Urinary Extracellular Vesicles Are a Novel Tool to Monitor Allograft Function in Kidney Transplantation: A Systematic Review.
Liang WuKarin BoerWouter W WoudSuwasin UdomkarnjananunDennis A HesselinkCarla C BaanPublished in: International journal of molecular sciences (2021)
Extracellular vesicles (EVs) are nanoparticles that transmit molecules from releasing cells to target cells. Recent studies link urinary EVs (uEV) to diverse processes such as infection and rejection after kidney transplantation. This, and the unmet need for biomarkers diagnosing kidney transplant dysfunction, has led to the current high level of interest in uEV. uEV provide non-intrusive access to local protein, DNA, and RNA analytics without invasive biopsy. To determine the added value of uEV measurements for detecting allograft dysfunction after kidney transplantation, we systematically included all related literature containing directly relevant information, with the addition of indirect evidence regarding urine or kidney injury without transplantation. According to their varying characteristics, uEV markers after transplantation could be categorized into kidney-specific, donor-specific, and immune response-related (IR-) markers. A few convincing studies have shown that kidney-specific markers (PODXL, ion cotransporters, SYT17, NGAL, and CD133) and IR-markers (CD3, multi-mRNA signatures, and viral miRNA) could diagnose rejection, BK virus-associated nephropathy, and calcineurin inhibitor nephrotoxicity after kidney transplantation. In addition, some indirect proof regarding donor-specific markers (donor-derived cell-free DNA) in urine has been demonstrated. Together, this literature review provides directions for exploring novel uEV markers' profiling complications after kidney transplantation.
Keyphrases
- kidney transplantation
- induced apoptosis
- immune response
- oxidative stress
- systematic review
- cell cycle arrest
- genome wide
- signaling pathway
- sars cov
- stem cells
- endoplasmic reticulum stress
- inflammatory response
- mesenchymal stem cells
- cell death
- artificial intelligence
- dendritic cells
- ultrasound guided
- machine learning
- single molecule
- health information
- circulating tumor
- deep learning
- case control
- pi k akt