Urinary CXCL10 Research Articles

Discovery and Validation of a Kidney Rejection Prediction Model Using Urinary CXCL9 and CXCL10

Discovery and Validation of a Kidney Rejection Prediction Model Using Urinary CXCL9 and CXCL10

Next-Level Approach to Antibody-Mediated Rejection and T Cell-Mediated Rejection Diagnosis in Kidney Transplantation: Dynamic Duo of Urine CXCL10 and Donor-Derived Cell-Free DNA

Next-Level Approach to Antibody-Mediated Rejection and T Cell-Mediated Rejection Diagnosis in Kidney Transplantation: Dynamic Duo of Urine CXCL10 and Donor-Derived Cell-Free DNA

Next-level approach to AMR and TCMR diagnosis in kidney transplantation; the dynamic duo of urine CXCL10 and donor-derived cell free DNA

Next-level approach to AMR and TCMR diagnosis in kidney transplantation; the dynamic duo of urine CXCL10 and donor-derived cell free DNA

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.

Transforming kidney transplant monitoring with urine CXCL9 and CXCL10: practical clinical implementation

In kidney transplant recipients, urine CXCL9 and CXCL10 (uCXCL9/10) chemokines have reached a sufficiently high level of evidence to be recommended by the European Society of Organ Transplantation for the monitoring of immune quiescence. To assess the risk of acute rejection (AR), the advantage of uCXCL9/10 is their cost-effectiveness and their high diagnostic performance. Here, we evaluated the feasibility of a next-generation immunoassay for quantifying uCXCL9/10 levels. It demonstrated high efficiency with minimal workflow and a 90-min time to result. Preanalytical studies indicated stability of uCXCL9/10 levels and analytical studies confirmed excellent linearity and precision. In a cohort of 1048 samples collected at biopsy, the results correlated significantly with ELISA quantification and were integrated into a previously validated 8-parameter urine chemokine model. The next generation immunoassay achieved an accuracy of 0.84 for AR diagnosis. This study validates this technology as a robust, locally available and unexpensive platform and marks a significant step towards the widespread implementation of uCXCL9/10, for immune quiescence monitoring. Therefore, we developed an open-access web application using uCXCL9/10 to calculate AR risk and improve clinical decision-making to perform biopsy, ushering in a new era in kidney transplantation, where personalized, data-driven care becomes the norm.

201.4: The combination of urine CXCL10 and donor-derived cell free DNA in the non-invasive diagnosis of antibody mediated and T cell mediated rejection in kidney transplantation.

201.4: The combination of urine CXCL10 and donor-derived cell free DNA in the non-invasive diagnosis of antibody mediated and T cell mediated rejection in kidney transplantation.

Urinary Chemokines CXCL9 and CXCL10 Are Non-Invasive Biomarkers of Kidney Transplant Rejection.

BACKGROUND Rejection is the main cause of kidney allograft failure, and kidney biopsy is the criterion standard method to diagnose it. However, non-invasive techniques to detect kidney transplant rejection are necessary. This study aimed to evaluate urinary chemokines CXCL9 and CXCL10 as potential biomarkers of kidney transplant rejection and to analyze chemokine association with allograft prognosis. MATERIAL AND METHODS We collected 117 urine samples from kidney transplant recipients undergoing allograft biopsy. CXCL9 and CXCL10 levels were measured by ELISA and the ratio to urine creatinine was calculated. Histology and other clinical data were collected from medical records. RESULTS The diagnostic performance of urinary CXCL9/cre in discriminating rejection from all other histological groups showed an ROC AUC value of 0.728 (95% CI 0.632-0.824, p<0.001), and a cut-off value 0.11 ng/mmol had the best sensitivity (76.9%) and specificity (73.1%). The ability of CXCL10/cre to discriminate transplant rejection from all other histological groups had ROC AUC value 0.73 (95% CI 0.63-0.84, P<0.001), the cut-off value 0.42 ng/mmol with best sensitivity (71.4%) and specificity (84.6%). CXCL9 and CXCL10 levels were also increased in patients with polyoma BK virus, recurrent AA amyloidosis, and thrombotic microangiopathy. Patients with higher CXCL9/cre (≥0.11 ng/mmol) and CXCL10/cre (≥0.42 ng/mmol) levels were at increased risk of transplant progression to ESRD (HR 3.25, 95% CI=1.27-8.36, P=0.01), irrespective of serum creatinine at the time of biopsy. CONCLUSIONS Urinary CXCL9/cre and CXCL10/cre were able to distinguished between patients with transplant rejection and those without rejection. High levels of urinary CXCL9/cre and CXCL10/cre were associated with worse allograft survival.

