Automated Urinary Chemokine Assays for Noninvasive Detection of Kidney Transplant Rejection: A Prospective Cohort Study.

RATIONALE & OBJECTIVE: Prior studies have demonstrated the diagnostic potential of urinary chemokines C-X-C motif ligand 9 (CXCL9) and CXCL10 for kidney transplant rejection. However, their benefit in addition to clinical information has not been demonstrated. We evaluated the diagnostic performance for detecting acute rejection of urinary CXCL9 and CXCL10 when integrated with clinical information. STUDY DESIGN: Single-center prospective cohort study. SETTING & PARTICIPANTS: We analyzed 1,559 biopsy-paired urinary samples from 622 kidney transplants performed between April 2013 and July 2019 at a single transplant center in Belgium. External validation was performed in 986 biopsy-paired urinary samples. TESTS COMPARED: We quantified urinary CXCL9 (uCXCL9) and CXCL10 (uCXCL10) using an automated immunoassay platform and normalized the values to urinary creatinine. Urinary chemokines were incorporated into a multivariable model with routine clinical markers (estimated glomerular filtration rate, donor-specific antibodies, and polyoma viremia) (integrated model). This model was then compared with the tissue diagnosis according to the Banff classification for acute rejection. OUTCOME: Acute rejection detected on kidney biopsy using the Banff classification. RESULTS: Chemokines integrated with routine clinical markers had high diagnostic value for detection of acute rejection (n=150) (receiver operating characteristic area under the curve 81.3% [95% CI, 77.6-85.0]). The integrated model would help avoid 59 protocol biopsies per 100 patients when the risk for rejection is predicted to be below 10%. The performance of the integrated model was similar in the external validation cohort. LIMITATIONS: The cross-sectional nature obviates investigating the evolution over time and prediction of future rejection. CONCLUSIONS: The use of an integrated model of urinary chemokines and clinical markers for noninvasive monitoring of rejection could enable a reduction in the number of biopsies. Urinary chemokines may be useful noninvasive biomarkers whose use should be further studied in prospective randomized trials to clarify their role in guiding clinical care and the use of biopsies to detect rejection after kidney transplantation. PLAIN-LANGUAGE SUMMARY: Urinary chemokines CXCL9 and CXCL10 have been suggested to be good noninvasive biomarkers of kidney transplant rejection. However, defining a context of use and integration with clinical information is necessary before clinical implementation can begin. In this study, we demonstrated that urinary chemokines CXCL9 and CXCL10, together with clinical information, have substantial diagnostic accuracy for the detection of acute kidney transplant rejection. Application of urinary chemokines together with clinical information may guide biopsy practices following kidney transplantation and potentially reduce the need for kidney transplant biopsies.

Urinary CXCL-10, a prognostic biomarker for kidney graft injuries: a systematic review and meta-analysis.

The challenges of long-term graft survival and the side effects of current immunosuppressive therapies in kidney transplantation highlight the need for improved drugs with fewer adverse effects. Biomarkers play a crucial role in quickly detecting post-transplant complications, with new biomarkers showing promise for ongoing monitoring of disease and potentially reducing the need for unnecessary invasive biopsies. The chemokines such as C-X-C motif chemokine ligand 10 (CXCL10), are particularly promising protein biomarkers for acute renal rejection, with urine samples being a desirable source for biomarkers. The aim of this review is to analyze the literature on the potential role of urinary CXCL10 protein in predicting kidney graft injuries. The results of this study demonstrate that evaluating urinary CXCL10 levels is more successful in identifying post-transplant injuries compared to assessing the CXCL10/Cr ratio.

Using Urine Biomarkers to Differentiate Bladder Dysfunctions in Women with Sensory Bladder Disorders.

