Multi-omics analysis identified extracellular vesicles as biomarkers for cardiovascular diseases

Abstract

Cell-derived extracellular vesicles (EVs) have emerged as a promising non-invasive liquid biopsy technique due to their accessibility and their ability to encapsulate and transport diverse biomolecules. EVs have garnered substantial research interest, notably in cardiovascular diseases (CVDs), where their roles in pathophysiology and as diagnostic and prognostic biomarkers are increasingly recognized. This review provides a comprehensive overview of EVs, starting with their origins, followed by the techniques used for their isolation and characterization. We explore the diverse cargo of EVs, including nucleic acids, proteins, lipids, and metabolites, highlighting their roles in intercellular communication and as potential biomarkers. We then delve into the application of genomics, transcriptomics, proteomics, and metabolomics in the analysis of EVs, particularly within the context of CVDs. Finally, we discuss how integrated multi-omics approaches are unveiling novel biomarkers, offering fresh insights into the diagnosis and prognosis of CVDs. This review underscores the growing importance of EVs in clinical diagnostics and the potential of multi-omics to propel future advancements in CVD biomarker discovery.

Keywords: Diagnostic biomarkers; Machine learning algorithms; Multi-omics analyses; cardiovascular diseases; extracellular vesicles.