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      The kSORT Assay to Detect Renal Transplant Patients at High Risk for Acute Rejection: Results of the Multicenter AART Study

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          Abstract

          Minnie Sarwal and colleagues developed a gene expression assay using peripheral blood samples to detect patients with renal transplant at high risk for acute rejection.

          Please see later in the article for the Editors' Summary

          Abstract

          Background

          Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR.

          Methods and Findings

          We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART) study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set—the Kidney Solid Organ Response Test (kSORT)—was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI 0.91–0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88–1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86–0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials.

          Conclusions

          The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants.

          Please see later in the article for the Editors' Summary

          Editors' Summary

          Background

          Throughout life, the kidneys filter waste products (from the normal breakdown of tissues and food) and excess water from the blood to make urine. If the kidneys stop working for any reason, the rate at which the blood is filtered decreases, and dangerous amounts of creatinine and other waste products build up in the blood. The kidneys can fail suddenly (acute kidney failure) because of injury or poisoning, but usually failing kidneys stop working gradually over many years (chronic kidney disease). Chronic kidney disease is very common, especially in people who have high blood pressure or diabetes and in elderly people. In the UK, for example, about 20% of people aged 65–74 years have some degree of chronic kidney disease. People whose kidneys fail completely (end-stage kidney disease) need regular dialysis (hemodialysis, in which blood is filtered by an external machine, or peritoneal dialysis, which uses blood vessels in the abdominal lining to do the work of the kidneys) or a renal transplant (the surgical transfer of a healthy kidney from another person into the patient's body) to keep them alive.

          Why Was This Study Done?

          Our immune system protects us from pathogens (disease-causing organisms) by recognizing specific molecules (antigens) on the invader's surface as foreign and initiating a sequence of events that kills the invader. Unfortunately, the immune system sometimes recognizes kidney transplants as foreign and triggers transplant rejection. The chances of rejection can be minimized by “matching” the antigens on the donated kidney to those on the tissues of the kidney recipient and by giving the recipient immunosuppressive drugs. However, acute rejection (rejection during the first year after transplantation) affects about 20% of kidney transplants. Acute rejection needs to be detected quickly and treated with a short course of more powerful immunosuppressants because it increases the risk of transplant failure. The current “gold standard” method for detecting acute rejection if the level of creatinine in the patient's blood begins to rise is to surgically remove a small piece (biopsy) of the transplanted kidney for analysis. However, other conditions can change creatinine levels, acute rejection can occur without creatinine levels changing (subclinical acute rejection), and biopsies are invasive. Here, the researchers develop a noninvasive test for acute kidney rejection called the Kidney Solid Organ Response Test (kSORT) based on gene expression levels in the blood.

          What Did the Researchers Do and Find?

          For the Assessment of Acute Rejection in Renal Transplantation (AART) study, the researchers used an assay called quantitative polymerase chain reaction (QPCR) to measure the expression of 43 genes whose expression levels change during acute kidney rejection in blood samples collected from patients who had had a kidney transplant. Using a training set of 143 samples and statistical analyses, the researchers identified a 17-gene set (kSORT) that discriminated between patients with and without acute rejection detected by kidney biopsy. The 17-gene set correctly identified 39 of the samples taken from 47 patients with acute rejection as being from patients with acute rejection, and 87 of 96 samples from patients without acute rejection as being from patients without acute rejection. The researchers validated the gene set using 124 independent samples. Then, using 191 serial samples, they showed that the gene set was able to predict acute rejection up to three months before detection by biopsy. Finally, the researchers used 100 blood samples to develop an algorithm (a step-wise calculation) to classify patients as being at high or low risk of acute rejection.

          What Do These Findings Mean?

          These findings describe the early development of a noninvasive tool (kSORT) that might, eventually, help clinicians identify patients at risk of acute rejection after kidney transplantation. kSORT needs to be tested in more patients before being used clinically, however, to validate its predictive ability, particularly given that the current gold standard test against which it was compared (biopsy) is far from perfect. An additional limitation of kSORT is that it did not discriminate between cell-mediated and antibody-mediated immune rejection. These two types of immune rejection are treated in different ways, so clinicians ideally need a test for acute rejection that indicates which form of immune rejection is involved. The authors are conducting a follow-up study to help determine whether kSORT can be used in clinical practice to identify acute rejection and to identify which patients are at greatest risk of transplant rejection and may require biopsy.

          Additional Information

          Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001759.

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          Most cited references30

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            The natural history of chronic allograft nephropathy.

            With improved immunosuppression and early allograft survival, chronic allograft nephropathy has become the dominant cause of kidney-transplant failure. We evaluated the natural history of chronic allograft nephropathy in a prospective study of 120 recipients with type 1 diabetes, all but 1 of whom had received kidney-pancreas transplants. We obtained 961 kidney-transplant-biopsy specimens taken regularly from the time of transplantation to 10 years thereafter. Two distinctive phases of injury were evident as chronic allograft nephropathy evolved. An initial phase of early tubulointerstitial damage from ischemic injury (P<0.05), prior severe rejection (P<0.01), and subclinical rejection (P<0.01) predicted mild disease by one year, which was present in 94.2 percent of patients. Early subclinical rejection was common (affecting 45.7 percent of biopsy specimens at three months), and the risk was increased by the occurrence of a prior episode of severe rejection and reduced by tacrolimus and mycophenolate therapy (both P<0.05) and gradually abated after one year. Both subclinical rejection and chronic rejection were associated with increased tubulointerstitial damage (P<0.01). Beyond one year, a later phase of chronic allograft nephropathy was characterized by microvascular and glomerular injury. Chronic rejection (defined as persistent subclinical rejection for two years or longer) was uncommon (5.8 percent). Progressive high-grade arteriolar hyalinosis with luminal narrowing, increasing glomerulosclerosis, and additional tubulointerstitial damage was accompanied by the use of calcineurin inhibitors. Nephrotoxicity, implicated in late ongoing injury, was almost universal at 10 years, even in grafts with excellent early histologic findings. By 10 years, severe chronic allograft nephropathy was present in 58.4 percent of patients, with sclerosis in 37.3 percent of glomeruli. Tubulointerstitial and glomerular damage, once established, was irreversible, resulting in declining renal function and graft failure. Chronic allograft nephropathy represents cumulative and incremental damage to nephrons from time-dependent immunologic and nonimmunologic causes. Copyright 2003 Massachusetts Medical Society
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              Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling.