Sensory bladder disorders encompass several distinct conditions with overlapping symptoms, which pose diagnostic challenges. This study aimed to evaluate urine biomarkers for differentiating between various sensory bladder disorders, including non-Hunner's interstitial cystitis (NHIC), detrusor overactivity (DO), hypersensitive bladder (HSB), and urodynamically normal women. A retrospective analysis of 191 women who underwent a videourodynamic study (VUDS) was conducted, with some also receiving cystoscopic hydrodistention to confirm the presence of NHIC. Participants were categorized into four groups: DO (n = 51), HSB (n = 29), NHIC (n = 81), and normal controls (n = 30). The urine levels of inflammatory and oxidative stress biomarkers were measured. The DO patients exhibited elevated IP-10 levels, while the HSB patients had decreased TAC and 8-OHdG levels. The NHIC patients showed lower IL-2 and higher TNF-α levels. A TNF-α ≥ 1.05 effectively identified NHIC, with an AUROC of 0.889, a sensitivity of 98.8%, and a specificity of 81.3%. An IP-10 ≥ 6.31 differentiated DO with an AUROC of 0.695, a sensitivity of 56.8%, and a specificity of 72.3%. An 8-OHdG ≤ 14.705 and a TAC ≤ 528.7 identified HSB with AUROCs of 0.754 and 0.844, respectively. The combination of 8-OHdG and TAC provided an AUROC of 0.853 for HSB. These findings suggest that TNF-α, IP-10, TAC, 8-OHdG, and IL-2 are promising non-invasive biomarkers for distinguishing between these conditions, which may improve diagnosis and management.

Urine CXCL10 as a biomarker in kidney transplantation.

PURPOSE OF REVIEW: Urine CXCL10 is a promising biomarker for posttransplant renal allograft monitoring but is currently not widely used for clinical management. RECENT FINDINGS: Large retrospective studies and data from a prospective randomized trial as well as a prospective cohort study demonstrate that low urine CXCL10 levels are associated with a low risk of rejection and can exclude BK polyomavirus replication with high certainty. Urine CXCL10 can either be used as part of a multiparameter based risk assessment tool, or as an individual biomarker taking relevant confounders into account. A novel Luminex-based CXCL10 assay has been validated in a multicenter study, and proved to be robust, reproducible, and accurate. SUMMARY: Urine CXCL10 is a well characterized inflammation biomarker, which can be used to guide performance of surveillance biopsies. Wide implementation into clinical practice depends on the availability of inexpensive, thoroughly validated assays with approval from regulatory authorities.

Serum and urine interferon-inducible protein 10, galectin-9, and SIGLEC-1 as biomarkers of disease activity in systemic lupus erythematosus.

Background/aim: In this prospective study, we aimed to investigate the association of serum (s) and urine (u) IP-10, galectin-9, and SIGLEC-1 with disease activity in patients with systemic lupus erythematosus (SLE). Materials and methods: Sixty-three patients with active SLE (31 renal, 32 extrarenal) were included. Thirty patients with inactive SLE (15 renal, 15 extrarenal), 17 with renal active AAV, and 32 healthy volunteers were selected as control groups. Serum and urine IP-10, galectin-9, and SIGLEC-1 were tested using ELISA. Results: Levels of sIP-10 (p = 0.046), uIP-10 (p < 0.001), sGalectin-9 (p = 0.03), and uSIGLEC-1 (p = 0.006) were significantly higher in active SLE group compared to the inactive SLE; however, no differences were detected in the comparison of uGalectin-9 (p = 0.18) and sSIGLEC-1 (p = 0.69) between two groups. None of the biomarkers discriminated patients with active renal SLE from active extrarenal SLE. ROC analyses revealed an AUC of 0.63 (0.52-0.73) for sIP-10, 0.78 (0.68-0.86) for uIP-10, 0.64 (0.53-0.74) for sGalectin-9, and 0.68 (0.57-0.77) for uSIGLEC-1 in discriminating disease activity in SLE, which did not outperform C3 (0.75, 0.64-0.84) and C4 (0.72, 0.61-0.82). sIP-10 (p = 0.001), uIP-10 (p = 0.042), and uGalectin-9 (p = 0.009) were significantly increased in patients with active renal SLE compared to active renal AAV. sGalectin-9 (p < 0.001) and sIP-10 levels (p = 0.06) were decreased after 8 (5-22.5) months of treatment. Conclusion: sIP-10, uIP-10, sGalectin-9, and uSIGLEC-1 reflect global disease activity in SLE but do not outperform C3 and C4. sIP-10 and uIP-10 may be specific for active SLE compared to active AAV. sIP-10 and sGalectin-9 might be valuable in monitoring response after treatment.

