Multicenter, prospective, observational study for urinary exosomal biomarkers of kidney allograft fibrosis.
Mi Joung KimHye Eun KwonHye-Won JangJin-Myung KimJae Jun LeeJoo Hee JungYoungmin KoHyunwook KwonYoung Hoon KimHeungman JunSang Jun ParkJun-Gyo GwonSung ShinPublished in: Scientific reports (2024)
Severity of deceased donor kidney fibrosis impacts graft survival in deceased-donor kidney transplantation. Our aim was to identify potential miRNA biomarkers in urinary exosomes that mirror interstitial fibrosis and tubular atrophy (IFTA) severity. Among 109 urine samples from deceased donors, 34 displayed no IFTA in the zero-day biopsy (No IFTA group), while the remaining 75 deceased donor kidneys exhibited an IFTA score ≥ 1 (IFTA group). After analyzing previous reports and electronic databases, six miRNAs (miR-19, miR-21, miR-29c, miR-150, miR-200b, and miR-205) were selected as potential IFTA biomarker candidates. MiR-21, miR-29c, miR-150, and miR-205 levels were significantly higher, while miR-19 expression was significantly lower in the IFTA group. MiR-21 (AUC = 0.762; P < 0.001) and miR-29c (AUC = 0.795; P < 0.001) showed good predictive accuracy for IFTA. In the No IFTA group, the eGFR level at 1 week after transplantation was significantly higher compared to the IFTA group (41.34 mL/min/1.73m 2 vs. 28.65 mL/min/1.73m 2 , P = 0.012). These findings signify the potential of urinary exosomal miRNAs as valuable biomarker candidates for evaluating the severity of IFTA in deceased donor kidneys before they undergo recovery.
Keyphrases
- cell proliferation
- long non coding rna
- long noncoding rna
- kidney transplantation
- poor prognosis
- small cell lung cancer
- mesenchymal stem cells
- machine learning
- risk assessment
- climate change
- cross sectional
- epidermal growth factor receptor
- tyrosine kinase
- deep learning
- artificial intelligence
- drug induced
- big data
- cell therapy
- human health