
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39223169
71279
10.1038/s41598-024-71279-5
Article
Multicenter, prospective, observational study for urinary exosomal biomarkers of kidney allograft fibrosis
Kim Mi Joung 1
Kwon Hye Eun 1
Jang Hye-Won 2
Kim Jin-Myung 1
Lee Jae Jun 1
Jung Joo Hee 1
Ko Youngmin 1
Kwon Hyunwook 1
Kim Young Hoon 1
Jun Heungman 3
Park Sang Jun 4
https://orcid.org/0000-0002-1681-1014
Gwon Jun Gyo doctorgjg@gmail.com

2
https://orcid.org/0000-0001-7318-4208
Shin Sung sshin@amc.seoul.kr

1
1 grid.267370.7 0000 0004 0533 4667 Division of Kidney and Pancreas Transplantation, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505 Republic of Korea
2 grid.267370.7 0000 0004 0533 4667 Division of Vascular Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505 Republic of Korea
3 https://ror.org/047dqcg40 grid.222754.4 0000 0001 0840 2678 Department of Surgery, Korea University Medicine Anam, Korea University College of Medicine, Seoul, Korea
4 grid.267370.7 0000 0004 0533 4667 Department of Surgery, Ulsan University Hospital, University of Ulsan College of Medicine, Seoul, Republic of Korea
2 9 2024
2 9 2024
2024
14 2031910 12 2023
26 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
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/1.73m2 vs. 28.65 mL/min/1.73m2, 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.

Subject terms

Biomarkers
Diagnostic markers
the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea governmentNRF-2021R1G1A1004361 Gwon Jun Gyo the Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea2020IP0063-1 Shin Sung issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

Kidney transplantation (KT) is well-known as the most effective way to treat chronic kidney disease in terms of patient survival and cost1,2. The administration of immunosuppressants, such as tacrolimus and anti-thymocyte globulin, has improved long-term survival by reducing rejection rates3,4. The long-term outcomes of KT are also influenced by the chronic fibrosis status of the donor’s kidney5,6. The evaluation of kidney tissue through preimplantation biopsies has been identified as a standalone factor for predicting the success of grafts in expanded criteria donor (ECD) KT. Consequently, various research teams utilize renal histology to assess the viability of ECD kidneys7,8. However, the preimplantation kidney tissue necessitates prompt delivery to the pathology laboratory and expeditious examination by on-call pathologists within a few hours to mitigate cold ischemic time. Consequently, the universal adoption of this strategy poses considerable challenges.

MicroRNAs (miRNAs) are small noncoding RNAs consisting of about 18–23 nucleotides. In many studies, miRNAs are reported as regulators of gene expression at the post-transcriptional level9,10. In addition to these regulatory functions, miRNAs are known to be highly stable particles in plasma and urine10–13. Exosomes are small vesicles or membrane-bound particles that are secreted by many types of cells, including kidney cells14,15, and have been found to contain various biomolecules, including miRNAs, proteins, and lipids, and they play a role in intercellular communication. miRNA can also be contained within exosomes, which are then delivered between cells16. Exosomal miRNAs are of particular interest in research and clinical studies because they can play a role in cell signaling, and disease processes, and potentially serve as biomarkers for various conditions14–16. As such, many efforts have been made to develop miRNAs as diagnostic tools for various diseases, including cancers, metabolic diseases, and inflammatory diseases17.

Multiple studies reported that the expression levels of several miRNAs, including miR-142-5p or miR-142-3p, from kidney biopsy and peripheral blood mononuclear cell samples of kidney transplant recipients were closely associated with allograft rejection and interstitial fibrosis and tubular atrophy (IFTA)18–21. From a pilot study, we found that urinary transglutaminase 2 (TG2) is a potent biomarker for predicting IFTA in kidney allografts during the early post-transplant period in deceased donor kidney transplantation22.

The aim of this study was to identify a panel of new markers associated with IFTA in deceased donor kidney prior to KT. To this end, we isolated and analyzed the exosomal miRNA candidates related to kidney fibrosis and TG2 in urine samples from deceased donors to assess their correlation with kidney fibrosis.

Results

Baseline characteristics and zero-day biopsy

Among a total of 109 recipients, 34 (31%) were classified into the No IFTA group, while the remaining 75 were classified into the IFTA group (Fig. 1, Table 1). ECDs are characterized as donors who are either (1) aged 60 years or older, with or without comorbidities, or (2) aged 50–59 with at least two out of the following comorbid conditions (elevated serum creatinine levels [> 1.5 mg/dL], a history of hypertension, or death caused by cerebrovascular accident). There were 36 (33%) ECD donors and only one donor after cardiac death (DCD) in this cohort. There were no significant differences in the baseline characteristics of recipients and donors between the two groups, except for the lower level of terminal serum creatinine in the No IFTA group compared to the IFTA group (1.49 ± 1.16 mg/dL vs. 2.46 ± 2.15 mg/dL, P = 0.003). Of the induction regimen, basiliximab was more frequently used in both groups although there was no significant difference between the two groups. Almost all recipients had tacrolimus (98.2%), mycophenolic acid (96.3%), and steroid (100%) as a maintenance regimen.Fig. 1 Patient flow diagram.

Table 1 Baseline characteristics of recipients and donors.

Variables	No IFTA
N = 34	IFTA
N = 75	P-value	
Recipient characteristics	
 Mean age, years (SD)	55.0 (11.2)	55.9 (8.8)	0.639	
 Female sex, n (%)	18 (52.9)	28 (37.3)	0.126	
 Body mass index, kg/m2 (SD)	23.3 (3.3)	23.9 (4.3)	0.501	
 Diabetes mellitus, n (%)	12 (35.3)	21 (28.0)	0.443	
 Hypertension, n (%)	31 (91.2)	59 (78.7)	0.111	
 Duration of pre-transplant dialysis, months	90.48 (0–228)	93.81 (7–276)	0.828	
 HLA-A, B, DR mismatch, n (SD)	3.62 (1.95)	3.59 (1.78)	0.935	
 HLA-DR mismatch, n (SD)	1.15 (0.82)	1.19 (0.73)	0.801	
 DSA-positive, n (%)	3 (8.8)	8 (10.8)	1.000	
 Induction regimen	0.196	
  Basiliximab, n (%)	28 (82.4)	53 (70.7)		
  Anti-thymocyte globulin, n (%)	6 (17.6)	22 (29.3)		
 Calcineurin inhibitor	0.529	
  Tacrolimus, n (%)	33 (97.1)	74 (98.7)		
  Cyclosporine, n (%)	1 (2.9)	1 (1.3)		
 Anti-metabolite	0.967	
  Mycophenolate mofetil, n (%)	25 (73.5)	73 (97.3)		
  Enteric-coated mycophenoate sodium, n (%)	4 (11.8)	0		
  None, n (%)	5 (14.7)	2 (2.7)		
 Steroid maintenance, n (%)	34 (100)	75 (100)		
Donor characteristics	
 Mean age, years (SD)	53.3 (13.3)	53.6 (10.8)	0.913	
 Female sex, n (%)	11 (30.6)	25 (32.5)	0.839	
 Cold ischemia time, hours (SD)	4.91 (2.83)	4.42 (1.82)	0.288	
 Terminal serum creatinine, mg/dL (SD)	1.49 (1.16)	2.46 (2.15)	0.003	
 ECD, n (%)	8 (23.5)	28 (37.8)	0.365	
 KDPI, % (SD)	64.6 (27.0)	69.3 (20.7)	0.381	
 Cause of death, CVA, n (%)	12 (35.3)	32 (42.7)	0.467	
FSGS, focal segmental glomerulosclerosis; PCKD, polycystic kidney disease; ECD, expanded criteria donor; KDPI, kidney donor profile index.