Serum and urinary galectin-9 and C-X-C motif chemokine ligand 10.

BACKGROUND: Systemic lupus erythematosus (SLE) is characterized by a type I interferon (IFN) signature, and traditional methods for its measurement like gene expression analysis are cumbersome for routine use. Thus, we aimed to study galectin-9 as a biomarker and compared it with a validated marker, C-X-C motifchemokine ligand 10(CXCL-10). METHODS: Ninety-seven patients with SLE (26 years; 89 females) were included and stratified based on renal involvement and activity into - active (SLEDAI > 4) renal (35), active non-renal (32) and inactive renal subgroups (30) along with 20 healthy controls (HC, 25 years; 15 females). The median disease duration was 24 months (6-48), and SLEDAI 2K was 9 (2-15). Serum and urine galectin-9 and CXCL-10 levels were measured by ELISA. Urine levels were normalized with spot urine creatinine values. Follow-up serum and urine galectin-9 levels were measured for those in the active renal group at 6 months. RESULTS: Patients with SLE had higher serum galectin-9 (5.6 vs 1.7 µg/mL, p = .0001) but not urine galectin-9 (0.52 vs 0.32 µg, p = .7) levels as compared to HC. Serum galectin-9 but not urine galectin-9 was higher in patients with active as compared to inactive lupus (12.9 - active renal, 16.7 - active non-renal vs 3.57 µg/mL, p = .04 and .005). Serum CXCL-10 (0.16 vs 0.05, p = .01) and urine CXCL-10 (0 vs 0, p = .01) were both significantly higher in the SLE group as compared with HC. Serum but not urine CXCL-10 was higher in the active as compared to inactive lupus (0.2 - active renal, 0.3 - active non-renal vs 0.08 µg/mL, p = .9 and .02). Serum galectin-9 showed a modest correlation with CXCL-10 0.4 (0.2-0.6), whereas none was found between their urine levels.Serum galectin-9 and CXCL-10 showed a moderate positive correlation with SLEDAI 2K. Serum galectin-9 showed a greater AUC than CXCL-10 (0.77 vs 0.67) in differentiating active from inactive SLE, and both tested together had the best AUC of 0.82. However, urinary levels had no association with SLEDAI 2K or renal SLEDAI. In a subset of patients with active renal disease, serum galectin-9 but not urine levels declined significantly after 6 months. CONCLUSION: Serum galectin-9 is a good marker of lupus activity; however, it does not differentiate between active renal and active non-renal disease. It performs slightly better than CXCL-10. Urinary galectin-9 does not reflect renal activity.

Advantages of plasmatic CXCL-10 as a prognostic and diagnostic biomarker for the risk of rejection and subclinical rejection in kidney transplantation.

This study evaluate the potential of plasmatic CXCL-10 (pCXCL-10) as a pre&post transplantation prognostic and diagnostic biomarker of T-cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR) and subclinical rejection (SCR) risk in adult kidney recipients considering BKV and CMV infections as possible clinical confounder factors. Twenty-eight of 100 patients included experienced rejection (TCMR:14; ABMR:14); 8 SCR; 13 and 16 were diagnosed with BKV and CMV infection, respectively. Pre-transplantation pCXCL-10 was significantly increased in TCMR and ABMR and post-transplantation in TCMR, ABMR and SCR compared with nonrejectors. All CMV+ patients showed pCXCL-10 levels above the cutoff values established for rejection whereas the 80% of BKV+ patients showed pCXCL-10 concentration < 100 pg/mL. pCXCL-10 could improve pre-transplantation patient stratification and immunosuppressive treatment selection according to rejection risk; and after kidney transplantation could be a potential early prognostic biomarker for rejection. Clinical confounding factor in BKV+ and particularly in CMV+ patients must be discarded.

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.

Acute Kidney Injury in Children after Hematopoietic Cell Transplantation Is Associated with Elevated Urine CXCL10 and CXCL9.

