Novel non-invasive method for urine mapping: Deep-learning-enabled SERS spectroscopy for the rapid differential detection of kidney allograft injury.

The kidney allograft has been under continuous attack from diverse injuries since the very beginning of organ procurement, leading to a gradual decline in function, chronic fibrosis, and allograft loss. It is vital to routinely and precisely monitor the risk of injuries after renal transplantation, which is difficult to achieve because the traditional laboratory tests lack sensitivity and specificity, and graft biopsies are invasive with the risk of many complications and time-consuming. Herein, a novel method for the diagnosis of graft injury is demonstrated, using deep learning-assisted surface-enhanced Raman spectroscopy (SERS) of the urine analysis. Specifically, we developed a hybrid SERS substrate composed of gold and silver with high sensitivity to the urine composition under test, eliminating the need for labels, which makes measurements easy to perform and meanwhile results in extremely abundant and complex Raman vibrational bands. Deep learning algorithms were then developed to improve the interpretation of the SERS spectral fingerprints. The deep learning model was trained with SERS signals of urine samples of recipients with different injury types including delayed graft function (DGF), calcineurin-inhibitor toxicity (CNIT), T cell-mediated rejection (TCMR), antibody-mediated rejection (AMR), and BK virus nephropathy (BKVN), which explored the features of these types and achieved the injury differentiation with an overall accuracy of 93.03%. The results highlight the potential of combining label-free SERS spectroscopy with deep learning as a method for liquid biopsy of kidney allograft injuries, which can provide great potential to diagnose and evaluate allograft injuries, and thus extend the life of kidney allografts.

Biomarker-Development Proteomics in Kidney Transplantation: An Updated Review.

Kidney transplantation (KT) is the optimal therapeutic strategy for patients with end-stage renal disease. The key to post-transplantation management is careful surveillance of allograft function. Kidney injury may occur from several different causes that require different patient management approaches. However, routine clinical monitoring has several limitations and detects alterations only at a later stage of graft damage. Accurate new noninvasive biomarker molecules are clearly needed for continuous monitoring after KT in the hope that early diagnosis of allograft dysfunction will lead to an improvement in the clinical outcome. The advent of "omics sciences", and in particular of proteomic technologies, has revolutionized medical research. Proteomic technologies allow us to achieve the identification, quantification, and functional characterization of proteins/peptides in biological samples such as urine or blood through supervised or targeted analysis. Many studies have investigated proteomic techniques as potential molecular markers discriminating among or predicting allograft outcomes. Proteomic studies in KT have explored the whole transplant process: donor, organ procurement, preservation, and posttransplant surgery. The current article reviews the most recent findings on proteomic studies in the setting of renal transplantation in order to better understand the effective potential of this new diagnostic approach.

Urinary cell mRNA profiling of kidney allograft recipients: Development of a portable protocol for noninvasive diagnosis of T cell mediated rejection and BK virus nephropathy.