Detailed Banff scores of the zero-day biopsy for interstitial fibrosis, tubular atrophy, and vascular fibrous intimal thickening are described in Table 2. The IFTA group had significantly higher scores for interstitial fibrosis (ci) (0.03 ± 0.17 vs. 0.48 ± 0.66, P < 0.001), tubular atrophy (ct) (0.03 ± 0.17 vs. 0.52 ± 0.53, P < 0.001), and vascular fibrous intimal thickening (cv) (0.00 ± 0.00, 0.19 ± 0.43, P < 0.001).Table 2 Comparison of mean Banff score according to the presence of IFTA.

Banff score	No IFTA
N = 34	IFTA
N = 75	P-value	
ci	0.03 ± 0.17	0.48 ± 0.66	 < 0.001	
ct	0.03 ± 0.17	0.52 ± 0.53	 < 0.001	
cv	0.00 ± 0.00	0.19 ± 0.43	 < 0.001	
IFTA, interstitial fibrosis and tubular atrophy.

Selection of miRNA biomarker candidates for deceased donor kidney fibrosis

Based on previous reports, we selected six miRNAs that are associated with renal fibrosis and TG2. Subsequently, we verified the selected exosomal miRNAs using the ExoCarta database (http://www.exocarta.org/) (kidney fibrosis: miR-29c, miR-150, miR-200b, and miR-21; TG2: miR-19 and miR-205) (Fig. 2). In addition, we compared these potential biomarkers with the EVmiRNA database (http://bioinfo.life.hust.edu.cn/EVmiRNA) whether the candidates were urinary exosomal miRNA or kidney-specific exosomal miRNA (Fig. 3). In Fig. 3, two Venn diagrams serve to elucidate the intersection of potential biomarkers with established databases of extracellular vesicle microRNAs.Fig. 2 Study design.

Fig. 3 Intersection of identified proteins in published exosome datasets. Intersecting proteins in the compared public datasets are demonstrated by Venn diagrams (A and B). The left diagram (A) presents a binary comparison: the ExoCarta database is depicted by a blue circle, encompassing 1348 unique miRNAs, whereas the red circle, representing the current study, shows no unique miRNAs, with an intersection of six shared miRNAs between the two datasets. The right diagram (B) compares three distinct datasets—Urinary exosomal miRNA (blue), Kidney exosomal miRNA (red), and the current study (green). The urinary and kidney exosomal miRNA datasets possess 82 and 51 unique miRNAs respectively, while the current study identifies four unique miRNAs. Central to the diagram is a single miRNA shared across all three datasets. Notably, one miRNA, miR-29c, is exclusively shared between the urinary exosomal miRNAs and the current study, and another, miR-21, is shared between the kidney exosomal miRNAs and the current study, as indicated by the arrows. The pairwise overlap between urinary and kidney exosomal miRNAs reveals nine shared miRNAs, whereas no miRNAs are exclusively shared between kidney exosomal miRNAs and the current study, underscoring the specificity of the miRNA distribution within these biological contexts.

Exosome identification

Using transmission electron microscopy, the exosomes isolated from urine samples were negatively stained with 2% uranyl acetate (Fig. 4A). The diameter of each exosome was 100–300 nm, as determined by nanoparticle tracking analysis (Fig. 4B). In addition, the expression of TSG101, CD63, CD9, HSP70, and Actin, which are markers of exosomes, was also identified by Western blot analysis (Fig. 4C and Supplementary Fig. 1). There were no significant differences in concentration (no IFTA: 8.40e + 10 ± 1.18E + 11 vs. IFTA: 1.50E + 11 ± 3.46E + 11) and size (206.32 ± 34.63 nm vs. 208.50 ± 28.32 nm) of particles between the groups (Fig. 4D, E).Fig. 4 Urinary exosome characterization. (A) Transmission electron microscopy view of the exosomes isolated from urine samples that were negatively stained with 2% uranyl acetate. (B) The diameter of each exosome was 100–300 nm on nanoparticle tracking analysis. (C) Western blot analysis of the expression of exosomal markers TSG101, CD63, CD9, HSP70, and actin in urinary exosome proteins. There were no significant differences in the concentration (D) and size (E) of particles between the groups.

miRNA expression levels

The expression level of each miRNA was quantified using qRT-PCR, and the differences between the two groups were analyzed using an unpaired Mann–Whitney test (Fig. 5, Table 3). Among the six potential biomarkers, the relative expression levels of miR-21 (P < 0.001), miR-29c (P < 0.001), and miR-205 (P = 0.004) were significantly higher in the IFTA group. In contrast, the IFTA group showed significantly lower expression levels of miR-19 (P = 0.0046) and miR-150 compared to the No IFTA group. As MiR-150 was expressed in only 71.2% of the total samples, it had limited use as a biomarker.Fig. 5 Comparison of miRNA expression (miR-19, miR-21, miR-29c, miR-150, miR-200b, and miR-205) by qRT-PCR according to the IFTA grade.

Table 3 Expression of miRNA.

miRNA	no IFTA	IFTA	Fold difference	
miR-19	2.304 ± 3.308	0.752 ± 0.867	− 3.064	
miR-21	1.589 ± 1.874	3.068 ± 2.492	1.931	
miR-29c	2.077 ± 2.039	5.371 ± 3.653	2.586	
miR-150	6.403 ± 10.036	3.106 ± 10.281	− 2.061	
miR-200b	3.459 ± 8.824	2.235 ± 1.824	− 1.548	
miR-205	1.572 ± 0.210	3.284 ± 3.253	2.089	

Prognostic value of the miRNA panel

The ROC curves of the selected biomarkers showed statistically significant prognostic accuracy (Fig. 6). The ROC analysis of miR-21, miR-29c, and miR-19 showed significant sensitivity and specificity in predicting the grade of IFTA.Fig. 6 Receiver operating characteristic (ROC) curves. (A) Individual miRNAs. (B) Combined biomarkers.