Acute kidney injury (AKI) is nearly universally associated with worse outcomes, especially among children after hematopoietic stem cell transplant (HCT). Our objective was to examine urinary immune biomarkers of AKI after HCT to provide insights into novel mechanisms of kidney injury in this population. Studying patients undergoing allogeneic HCT provides a unique opportunity to examine immune markers of AKI because the risk of AKI is high and the immune system newly develops after transplant. Children (>2 years old) and young adults undergoing their first allogeneic HCT and enrolled in a prospective, observational cohort study at 2 large children's hospitals had urine collected pre-HCT and monthly for the first 4 months after HCT. Urine samples at each monthly time point were assayed for 8 immune-related biomarkers. AKI was defined as a 1.5-fold increase in the monthly serum creatinine value, which was recorded ±1 day from when the research urine sample was obtained, as compared with the pre-HCT baseline. Generalized estimating equation regression analysis evaluated the association between the monthly repeated measures (urinary biomarkers and AKI). A total of 176 patients were included from 2 pediatric centers. Thirty-six patients from 1 center were analyzed as a discovery cohort and the remaining 140 patients from the second center were analyzed as a validation cohort. AKI rates were 18% to 35% depending on the monthly time point after HCT. Urine CXCL10 and CXCL9 concentrations were significantly higher among children who developed AKI compared with children who did not (P < .01) in both cohorts. In order to gain a better understanding of the cellular source for these biomarkers in the urine, we also analyzed in vitro expression of CXCL10 and CXCL9 in kidney cell lines after stimulation with interferon-γ and interferon-α. HEK293-epithelial kidney cells demonstrated interferon-induced expression of CXCL10 and CXCL9, suggesting a potential mechanism driving the key finding. CXCL10 and CXCL9 are associated with AKI after HCT and are therefore promising biomarkers to guide improved diagnostic and treatment strategies for AKI in this high-risk population.

Soluble TNF-R1, VEGF and other cytokines as markers of disease activity in systemic lupus erythematosus and lupus nephritis.

BACKGROUND: Current non-invasive methods of assessing disease activity in systemic lupus erythematosus (SLE) are of limited sensitivity and specificity. Testing includes acute phase markers, autoantibodies and complement levels. Although measurements of dsDNA antibodies and complement C3/C4 levels are routine, they remain of limited value. Improved blood and urine markers may help in early detection of flare, distinction between flare and chronic damage, and monitoring response to therapy. METHODS: A total of 87 patients with SLE were tested for the following cytokines in serum and urine: monocyte chemoattractant protein 1 (MCP-1), regulated upon activation, normal T cell expressed and secreted (RANTES), soluble tumour necrosis factor receptor 1 (sTNF-R1), interferon-inducible protein 10 (IP-10), monocyte inhibitory protein 1α (MIP-1α) and vascular endothelial growth factor (VEGF). Patients attending the Lupus Unit at St Thomas' Hospital, London, UK were divided into active lupus nephritis (LN), inactive LN and non-renal SLE groups based on their renal pathology and SLE disease activity index (SLEDAI). Cytokine testing was performed using the FIDIS multiplex bead assay. RESULTS: The mean level of serum sTNF-R1 was higher in the active LN group compared with both inactive LN and non-renal SLE groups ( p < 0.001). For urine measurements there were significant differences between active LN and non-renal SLE for VEGF ( p = 0.016), after statistical correction for multiple testing. Both urinary and serum sTNF-R1 and IP-10 levels correlated with SLEDAI scores ( p < 0.001), while serum VEGF correlated weakly with SLEDAI ( p = 0.025). The optimum combination for differentiating active from inactive LN patients was serum VEGF, sTNF-R1, MCP-1 and glomerular filtration rate plus urinary sTNF-R1 and protein-creatinine ratio. CONCLUSION: These results indicate that for active LN, sTNF-R1 could be a useful serum cytokine marker, with potential for VEGF in the urine. This study has confirmed the ability of the multiplex bead technique to detect cytokines in a good analytical range, including very low and high levels, in both serum and urine. Combining serum and urine markers provided additional sensitivity in distinguishing active from inactive LN.