BACKGROUND: We developed urinary cell mRNA profiling for noninvasive diagnosis of acute T cell mediated rejection (TCMR) and BK virus nephropathy (BKVN), two significant post-transplant complications. Our profiling protocol for the multicenter Clinical Trial of Transplantation-04 (CTOT-04) study consisted of centrifugation of urine to prepare cell pellets, washes, addition of an RNA preservative, storage at 800C and shipment in cold containers to our Gene Expression Monitoring (GEM) Core for RNA isolation and quantification of mRNA in RT-qPCR assays. To simplify profiling, we developed a filter-based protocol (ZFBP) that eliminated the need for centrifugation, RNA preservative, storage at 800C, and shipment in cold containers for mRNA profiling. Furthermore, we trained kidney allograft recipients to perform the filtration of urine at home using the filter and post the urinary cell lysate containing the RNA at ambient temperature to our GEM Core for profiling. Here, we report our refinement of ZFBP and investigation of its diagnostic performance characteristics. METHODS: Total RNA was isolated from kidney allograft biopsy-matched urines using a filter-based protocol complemented by a silica-membrane-based cartridge for mRNA enrichment, the Weill Cornell Hybrid Protocol (WCHP). Absolute copy numbers of CD3ε mRNA, CXCL10 mRNA, and 18S rRNA, components of the CTOT-04 three-gene TCMR diagnostic signature, and urinary cell BKV VP 1 mRNA copy number were measured using RT-qPCR assays. Mann-Whitney test, Fischer exact test, and receiver operating characteristic (ROC) curve analysis were used for data analyses. RESULTS: Urinary cell three-gene TCMR diagnostic signature scores in urines processed using the WCHP discriminated kidney allograft recipients with TCMR (12 TCMR biopsies from 11 patients) from those without TCMR or BKVN (29 No TCMR/No BKVN biopsies from 29 patients). The median (25th and 75th percentiles) score of the CTOT-04 three-gene TCMR diagnostic signature was -0.448 (-1.664, 0.204) in the TCMR group and - 2.542 (-3.267, -1.365) in the No TCMR/ No BKVN group (P = 0.0005, Mann-Whitney test). ROC curve analysis discriminated the TCMR group from the No TCMR/ No BKVN group; the area under the ROC curve (AUROC) was 0.84 (95% Confidence Intervals [CI], 0.69 to 0.98) (P < 0.001), and TCMR was diagnosed with a sensitivity of 67% (95% CI, 35 to 89) at a specificity of 86% (95% CI, 67 to 95) using the CTOT-04 validated cutpoint of -1.213 (P = 0.0016, Fisher exact test). BKV VP1 mRNA copy number in urines processed using the WCHP discriminated patients with BKVN (n = 7) from patients without TCMR or BKVN (n = 29) and the AUROC was 1.0 (95% CI, 1.00 to 1.00) (P < 0.0001) and BKVN was diagnosed with a sensitivity of 86% (95% CI, 42 to 99) at a specificity of 100% (95% CI, 85 to 100) with the previously validated cutpoint of 6.5 × 108 BKV-VP1 mRNA copies per microgram of RNA (P < 0.0001, Fisher exact test). CONCLUSION: Urine processed using the WCHP predicted TCMR and BKVN in kidney allograft recipients. WCHP represents not only a significant advance toward the portability of urinary cell mRNA profiling but also improved patient management by minimizing their visits for urine collection.

Point-of-care non-invasive enzyme-cleavable nanosensors for acute transplant rejection detection.

Accurate and non-invasive monitoring of allograft posttransplant is essential for early detection of acute cellular rejection and determines the long-term survival of the graft. Clinically, tissue biopsy is the most effective approach for diagnosing transplant rejection. Nonetheless, the procedure is invasive and potentially triggers organ failure. This work aims to design and apply GzmB-responsive nanosensors (GBRNs) that can readily size-change in graft tissues. Subsequently, we investigate the activity of serine protease granzyme B by generating a direct colorimetric urinary readout for non-invasive detection of transplant rejection in under 1 h. In preclinical heart graft mice models of transplant rejection, GBRNs were cleaved by GzmB and excreted by the kidneys via accurate nanometre-size glomerular filtration. By exploiting the catalytic activity of ultrasmall gold nanoclusters, GBRNs urinalysis promotes ultrasensitive surveillance of rejection episodes with a receiver operator characteristic curve area under the curve of 0.896 as well as a 95% confidence interval of about 0.7701-1.000. Besides, the catalytic activity of gold nanoclusters in urine can be detected at point-of-care testing to predict the immunity responses in mice with insufficient immunosuppressive therapy. Therefore, this non-invasive, sensitive, and quantitative method is a robust and informative approach for rapid and routine monitoring of transplant allografts without invasive biopsy.

Urinary Extracellular Vesicles Are a Novel Tool to Monitor Allograft Function in Kidney Transplantation: A Systematic Review.

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.

Differentiating Acute Rejection From Preeclampsia After Kidney Transplantation.