Next, we tested the prognostic value of combined miRNAs to enhance the accuracy of prognosis for IFTA. The sensitivities, specificities, and AUC values of the combined miRNA biomarkers are summarized in Table 4. Based on these prognostic parameters, model 3 demonstrated the highest prognostic accuracy compared to the other models.Table 4 Diagnostic efficacy parameter of 4 diagnostic models.

miRNAs	AUC	95% CI	P-value	cutoff	Sensitivity	Specificity	PPV	NPV	
(A) Model 1	
 miR-21	0.762	0.658–0.846	 < 0.001	 > 1.032	84.5	69.0	84.5	68.9	
 miR-29c	0.795	0.694–0.874	 < 0.001	 > 1.605	98.3	67.9	86.3	95.0	
 Combination	0.802	0.702–0.880	 < 0.001	 > 0.430	96.5	62.1	83.4	90.0	
(B) Model 2	
 miR-21	0.762	0.658–0.846	 < 0.001	 > 1.032	84.5	69.0	84.5	68.9	
 miR-29c	0.795	0.694–0.874	 < 0.001	 > 1.605	98.3	67.9	86.3	95.0	
 miR-205	0.691	0.582–0.787	0.001	 > 2.642	41.1	89.7	88.5	44.1	
Combination	0.810	0.711–0.887	 < 0.001	 > 0.377	98.2	48.3	78.6	93.3	
(C) Model 3	
 miR-19a	0.687	0.579–0.782	0.003	 ≤ 0.919	82.8	55.2	78.7	61.6	
 miR-21	0.762	0.658–0.846	 < 0.001	 > 1.032	84.5	69.0	84.5	68.9	
 miR-29c	0.795	0.694–0.874	 < 0.001	 > 1.605	98.3	67.9	86.3	95.0	
 miR-205	0.691	0.582–0.787	0.001	 > 2.642	41.1	89.7	88.5	44.1	
 Combination	0.837	0.742–0.908	p < 0.001	 > 0.582	87.5	72.4	86.0	75.0	

Pathway enrichment analysis and human microRNA–disease network analysis

Figure 7 presents an integrative analysis employing the DIANA mirPath v.4 (https://diana-lab.e-ce.uth.gr/app/miRPathv4) computational tool for KEGG pathway enrichment and the STRING database for interaction network mapping of miRNA targets. In Fig. 7A, pathway enrichment analysis with a significance threshold of P < 0.001 unveils the top 10 pathways associated with the up-regulated miRNAs in the interstitial fibrosis and tubular atrophy (IFTA) group, with ‘Focal adhesion’ emerging as the pathway most significantly implicated, followed by pathways involved in oncogenesis and signaling such as ‘Pathways in cancer’ and ‘PI3K-Akt signaling pathway’. These pathways highlight a potential link between the molecular changes in IFTA and pivotal cellular processes. The focal adhesion pathway plays a crucial role in the development of fibrosis through its involvement in myofibroblast activation, TGF-β signaling, and cell–matrix interactions23–25. Figure 7B, constructed using STRING database, illustrates a complex interaction network of 58 gene targets, offering a visual representation of the proteomic landscape influenced by the dysregulated miRNAs. Figure 7C complements the preceding analyses by delineating the disease-specific associations of the 58 gene targets modulated by the up-regulated miRNAs in IFTA. This figure adopts a bar chart format to quantify the prevalence of each gene target across a spectrum of pathological states, drawing upon annotations from comprehensive biomedical databases and literature. The bar chart format allows for precise quantification of the number of gene targets associated with each specific condition. By aligning bars horizontally, we can systematically compare the extent to which different diseases are associated with the modulated gene targets. In addition, this format provides a straightforward visual representation that makes it easier to identify patterns and trends. Researchers can quickly discern which conditions have higher associations, facilitating a more intuitive understanding of the data. This multilayered analysis elucidates the broad biological ramifications of miRNA dysregulation, affirming their role as key molecular determinants in IFTA and possibly in a spectrum of other pathological contexts. It is hypothesized that the three validated miRNAs will be involved in the progression of IFTA by regulating common target factors identified through pathway analysis.Fig. 7 Target gene pathway (A), gene network analysis for focal adhesion pathway (B) and Human microRNA–disease network analysis (C). In (A), pathway enrichment analysis with a significance threshold of P < 0.001 unveils the top 10 pathways associated with the up-regulated miRNAs in the interstitial fibrosis and tubular atrophy (IFTA) group, with 'Focal adhesion' emerging as the pathway most significantly implicated, followed by pathways involved in oncogenesis and signaling such as ‘Pathways in cancer’ and ‘PI3K-Akt signaling pathway’. In (B), constructed using STRING database, illustrates a complex interaction network of 58 gene targets, offering a visual representation of the proteomic landscape influenced by the dysregulated miRNAs. Nodes represent individual gene targets, while edges denote the interactions, underscoring the extensive cross-talk and potential synergistic effects on cellular functions. In (C) complements the preceding analyses by delineating the disease-specific associations of the 58 gene targets modulated by the up-regulated miRNAs in IFTA. Each bar represents a discrete condition—ranging from ‘ovarian neoplasm’ to ‘cirrhosis’ to ‘bipolar disorder’—and is proportioned to reflect the count of implicated gene targets. The anticipated color-coding scheme would facilitate distinction among categories such as neoplastic, metabolic, and neuropsychiatric disorders, allowing for an immediate visual appraisal of the data. The configuration of bars would thus illustrate not only the concentrated involvement of these miRNAs in renal fibrotic transformation but also their potential systemic influence, reinforcing the concept of miRNAs as critical regulators with extensive biomedical relevance.

Comparison of clinical outcomes between the groups

We then compared clinical outcomes such as delayed graft function, eGFR, BPAR of kidney allograft, kidney allograft survival, and patient survival. There was no significant difference in the incidence of delayed graft function between the two groups (17.6% vs 25.3%, P = 0.377). The eGFR level of the No IFTA group was significantly higher than that of the IFTA group at 1 week post-transplant (41.34 mL/min/1.73m2 vs. 28.65 mL/min/1.73m2, P = 0.012). According to the linear mixed model, the No IFTA group showed a significantly earlier improving pattern of eGFR over time compared to the IFTA group (Time*Group P = 0.031; Supplementary Fig. 2A). During the 3-year follow-up period, there were no significant differences observed in patient survival (Supplementary Fig. 2B), kidney allograft survival (Supplementary Fig. 2C), and the incidence of BPAR (Supplementary Fig. 2D) between the two groups.

Discussion

In this study, we identified several promising biomarkers in urine specimens from deceased KT donors that correlated with the fibrotic status of deceased donor kidneys. In the IFTA group, miR-21, miR-29c, and miR-205 were expressed at higher levels compared to the No IFTA group, while miR-19 exhibited lower expression levels. Moreover, miR-21 and miR-29c demonstrated significant prognostic value in the ROC analysis.

