Urinary exosomal metabolites: Overlooked clue for predicting cardiovascular risk

Over the last decade, increasing research has focused on urinary exosomes (UEs) in biological fluids and their relationship with physiological and pathological processes. UEs are membranous vesicles with a size of 40-100 nm, containing a number of bioactive molecules such as proteins, lipids, mRNAs, and miRNAs. These vesicles are an inexpensive non-invasive source that can be used in clinical settings to differentiate healthy patients from diseased patients, thereby serving as potential biomarkers for the early identification of disease. Recent studies have reported the isolation of small molecules called exosomal metabolites from individuals' urine with different diseases. These metabolites could utilize for a variety of purposes, such as the discovery of biomarkers, investigation of mechanisms related to disease development, and importantly prediction of cardiovascular diseases (CVDs) risk factors, including thrombosis, inflammation, oxidative stress, hyperlipidemia as well as homocysteine. It has been indicated that alteration in urinary metabolites of N1-methylnicotinamide, 4-aminohippuric acid, and citric acid can be valuable in predicting cardiovascular risk factors, providing a novel approach to evaluating the pathological status of CVDs. Since the UEs metabolome has been clearly and precisely so far unexplored in CVDs, the present study has specifically addressed the role of the mentioned metabolites in the prediction of CVDs risk factors.

Automated summary

Increasing research over the past decade has focused on urinary exosomes (UEs) and their relationship with physiological and pathological processes. UEs are membranous vesicles containing bioactive molecules that can serve as biomarkers for early disease identification. Recent studies have isolated exosomal metabolites from urine, which can be used for discovery of biomarkers, investigation of disease mechanisms, and prediction of cardiovascular disease risk factors. Alterations in certain urinary metabolites have shown potential in predicting cardiovascular risk factors, offering a novel approach to evaluate the pathological status of cardiovascular diseases.