A urine score for noninvasive accurate diagnosis and prediction of kidney transplant rejection.
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ABSTRACT:
SUBMITTER: Yang JYC
PROVIDER: S-EPMC8289390 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Monitoring allograft health is an important component of posttransplant therapy. Endomyocardial biopsy is the current gold standard for cardiac allograft monitoring but is an expensive and invasive procedure. Proof of principle of a universal, noninvasive diagnostic method based on high-throughput screening of circulating cell-free donor-derived DNA (cfdDNA) was recently demonstrated in a small retrospective cohort. We present the results of a prospective cohort study (65 patients, 565 samples) that tested the utility of cfdDNA in measuring acute rejection after heart transplantation. Circulating cell-free DNA was purified from plasma and sequenced (mean depth, 1.2 giga-base pairs) to quantify the fraction of cfdDNA. Through a comparison with endomyocardial biopsy results, we demonstrate that cfdDNA enables diagnosis of acute rejection after heart transplantation, with an area under the receiver operating characteristic curve of 0.83 and sensitivity and specificity that are comparable to the intrinsic performance of the biopsy itself. This noninvasive genome transplant dynamics approach is a powerful and informative method for routine monitoring of allograft health without incurring the risk, discomfort, and expense of an invasive biopsy.
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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.
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Project description:A Common Rejection Module (CRM) consisting of 11 genes expressed in allograft biopsies was previously reported to serve as a biomarker for acute rejection (AR), correlate with the extent of graft injury, and predict future allograft damage. We investigated the use of this gene panel on the urine cell pellet of kidney transplant patients. Urinary cell sediments collected from patients with biopsy-confirmed acute rejection, borderline AR (bAR), BK virus nephropathy (BKVN), and stable kidney grafts with normal protocol biopsies (STA) were analyzed for expression of these 11 genes using quantitative polymerase chain reaction (qPCR). We assessed these 11 CRM genes for their abundance, autocorrelation, and individual expression levels. Expression of 10/11 genes were elevated in AR when compared to STA. Psmb9 and Cxcl10could classify AR versus STA as accurately as the 11-gene model (sensitivity = 93.6%, specificity = 97.6%). A uCRM score, based on the geometric mean of the expression levels, could distinguish AR from STA with high accuracy (AUC = 0.9886) and correlated specifically with histologic measures of tubulitis and interstitial inflammation rather than tubular atrophy, glomerulosclerosis, intimal proliferation, tubular vacuolization or acute glomerulitis. This urine gene expression-based score may enable the non-invasive and quantitative monitoring of AR.
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Project description:It is challenging to monitor the health of transplanted organs, particularly with respect to rejection by the host immune system. Because transplanted organs have genomes that are distinct from the recipient's genome, we used high throughput shotgun sequencing to develop a universal noninvasive approach to monitoring organ health. We analyzed cell-free DNA circulating in the blood of heart transplant recipients and observed significantly increased levels of cell-free DNA from the donor genome at times when an endomyocardial biopsy independently established the presence of acute cellular rejection in these heart transplant recipients. Our results demonstrate that cell-free DNA can be used to detect an organ-specific signature that correlates with rejection, and this measurement can be made on any combination of donor and recipient. This noninvasive test holds promise for replacing the endomyocardial biopsy in heart transplant recipients and may be applicable to other solid organ transplants.
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Project description:Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unrealistic. Various biomarkers for diagnosing allograft rejection have been developed over the last two decades based on omics technologies to overcome these limitations. Omics technologies are based on a holistic view of the molecules that constitute an individual. They include genomics, transcriptomics, proteomics, and metabolomics. The omics approach has dramatically accelerated biomarker discovery and enhanced our understanding of multifactorial biological processes in the field of transplantation. However, clinical application of omics-based biomarkers is limited by several issues. First, no large-scale prospective randomized controlled trial has been conducted to compare omics-based biomarkers with traditional biomarkers for rejection. Second, given the variety and complexity of injuries that a kidney allograft may experience, it is likely that no single omics approach will suffice to predict rejection or outcome. Therefore, integrated methods using multiomics technologies are needed. Herein, we introduce omics technologies and review the latest literature on omics biomarkers predictive of allograft rejection in kidney transplant recipients.
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Project description:This SuperSeries is composed of the SubSeries listed below.
2016-10-18 | GSE88846 | GEO
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2018-04-25 | GSE106074 | GEO
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. All consenting renal transplant patients undergoing biopsies for cause as standard of care. 403 samples and 8 controls (nephrectomies). This dataset is part of the TransQST collection.
2013-02-13 | E-GEOD-36059 | biostudies-arrayexpress
Project description:In transplantation, there is a critical need for non-invasive biomarker platforms for monitoring immunologic rejection. We hypothesized that transplanted tissues release donor specific exosomes into recipient circulation/ bodily fluids, and that the quantitation and profiling of their intra-exosomal cargoes would constitute a novel biomarker platform for monitoring rejection. We tested this hypothesis in a human into mouse xenogeneic islet transplant model, and validated the concept in clinical settings of islet and renal transplantation. In the xenogeneic model, islet transplant exosomes in recipient blood were quantified over long-term follow-up using anti-human leukocyte antigen (HLA) antibody that is only expressed on human islets (p=1.6x10-14). Transplant islet exosomes were purified using anti-HLA antibody conjugated beads and their cargoes contained bona fide islet endocrine hormone markers insulin, glucagon, and somatostatin. Rejection led to significant decrease in transplant islet exosome signal (p=4x10-15), along with distinct changes in its microRNA and proteomic profiles prior to appearance of hyperglycemia. In the clinical settings of islet (n=5) and renal (n=5) transplantation, donor exosomes with respective tissue specificity for islet β cells and renal epithelial cells were reliably characterized in recipient plasma over follow-up (up to 5 years; p=0.0001). Collectively, these findings demonstrate the biomarker potential of transplant exosome characterization for providing a non-invasive window into the conditional state of the transplant tissue.
2016-10-18 | GSE88845 | GEO