Several studies have attempted to find non-invasive methods to predict the progression of kidney fibrosis and allograft rejection26–28. Schaub et al.29 analyzed the urine protein profiles of kidney transplant recipients. Some researchers have demonstrated specific biomarkers related to kidney allograft fibrosis; for example, Cheng et al.30 suggested that connective tissue growth factor could serve as both a biomarker and a therapeutic target for kidney allograft fibrosis. Still, these biomarkers have not replaced allograft biopsy as the primary method for diagnosing kidney allograft pathology.

Recently, miRNAs have emerged as promising candidates for biomarkers to monitor allograft injury or rejection following KT. These single-stranded RNAs are transcribed by RNA polymerase II enzymes and processed by RNases. The role of miRNAs is to regulate gene expression in intercellular communication31. These molecules can act in distant organs from their origins because they bind to specific proteins such as Ago2 or are transported in exosomes32,33. In this way, miRNAs can be maintained stably in human body fluids. Because of their stability and accessibility, miRNAs are already considered excellent biomarkers for diagnosis and therapeutic targets in the field of oncology34. Moreover, Wang et al.35 reported that urinary levels of miR-29b and miR-29c were higher in patients with IgA nephropathy, and these levels were found to be associated with the progression of renal fibrosis in IgA nephropathy. Lv et al.36 also suggested that there is a significant dysregulation of exosomal miR-29c and miR-21, which correlates with renal fibrosis.

The miRNAs selected as potential biomarkers in this study were previously reported as possible biomarkers for renal fibrosis in other studies. It is reported that urinary miR-21 plays an important role in renal injury and is closely associated with kidney fibrosis37–42. miR-29c is also noted as a molecule that inhibits renal interstitial fibrosis through the activation of HIF-α and the PI3K-PKB pathway43,44, and miR-205 and miR-19 influence renal injury through the regulation of PTEN45,46.

Different from previous studies, we aimed to assess the potential of urinary exosomal miRNA as non-invasive biomarkers for determining the IFTA grade of a deceased donor kidney prior to KT. We discovered that the disparity in renal function following KT was associated with the grade of IFTA observed in the zero-day biopsy. Taken together, it may be reasonable to explain that urinary exosomal miRNAs play essential roles as biomarkers in reflecting the grade of IFTA of deceased donor kidneys. To our knowledge, this study is the first to assess the relationship between urinary exosomal miRNA and the IFTA status of a deceased donor kidney prior to kidney transplantation. The timeframe for obtaining results from miRNA analysis indeed varies based on several factors, including the specific methods employed, the availability of equipment and reagents, and the overall efficiency of the laboratory workflow. However, from the isolation of urinary exosomes to conducting quantitative reverse transcription polymerase chain reaction (qRT-PCR), the process generally takes between 7 and 16 h. Given this manageable timeframe, it is both practical and feasible to utilize urinary exosomal miRNAs as biomarkers in daily clinical practice.

The combination of multiple miRNAs demonstrates a higher AUC than that of a single marker (miR-29c), yet lower sensitivity, specificity, PPV, and NPV. This discrepancy raises important considerations in the interpretation of our results. The higher AUC value achieved by the combined miRNA panel underscores the potential synergistic effect of leveraging multiple markers for predictive purposes, enhancing the overall discriminatory power of the model. However, the observed reduction in sensitivity, specificity, PPV, and NPV when transitioning from a single miRNA to a combined panel highlights the trade-off between maximizing AUC and maintaining diagnostic accuracy across all parameters. We recognize the need to further investigate the underlying factors contributing to this phenomenon, including the interplay between different miRNAs, their individual diagnostic strengths, and potential interactions within the combined panel. Additionally, we acknowledge the importance of conducting additional analyses, such as establishing cut-off values in a development set and validating performance in an independent cohort, to refine and validate the diagnostic efficacy of the miRNA panel in the near future.

There are several limitations to this study that should be noted. First, the mean Banff ‘ci’ and ‘ct’ scores were less than 1 in the IFTA group as well. Initially, we attempted to classify the cohort based on the severity of IFTA and ‘cv’ and ‘cg’ scores. However, we encountered limitations: the combined ‘ci’ and ‘ct’ scores exceeded 2 in only two zero-day biopsies. Additionally, the ‘cg’ score was 0 in nearly all zero-day biopsies, with only two exceptions showing a score of 1. In terms of vascular fibrous intimal thickening, the ‘cg’ score was 1 or higher (1 in ten biopsies and 2 in one biopsy) in eleven biopsies within the IFTA group. These observations indicate that further division of the IFTA group by different histological lesions is constrained within our cohort. Therefore, we expect that our findings be validated in an independent cohort classified by these different histological lesions. Second, The follow-up period in this study was only 3 years. Therefore, further observation is necessary to determine the impact of urinary exosomal miRNAs from deceased donors on long-term clinical outcomes including kidney allograft survival and renal function. Third, comprehensive data on 24-h proteinuria or additional urinary biomarkers of tubular injury were unattainable due to variations in the protocols employed for managing each deceased donor at differing centers. Fourth, The small sizes of EVs pose technical challenges in detection and characterization. Additionally, their heterogeneity in biogenesis, size distribution, and molecular cargos complicates their study. Surface proteins such as tetraspanins (CD63 and CD9) are important for EV characterization, but they may form dimers or clusters, adding another layer of complexity. These factors limit the precision and consistency of our methodologies on EV characterization. Lastly, this study did not aim to reveal the mechanism by which these miRNAs influence kidney fibrosis. However, the mechanism by which IFTA is induced could be predicted through target gene network analysis of the verified miRNA. We expect to discover the process by which biomarkers regulate kidney fibrosis in further studies and, eventually, develop new agents to prevent kidney allograft fibrosis. Although it is reasonable to select six miRNA biomarkers using a bioinformatic approach, employing a miRNA array is recommended in the future study. The miRNA array can provide a comprehensive overview of miRNA expression and quantitative expression data. Furthermore, it combines both unbiased discovery and validation in a single step enabling robust statistical analysis and comparison.

In conclusion, our study showed that urinary exosomal miRNAs are promising biomarker candidates for assessing the severity of IFTA in kidneys prior to recovery from a deceased donor.

Methods

Patients, classification, and endpoint

This multicenter, prospective observational study involved four medical centers in Korea, including Asan Medical Center (AMC), Korea University Medicine Anam, Ulsan University Hospital, and Paik Hospital Ilsan. After obtaining written informed consent from all participants, the medical records were assessed. All methods and experimental protocols were approved by the institutional review board of Asan Medical Center (approval number: 2019-0337). All clinical activities in this study were conducted in compliance with the Declaration of Helsinki and the ethical principles stated in the Declaration of Istanbul on Organ Trafficking and Transplant Tourism. Urine specimens were collected from donors at the time of solid organ recovery and prior to transplantation. Zero-day biopsies of the grafts were performed on the back table. Among 141 deceased kidney donors between May 2019 and June 2021 at these centers, 32 cases were excluded due to insufficient zero-day biopsy data (n = 28) or lost urine samples (n = 4). Consequently, a total of 109 cases were included in this study (Fig. 1).