OBJECTIVE: To evaluate the clinical and laboratory characteristics in pregnancy that differentiate preeclampsia from acute renal allograft rejection and to investigate the maternal, neonatal, and graft sequelae of these diagnoses. METHODS: We conducted a retrospective case-controlled registry study of data abstracted from Transplant Pregnancy Registry International deliveries between 1968 and 2019. All adult kidney transplant recipients with singleton pregnancies of at least 20 weeks of gestation were included. Acute rejection was biopsy proven and preeclampsia was diagnosed based on contemporary criteria. Variables were compared using χ2, Fisher exact, and Wilcoxon rank sum tests as appropriate. Multivariable linear regression was used to analyze preterm birth. Kaplan-Meier curves with log-rank test and Cox proportional hazards model were used to compare graft loss over time. RESULTS: There were 26 pregnant women with biopsy-confirmed acute rejection who were matched by the year they conceived to 78 pregnant women with preeclampsia. Recipients with acute rejection had elevated peripartum serum creatinine levels (73% vs 14%, P<.001), with median intrapartum creatinine of 3.90 compared with 1.15 mg/dL (P<.001). Conversely, only patients with preeclampsia had a significant increase in proteinuria from baseline. Although there were no significant differences in maternal outcomes, graft loss within 2 years postpartum (42% vs 10%) and long-term graft loss (73% vs 35%) were significantly increased in recipients who experienced acute rejection (P<.001 for both). The frequency of delivery before 32 weeks of gestation was 53% with acute rejection and 20% with preeclampsia. After controlling for hypertension and immunosuppressant use, acute rejection was associated with higher frequency of delivery at less than 32 weeks of gestation (adjusted odds ratio 4.04, 95% CI 1.10-15.2). CONCLUSION: In pregnancy, acute rejection is associated with higher creatinine levels, and preeclampsia is associated with increased proteinuria. Acute rejection in pregnancy carries a risk of prematurity and graft loss beyond that of preeclampsia for kidney transplant recipients. FUNDING SOURCE: The Transplant Pregnancy Registry International is supported in part by an educational grant from Veloxis Pharmaceuticals.

Urinary Cell mRNA Profiles Predictive of Human Kidney Allograft Status.

Immune monitoring of kidney allograft recipients and personalized therapeutics may help reach the aspirational goal of "one transplant for life." The invasive kidney biopsy procedure, the diagnostic tool of choice, has become safer and the biopsy classification more refined. Nevertheless, biopsy-associated complications, interobserver variability in biopsy specimen scoring, and costs continue to be significant concerns. The dynamics of the immune repertoire make frequent assessments of allograft status necessary, but repeat biopsies of the kidney are neither practical nor safe. To address the existing challenges, we developed urinary cell mRNA profiling and investigated the diagnostic, prognostic, and predictive accuracy of absolute levels of a hypothesis-based panel of mRNAs encoding immunoregulatory proteins. Enabled by our refinements of the PCR assay and by investigating mechanistic hypotheses, our single-center studies identified urinary cell mRNAs associated with T cell-mediated rejection, antibody-mediated rejection, interstitial fibrosis and tubular atrophy, and BK virus nephropathy. In the multicenter National Institutes of Health Clinical Trials in Organ Transplantation-04, we discovered and validated a urinary cell three-gene signature of T-cell CD3 ε chain mRNA, interferon gamma inducible protein 10 (IP-10) mRNA, and 18s ribosomal RNA that is diagnostic of subclinical acute cellular rejection and acute cellular rejection and prognostic of acute cellular rejection and graft function. The trajectory of the signature score remained flat and below the diagnostic threshold for acute cellular rejection in the patients with no rejection biopsy specimens, whereas a sharp rise was observed during the weeks before the biopsy specimen that showed acute cellular rejection. Our RNA sequencing and bioinformatics identified kidney allograft biopsy specimen gene signatures of acute rejection to be enriched in urinary cells matched to acute rejection biopsy specimens. The urinary cellular landscape was more diverse and more enriched for immune cell types compared with kidney allograft biopsy specimens. Urinary cell mRNA profile-guided clinical trials are needed to evaluate their value compared with current standard of care.

