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A urine score for noninvasive accurate diagnosis and prediction of kidney transplant rejection.

ABSTRACT: Accurate and noninvasive monitoring of renal allograft posttransplant is essential for early detection of acute rejection (AR) and to affect the long-term survival of the transplant. We present the development and validation of a noninvasive, spot urine-based diagnostic assay based on measurements of six urinary DNA, protein, and metabolic biomarkers. The performance of this assay for detecting kidney injury in both native kidneys and renal allografts is presented on a cohort of 601 distinct urine samples. The urinary composite score enables diagnosis of AR, with a receiver-operator characteristic curve area under the curve of 0.99 and an accuracy of 96%. In addition, we demonstrate the clinical utility of this assay for predicting AR before a rise in the serum creatinine, enabling earlier detection of rejection than currently possible by standard of care tests. This noninvasive, sensitive, and quantitative approach is a robust and informative method for the rapid and routine monitoring of renal allografts.

SUBMITTER: Yang JYC

PROVIDER: S-EPMC8289390 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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A urine score for noninvasive accurate diagnosis and prediction of kidney transplant rejection.

Yang Joshua Y C JYC Sarwal Reuben D RD Sigdel Tara K TK Damm Izabella I Rosenbaum Ben B Liberto Juliane M JM Chan-On Chitranon C Arreola-Guerra José M JM Alberu Josefina J Vincenti Flavio F Sarwal Minnie M MM

Science translational medicine 20200301 535

Accurate and noninvasive monitoring of renal allograft posttransplant is essential for early detection of acute rejection (AR) and to affect the long-term survival of the transplant. We present the development and validation of a noninvasive, spot urine-based diagnostic assay based on measurements of six urinary DNA, protein, and metabolic biomarkers. The performance of this assay for detecting kidney injury in both native kidneys and renal allografts is presented on a cohort of 601 distinct uri ...[more]

PMID: 32188722

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Project description:Histologic diagnosis of T cell-mediated rejection in kidney transplant biopsies has limited reproducibility because it is based on non-specific lesions using arbitrary rules that are subject to differing interpretations. We used microarray results from 403 indication biopsies previously given histologic diagnoses to develop a molecular classifier that assigned a molecular T cell-mediated rejection score to each biopsy. Independent assessment of the biopsies by multiple pathologists confirmed considerable disagreement on the presence of TCMR features: 79-88% accuracy and 35-69% sensitivity. The agreement of the molecular T cell-mediated rejection score with the histology diagnosis was similar to agreement among individual pathologists: accuracy 89%, sensitivity 51%. However, the score also predicted the consensus among pathologists, being highest when all agreed. Many discrepancies between the scores and the histologic diagnoses were in situations where histology is unreliable e.g. scarred biopsies. The score correlated with histologic lesions and gene sets associated with T cell-mediated rejection. The transcripts most often selected by the classifier were expressed in effector T cells, dendritic cells, or macrophages or inducible by interferon-gamma. Thus the T cell-mediated rejection score offers an objective assessment of kidney transplant biopsies, predicting the consensus opinion among multiple pathologists, and offering insights into underlying disease mechanisms. Antibody-mediated rejection is a major cause of kidney transplant failure, but the current diagnostic system misses most cases due to dependency on subjective non-standardized tests. We hypothesized that molecular features could provide a test to address this problem. We classified 403 biopsies by a reference standard based on microcirculation lesions and donor-specific HLA antibody, and used microarray analysis to develop a classifier that assigned each biopsy a score reflecting the probability of antibody-mediated rejection. The scores correlated with donor-specific antibody and histologic lesions: 42/45 biopsies with antibody-mediated rejection scores >0.5 had both donor-specific antibody and microcirculation lesions. Intermediate scores (0.2-0.5) were more ambiguous, but became more specific combined with donor-specific antibody. Compared to diagnoses based on histology-plus-donor-specific antibody, the scores had sensitivity 0.67; specificity 0.90. Donor-specific antibody improved the specificity to 0.97. The score correlated not only with diagnoses of individual pathologists but with the consensus among multiple pathologists. The classifier used transcripts expressed in endothelial cells (e.g. CDH13, DARC, ROBO4) and NK cells (e.g. CX3CR1, FGFBP2), as well as IFNG-inducible transcripts e.g. CXCL11. Thus the molecular phenotype of antibody-mediated rejection provides not only an objective test that predicts microcirculation lesions and donor-specific HLA antibody, but also offers mechanistic insights.

Project description:IntroductionThe use of noninvasive biomarkers may avoid the need for liver biopsy (LB) and could guide immunosuppression adjustment in liver transplantation (LT). The aims of this study were: to confirm the predictive and diagnostic capacity of plasmatic expression of miR-155-5p, miR-181a-5p, miR-122-5p and CXCL-10 for assessing T-cell mediated rejection (TCMR) risk; to develop a score based on a panel of noninvasive biomarkers to predict graft rejection risk and to validate this score in a separate cohort.MethodsA prospective, observational study was conducted with a cohort of 79 patients followed during the first year after LT. Plasma samples were collected at predetermined time points for the analysis of miRNAs and the CXCL-10. Patients with LFTs abnormalities were submitted to a LB to rule out rejection, assessing previous and concurrent expression of the biomarkers to evaluate their predictive and diagnostic ability. Information from 86 patients included in a previous study was collected and used as a validation cohort.ResultsTwenty-four rejection episodes were diagnosed in 22 patients. Plasmatic CXCL-10 concentration and the expression of the three miRNAs were significantly elevated prior to and at the moment of the diagnosis of rejection. We developed a logistic model for rejection prediction and diagnosis, which included CXCL-10, miR-155-5p and miR-181a-5p. The area under the ROC curve (AUROC) for rejection prediction was 0.975 (79.6% sensitivity, 99.1% specificity, 90,7% PPV; 97.7% NPV; 97.1% correctly classified) and 0.99 for diagnosis (87.5% sensitivity, 99.5% specificity, 91.3% PPV; 99.3% NPV; 98.9% correctly classified). In the validation cohort (n=86; 14 rejections), the same cut-off points were used obtaining AUROCs for rejection prediction and diagnosis of 0.89 and 0.92 respectively. In patients with graft dysfunction in both cohorts the score could discriminate those with rejection regarding other causes with an AUROC of 0.98 (97.3% sensitivity, 94.1%specificity).ConclusionThese results suggest that the clinical implementation of the monitoring of this noninvasive plasmatic score may allow the prediction and diagnosis of rejection and identify patients with graft dysfunction due to rejection, helping with a more efficient guide for immunosuppressive therapy adjustment. This finding warrants the development of prospective biomarker-guided clinical trials.

Dataset Information

A urine score for noninvasive accurate diagnosis and prediction of kidney transplant rejection.

Publications

A urine score for noninvasive accurate diagnosis and prediction of kidney transplant rejection.

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