored in cardiovascular disease (CVD), and here, we developed an analytical strategy aimed at probing urinary exosomal metabolite content and its association to CV risk. RESULTS: Direct analysis of the exosomes without metabolite extraction was evaluated by high-resolution magic angle spinning (1H HR-MAS). Other two methodologies for the analysis of exosomal metabolites by 1H NMR were set up, based on methanol or organic solvents sequential extraction. The three methods were compared in terms of the number of detected signals and signal to noise ratio (S/N). The methanol method was applied to identify altered metabolites in the urinary exosomes of subjects with programmed coronary artery by-pass grafting (CABG) versus a control group. Target mass spectrometry (MS) was also performed for differential analysis. The clinical performance of exosomal metabolites of interest in CVD was investigated, and the added value of the exosomes compared to urine analysis was evaluated. Based on S/N ratio, simplicity, reproducibility, and quality of the spectrum, the methanol method was chosen for the study in CVD. A cardiometabolic signature composed by 4-aminohippuric acid, N-1-methylnicotinamide, and citric acid was identified in urinary exosomes. Directly in urine, 4-aminohippuric acid and citric acid do not show variation between groups and changes in N-1-methylnicotinamide are less pronounced, proving the added value of exosomes. CONCLUSIONS: We set up a novel methodology to analyze metabolic alterations in urinary exosomes and identified a cardiometabolic signature in these microvesicles. This study constitutes the first evidence of a role for the exosomal metabolism in CVD and demonstrates the possibility to evaluate the urinary exosomal metabolic content by NMR and MS.

Metabolic Alterations Identified in Urine, Plasma and Aortic Smooth Muscle Cells Reflect Cardiovascular Risk in Patients with Programmed Coronary Artery Bypass Grafting.

Atherosclerosis is the predominant pathology associated to premature deaths due to cardiovascular disease. However, early intervention based on a personalized diagnosis of cardiovascular risk is very limited. We have previously identified metabolic alterations during atherosclerosis development in a rabbit model and in subjects suffering from an acute coronary syndrome. Here we aim to identify specific metabolic signatures which may set the basis for novel tools aiding cardiovascular risk diagnosis in clinical practice. In a cohort of subjects with programmed coronary artery bypass grafting (CABG), we have performed liquid chromatography and targeted mass spectrometry analysis in urine and plasma. The role of vascular smooth muscle cells from human aorta (HA-VSMCs) was also investigated by analyzing the intra and extracellular metabolites in response to a pro-atherosclerotic stimulus. Statistically significant variation was considered if p value < 0.05 (Mann-Whitney test). Urinary trimethylamine N-oxide (TMAO), arabitol and spermidine showed higher levels in the CVrisk group compared with a control group; while glutamine and pantothenate showed lower levels. The same trend was found for plasma TMAO and glutamine. Plasma choline, acetylcholine and valine were also decreased in CVrisk group, while pyruvate was found increased. In the secretome of HA-VSMCs, TMAO, pantothenate, glycerophosphocholine, glutathion, spermidine and acetylcholine increased after pro-atherosclerotic stimulus, while secreted glutamine decreased. At intracellular level, TMAO, pantothenate and glycerophosphocholine increased with stimulation. Observed metabolic deregulations pointed to an inflammatory response together with a deregulation of oxidative stress counteraction.

Urinary metabolic signatures reflect cardiovascular risk in the young, middle-aged, and elderly populations.

The predictive value of traditional cardiovascular risk estimators is limited, and young and elderly populations are particularly underrepresented. We aimed to investigate the urine metabolome and its association with cardiovascular risk to identify novel markers that might complement current estimators based on age. Urine samples were collected from 234 subjects categorized into three age-grouped cohorts: 30-50 years (cohort I, young), 50-70 years (cohort II, middle-aged), and > 70 years (cohort III, elderly). Each cohort was further classified into three groups: (a) control, (b) individuals with cardiovascular risk factors, and (c) those who had a previous cardiovascular event. Novel urinary metabolites linked to cardiovascular risk were identified by nuclear magnetic resonance in cohort I and then evaluated by target mass spectrometry quantification in all cohorts. A previously identified metabolic fingerprint associated with atherosclerosis was also analyzed and its potential risk estimation investigated in the three aged cohorts. Three different metabolic signatures were identified according to age: 2-hydroxybutyrate, gamma-aminobutyric acid, hypoxanthine, guanidoacetate, oxaloacetate, and serine in young adults; citrate, cyclohexanol, glutamine, lysine, pantothenate, pipecolate, threonine, and tyramine shared by middle-aged and elderly adults; and trimethylamine N-oxide and glucuronate associated with cardiovascular risk in all three cohorts. The urinary metabolome contains a metabolic signature of cardiovascular risk that differs across age groups. These signatures might serve to complement existing algorithms and improve the accuracy of cardiovascular risk prediction for personalized prevention. KEY MESSAGES: • Cardiovascular risk in the young and elderly is underestimated. • The urinary metabolome reflects cardiovascular risk across all age groups. • Six metabolites constitute a metabolic signature of cardiovascular risk in young adults. • Middle-aged and elderly adults share a cardiovascular risk metabolic signature. • TMAO and glucuronate levels reflect cardiovascular risk across all age groups.

Identification of six cardiovascular risk biomarkers in the young population: A promising tool for early prevention.

BACKGROUND AND AIMS: The predictive value of traditional CV risk calculators is limited. Novel indicators of CVD progression are needed particularly in the young population. The main aim of this study was the identification of a molecular profile with added value to classical CV risk estimation. METHODS: Eighty-one subjects (30-50 years) were classified in 3 groups according to their CV risk: healthy subjects; individuals with CV risk factors; and those who had suffered a previous CV event. The urine proteome was quantitatively analyzed and significantly altered proteins were identified between patients' groups, either related to CV risk or established organ damage. Target-MS and ELISA were used for confirmation in independent patients' cohorts. Systems Biology Analysis (SBA) was carried out to identify functional categories behind CVD. RESULTS: 4309 proteins were identified, 75 of them differentially expressed. ADX, ECP, FETUB, GDF15, GUAD and NOTCH1 compose a fingerprint positively correlating with lifetime risk estimate (LTR QRISK). Best performance ROC curve was obtained when ECP, GDF15 and GUAD were combined (AUC = 0.96). SBA revealed oxidative stress response, dilated cardiomyopathy, signaling by Wnt and proteasome, as main functional processes related to CV risk. CONCLUSIONS: A novel urinary protein signature is shown, which correlates with CV risk estimation in young individuals. Pending further confirmation, this six-protein-panel could help in CV risk assessment.