Combination of urinary biomarkers and machine-learning models provided a higher predictive accuracy to predict long-term treatment outcomes of patients with interstitial cystitis/bladder pain syndrome.

To identify predictive factors for satisfactory treatment outcome of the patients with IC/BPS using urine biomarkers and machine-learning models. The IC/BPS patients were prospectively enrolled and provide urine samples. The targeted analytes included inflammatory cytokines, neurotrophins, and oxidative stress biomarkers. The patients with overall subjective symptom improvement of ≥ 50% were considered to have satisfactory results. Binary logistic regression, receiver-operating characteristic (ROC) curve, machine-learning decision tree, and random forest models were used to analyze urinary biomarkers to predict satisfactory results. Altogether, 57.4% of the 291 IC/BPS patients obtained satisfactory results. The patients with satisfactory results had lower levels of baseline urinary inflammatory cytokines and oxidative biomarkers than patients without satisfying results, including interleukin-6, monocyte chemoattractant protein-1 (MCP-1), C-X-C motif chemokine 10 (CXCL10), oxidative stress biomarkers 8-hydroxy-2'-deoxyguanosine (8-OHDG), 8-isoprostane, and total antioxidant capacity (TAC). Logistic regression and multivariable analysis revealed that lower levels of urinary CXCL10, MCP-1, 8-OHDG, and 8-isoprostane were independent factors. The ROC curve revealed that MCP-1 level had best area under curve (AUC: 0.797). In machine-learning decision tree model, combination of urinary C-C motif chemokine 5, 8-isoprostane, TAC, MCP-1, and 8-OHDG could predict satisfactory results (accuracy: 0.81). The random forest model revealed that urinary 8-isoprostance, MCP-1, and 8-OHDG levels had the most important influence on accuracy. Machine learning decision tree model provided a higher accuracy for predicting treatment outcome of patients with IC/BPS than logistic regression, and levels of 8-isoprostance, MCP-1, and 8-OHDG had the most important influence on accuracy.

Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis.

Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis.

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

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. Single-center prospective cohort study. 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. 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. Acute rejection detected on kidney biopsy using the Banff classification. 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. The cross-sectional nature obviates investigating the evolution over time and prediction of future rejection. 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. 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.

Immune urinary biomarkers predict infant cardiac surgery-associated acute kidney injury.

Acute kidney injury(AKI) occurs frequently after infant cardiac surgery and is associated with poor outcomes, including mortality and prolonged length of stay. AKI mechanisms are poorly understood, limiting therapeutic targets. Emerging data implicates dysregulated immune activation in post-cardiac surgery AKI development. We sought to identify immune-mediated AKI biomarkers after infant cardiopulmonary bypass (CPB)-assisted cardiac surgery. A single-center prospective study of 126 infants less than 1year old undergoing CPB-assisted surgery enrolled between 10/2017 and 6/2019. Urine samples were collected before CPB and at 6, 24, 48, and 72h after surgery. Immune-mediated biomarkers were measured using commercial ELISA and Luminex™ multiplex kits. Based on subject age, neonatal KDIGO (< 1month) or KDIGO criteria defined AKI. The Kruskal-Wallis rank test determined the relationship between urinary biomarker measurements and AKI. A total of 35 infants (27%) developed AKI. AKI subjects were younger, underwent more complex surgery, and had longer CPB time. Subjects with AKI vs. those without AKI had higher median urinary chemokine 10 (C-X-C motif) ligand levels at 24, 48, and 72h, respectively: 14.3pg/ml vs. 5.3pg/ml, 3.4pg/ml vs. 0.8pg/ml, and 1.15pg/ml vs. 0.22pg/ml (p < 0.05) post-CPB. At 6h post-CPB, median vascular cell adhesion protein 1 (VCAM) levels (pg/mL) were higher among AKI subjects (491pg/ml vs. 0pg/ml, p = 0.04). Urinary CXCL10 and VCAM are promising pro-inflammatory biomarkers for early AKI detection and may indicate eventual AKI therapeutic targets. A higher resolution version of the Graphical abstract is available as Supplementary information.

