The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study

Blood Gene Signature as a Biomarker for Subclinical Kidney Allograft Rejection: Where Are We?

The observation decades ago that inflammatory injuries because of an alloimmune response might be present even in the absence of concomitant clinical impairment in allograft function conduced to the later definition of subclinical rejection. Many studies have investigated the different subclinical rejections defined according to the Banff classification (subclinical T cell-mediated rejection and antibody-mediated rejection), overall concluding that these episodes worsened long-term allograft function and survival. These observations led several transplant teams to perform systematic protocolar biopsies to anticipate treatment of rejection episodes and possibly prevent allograft loss. Paradoxically, the invasive characteristics and associated logistics of such procedures paved the way to investigate noninvasive biomarkers (urine and blood) of subclinical rejection. Among them, several research teams proposed a blood gene signature developed from cohort studies, most of which achieved excellent predictive values for the occurrence of subclinical rejection, mainly antibody-mediated rejection. Interestingly, although all identified genes relate to immune subsets and pathways involved in rejection pathophysiology, very few transcripts are shared among these sets of genes, highlighting the heterogenicity of such episodes and the difficult but mandatory need for external validation of such tools. Beyond this, their application and value in clinical practice remain to be definitively demonstrated in both biopsy avoidance and prevention of clinical rejection episodes. Their combination with other biomarkers, either epidemiological or biological, could contribute to a more accurate picture of a patient's risk of rejection and guide clinicians in the follow-up of kidney transplant recipients.

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood

INTRODUCTION

We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood.

MATERIALS AND METHODS

We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47).

RESULTS

A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%.

CONCLUSION

A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

An autophagy-associated diagnostic signature based on peripheral blood for antibody-mediated rejection in renal transplantation

BACKGROUND

Antibody-mediated rejection (ABMR) emerged as a major cause of graft loss in renal transplantation. Needle biopsy is the gold standard for diagnosis of ABMR in renal allografts. Thus, noninvasive diagnosis methods of ABMR with high accuracy are urgently needed to prevent unnecessary biopsies.

METHODS

We collected peripheral blood transcriptome data from two independent renal transplantation cohorts with patients with ABMR, stable well-functioning transplants (STA), and T-cell mediated rejection (TCMR). Differentially expressed genes (DEGs) were identified by comparing the ABMR group with the STA group. In addition, functional enrichment analysis and gene set enrichment analysis were performed to seek new key underlying mechanisms in ABMR. Subsequently, we utilized a Boruta algorithm and least absolute shrinkage and selection operator logistic algorithm to establish a diagnostic model which was then evaluated and validated in an independent cohort.

RESULTS

According to functional enrichment analysis, autophagy was found to be the primary upregulated biological process in ABMR. Based on algorithms, three autophagy-associated genes, ubiquitin specific peptidase 33 (USP33), Ras homolog mTORC1 binding (RHEB), and ABL proto-oncogene 2 (ABL2), were selected to establish the diagnostic model in the training cohort. This autophagy-related gene model possessed good diagnostic value in distinguishing ABMR from STA blood samples in the training cohort (AUC = 0.907) and in the validation cohort (AUC = 0.972). In addition, this model also showed good discernibility in distinguishing ABMR from TCMR in the training and validation cohorts (AUCs = 0.908 and 0.833).

CONCLUSION

We identified and validated an autophagy-associated diagnostic model with high accuracy for renal transplant patients with ABMR. Our study provided a new potential test for the non-invasive diagnosis of ABMR in clinical practice and highlighted the importance of autophagy in ABMR.

Heart transplantation and biomarkers: a review about their usefulness in clinical practice

Advanced heart failure (AdvHF) can only be treated definitively by heart transplantation (HTx), yet problems such right ventricle dysfunction (RVD), rejection, cardiac allograft vasculopathy (CAV), and primary graft dysfunction (PGD) are linked to a poor prognosis. As a result, numerous biomarkers have been investigated in an effort to identify and prevent certain diseases sooner. We looked at both established biomarkers, such as NT-proBNP, hs-troponins, and pro-inflammatory cytokines, and newer ones, such as extracellular vesicles (EVs), donor specific antibodies (DSA), gene expression profile (GEP), donor-derived cell free DNA (dd-cfDNA), microRNA (miRNA), and soluble suppression of tumorigenicity 2 (sST2). These biomarkers are typically linked to complications from HTX. We also highlight the relationships between each biomarker and one or more problems, as well as their applicability in routine clinical practice.

