Gene expression biomarkers for kidney transplant rejection - The entire landscape.
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ABSTRACT:
SUBMITTER: Friedewald J
PROVIDER: S-EPMC6491954 | biostudies-literature | 2019 Apr
REPOSITORIES: biostudies-literature
Publications
Gene expression biomarkers for kidney transplant rejection - The entire landscape.
Friedewald John J Abecassis Michael M Kurian Sunil S
EBioMedicine 20190322
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Project description:Kidney transplantation is the preferred treatment for end-stage renal failure, but the limited availability of donors and the risk of immune rejection pose significant challenges. Early detection of acute renal rejection is a critical step to increasing the lifespan of the transplanted kidney. Investigating the clinical, genetic, and histopathological markers correlated to acute renal rejection, as well as finding noninvasive markers for early detection, is urgently needed. It is also crucial to identify which markers are associated with different types of acute renal rejection to manage treatment effectively. This short review summarizes recent studies that investigated various markers, including genomics, histopathology, and clinical markers, to differentiate between different types of acute kidney rejection. Our review identifies the markers that can aid in the early detection of acute renal rejection, potentially leading to better treatment and prognosis for renal-transplant patients.
| S-EPMC10525551 | biostudies-literature
Project description:Zero-time biopsies are taken to determine the quality of the donor organ at the time of transplantation. Histological analyses alone have so far not been able to identify parameters that allow the prediction of subsequent rejection episodes or graft survival. This study investigated whether gene expression analyses of zero-time biopsies might support this prediction. Using a well-characterized cohort of 26 zero-time biopsies from renal transplant patients that include 4 living donor (LD) and 22 deceased donor (DD) biopsies that later developed no rejection (Ctrl, n = 7), delayed graft function (DGF, n = 4), cellular (T-cell mediated rejection; TCMR, n = 8), or antibody-mediated rejection (ABMR, n = 7), we analyzed gene expression profiles for different types of subsequent renal transplant complication. To this end, RNA was isolated from formalin-fixed, paraffin-embedded (FFPE) sections and gene expression profiles were quantified. Results were correlated with transplant data and B-cell, and plasma cell infiltration was assessed by immunofluorescence microscopy. Both principal component analysis and clustering analysis of gene expression data revealed marked separation between LDs and DDs. Differential expression analysis identified 185 significant differentially expressed genes (adjusted p < 0.05). The expression of 68% of these genes significantly correlated with cold ischemia time (CIT). Furthermore, immunoglobulins were differentially expressed in zero-time biopsies from transplants later developing rejection (TCMR + ABMR) compared to non-rejected (Ctrl + DGF) transplants. In addition, immunoglobulin expression did not correlate with CIT but was increased in transplants with previous acute renal failure (ARF). In conclusion, gene expression profiles in zero-time biopsies derived from LDs are markedly different from those of DDs. Pre-transplant ARF increased immunoglobulin expression, which might be involved in triggering later rejection events. However, these findings must be confirmed in larger cohorts and the role of early immunoglobulin upregulation in zero-biopsies needs further clarification.
| S-EPMC9005644 | biostudies-literature
Project description:Background and objectivesSubclinical acute rejection is associated with poor outcomes in kidney transplant recipients. As an alternative to surveillance biopsies, noninvasive screening has been established with a blood gene expression profile. Donor-derived cellfree DNA (cfDNA) has been used to detect rejection in patients with allograft dysfunction but not tested extensively in stable patients. We hypothesized that we could complement noninvasive diagnostic performance for subclinical rejection by combining a donor-derived cfDNA and a gene expression profile assay.Design, setting, participants, & measurementsWe performed a post hoc analysis of simultaneous blood gene expression profile and donor-derived cfDNA assays in 428 samples paired with surveillance biopsies from 208 subjects enrolled in an observational clinical trial (Clinical Trials in Organ Transplantation-08). Assay results were analyzed as binary variables, and then, their continuous scores were combined using logistic regression. The performance of each assay alone and in combination was compared.ResultsFor diagnosing subclinical rejection, the gene expression profile demonstrated a negative predictive value of 82%, a positive predictive value of 47%, a balanced accuracy of 64%, and an area under the receiver operating curve of 0.75. The donor-derived cfDNA assay showed similar negative predictive value (84%), positive predictive value (56%), balanced accuracy (68%), and area under the receiver operating curve (0.72). When both assays were negative, negative predictive value increased to 88%. When both assays were positive, positive predictive value increased to 81%. Combining assays using multivariable logistic regression, area under the receiver operating curve was 0.81, significantly higher than the gene expression profile (P<0.001) or donor-derived cfDNA alone (P=0.006). Notably, when cases were separated on the basis of rejection type, the gene expression profile was significantly better at detecting cellular rejection (area under the receiver operating curve, 0.80 versus 0.62; P=0.001), whereas the donor-derived cfDNA was significantly better at detecting antibody-mediated rejection (area under the receiver operating curve, 0.84 versus 0.71; P=0.003).ConclusionsA combination of blood-based biomarkers can improve detection and provide less invasive monitoring for subclinical rejection. In this study, the gene expression profile detected more cellular rejection, whereas donor-derived cfDNA detected more antibody-mediated rejection.
| S-EPMC8499014 | biostudies-literature
Project description:Acute renal allograft rejection is an important complication in kidney transplantation. Accurate diagnosis of rejection events is necessary for timely response and treatment. We illustrate the usefulness and biological relevance of selected multivariate approaches to detect rejection from genomic and proteomic signals. The data was used to study gene expression changes using whole genome microarray analysis of peripheral blood from subjects with acute rejection (n=20) and non-rejecting controls (n=20) to obtain insight into the molecular and biological causation of acute renal allograft rejection when combined with proteomics (iTRAQ) data for the same patients/time-points.