Urinary CXCL9: a biomarker for AIN.

Urinary CXCL9: a biomarker for AIN.

Urine CXCL10 to Assess BK Polyomavirus Replication After Kidney Transplantation.

Urine CXCL10 is a biomarker for renal allograft inflammation induced by rejection, urinary tract infection, or BK polyomavirus (BKPyV) replication. This study aimed to compare urine CXCL10 levels in different stages of BKPyV reactivation and to investigate urine CXCL10 as a biomarker for BKPyV replication. We included 763 urine samples (235 patients) from an interventional, randomized trial obtained in the context of regular screening for urine CXCL10 levels. All urine samples had a complete urine sediment analysis, no rejection episode noted within 30 d before urine collection, and a urine decoy cell analysis was conducted within ±3 d. Urine CXCL10 levels were 2.31 ng/mmol in samples without BKPyV viruria, slightly rose to 4.35 ng/mmol with BKPyV viruria, and then markedly increased to 16.42 ng/mmol when decoy cells were detectable, but still in the absence of BKPyV DNAemia ( P < 0.001). The highest urine CXCL10 values were observed in samples with BKPyV DNAemia (median 42.59 ng/mmol). The area under the curve of urine CXCL10 levels to detect ≥3 decoy cells was 0.816. At a CXCL10 cutoff of 3 ng/mmol, the negative predictive value was 97%. The area under the curve of urine CXCL10 levels to detect BKPyV DNAemia was 0.882, with a negative predictive value of 99% at a CXCL10 cutoff of 3 ng/mmol. Urine CXCL10 levels are already significantly elevated in BKPyV viruria (especially with decoy cell shedding) and further increase with BKPyV DNAemia. Low urine CXCL10 values can rule out the presence of ≥3 decoy cells and BKPyV DNAemia with high certainty.

Urine CXCL10 Levels as a Predictor for Various Phases of BKPyV Replication Among Kidney Transplant Recipients: Utility and Clinical Implementation.

Urine CXCL10 Levels as a Predictor for Various Phases of BKPyV Replication Among Kidney Transplant Recipients: Utility and Clinical Implementation.

Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis.

BackgroundAcute tubulointerstitial nephritis (AIN) is one of the few causes of acute kidney injury with diagnosis-specific treatment options. However, due to the need to obtain a kidney biopsy for histological confirmation, AIN diagnosis can be delayed, missed, or incorrectly assumed. Here, we identify and validate urinary CXCL9, an IFN-γ-induced chemokine involved in lymphocyte chemotaxis, as a diagnostic biomarker for AIN.MethodsIn a prospectively enrolled cohort with pathologist-adjudicated histological diagnoses, termed the discovery cohort, we tested the association of 180 immune proteins measured by an aptamer-based assay with AIN and validated the top protein, CXCL9, using sandwich immunoassay. We externally validated these findings in 2 cohorts with biopsy-confirmed diagnoses, termed the validation cohorts, and examined mRNA expression differences in kidney tissue from patients with AIN and individuals in the control group.ResultsIn aptamer-based assay, urinary CXCL9 was 7.6-fold higher in patients with AIN than in individuals in the control group (P = 1.23 × 10-5). Urinary CXCL9 measured by sandwich immunoassay was associated with AIN in the discovery cohort (n = 204; 15% AIN) independently of currently available clinical tests for AIN (adjusted odds ratio for highest versus lowest quartile: 6.0 [1.8-20]). Similar findings were noted in external validation cohorts, where CXCL9 had an AUC of 0.94 (0.86-1.00) for AIN diagnosis. CXCL9 mRNA expression was 3.9-fold higher in kidney tissue from patients with AIN (n = 19) compared with individuals in the control group (n = 52; P = 5.8 × 10-6).ConclusionWe identified CXCL9 as a diagnostic biomarker for AIN using aptamer-based urine proteomics, confirmed this association using sandwich immunoassays in discovery and external validation cohorts, and observed higher expression of this protein in kidney biopsies from patients with AIN.FundingThis study was supported by National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) awards K23DK117065 (DGM), K08DK113281 (KM), R01DK128087 (DGM), R01DK126815 (DGM and LGC), R01DK126477 (KNC), UH3DK114866 (CRP, DGM, and FPW), R01DK130839 (MES), and P30DK079310 (the Yale O'Brien Center). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Noninvasive testing for mycophenolate exposure in children with renal transplant using urinary metabolomics.