Based on the histologic findings using the Banff 2018 classification, the enrolled cases were classified into two groups. A recipient was classified into the “No IFTA group” if both the ‘ci’ and ‘ct’ scores were 0 in the zero-day biopsy, and into the “IFTA group” if the sum of the ‘ci’ and ‘ct’ scores was 1 or higher. The purpose of this study was to identify specific exosomal miRNAs from donor urine samples that reflect the severity of IFTA. The primary endpoint was the correlation between the levels of selected urine biomarkers and the status of IFTA on the zero-day biopsy. Additionally, we analyzed clinical outcomes such as the estimated glomerular filtration rate (eGFR), biopsy-proven acute rejection (BPAR), allograft survival, and patient survival for both groups. All the rejection episodes were diagnosed using a for-cause biopsy for clinical indications such as progressive proteinuria, elevated serum creatinine, and decreased urine output.

Urine processing

During the recovery procedures, urine samples (≥ 30 mL) were obtained from deceased donors in the operating room, and a protease inhibitor mix (consisting of 4-(2-aminoethyl) benzenesulfonyl fluoride hydrochloride (AEBSF-HCl, Sigma-Aldrich), leupeptin-hemisulfate (Sigma-Aldrich), and NaN3 (Sigma-Aldrich)) was promptly added. The samples were centrifuged at 4000 rpm for 15 min at 4 ℃ to remove urinary sediments. After centrifugation, the supernatants were collected and stored at – 80 ℃ until the extraction of exosomes.

Exosome extraction

Upon thawing 15 mL of frozen urine samples, they were vortexed for one minute and centrifuged at 17,000 g for 15 min at room temperature. The collected supernatant was then subjected to ultracentrifugation at 200,000 g for 70 min at room temperature using a Beckman Coulter Optima L-80xp ultracentrifuge equipped with an SW40Ti rotor (Beckman Coulter; Brea, CA, USA). The supernatant was discarded, and the resulting pellet was dissolved in 11 mL of DPBS for washing. Then, another round of ultracentrifugation was performed at 200,000 × g for 70 min at room temperature. The supernatant was removed, and the exosome pellet was used for miRNA isolation or quantification of exosome particles. Transmission electron microscopy was used to confirm the presence of exosomes. The isolated urinary exosomes were then examined and characterized through nanoparticle tracking analysis using NanoSight NS300 (Malvern Instruments Ltd., UK) and Western blot analysis47. The blots were probed with primary antibodies including TSG101, HSP70, CD9, CD63 (Exosome panel kit, Ab275018, Abcam, Cambridge, UK), and Actin (A3854, Sigma-Aldrich).

RNA isolation

Total RNA was extracted using the miRNeasy Mini Kit from Qiagen, according to the manufacturer's instructions. RNA quality was assessed using the Agilent 2100 Bioanalyzer with the RNA 6000 Pico Chip (Agilent Technologies, Amstelveen, The Netherlands). RNA quantification was performed using the NanoDrop 2000 Spectrophotometer system (Thermo Fisher Scientific, Waltham, MA, USA).

Quantitative real-time PCR

The expression of miRNAs in urinary exosomes was validated by qRT-PCR. To quantify microRNAs, a TaqMan RT-PCR assay was used in this experiment. The process involved isolating total RNA, followed by reverse transcription of RNA using the Applied Biosystems™ TaqMan™ Advanced miRNA cDNA Synthesis Kit. The TaqMan RT-PCR assay was performed in duplicate using TaqMan™ Advanced miRNA Assays and TaqMan™ Fast Advanced Master Mix. To ensure the accuracy of the results, the expression of hsa-miR-16-5p was used as an endogenous control for normalization48,49. The relative expression levels of miRNAs were calculated using the comparative 2−△△Ct method. The primers used for RT-PCR are provided in Supplementary Table 1.

Human miRNA–disease association dataset

The human miRNA–disease association dataset was downloaded from the HMDD database (version 4.0) (http://www.cuilab.cn/hmdd/). The HMDD database is a collection of experimentally verified evidence for associations between human miRNAs and diseases.

Statistical analysis

Categorical variables were assessed using the chi-squared test, while continuous variables were examined with either the Student’s t-test or the Wilcoxon rank-sum test. The unpaired Mann–Whitney test was used to assess differences in miRNA expression levels between the two groups. We compared the patterns of eGFR improvement over time using a linear mixed model. Patient and graft survival were estimated using Kaplan–Meier survival estimates and assessed with the log-rank test.

Statistical analyses were conducted using IBM SPSS Statistics for Windows, version 28.0 (https://www.ibm.com/products/spss-statistics) (IBM Corp., Armonk, NY, USA), and GraphPad Prism, version 9.4.1 (https://www.graphpad.com) (GraphPad Software Inc., Boston, MA, USA). A significance level of P < 0.05 was considered statistically significant. Receiver operating characteristic (ROC) curves were calculated using MedCalc Statistical Software, version 20.106 (https://www.medcalc.org/download.php) (MedCalc Software Ltd., Ostend, Belgium).

Supplementary Information

Supplementary Figures.

Supplementary Table 1.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71279-5.

Author contributions

S.S., J.G., S.P., and H.J. conceived the study design and analysis plan. M.K., H.E.K., H.J., and J.K. collected data and performed experiments. M.K., H.E.K., J.L., J.J., Y.K., H.K., and Y.K. performed data analysis and generated all figures and tables. S.S., J.G., S.P., and H.J. drafted and revised the manuscript. S.S., J.G., S.P., and H.J. approved the final version of the manuscript. S.S. supervised the work.

Funding

This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (NRF-2021R1G1A1004361) and the Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea (2020IP0063-1).

Data availability

The datasets used and/or analyzed in the present study can be obtained upon reasonable request from the corresponding author, who can be contacted at sshin@amc.seoul.kr.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Mi Joung Kim and Hye Eun Kwon.
==== Refs
References