Interferon-Inducible Protein 10 and Disease Activity in Systemic Lupus Erythematosus and Lupus Nephritis: A Systematic Review and Meta-Analysis.

There is increasing evidence of a correlation between interferon-inducible protein 10 (IP-10) and disease activity of systemic lupus erythematosus (SLE) and lupus nephritis (LN). We conducted a comprehensive search on IP-10 using MEDLINE, Scopus, and Cochrane electronic databases from the beginning to the end of December 2017. All studies that compared serum and/or urine IP-10 between active SLE/LN patients and any control groups were identified and included in this systematic review and meta-analysis. The mean difference (MD) of IP-10 level among active SLE and LN patients, as well as the correlation of IP-10 with disease activity, were meta-analyzed using a random-effects model. From 23 eligible studies, 15 provided adequate data for meta-analysis. Serum IP-10 was significantly elevated in patients with active SLE compared to non-active SLE patients (MD 356.5 pg/mL, 95% CI 59.6 to 653.4, p = 0.019). On the other hand, the levels of serum IP-10 was not different between active LN and non-active LN. However, serum IP-10 was positively correlated with disease activity like SLE disease activity index (SLEDAI) (pooled r = 0.29, 95% CI 0.22 to 0.35, p < 0.001). Furthermore, urine IP-10 tended to be higher in patients with active LN compared to non-active LN patients but this did not reach statistical significance (MD 3.47 pg/mgCr × 100, 95% CI -0.18 to 7.12, p = 0.06). Nevertheless, urine IP-10 was positively correlated with renal SLEDAI (pooled r = 0.29, 95% CI 0.05 to 0.50, p = 0.019). In conclusion, serum and urine IP-10 levels may be useful in monitoring the disease activity of SLE and LN. Serum IP-10 was correlated with systemic disease whereas urine IP-10 was a useful biomarker for detecting active LN.

Urine IP-10 as a biomarker of therapeutic response in patients with active pulmonary tuberculosis.

BACKGROUND: Prior to clinical trials of new TB drugs or therapeutic vaccines, it is necessary to develop monitoring tools to predict treatment outcomes in TB patients. Urine interferon gamma inducible protein 10 (IP-10) is a potential biomarker of treatment response in chronic hepatitis C virus infection and lung diseases, including tuberculosis. In this study, we assessed IP-10 levels in urine samples from patients with active TB at diagnosis, during treatment, and at completion, and compared these with levels in serum samples collected in parallel from matched patients to determine whether urine IP-10 can be used to monitor treatment response in patients with active TB. METHODS: IP-10 was measured using enzyme-linked immunosorbent assays in urine and serum samples collected concomitantly from 23 patients with active TB and 21 healthy adults (44 total individuals). The Mann-Whitney U test and Wilcoxon matched-pairs signed rank test were used for comparisons among healthy controls and patients at three time points, and LOESS regression was used for longitudinal data. RESULTS: The levels of IP-10 in urine increased significantly after 2 months of treatment (P = 0.0163), but decreased by the completion of treatment (P = 0.0035). Serum IP-10 levels exhibited a similar trend, but did not increase significantly after 2 months of treatment in patients with active TB. CONCLUSIONS: Unstimulated IP-10 in urine can be used as a biomarker to monitor treatment response in patients with active pulmonary TB.

Diagnostic value of urinary CXCL10 as a biomarker for predicting Hunner type interstitial cystitis.