Despite the common use of mycophenolate in pediatric renal transplantation, lack of effective therapeuic drug monitoring increases uncertainty over optimal drug exposure and risk for adverse reactions. This study aims to develop a novel urine test to estimate MPA exposure based using metabolomics. Urine samples obtained on the same day of MPA pharmacokinetic testing from two prospective cohorts of pediatric kidney transplant recipients were assayed for 133 unique metabolites by mass spectrometry. Partial least squares (PLS) discriminate analysis was used to develop a top 10 urinary metabolite classifier that estimates MPA exposure. An independent cohort was used to test pharmacodynamic validity for allograft inflammation (urinary CXCL10 levels) and eGFR ratio (12mo/1mo eGFR) at 1 year. Fifty-two urine samples from separate children (36.5% female, 12.0± 5.3 years at transplant) were evaluated at 1.6± 2.5 years post-transplant. Using all detected metabolites (n= 90), the classifier exhibited strong association with MPA AUC by principal component regression (r= 0.56, p< .001) and PLS (r= 0.75, p< .001). A practical classifier (top 10 metabolites; r= 0.64, p< .001) retained similar accuracy after cross-validation (LOOCV; r= 0.52, p< .001). When applied to an independent cohort (n= 97 patients, 1053 samples), estimated mean MPA exposure over Year 1 was inversely associated with mean urinary CXCL10:Cr (r= -0.28, 95% CI -0.45, -0.08) and exhibited a trend for association with eGFR ratio (r= 0.35, p= .07), over the same time period. This urinary metabolite classifier can estimate MPA exposure and correlates with allograft inflammation. Future studies with larger samples are required to validate and evaluate its clinical application.

Tertiary lymphoid structure signatures are associated with immune checkpoint inhibitor related acute interstitial nephritis.

Tertiary lymphoid structures (TLSs) are associated with anti-tumor response following immune checkpoint inhibitor (ICI) therapy, but a commensurate observation of TLS is absent for immune related adverse events (irAEs) i.e. acute interstitial nephritis (AIN). We hypothesized that TLS-associated inflammatory gene signatures are present in AIN and performed NanoString-based gene expression and multiplex 12-chemokine profiling on paired kidney tissue, urine and plasma specimens of 36 participants who developed acute kidney injury (AKI) on ICI therapy: AIN (18), acute tubular necrosis (9), or HTN nephrosclerosis (9). Increased T and B cell scores, a Th1-CD8+ T cell axis accompanied by interferon-g and TNF superfamily signatures were detected in the ICI-AIN group. TLS signatures were significantly increased in AIN cases and supported by histopathological identification. Furthermore, urinary TLS signature scores correlated with ICI-AIN diagnosis but not paired plasma. Urinary CXCL9 correlated best to tissue CXCL9 expression (rho 0.75, p < 0.001) and the ability to discriminate AIN vs. non-AIN (AUC 0.781, p-value 0.003). For the first time, we report the presence of TLS signatures in irAEs, define distinctive immune signatures, identify chemokine markers distinguishing ICI-AIN from common AKI etiologies and demonstrate that urine chemokine markers may be used as a surrogate for ICI-AIN diagnoses.

Anti-interleukin-6 Antibody Clazakizumab in Antibody-mediated Kidney Transplant Rejection: Effect on Donor-derived Cell-free DNA and C-X-C Motif Chemokine Ligand 10.

We report a secondary endpoint analysis of a phase 2 trial of anti-IL-6 antibody clazakizumab in late AMR (ClinicalTrials.gov, NCT03444103). Twenty kidney transplant recipients were randomized to treatment with clazakizumab or placebo over 12 wk (part A), followed by an extension in which all recipients received clazakizumab through week 52 (part B). Biomarkers were evaluated at day 0 and after 12 and 52 wk, respectively. Fractional dd-cfDNA (dd-cfDNA[%]) did not significantly change under clazakizumab, with no differences between study arms (clazakizumab versus placebo) at week 12 (1.65% [median; interquartile range: 0.91%-2.78%] versus 0.97% [0.56%-2.30%]; P = 0.25) and no significant decrease from weeks 12 to 52 (1.15% [0.70%-2.38%] versus 1.0% [0.61%-1.70%]; P = 0.25). Similarly, urine CXCL10 was not different between groups at week 12 (55.7 [41.0-91.4] versus 60.2 [48.8-208.7.0] pg/mg creatinine; P = 0.44) and did not change over part B (CXCL10 [pg/mg creatinine]: from 58 [46.3-93.1] to 67.4 [41.5-132.0] pg/mL creatinine; P = 0.95). Similar results were obtained for serum CXCL10. There was no association between biomarker levels and resolution of molecular and morphologic AMR activity. Our results suggest that IL-6 blockade does not significantly affect levels of dd-cfDNA[%] and CXCL10. Subtle responses to this therapeutic principle may be overlooked by early biomarker surveillance.