1. Wolfe RA Comparison of mortality in all patients on dialysis, patients on dialysis awaiting transplantation, and recipients of a first cadaveric transplant N. Engl. J. Med. 1999 341 1725 1730 10.1056/NEJM199912023412303 10580071
Wolfe, R. A. et al. Comparison of mortality in all patients on dialysis, patients on dialysis awaiting transplantation, and recipients of a first cadaveric transplant. N. Engl. J. Med. 341, 1725–1730 (1999).10580071 10.1056/NEJM199912023412303
2. Merion RM Deceased-donor characteristics and the survival benefit of kidney transplantation Jama 2005 294 2726 2733 10.1001/jama.294.21.2726 16333008
Merion, R. M. et al. Deceased-donor characteristics and the survival benefit of kidney transplantation. Jama 294, 2726–2733 (2005).16333008 10.1001/jama.294.21.2726
3. Halloran PF Immunosuppressive drugs for kidney transplantation N. Engl. J. Med. 2004 351 2715 2729 10.1056/NEJMra033540 15616206
Halloran, P. F. Immunosuppressive drugs for kidney transplantation. N. Engl. J. Med. 351, 2715–2729 (2004).15616206 10.1056/NEJMra033540
4. Waichi W Venetz J-P Tolkoff-Rubin N Pascual M Inmunosuppressive strategies in kidney transplantation: Which role for the calcineurin inhibitors. [Estrategias Inmunosupresoras en el trasplante renal: El papel de los inhibidores de la calcineurina] Transplantation 2005 80 289 296 16082321
Waichi, W., Venetz, J.-P., Tolkoff-Rubin, N. & Pascual, M. Inmunosuppressive strategies in kidney transplantation: Which role for the calcineurin inhibitors. [Estrategias Inmunosupresoras en el trasplante renal: El papel de los inhibidores de la calcineurina]. Transplantation 80, 289–296 (2005).16082321
5. Bae S Changes in discard rate after the introduction of the Kidney Donor Profile Index (KDPI) Am. J. Transplant. 2016 16 2202 2207 10.1111/ajt.13769 26932575
Bae, S. et al. Changes in discard rate after the introduction of the Kidney Donor Profile Index (KDPI). Am. J. Transplant. 16, 2202–2207 (2016).26932575 10.1111/ajt.13769
6. Gaber LW Glomerulosclerosis as a determinant of posttransplant function of older donor renal allografts Transplantation 1995 60 334 338 10.1097/00007890-199508270-00006 7652761
Gaber, L. W. et al. Glomerulosclerosis as a determinant of posttransplant function of older donor renal allografts. Transplantation 60, 334–338 (1995).7652761 10.1097/00007890-199508270-00006
7. Ibernon M Donor structural and functional parameters are independent predictors of renal function at 3 months Transplant. Proc. 2007 39 2095 2098 10.1016/j.transproceed.2007.06.026 17889104
Ibernon, M. et al. Donor structural and functional parameters are independent predictors of renal function at 3 months. Transplant. Proc. 39, 2095–2098. 10.1016/j.transproceed.2007.06.026 (2007).17889104 10.1016/j.transproceed.2007.06.026
8. Lopes JA Evaluation of pre-implantation kidney biopsies: Comparison of Banff criteria to a morphometric approach Kidney Int. 2005 67 1595 1600 10.1111/j.1523-1755.2005.00241.x 15780116
Lopes, J. A. et al. Evaluation of pre-implantation kidney biopsies: Comparison of Banff criteria to a morphometric approach. Kidney Int. 67, 1595–1600. 10.1111/j.1523-1755.2005.00241.x (2005).15780116 10.1111/j.1523-1755.2005.00241.x
9. Bartel DP MicroRNAs: Target recognition and regulatory functions Cell 2009 136 215 233 10.1016/j.cell.2009.01.002 19167326
Bartel, D. P. MicroRNAs: Target recognition and regulatory functions. Cell 136, 215–233 (2009).19167326 10.1016/j.cell.2009.01.002
10. Bartel DP MicroRNAs: Genomics, biogenesis, mechanism, and function Cell 2004 116 281 297 10.1016/S0092-8674(04)00045-5 14744438
Bartel, D. P. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 116, 281–297 (2004).14744438 10.1016/S0092-8674(04)00045-5
11. Krol J Loedige I Filipowicz W The widespread regulation of microRNA biogenesis, function and decay Nat. Rev. Genet. 2010 11 597 610 10.1038/nrg2843 20661255
Krol, J., Loedige, I. & Filipowicz, W. The widespread regulation of microRNA biogenesis, function and decay. Nat. Rev. Genet. 11, 597–610 (2010).20661255 10.1038/nrg2843
12. Turchinovich A Weiz L Burwinkel B Extracellular miRNAs: The mystery of their origin and function Trends Biochem. Sci. 2012 37 460 465 10.1016/j.tibs.2012.08.003 22944280
Turchinovich, A., Weiz, L. & Burwinkel, B. Extracellular miRNAs: The mystery of their origin and function. Trends Biochem. Sci. 37, 460–465 (2012).22944280 10.1016/j.tibs.2012.08.003
13. Mall C Rocke DM Durbin-Johnson B Weiss RH Stability of miRNA in human urine supports its biomarker potential Biomark. Med. 2013 7 623 631 10.2217/bmm.13.44 23905899
Mall, C., Rocke, D. M., Durbin-Johnson, B. & Weiss, R. H. Stability of miRNA in human urine supports its biomarker potential. Biomark. Med. 7, 623–631 (2013).23905899 10.2217/bmm.13.44
14. Karpman D Ståhl AL Arvidsson I Extracellular vesicles in renal disease Nat. Rev. Nephrol. 2017 13 545 562 10.1038/nrneph.2017.98 28736435
Karpman, D., Ståhl, A. L. & Arvidsson, I. Extracellular vesicles in renal disease. Nat. Rev. Nephrol. 13, 545–562. 10.1038/nrneph.2017.98 (2017).28736435 10.1038/nrneph.2017.98
15. Kwon SH Extracellular vesicles in renal physiology and clinical applications for renal disease Korean J. Intern. Med. 2019 34 470 479 10.3904/kjim.2019.108 31048657
Kwon, S. H. Extracellular vesicles in renal physiology and clinical applications for renal disease. Korean J. Intern. Med. 34, 470–479. 10.3904/kjim.2019.108 (2019).31048657 10.3904/kjim.2019.108
16. Wang Y Zhang M Urinary exosomes: A promising biomarker for disease diagnosis Lab. Med. 2023 54 115 125 10.1093/labmed/lmac087 36065158
Wang, Y. & Zhang, M. Urinary exosomes: A promising biomarker for disease diagnosis. Lab. Med. 54, 115–125. 10.1093/labmed/lmac087 (2023).36065158 10.1093/labmed/lmac087
17. Condrat CE miRNAs as biomarkers in disease: Latest findings regarding their role in diagnosis and prognosis Cells 2020 9 276 10.3390/cells9020276 31979244