AIM: To investigate the feasibility of chemokines and cytokines potentially elevated in the bladder tissue of Hunner type interstitial cystitis (HIC) as urinary markers for distinguishing HIC from non-Hunner type interstitial cystitis (NHIC) METHODS: Urine specimens were collected from 41 HIC patients, 25 NHIC patients, and 31 healthy volunteers (control). The supernatants of urine specimens were subjected to ELISA kits for measurements of 10 cytokines and chemokines, whose gene expression was known to be elevated in HIC bladder tissue. Urinary levels normalized by urinary creatinine (Cr) concentration were compared among three groups. Efficiency in differentiating IC and IC subtypes was explored by ROC analysis. The correlation of marker levels with symptom severity, assessed by O'Leary-Sant's symptom index (OSSI) and problem index (OSPI), was examined. RESULTS: The urinary levels of CXCL10 and NGF were significantly higher in HIC than NHIC. CXCL10 and NGF differentiated HIC against NHIC with AUC of 0.78 and 0.68, respectively. Combination of CXCL10 and NGF levels yielded an AUS of 0.81. The CXCL10 cut-off of 53.2 pg/mg Cr had sensitivity of 46.1%, specificity of 93.7%, positive predictive value of 97.7%, and negative predictive value of 60.0%. The urinary level of other cytokines showed no significant difference between HIC and NHIC. Significant correlation with symptoms was detected for CXCL10 alone. CONCLUSION: The results suggested that increased urinary level of CXCL10 combined with or without high NGF level could be a promising supplementary biomarker for differentiating HIC from NHIC with modest sensitivity and high specificity.

Evolution of renal function and urinary biomarker indicators of inflammation on serial kidney biopsies in pediatric kidney transplant recipients with and without rejection.

Urinary CXCL10 and metabolites are biomarkers independently associated with TCMR. We sought to test whether these biomarkers fluctuate in association with histological severity of TCMR over short time frames. Forty-nine pairs of renal biopsies obtained 1-3 months apart from 40 pediatric renal transplant recipients were each scored for TCMR acuity score (i + t; Banff criteria). Urinary CXCL10:Cr and TCMR MDS were obtained at each biopsy and were tested for association with changes between biopsies in acuity, estimated GFR (ΔeGFR), and 12-month ΔeGFR. Sequential biopsies were obtained 1.8 ± 0.8 months apart. Biopsy 1 was usually obtained under protocol (75%), and 62% percent had evidence of TCMR. Using each biopsy pair for comparison, ΔeGFR did not predict change in acuity. By contrast, change in acuity was significantly correlated with change in urinary CXCL10:Cr (ρ 0.45, P = .003) and MDS (ρ 0.29, P = .04) between biopsies. The 12-month ΔeGFR was not predicted by TCMR acuity or CXCL10:Cr at Biopsy 2; however, an inverse correlation was seen with urinary MDS (ρ -0.35; P = .02). Changes in eGFR correlate poorly with evolving TCMR acuity on histology. Urinary biomarkers may be superior for non-invasive monitoring of rejection, including histological response to therapy, and may be prognostic for medium-term function.

New developments in transplant proteomics.

PURPOSE OF REVIEW: Despite modern immunosuppression, renal allograft rejection remains a major contributor to graft loss. Novel biomarkers may help improve posttransplant outcomes through the early detection and treatment of rejection. Our objective is to provide an overview of proteomics, review recent discovery-based rejection studies, and explore innovative approaches in biomarker development. RECENT FINDINGS: Urine MMP7 was identified as a biomarker of subclinical and clinical rejection using two-dimensional liquid chromatography tandem-mass spectrometry (LC-MS/MS) and improved the overall diagnostic discrimination of urine CXCL10 : Cr alone for renal allograft inflammation. A novel peptide signature to classify stable allografts from acute rejection, chronic allograft injury, and polyoma virus (BKV) nephropathy was identified using isobaric tag for relative and absolute quantitation (TRAQ) and label-free MS, with independent validation by selected reaction monitoring mass spectrometry (SRM-MS). Finally, an in-depth exploration of peripheral blood mononuclear cells identified differential proteoform expression in healthy transplants versus rejection. SUMMARY: There is still much in the human proteome that remains to be explored, and further integration of renal, urinary, and exosomal data may offer deeper insight into the pathophysiology of rejection. Functional proteomics may be more biologically relevant than protein/peptide quantity alone, such as assessment of proteoforms or activity-based protein profiling. Discovery-based studies have identified potential biomarker candidates, but external validation studies are required.

A critical review of biomarkers in kidney transplantation.