2014-04-26 | GSE46474 | GEO
Project description:There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.
| S-EPMC4439107 | biostudies-literature
Project description: Not available
| S-EPMC9727519 | biostudies-literature
Project description:Different types of kidney transplantations are performed worldwide, including biologically diverse donor/recipient combinations, which entail distinct patient/graft outcomes. Thus, proper immunological and non-immunological risk stratification should be considered, especially for patients included in interventional randomized clinical trials. This paper was prepared by a working group within the European Society for Organ Transplantation, which submitted a Broad Scientific Advice request to the European Medicines Agency (EMA) relating to clinical trial endpoints in kidney transplantation. After collaborative interactions, the EMA sent its final response in December 2020, highlighting the following: 1) transplantations performed between human leukocyte antigen (HLA)-identical donors and recipients carry significantly lower immunological risk than those from HLA-mismatched donors; 2) for the same allogeneic molecular HLA mismatch load, kidney grafts from living donors carry significantly lower immunological risk because they are better preserved and therefore less immunogenic than grafts from deceased donors; 3) single-antigen bead testing is the gold standard to establish the repertoire of serological sensitization and is used to define the presence of a recipient's circulating donor-specific antibodies (HLA-DSA); 4) molecular HLA mismatch analysis should help to further improve organ allocation compatibility and stratify immunological risk for primary alloimmune activation, but without consensus regarding which algorithm and cut-off to use it is difficult to integrate information into clinical practice/study design; 5) further clinical validation of other immune assays, such as those measuring anti-donor cellular memory (T/B cell ELISpot assays) and non-HLA-DSA, is needed; 6) routine clinical tests that reliably measure innate immune alloreactivity are lacking.
| S-EPMC9163827 | biostudies-literature
Project description:Despite advances in post-transplant management, the long-term survival rate of kidney grafts and patients has not improved as approximately forty percent of transplants fails within ten years after transplantation. Both immunologic and non-immunologic factors contribute to late allograft loss. Chronic kidney transplant rejection (CKTR) is often clinically silent yet progressive allogeneic immune process that leads to cumulative graft injury, deterioration of graft function. Chronic active T cell mediated rejection (TCMR) and chronic active antibody-mediated rejection (ABMR) are classified as two principal subtypes of CKTR. While significant improvements have been made towards a better understanding of cellular and molecular mechanisms and diagnostic classifications of CKTR, lack of early detection, differential diagnosis and effective therapies continue to pose major challenges for long-term management. Recent development of high throughput cellular and molecular biotechnologies has allowed rapid development of new biomarkers associated with chronic renal injury, which not only provide insight into pathogenesis of chronic rejection but also allow for early detection. In parallel, several novel therapeutic strategies have emerged which may hold great promise for improvement of long-term graft and patient survival. With a brief overview of current understanding of pathogenesis, standard diagnosis and challenges in the context of CKTR, this mini-review aims to provide updates and insights into the latest development of promising novel biomarkers for diagnosis and novel therapeutic interventions to prevent and treat CKTR.
| S-EPMC8173220 | biostudies-literature
Project description:Kidney transplant patients require life-long surveillance to detect allograft rejection. Repeated biopsy, albeit the clinical gold standard, is an invasive procedure with the risk of complications and comparatively high cost. Conversely, serum creatinine or urinary proteins are noninvasive alternatives but are late markers with low specificity. We report a urine-based platform to detect kidney transplant rejection. Termed iKEA (integrated kidney exosome analysis), the approach detects extracellular vesicles (EVs) released by immune cells into urine; we reasoned that T cells, attacking kidney allografts, would shed EVs, which in turn can be used as a surrogate marker for inflammation. We optimized iKEA to detect T-cell-derived EVs and implemented a portable sensing system. When applied to clinical urine samples, iKEA revealed high level of CD3-positive EVs in kidney rejection patients and achieved high detection accuracy (91.1%). Fast, noninvasive, and cost-effective, iKEA could offer new opportunities in managing transplant recipients, perhaps even in a home setting.
| S-EPMC6237084 | biostudies-literature
Project description:BackgroundNoninvasive biomarkers distinguishing early immune activation before acute rejection (AR) could more objectively inform immunosuppression management in liver transplant recipients (LTRs). We previously reported a genomic profile distinguishing LTR with AR versus stable graft function. This current study includes key phenotypes with other causes of graft dysfunction and uses a novel random forest approach to augment the specificity of predicting and diagnosing AR.MethodsGene expression results in LTRs with AR versus non-AR (combination of other causes of graft dysfunction and normal function) were analyzed from single and multicenter cohorts. A 70:30 approach (61 ARs; 162 non-ARs) was used for training and testing sets. Microarray data were normalized using a LT-specific vector.ResultsRandom forest modeling on the training set generated a 59-probe classifier distinguishing AR versus non-AR (area under the curve 0.83; accuracy 0.78, sensitivity 0.70, specificity 0.81, positive predictive value 0.54, negative predictive value [NPV] 0.89; F-score 0.61). Using a locked threshold, the classifier performed well on the testing set (accuracy 0.72, sensitivity 0.67, specificity 0.73, positive predictive value 0.48, NPV 0.86; F-score 0.56). Probability scores increased in samples preceding AR versus non-AR, when liver function tests were normal, and decreased following AR treatment (P < 0.001). Ingenuity pathway analysis of the genes revealed a high percentage related to immune responses and liver injury.ConclusionsWe have developed a blood-based biologically relevant biomarker that can be detected before AR-associated graft injury distinct from LTR never developing AR. Given its high NPV ("rule out AR"), the biomarker has the potential to inform precision-guided immunosuppression minimization in LTRs.
| S-EPMC9301991 | biostudies-literature