Condrat, C. E. et al. miRNAs as biomarkers in disease: Latest findings regarding their role in diagnosis and prognosis. Cells 9, 276 (2020).31979244 10.3390/cells9020276
18. Aomatsu A MicroRNA expression profiling in acute kidney injury Transl. Res. 2022 244 1 31 10.1016/j.trsl.2021.11.010 34871811
Aomatsu, A. et al. MicroRNA expression profiling in acute kidney injury. Transl. Res. 244, 1–31 (2022).34871811 10.1016/j.trsl.2021.11.010
19. Van de Vrie M Deegens J Eikmans M van der Vlag J Hilbrands L Urinary microRNA as biomarker in renal transplantation Am. J. Transplant. 2017 17 1160 1166 10.1111/ajt.14082 27743494
Van de Vrie, M., Deegens, J., Eikmans, M., van der Vlag, J. & Hilbrands, L. Urinary microRNA as biomarker in renal transplantation. Am. J. Transplant. 17, 1160–1166 (2017).27743494 10.1111/ajt.14082
20. Amrouche L MicroRNA-146a in human and experimental ischemic AKI: CXCL8-dependent mechanism of action J. Am. Soc. Nephrol. 2017 28 479 493 10.1681/ASN.2016010045 27444565
Amrouche, L. et al. MicroRNA-146a in human and experimental ischemic AKI: CXCL8-dependent mechanism of action. J. Am. Soc. Nephrol. 28, 479–493 (2017).27444565 10.1681/ASN.2016010045
21. Soltaninejad E Altered expression of microRNAs following chronic allograft dysfunction with interstitial fibrosis and tubular atrophy Iran. J. Allergy Asthma Immunol. 2015 2015 615 623
Soltaninejad, E. et al. Altered expression of microRNAs following chronic allograft dysfunction with interstitial fibrosis and tubular atrophy. Iran. J. Allergy Asthma Immunol. 2015, 615–623 (2015).
22. Kim JY Urinary transglutaminase 2 as a potent biomarker to predict interstitial fibrosis and tubular atrophy of kidney allograft during early posttransplant period in deceased donor kidney transplantation Ann. Surg. Treatment Res. 2019 97 27 35 10.4174/astr.2019.97.1.27
Kim, J. Y. et al. Urinary transglutaminase 2 as a potent biomarker to predict interstitial fibrosis and tubular atrophy of kidney allograft during early posttransplant period in deceased donor kidney transplantation. Ann. Surg. Treatment Res. 97, 27–35 (2019).10.4174/astr.2019.97.1.27
23. Yu WK Nintedanib inhibits endothelial mesenchymal transition in bleomycin-induced pulmonary fibrosis via focal adhesion kinase activity reduction Int. J. Mol. Sci. 2022 2022 23 10.3390/ijms23158193
Yu, W. K. et al. Nintedanib inhibits endothelial mesenchymal transition in bleomycin-induced pulmonary fibrosis via focal adhesion kinase activity reduction. Int. J. Mol. Sci. 2022, 23. 10.3390/ijms23158193 (2022).10.3390/ijms23158193
24. Zhao XK Focal adhesion kinase regulates hepatic stellate cell activation and liver fibrosis Sci. Rep. 2017 7 4032 10.1038/s41598-017-04317-0 28642549
Zhao, X. K. et al. Focal adhesion kinase regulates hepatic stellate cell activation and liver fibrosis. Sci. Rep. 7, 4032. 10.1038/s41598-017-04317-0 (2017).28642549 10.1038/s41598-017-04317-0
25. Leask A Focal adhesion kinase: A key mediator of transforming growth factor beta signaling in fibroblasts Adv. Wound Care (New Rochelle) 2013 2 247 249 10.1089/wound.2012.0363 24527346
Leask, A. Focal adhesion kinase: A key mediator of transforming growth factor beta signaling in fibroblasts. Adv. Wound Care (New Rochelle) 2, 247–249. 10.1089/wound.2012.0363 (2013).24527346 10.1089/wound.2012.0363
26. Böhmig G Regele H Diagnosis and treatment of antibody-mediated kidney allograft rejection Transplant. Int. 2003 16 773 787 10.1007/s00147-003-0658-3
Böhmig, G. & Regele, H. Diagnosis and treatment of antibody-mediated kidney allograft rejection. Transplant. Int. 16, 773–787. 10.1007/s00147-003-0658-3 (2003).10.1007/s00147-003-0658-3
27. Loupy A Lefaucheur C Antibody-mediated rejection of solid-organ allografts N. Engl. J. Med. 2018 379 1150 1160 10.1056/NEJMra1802677 30231232
Loupy, A. & Lefaucheur, C. Antibody-mediated rejection of solid-organ allografts. N. Engl. J. Med. 379, 1150–1160. 10.1056/NEJMra1802677 (2018).30231232 10.1056/NEJMra1802677
28. Seron D Proposed definitions of T cell-mediated rejection and tubulointerstitial inflammation as clinical trial endpoints in kidney transplantation Transplant. Int. 2022 35 10135 10.3389/ti.2022.10135
Seron, D. et al. Proposed definitions of T cell-mediated rejection and tubulointerstitial inflammation as clinical trial endpoints in kidney transplantation. Transplant. Int. 35, 10135. 10.3389/ti.2022.10135 (2022).10.3389/ti.2022.10135
29. Schaub S Proteomic-based detection of urine proteins associated with acute renal allograft rejection J. Am. Soc. Nephrol. 2004 15 219 227 10.1097/01.ASN.0000101031.52826.BE 14694176
Schaub, S. et al. Proteomic-based detection of urine proteins associated with acute renal allograft rejection. J. Am. Soc. Nephrol. 15, 219–227 (2004).14694176 10.1097/01.ASN.0000101031.52826.BE
30. Cheng O Connective tissue growth factor is a biomarker and mediator of kidney allograft fibrosis Am. J. Transplant. 2006 6 2292 2306 10.1111/j.1600-6143.2006.01493.x 16889607
Cheng, O. et al. Connective tissue growth factor is a biomarker and mediator of kidney allograft fibrosis. Am. J. Transplant. 6, 2292–2306 (2006).16889607 10.1111/j.1600-6143.2006.01493.x
31. Fu G Brkić J Hayder H Peng C MicroRNAs in human placental development and pregnancy complications Int. J. Mol. Sci. 2013 14 5519 5544 10.3390/ijms14035519 23528856
Fu, G., Brkić, J., Hayder, H. & Peng, C. MicroRNAs in human placental development and pregnancy complications. Int. J. Mol. Sci. 14, 5519–5544 (2013).23528856 10.3390/ijms14035519
32. Théry C Exosomes: Secreted vesicles and intercellular communications F1000 Biol. Rep. 2011 2011 3
Théry, C. Exosomes: Secreted vesicles and intercellular communications. F1000 Biol. Rep. 2011, 3 (2011).
33. Théry C Zitvogel L Amigorena S Exosomes: Composition, biogenesis and function Nat. Rev. Immunol. 2002 2 569 579 10.1038/nri855 12154376
Théry, C., Zitvogel, L. & Amigorena, S. Exosomes: Composition, biogenesis and function. Nat. Rev. Immunol. 2, 569–579 (2002).12154376 10.1038/nri855