240.3: Detection of CMV Mediated Sub-Clinical Rejection by Urine Biomarkers

Methods: Research on early detection of Cytomegalovirus (CMV) mediated sub-clinical rejection (sAR) is in its nascence. This study explores the efficacy of urine-based biomarkers for sAR risk prognostication. Urine samples were serially collected (1 week- 2yrs) across 125 unique renal allograft recipients from UCSF and UCLA. These CMV+ (blood CMV-PCR) patients received valganciclovir therapy until CMV- for 3 consecutive months. Analysis: We computed a machine-learning based rejection prediction score incorporating urine cell-free DNA (cfDNA), methylated cfDNA, total protein, CXCL10, clusterin and creatinine. Rejection was determined between scores of 32-100; higher score associated with biopsy severity (Yang et al, STM 2021). In a cross-sectional analysis, Kruskal-Wallis test was performed on the urine-score distribution, to determine sAR during CMV+. Subsequently UCSF samples were analyzed longitudinally to establish the relationship between CMV and sAR; this was validated independently in UCLA samples. Results: Significant differences were observed in scores >32 between biopsy-confirmed AR vs. stable (p: 0.0034) and CMV vs. stable (p=0.003). Longitudinal analysis yielded 3 primary sAR patterns following CMV infection; (i)persistence of sAR leading to new development of chronic allograft injury; (ii)early sAR (score >32) followed by a further increase in score (>55) with biopsy confirmed cAR; (iii)sAR (>32) followed by recovery of injury with CMV resolution and a decline in score <32). Conclusions: We provide a urine-based method for detecting sAR at the time of CMV infection, and its potential clinical utility for titrating use of anti-viral therapy and recipient immunosuppression load.

Levels of donor-derived cell-free DNA and chemokines in BK polyomavirus-associated nephropathy.

BK polyomavirus-associated nephropathy (BKPyVAN) carries a risk of irreversible allograft injury. While detection of BK viremia and biopsy assessment are the current diagnostic gold standard, the diagnostic value of biomarkers reflecting tissue injury (donor-derived cell-free DNA [dd-cfDNA]) or immune activation (C-X-C motif chemokine ligand [CXCL]9 and CXCL10) remains poorly defined. For this retrospective study, 19 cases ofBKPyVANwere selected from the Vienna transplant cohort (biopsies performed between 2012 and 2019). Eight patients with T cell-mediated rejection (TCMR), 17 with antibody-mediated rejection (ABMR) and 10 patients without polyomavirus nephropathy or rejection served as controls. Fractions of dd-cfDNAwere quantified using next-generation sequencing and CXCL9 and CXCL10 were detected using multiplex immunoassays. BKPyVANwas associated with a slight increase in dd-cfDNA(median; interquartile range: .38% [.27%-1.2%] vs. .21% [.12%-.34%] in non-rejecting control patients; p=.005). Levels were far lower than in ABMR (1.2% [.82%-2.5%]; p=.004]), but not different from TCMR (.54% [.26%-3.56%]; p=.52). Within theBKPyVANcohort, we found no relationship between dd-cfDNAlevels and the extent of tubulo-interstitial infiltrates,BKPyVANclass and BK viremia/viruria, respectively. In some contrast to dd-cfDNA, concentrations of urinary CXCL9 and CXCL10 exceeded those detected in ABMR, but similar increases were also found in TCMR. BKPyVANcan induce moderate increases in dd-cfDNAand concomitant high urinary excretion of chemokines, but this pattern may be indistinguishable from that of TCMR. Our results argue against a significant value of these biomarkers to reliably distinguishBKPyVANfrom rejection.