Urinary vitronectin identifies patients with high levels of fibrosis in kidney grafts.

BACKGROUND: In kidney transplantation, fibrosis represents the final and irreversible consequence of the pathogenic mechanisms that lead to graft failure, and in the late stages it irremediably precedes the loss of renal function. The invasiveness of kidney biopsy prevents this condition from being frequently monitored, while clinical data are rather unspecific. The objective of this study was to find noninvasive biomarkers of kidney rejection. METHODS: We carried out proteomic analysis of the urinary Extracellular Vesicles (uEVs) from a cohort of kidney transplant recipients (n = 23) classified according to their biopsy-based diagnosis and clinical parameters as interstitial fibrosis and tubular atrophy (IFTA), acute cellular rejection (ACR), calcineurin inhibitors toxicity (CNIT) and normal kidney function (NKF). RESULTS: Shotgun mass spectrometry of uEV-proteins identified differential expression of several proteins among these different groups. Up to 23 of these proteins were re-evaluated using targeted proteomics in a new independent cohort of patients (n = 41) classified in the same diagnostic groups. Among other results, we found a differential expression of vitronectin (VTN) in patients displaying chronic interstitial and tubular lesions (ci and ct mean > 2 according to Banff criteria). These results were further confirmed by a pilot study using enzyme-linked immunosorbent assay (ELISA). CONCLUSION: Urinary vitronectin levels are a potential stand-alone biomarker to monitor fibrotic changes in kidney transplant recipients in a non-invasive fashion.

Biomarker implementation: Evaluation of the decision-making impact of CXCL10 testing in a pediatric cohort.

BACKGROUND: Children are at high risk for subclinical rejection, and kidney biopsy is currently used for surveillance. Our objective was to test how novel rejection biomarkers such as urinary CXCL10 may influence clinical decision-making to indicate need for a biopsy. METHODS: A minimum dataset for standard decision-making to indicate a biopsy was established by an expert panel and used to design clinical vignettes for use in a survey. Pediatric nephrologists were recruited to review the vignettes and A) estimate rejection risk and B) decide whether to biopsy; first without and then with urinary CXCL10/Cr level. Accuracy of biopsy decisions was then tested against the biopsy results. IRA was assessed by Fleiss Kappa (κ) for binary choice and ICC for probabilities. RESULTS: Eleven pediatric nephrologists reviewed 15 vignettes each. ICC of probability assessment for rejection improved from poor (0.28, P < .01) to fair (0.48, P < .01) with addition of CXCL10/Cr data. It did not, however, improve the IRA for decision to biopsy (K = 0.48 and K = 0.43, for the comparison). Change in clinician estimated probability of rejection with additional CXCL10/Cr data was correlated with CXCL10/Cr level (r2  = 0.7756, P < .0001). Decision accuracy went from 8/15 (53.3%) cases to 11/15 (73.3%) with CXCL10/Cr, although improvement did not achieve statistical significance. Using CXCL10/Cr alone would have been accurate in 12/15 cases (80%). CONCLUSION: There is high variability in decision-making on biopsy indication. Urinary CXCL10/Cr improves probability estimates for risk of rejection. Training may be needed to assist nephrologists in better integrate biomarker information into clinical decision-making.

Urinary nitrate concentration as a marker for kidney transplant rejection.