34. Ho PT Clark IM Le LT MicroRNA-based diagnosis and therapy Int. J. Mol. Sci. 2022 23 7167 10.3390/ijms23137167 35806173
Ho, P. T., Clark, I. M. & Le, L. T. MicroRNA-based diagnosis and therapy. Int. J. Mol. Sci. 23, 7167 (2022).35806173 10.3390/ijms23137167
35. Wang G Urinary miR-21, miR-29, and miR-93: Novel biomarkers of fibrosis Am. J. Nephrol. 2012 36 412 418 10.1159/000343452 23108026
Wang, G. et al. Urinary miR-21, miR-29, and miR-93: Novel biomarkers of fibrosis. Am. J. Nephrol. 36, 412–418 (2012).23108026 10.1159/000343452
36. Lv C-Y A PEG-based method for the isolation of urinary exosomes and its application in renal fibrosis diagnostics using cargo miR-29c and miR-21 analysis Int. Urol. Nephrol. 2018 50 973 982 10.1007/s11255-017-1779-4 29330775
Lv, C.-Y. et al. A PEG-based method for the isolation of urinary exosomes and its application in renal fibrosis diagnostics using cargo miR-29c and miR-21 analysis. Int. Urol. Nephrol. 50, 973–982 (2018).29330775 10.1007/s11255-017-1779-4
37. Kang Z Remote ischemic preconditioning upregulates microRNA-21 to protect the kidney in children with congenital heart disease undergoing cardiopulmonary bypass Pediatr. Nephrol. 2018 33 911 919 10.1007/s00467-017-3851-9 29197999
Kang, Z. et al. Remote ischemic preconditioning upregulates microRNA-21 to protect the kidney in children with congenital heart disease undergoing cardiopulmonary bypass. Pediatr. Nephrol. 33, 911–919 (2018).29197999 10.1007/s00467-017-3851-9
38. Larrue R The versatile role of miR-21 in renal homeostasis and diseases Cells 2022 11 3525 10.3390/cells11213525 36359921
Larrue, R. et al. The versatile role of miR-21 in renal homeostasis and diseases. Cells 11, 3525 (2022).36359921 10.3390/cells11213525
39. Saikumar J Expression, circulation, and excretion profile of microRNA-21,-155, and-18a following acute kidney injury Toxicol. Sci. 2012 129 256 267 10.1093/toxsci/kfs210 22705808
Saikumar, J. et al. Expression, circulation, and excretion profile of microRNA-21,-155, and-18a following acute kidney injury. Toxicol. Sci. 129, 256–267 (2012).22705808 10.1093/toxsci/kfs210
40. Du J MicroRNA-21 and risk of severe acute kidney injury and poor outcomes after adult cardiac surgery PloS One 2013 8 e63390 10.1371/journal.pone.0063390 23717419
Du, J. et al. MicroRNA-21 and risk of severe acute kidney injury and poor outcomes after adult cardiac surgery. PloS One 8, e63390 (2013).23717419 10.1371/journal.pone.0063390
41. Chen C Urinary miR-21 as a potential biomarker of hypertensive kidney injury and fibrosis Sci. Rep. 2017 7 17737 10.1038/s41598-017-18175-3 29255279
Chen, C. et al. Urinary miR-21 as a potential biomarker of hypertensive kidney injury and fibrosis. Sci. Rep. 7, 17737 (2017).29255279 10.1038/s41598-017-18175-3
42. Zhao S Exosomal miR-21 from tubular cells contributes to renal fibrosis by activating fibroblasts via targeting PTEN in obstructed kidneys Theranostics 2021 11 8660 10.7150/thno.62820 34522205
Zhao, S. et al. Exosomal miR-21 from tubular cells contributes to renal fibrosis by activating fibroblasts via targeting PTEN in obstructed kidneys. Theranostics 11, 8660 (2021).34522205 10.7150/thno.62820
43. Feng W miR-29c inhibits renal interstitial fibrotic proliferative properties through PI3K-AKT pathway Appl. Bionics Biomech. 2022 2022 1 8 10.1155/2022/6382323
Feng, W. et al. miR-29c inhibits renal interstitial fibrotic proliferative properties through PI3K-AKT pathway. Appl. Bionics Biomech. 2022, 1–8 (2022).10.1155/2022/6382323
44. Fang Y miR-29c is downregulated in renal interstitial fibrosis in humans and rats and restored by HIF-α activation Am. J. Physiol.-Renal Physiol. 2013 304 F1274 F1282 10.1152/ajprenal.00287.2012 23467423
Fang, Y. et al. miR-29c is downregulated in renal interstitial fibrosis in humans and rats and restored by HIF-α activation. Am. J. Physiol.-Renal Physiol. 304, F1274–F1282 (2013).23467423 10.1152/ajprenal.00287.2012
45. Zhang Y Zhang G-X Che L-S Shi S-H Lin W-Y miR-19 promotes development of renal fibrosis by targeting PTEN-mediated epithelial-mesenchymal transition Int. J. Clin. Exp. Pathol. 2020 13 642 32355512
Zhang, Y., Zhang, G.-X., Che, L.-S., Shi, S.-H. & Lin, W.-Y. miR-19 promotes development of renal fibrosis by targeting PTEN-mediated epithelial-mesenchymal transition. Int. J. Clin. Exp. Pathol. 13, 642 (2020).32355512
46. Zhang Y MiR-205 influences renal injury in sepsis rats through HMGB1-PTEN signaling pathway Eur. Rev. Med. Pharmacol. Sci. 2019 23 10950 10956 31858563
Zhang, Y. et al. MiR-205 influences renal injury in sepsis rats through HMGB1-PTEN signaling pathway. Eur. Rev. Med. Pharmacol. Sci. 23, 10950–10956 (2019).31858563
47. Street JM Koritzinsky EH Glispie DM Yuen PS Urine exosome isolation and characterization Drug Saf. Eval. Methods Protocols 2017 2017 413 423 10.1007/978-1-4939-7172-5_23
Street, J. M., Koritzinsky, E. H., Glispie, D. M. & Yuen, P. S. Urine exosome isolation and characterization. Drug Saf. Eval. Methods Protocols 2017, 413–423 (2017).10.1007/978-1-4939-7172-5_23
48. Lange T Identification of miR-16 as an endogenous reference gene for the normalization of urinary exosomal miRNA expression data from CKD patients PLoS One 2017 12 e0183435 10.1371/journal.pone.0183435 28859135
Lange, T. et al. Identification of miR-16 as an endogenous reference gene for the normalization of urinary exosomal miRNA expression data from CKD patients. PLoS One 12, e0183435. 10.1371/journal.pone.0183435 (2017).28859135 10.1371/journal.pone.0183435
49. Wang XY Evaluation of the performance of serum miRNAs as normalizers in microRNA studies focused on cardiovascular disease J. Thorac. Dis. 2018 10 2599 2607 10.21037/jtd.2018.04.128 29997921
Wang, X. Y. et al. Evaluation of the performance of serum miRNAs as normalizers in microRNA studies focused on cardiovascular disease. J. Thorac. Dis. 10, 2599–2607. 10.21037/jtd.2018.04.128 (2018).29997921 10.21037/jtd.2018.04.128