              The causes and clinical course of acute rejection vary, and it is not possible to predict graft outcome reliably on the basis of available clinical, pathological, and genetic markers. We hypothesized that previously unrecognized molecular heterogeneity might underlie some of the variability in the clinical course of acute renal allograft rejection and in its response to treatment. We used DNA microarrays in a systematic study of gene-expression patterns in biopsy samples from normal and dysfunctional renal allografts. A combination of exploratory and supervised bioinformatic methods was used to analyze these profiles. We found consistent differences among the gene-expression patterns associated with acute rejection, nephrotoxic effects of drugs, chronic allograft nephropathy, and normal kidneys. The gene-expression patterns associated with acute rejection suggested at least three possible distinct subtypes of acute rejection that, although indistinguishable by light microscopy, were marked by differences in immune activation and cellular proliferation. Since the gene-expression patterns pointed to substantial variation in the composition of immune infiltrates, we used immunohistochemical staining to define these subtypes further. This analysis revealed a striking association between dense CD20+ B-cell infiltrates and both clinical glucocorticoid resistance (P=0.01) and graft loss (P<0.001). Systematic analysis of gene-expression patterns provides a window on the biology and pathogenesis of renal allograft rejection. Biopsy samples from patients with acute rejection that are indistinguishable on conventional histologic analysis reveal extensive differences in gene expression, which are associated with differences in immunologic and cellular features and clinical course. The presence of dense clusters of B cells in a biopsy sample was strongly associated with severe graft rejection, suggesting a pivotal role of infiltrating B cells in acute rejection. Copyright 2003 Massachusetts Medical Society
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                PLoS
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                1549-1277
                1549-1676
                November 2014
                11 November 2014
                : 11
                : 11
                : e1001759
                Affiliations
                [1 ]Department of Surgery, University of California San Francisco, San Francisco, California, United States of America
                [2 ]Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
                [3 ]California Pacific Medical Center, San Francisco, California, United States of America
                [4 ]Renal Transplant Unit, Bellvitge University Hospital, Barcelona, Spain
                [5 ]Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
                [6 ]Immunogenetics Center, University of California Los Angeles, Los Angeles, California, United States of America
                [7 ]Department of Surgery, Emory University, Atlanta, Georgia, United States of America
                [8 ]Laboratorio de Investigacion en Nefrologia, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
                [9 ]Stanford University, Stanford, California, United States of America
                Istituto Mario Negri, Italy
                Author notes

                MS is Chair of the SAB and Founder of Organ-I and Consultant for Immucor, Bristol Meyers Squibb, UCB, ISIS, Genentech; SR was a Consultant for Organ-I; TS and NS are Consultants for Organ-I, Immucor; FV has research grants with Astellas Pharma, Bristol Myers Squibb, Alexion, Pfizer, Novartis, Genentech.

                Conceived and designed the experiments: MS SR TS. Performed the experiments: SH HD TS SR NS MS. Analyzed the data: SR NS TS MS. Contributed reagents/materials/analysis tools: DM AZ AG JC CM RP OB MM FV NA OS RS AK ER MS NS. Wrote the first draft of the manuscript: SR MS NS TS. Wrote the paper: SR MS TS NS OB ER AK DM RS. ICMJE criteria for authorship read and met: SR TS NS SH HD DM AZ AG JC CM RP OB MM FV NA OS RS AK ER MS. Agree with manuscript results and conclusions: SR TS NS SH HD DM AZ AG JC CM RP OB MM FV NA OS RS AK ER MS. Enrolled patients: DM RP OB MM FV OS RS AK ER MS.

                [¤a]

                Current address: Stanford University, Stanford, California, United States of America

                [¤b]

                Current address: Department of Surgery, Duke University, Durham, North Carolina, United States of America

                Article
                PMEDICINE-D-14-00316
                10.1371/journal.pmed.1001759
                4227654
                25386950
                f9a70143-6995-4250-b3e2-c5c3cc3dfaa5
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 January 2014
                : 10 October 2014
                Page count
                Pages: 15
                Funding
                The study was funded by the NIAID U01AI077821 ( http://www.niaid.nih.gov), Mexican Federal Funds for Research (Ssa.746), NIH R01 AI042819 ( http://grants.nih.gov), Spanish national public grant (PI13/01263), and a European Commission grant within the BIODRIM Consortium (12CEE014 Bio-Drim). No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Genome Expression Analysis
                Genetics
                Genomics
                Computer and Information Sciences
                Medicine and Health Sciences
                Diagnostic Medicine
                Nephrology
                Surgical and Invasive Medical Procedures
                Transplantation
                Organ Transplantation
                Renal Transplantation
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.

                Medicine
                Medicine

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