BACKGROUND: Early identification and treatment of kidney transplant rejection episodes is vital to limit loss of function and prolong the life of the transplanted kidney and recipient. Current practice depends on detecting a creatinine rise. A biomarker to diagnose transplant rejection at an earlier time point than current practice, or to inform earlier decision making to biopsy, could be transformative. It has previously been shown that urinary nitrate concentration is elevated in renal transplant rejection. Nitrate is a nitric oxide (NO) oxidation product. Transplant rejection upregulates NO synthesis via inducible nitric oxide synthase leading to elevations in urinary nitrate concentration. We have recently validated a urinary nitrate concentration assay which could provide results in a clinically relevant timeframe. Our aim was to determine whether urinary nitrate concentration is a useful tool to predict renal transplant rejection in the context of contemporary clinical practice. METHODS: We conducted a prospective observational study, recruiting renal transplant participants over an 18-month period. We made no alterations to the patients' clinical care including medications, immunosuppression, diet and frequency of visits. We collected urine samples from every clinical attendance. We assessed the urinary nitrate to creatinine ratio (uNCR) between patient groups: routine attendances, biopsy proven rejection, biopsy proven no rejection and other call backs. uNCR was examined over time for those with biopsy proven transplant rejection. These four groups were compared using an ANOVA test. RESULTS: A total of 2656 samples were collected. uNCR during biopsy proven rejection, n = 15 (median 49 µmol/mmol, IQR 23-61) was not significantly different from that of routine samples, n = 164 (median 55 µmol/mmol, IQR 37-82) (p = 0.55), or biopsy proven no rejection, n = 12 (median 39 µmol/mmol, IQR 21-89) (P = 0.77). Overall uNCR was highly variable with no diagnostic threshold for kidney transplant rejection. Furthermore, within-patient uNCR was highly variable over time, and thus it was not possible to produce individualised patient thresholds to identify rejection. The total taking Tacrolimus was 204 patients, with no statistical difference between the uNCR of all those on Tacrolimus, against those not, p = 0.18. CONCLUSION: The urinary nitrate to creatinine ratio is not a useful biomarker for renal transplant rejection.

Urinary Biomarkers for Diagnosis and Prediction of Acute Kidney Allograft Rejection: A Systematic Review.

Noninvasive tools for diagnosis or prediction of acute kidney allograft rejection have been extensively investigated in recent years. Biochemical and molecular analyses of blood and urine provide a liquid biopsy that could offer new possibilities for rejection prevention, monitoring, and therefore, treatment. Nevertheless, these tools are not yet available for routine use in clinical practice. In this systematic review, MEDLINE was searched for articles assessing urinary biomarkers for diagnosis or prediction of kidney allograft acute rejection published in the last five years (from January 1, 2015 to May 31, 2020). This review follows the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Articles providing targeted or unbiased urine sample analysis for the diagnosis or prediction of both acute cellular and antibody-mediated kidney allograft rejection were included, analyzed, and graded for methodological quality with a particular focus on study design and diagnostic test accuracy measures. Urinary C-X-C motif chemokine ligands were the most promising and frequently studied biomarkers. The combination of precise diagnostic reference in training sets with accurate validation in real-life cohorts provided the most relevant results and exciting groundwork for future studies.

Interleukin 8 Is Overexpressed in Acute Rejection in Kidney Transplant Patients.

The main complication associated with renal graft loss is immune rejection. The gold standard for the diagnosis of renal graft rejection is percutaneous renal biopsy, which is expensive and can lead to complications. Inflammation is one of the main pathogenic pathways in allograft rejection, and urine samples seem to be efficient windows to explore the allograft condition with a high cost-benefit ratio. This study aimed to evaluate the messenger ribonucleic acid (mRNA) profile expression pattern for interleukin (IL) 2, IL-4, IL-6, IL-8, and IL-10; tumor necrosis factor alfa; gamma interferon; and transforming growth factor ß1 in the urine renal cells of patients with a diagnosis of humoral rejection and patients with a diagnosis of normal biopsy. METHODS: An observational, cross-sectional analytical study was performed. All kidney transplants were performed at the Organ Transplant Department between 2018 and 2019. Also, a healthy control with a normal blood test and no apparent infection was included. mRNA from urine samples and biopsies was isolated, and the expression of interleukins was analyzed in PCR real time. Data were analyzed by Shapiro-Wilk and Kruskal-Wallis tests. RESULTS: The proinflammatory IL expression pattern in urine samples of kidney rejection group showed overexpression for IL-8 (P = .0001). No differences were observed in the rest of the interleukins analyzed. When we compared the results in the rejected versus not rejected transplanted patients with a group of apparently healthy subjects, the difference remains consistent. Thus, mRNA of IL-8 could function as a diagnostic tool in cases of chronic damage secondary to fibrosis.