PURPOSE OF REVIEW: Improved long-term kidney allograft survival remains a critical goal in transplantation; the achievement of this, however, is highly dependent on the identification of biomarkers that can either predict or allow advance detection of patients at risk of allograft injury. The present review outlines the commonly used biomarkers in kidney transplantation, while also highlighting those currently under investigation, discussing their advantages and limitations. RECENT FINDINGS: Most of the approved biomarkers currently used in kidney transplantation capture antigen recognition or alloantibody production. However, tremendous progress has recently been made in the development of markers of other signaling pathways pertinent to the alloimmune response. Microarray gene sets that predict rejection or poor prognostic phenotypes have been identified in kidney biopsies (the 'molecular microscope diagnostic system' and the 'genomics of chronic allograft rejection' scores), peripheral blood (the 'kidney solid organ response test'), and urine (the '3-genes signature'). Strategies targeting serial measurements of urinary chemokines such as CXCL9 and CXCL10 also appear promising. SUMMARY: Although the range of biomarkers in current use is limited, there are many assays in the development and validation pipeline that appear promising but that have yet to reach mainstream clinical transplantation. The 'ideal biomarker' may eventually transpire to be the combination of several assays.

Urinary miR-155-5p and CXCL10 as prognostic and predictive biomarkers of rejection, graft outcome and treatment response in kidney transplantation.

AIMS: MicroRNAs (miRNAs) may be useful biomarkers of rejection and allograft outcome in kidney transplantation. Elevated urinary CXCL10 levels have been associated with acute rejection (AR) and may predict allograft failure. We examined the correlation of miRNA, CXCL10 levels and immunosuppressive drug exposure with AR and graft function in kidney transplant recipients. METHODS: Eighty de novo kidney transplant recipients were recruited from four European centres. All patients received tacrolimus, mycophenolate mofetil, and methylprednisolone. Urinary pellet expression of miR-142-3p, miR-210-3p and miR-155-5p was assessed by quantitative real-time polymerase chain reaction and urinary CXCL10 levels by enzyme-linked immunosorbent assay at the 1st week and the 1st , 2nd , 3rd and 6th months post-transplantation. RESULTS: Eight patients experienced AR. Before and during AR, patients showed a significant increase of urinary miR-142-3p, miR-155-5p and CXCL10 levels and a decrease of miR-210-3p levels. Receiver operating characteristic curve analysis showed that miR-155-5p (area under the curve = 0.875; P = 0.046) and CXCL10 (area under the curve = 0.865; P = 0.029) had excellent capacity to discriminate between rejectors and nonrejectors. The optimal cut-off values for the prognosis of AR were 0.51, with 85% sensitivity and 86% specificity for miR-155-5p and 84.73 pg ml-1 , with 84% sensitivity and 80% specificity for CXCL10. miR-155-5p and CXCL10 levels correlated with glomerular filtration rate. Levels of both biomarkers normalized after recovery of graft function. CONCLUSIONS: The regular early post-transplantation monitoring of urinary miR-155-5p and CXCL10 can help in the prognosis of AR and graft dysfunction. Large prospective randomized multicentre trials are warranted to refine our cut-off values and validate the clinical usefulness of these biomarkers.

The association of urinary interferon-gamma inducible protein-10 (IP10/CXCL10) levels with kidney allograft rejection.

BACKGROUND: Interferon-gamma inducible protein-10 (IP-10/CXCL10) is a chemokine involved in the alloimmune response against kidney allograft. We aimed to investigate the association of urinary CXCL10 protein levels with rejection in renal transplant patients. METHODS: A total of 273 urine samples from (biopsy-proven) rejection and non-rejection patients and controls were included in this study. CXCL10 levels were analyzed for association with rejection. RESULTS: The data showed statistically significant differences in the CXCL10 levels between rejection vs. non-rejection (p < 0.001). Among the rejection groups, statistically significant differences for CXCL10 levels were found between ACR vs. NAD (p < 0.001), ACR vs. BLR (p = 0.019) and AVR vs. NAD (p = 0.009). Receiver Operating Characteristic (ROC) curve analysis of CXCL10 showed an area under the curve (AUC) of 0.74 with 72% sensitivity and 71% specificity at 27.5 pg/ml between rejection and non-rejection group. Kaplan-Meier curve analysis among different levels of CXCL10 showed a better rejection-free graft survival in patients with <100 pg/ml when compared to >200 pg/ml (38 ± 6 vs. 12 ± 1.0 weeks; log-rank p < 0.001) and 100-200 pg/ml (38 ± 6 vs. 22 ± 9 weeks; log-rank p = 0.442) concentration. CONCLUSION: The results indicate significantly increased levels of CXCL10 protein in the urine at the time of allograft rejection. This association of urinary CXCL10 protein levels with rejection could provide an additional tool for the non-invasive monitoring of allograft rejection.