A Noninvasive Urine Metabolome Panel as Potential Biomarkers for Diagnosis of T Cell-Mediated Renal Transplant Rejection.

Acute T cell-mediated rejection (TCMR) is a major complication after renal transplantation. TCMR diagnosis is very challenging and currently depends on invasive renal biopsy and nonspecific markers such as serum creatinine. A noninvasive metabolomics panel could allow early diagnosis and improved accuracy and specificity. We report, in this study, on urine metabolome changes in renal transplant recipients diagnosed with TCMR, with a view to future metabolomics-based diagnostics in transplant medicine. We performed urine metabolomic analyses in three study groups: (1) 7 kidney transplant recipients with acute TCMR, (2) 15 kidney transplant recipients without rejection but with impaired kidney function, and (3) 6 kidney transplant recipients with stable renal function, using 1H-nuclear magnetic resonance. Multivariate modeling of metabolites suggested a diagnostic panel where the diagnostic accuracy of each metabolite was calculated by receiver operating characteristic curve analysis. The impaired metabolic pathways associated with TCMR were identified by pathway analysis. In all, a panel of nine differential metabolites encompassing nicotinamide adenine dinucleotide, 1-methylnicotinamide, cholesterol sulfate, gamma-aminobutyric acid (GABA), nicotinic acid, nicotinamide adenine dinucleotide phosphate, proline, spermidine, and alpha-hydroxyhippuric acid were identified as novel potential metabolite biomarkers of TCMR. Proline, spermidine, and GABA had the highest area under the curve (>0.7) and were overrepresented in the TCMR group. Nicotinate and nicotinamide metabolism was the most important pathway in TCMR. These findings call for clinical validation in larger study samples and suggest that urinary metabolomics warrants future consideration as a noninvasive research tool for TCMR diagnostic innovation.

New Markers for Transplant Rejection.

Monitoring allograft function after kidney transplant has routinely relied on the use of nonspecific markers, such as serum creatinine, glomerular filtration rate, proteinuria, and donor-specific antibodies. These traditional markers have low sensitivity and fail to detect subclinical changes. Diagnosis of renal allograft dysfunction still requires an allograft biopsy, as it remains the criterion standard for assessment of graft status. However, renal biopsy is an invasive procedure, and sampling errors may result in misdiagnosis, perhaps causing graft failure. New biomarkers have been developed to monitor allograft function, although many are not yet routinely used. Other shortcomings, such as lack of standardization and high cost, should be solved before their widespread application in the clinic. A recipient's immune status could be monitored by use of urine or blood samples. These include functional cell-based assays and the evaluation of molecular expression at the messenger RNA or protein levels. Molecular technologies, including molecular microscope diagnostic systems, have been recently developed to improve the yield of histologic evaluation of the allograft biopsy. Prospective, interventional trials are required to demonstrate whether these new biomarkers improve patient or transplant outcomes. Implementation of these technologies into standard clinical practice remains challenging until their generalizability, cost, ease of interpretation, and the identification of patients who may benefit from more than standard-of-care surveillance can be determined. These biomarkers could allow immunosuppressive therapy to be individualized for patients.

Kidney transplant monitoring by urinary flow cytometry: Biomarker combination of T cells, renal tubular epithelial cells, and podocalyxin-positive cells detects rejection.

Creatinine and proteinuria are used to monitor kidney transplant patients. However, renal biopsies are needed to diagnose renal graft rejection. Here, we assessed whether the quantification of different urinary cells would allow non-invasive detection of rejection. Urinary cell numbers of CD4+ and CD8+ T cells, monocytes/macrophages, tubular epithelial cells (TEC), and podocalyxin(PDX)-positive cells were determined using flow cytometry and were compared to biopsy results. Urine samples of 63 renal transplant patients were analyzed. Patients with transplant rejection had higher amounts of urinary T cells than controls; however, patients who showed worsening graft function without rejection had similar numbers of T cells. T cells correlated with histological findings (interstitial inflammation p = 0.0005, r = 0.70; tubulitis p = 0.006, r = 0.58). Combining the amount of urinary T cells and TEC, or T cells and PDX+ cells, yielded a significant segregation of patients with rejection from patients without rejection (all p < 0.01, area under the curve 0.89-0.91). Urinary cell populations analyzed by flow cytometry have the potential to introduce new monitoring methods for kidney transplant patients. The combination of urinary T cells, TEC, and PDX-positive cells may allow non-invasive detection of transplant rejection.

Potential urinary extracellular vesicle protein biomarkers of chronic active antibody-mediated rejection in kidney transplant recipients.

The aim of this study was to identify potential proteomic biomarkers for chronic active antibody-mediated rejection (CAMR) in kidney transplant recipients (KTRs). Among 385 KTRs enrolled in a cross-sectional multicenter study, 26 KTRs with biopsy-proven CAMR, 57 KTRs with long-term graft survival (LGS), and 10 rejection-free matched KTRs were included. A proteomic approach was employed to measure urinary extracellular vesicle (EV) changes in the KTRs. The urinary EVs were trypsin-digested using a gel-assisted protocol and quantified by label-free liquid chromatography with tandem mass spectrometry, using a data-dependent acquisition (DDA) mode. Western blot analysis was performed to confirm the protein levels for each candidate biomarker. Analysis of the isolated EV proteins revealed 93 and 97 proteins in the CAMR and LGS patients, respectively. Proteins that were identical in both groups were excluded and only high-significance proteins with a fold change of at least 1.5 were selected as candidate biomarkers. Six proteins (APOA1, TTR, PIGR, HPX, AZGP1, and CP) that were distinguishable between CAMR and LGS were selected. The proteins were confirmed by immunoblot analyses using independently acquired urinary EV samples. AZGP1 in particular was found to be a CAMR-specific proteomic biomarker that was distinguishable from the rejection-free control group with matching kidney function, duration of transplantation, and age. We identified and validated six proteomic biomarkers for CAMR and clarified one CAMR-specific proteomic biomarker in KTRs. Further clinical trials are needed before these rejection-specific biomarkers can be applied for the early prediction, diagnosis, and monitoring of the clinical response of KTRs to the treatment of CAMR.

A urinary metabolite constellation to detect acute rejection in kidney allografts.

BACKGROUND: To validate a novel method for post-transplant surveillance to detect kidney allograft rejection via a characteristic constellation of the urine metabolites alanine, citrate, lactate, and urea investigated by nuclear magnetic resonance (NMR) spectroscopy a first prospective, observational study was performed. METHODS: Within the UMBRELLA study 986 urine specimens were collected from 109 consecutively enrolled renal transplant recipients, and metabolite constellations were analyzed. A metabolite rejection score was calculated and compared to histopathological results of corresponding indication and protocol allograft biopsies (n = 206). FINDINGS: The metabolite constellation was found to be a useful biomarker to non-invasively detect acute allograft rejection (AUC = 0.75; 95% confidence interval (CI) 0.68-0.83; based on 46 cases and 520 control samples). Combined analysis of the metabolite rejection score and the estimated glomerular filtration rate (eGFR) at the time of urine sampling further improved the overall test performance significantly (AUC = 0.84; 95% CI 0.76-0.91; based on 42 cases and 468 controls). Regarding the time course analysis in patients without rejection episodes the test results remained well below a diagnostic threshold associated with high risk of acute rejection. In other cases, a marked increase above this threshold indicated acute allograft rejection already six to ten days before diagnostic renal biopsies were performed. INTERPRETATION: A combination of an NMR-based urine metabolite analysis and eGFR is promising as a non-invasive test for post-transplant surveillance and to support decision making whether renal allografts need histopathological evaluation.