Early Low Urinary CXCL9 and CXCL10 Might Predict Immunological Quiescence in Clinically and Histologically Stable Kidney Recipients.

We monitored the urinary C-X-C motif chemokine (CXCL)9 and CXCL10 levels in 1722 urine samples from 300 consecutive kidney recipients collected during the first posttransplantation year and assessed their predictive value for subsequent acute rejection (AR). The trajectories of urinary CXCL10 showed an early increase at 1 month (p = 0.0005) and 3 months (p = 0.0009) in patients who subsequently developed AR. At 1 year, the AR-free allograft survival rates were 90% and 54% in patients with CXCL10:creatinine (CXCL10:Cr) levels <2.79 ng/mmoL and >2.79 ng/mmoL at 1 month, respectively (p < 0.0001), and 88% and 56% in patients with CXCL10:Cr levels <5.32 ng/mmoL and >5.32 ng/mmoL at 3 months (p < 0.0001), respectively. CXCL9:Cr levels also associate, albeit less robustly, with AR-free allograft survival. Early CXCL10:Cr levels predicted clinical and subclinical rejection and both T cell- and antibody-mediated rejection. In 222 stable patients, CXCL10:Cr at 3 months predicted AR independent of concomitant protocol biopsy results (p = 0.009). Although its positive predictive value was low, a high negative predictive value suggests that early CXCL10:Cr might predict immunological quiescence on a triple-drug calcineurin inhibitor-based immunosuppressive regimen in the first posttransplantation year, even in clinically and histologically stable patients. The clinical utility of this test will need to be addressed by dedicated prospective clinical trials.

Urinary-cell mRNA profile and acute cellular rejection in kidney allografts.

BACKGROUND: The standard test for the diagnosis of acute rejection in kidney transplants is the renal biopsy. Noninvasive tests would be preferable. METHODS: We prospectively collected 4300 urine specimens from 485 kidney-graft recipients from day 3 through month 12 after transplantation. Messenger RNA (mRNA) levels were measured in urinary cells and correlated with allograft-rejection status with the use of logistic regression. RESULTS: A three-gene signature of 18S ribosomal (rRNA)-normalized measures of CD3ε mRNA and interferon-inducible protein 10 (IP-10) mRNA, and 18S rRNA discriminated between biopsy specimens showing acute cellular rejection and those not showing rejection (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.78 to 0.91; P<0.001 by receiver-operating-characteristic curve analysis). The cross-validation estimate of the AUC was 0.83 by bootstrap resampling, and the Hosmer-Lemeshow test indicated good fit (P=0.77). In an external-validation data set, the AUC was 0.74 (95% CI, 0.61 to 0.86; P<0.001) and did not differ significantly from the AUC in our primary data set (P=0.13). The signature distinguished acute cellular rejection from acute antibody-mediated rejection and borderline rejection (AUC, 0.78; 95% CI, 0.68 to 0.89; P<0.001). It also distinguished patients who received anti-interleukin-2 receptor antibodies from those who received T-cell-depleting antibodies (P<0.001) and was diagnostic of acute cellular rejection in both groups. Urinary tract infection did not affect the signature (P=0.69). The average trajectory of the signature in repeated urine samples remained below the diagnostic threshold for acute cellular rejection in the group of patients with no rejection, but in the group with rejection, there was a sharp rise during the weeks before the biopsy showing rejection (P<0.001). CONCLUSIONS: A molecular signature of CD3ε mRNA, IP-10 mRNA, and 18S rRNA levels in urinary cells appears to be diagnostic and prognostic of acute cellular rejection in kidney allografts. (Funded by the National Institutes of Health and others.).