Urinary Human Epididymis Secretory Protein 4 as a Useful Biomarker for Subclinical Acute Rejection Three Months after Kidney Transplantation.

Kidney transplantation is the treatment of choice for patients with advanced chronic kidney disease (CKD) and end stage renal disease (ESRD). However, acute rejection (AR) is a common complication in kidney transplantation and is associated with reduced graft survival. Current diagnosis of AR relies mainly on clinical monitoring including serum creatinine, proteinuria, and confirmation by histopathologic assessment in the biopsy specimen of graft kidney. Although an early protocol biopsy is indispensable for depicting the severity of pathologic lesions in subclinical acute rejection (subAR), it is not acceptable in some cases and cannot be performed because of its invasive nature. Therefore, we examined the detection of noninvasive biomarkers that are closely related to the pathology of subAR in protocol biopsies three months after kidney transplantation. In this study, the urinary level of microtubule-associated protein 1 light chain 3 (LC3), monocyte chemotactic protein-1 (MCP-1), liver-type fatty acid-binding protein (L-FABP), neutrophil gelatinase-associated lipocalin (NGAL), and human epididymis secretory protein 4 (HE4) were measured three months after kidney transplantation. Urine samples of 80 patients undergoing kidney transplantation between August 2014 to September 2016, were prospectively collected after three months. SubAR was observed in 11 patients (13.8%) in protocol biopsy. The urinary levels of LC3, MCP-1, NGAL, and HE4 were significantly higher in patients with subAR than in those without, while those of L-FABP did not differ between the two groups. Multivariate regression models, receiver-operating characteristics (ROC), and areas under ROC curves (AUC) were used to identify predicted values of subAR. Urinary HE4 levels were able to better identify subAR (AUC = 0.808) than the other four urinary biomarkers. In conclusion, urinary HE4 is increased in kidney transplant recipients of subAR three months after kidney transplantation, suggesting that HE4 has the potential to be used as a novel clinical biomarker for predicting subAR.

Urinary levels of CCL2 and CXCL10 chemokines as potential biomarkers of ongoing pathological processes in kidney allograft: an association with BK virus nephropathy.

INTRODUCTION: Early prognostic markers that identify high­risk kidney transplant recipients may lead to optimization of immunosuppressive therapy and improved long­term outcomes. OBJECTIVES: The aim of this study was to assess whether the measurement of urinary concentrations of CCL2 and CXCL10 chemokines can be a valuable noninvasive tool for identifying ongoing pathological processes in a kidney allograft. PATIENTS AND METHODS: The study included 40 patients who underwent a protocol biopsy within 1­year post kidney transplant. The urinary concentrations of CCL2 and CXCL10 with reference to creatinine in urine were assayed in all patients. On the basis of biopsy results, a study group was selected (n = 25), including patients with a diagnosis of interstitial fibrosis and tubular atrophy grades II to III (n = 16), BK virus (BKV) nephropathy (n = 4), or mild inflammatory lesions fulfilling the criteria for mild rejection processes or borderline lesions (n = 11). Patients with normal biopsy results were included in a control group (n = 15). RESULTS: The ratio of CCL2 to creatinine (CCL2:Cr) was a significant independent predictor of BKV ephropathy (odds ratio, 1.1; 95% CI, 1.0-1.2; P = 0.04). The CXCL10:Cr ratio was not found to be an independent predictor of BKV nephropathy (odds ratio, 1.3; 95% CI, 0.99-1.71; P = 0.06). CONCLUSIONS: The CCL2:Cr and CXCL10:Cr ratios may predict BKV nephropathy. The diagnostic value of CCL2 and CXCL10 in BKV infection should be further evaluated.