European Society of Organ Transplantation Consensus Statement on Testing for Non-Invasive Diagnosis of Kidney Allograft Rejection

To address the need for improved biomarkers for kidney transplant rejection, European Society of Organ Transplantation (ESOT) convened a dedicated working group comprised of experts in kidney transplant biomarkers to review literature pertaining to clinical and subclinical acute rejection to develop guidelines in the screening and diagnosis of acute rejection that were subsequently discussed and voted on during the Consensus Conference that took place in person in Prague. The findings and recommendations of the Working Group on Molecular Biomarkers of Kidney Transplant Rejection are presented in this article.

Immune monitoring of allograft status in kidney transplant recipients

Kidney transplant patients require careful management of immunosuppression to avoid rejection while minimizing the risk of infection and malignancy for the best long-term outcome. The gold standard for monitoring allograft status and immunosuppression adequacy is a kidney biopsy, but this is invasive and costly. Conventional methods of allograft monitoring, such as serum creatinine level, are non-specific. Although they alert physicians to the need to evaluate graft dysfunction, by the time there is a clinical abnormality, allograft damage may have already occurred. The development of novel and non-invasive methods of evaluating allograft status are important to improving graft outcomes. This review summarizes the available conventional and novel methods for monitoring allograft status after kidney transplant. Novel and less invasive methods include gene expression, cell-free DNA, urinary biomarkers, and the use of artificial intelligence. The optimal method to manage patients after kidney transplant is still being investigated. The development of less invasive methods to assess allograft function has the potential to improve patient outcomes and allow for a more personalized approach to immunosuppression management.

Performance and Advancement of the Kidney Solid Organ Response Test

BACKGROUND

The kidney solid organ response test (kSORT) has been investigated for the prediction of acute rejection in kidney transplant recipients with conflicting results. We aimed to investigate if the kSORT assay score is associated with rejection or immune quiescence.

METHODS

The blinded association between rejection and kSORT > 9 were investigated. Optimization of kSORT prediction was evaluated after unblinding to determine the optimal prediction cutoff value of kSORT score. Additionally, the predictive capability of the kSORT gene set was assessed using blinded normalized gene expression data from microarray (Affymetrix) and qPCR assays.

RESULTS

Of the 95 blood samples analyzed, 18 patients had blood samples before transplant, 77 patients after transplant and 71 had clinically indicated biopsies of which 15 biopsies showed acute rejection and 16 showed chronic active antibody-mediated rejection. When 31 patients with rejection were compared to the remaining 64 patients, positive predictive value (PPV) was 54.29% and negative predictive value (NPV) was 75% when stratified using a kSORT score > 9, and PPV was 57.89% and NPV was 78.95% when stratified using a kSORT score > 5. Using the kSORT assay for detection of rejection showed an area under the curve value of 0.71. Microarray data improved prediction accuracy with PPV of 53% and NPV of 84% compared to qPCR results (PPV and NPV were 36% and 66%), respectively.

CONCLUSIONS

The kSORT assay has the potential to be used as a predictive tool for active rejection and/or immune quiescence, but additional studies will be useful in improving and refining the kSORT assay, in particular the prediction algorithm.

Rejection markers in kidney transplantation: do new technologies help children?

Recent insights in allorecognition and graft rejection mechanisms revealed a more complex picture than originally considered, involving multiple pathways of both adaptive and innate immune response, supplied by efficient inflammatory synergies. Current pillars of transplant monitoring are serum creatinine, proteinuria, and drug blood levels, which are considered as traditional markers, due to consolidated experience, low cost, and widespread availability. The most diffuse immunological biomarkers are donor-specific antibodies, which are included in routine post-transplant monitoring in many centers, although with some reproducibility issues and interpretation difficulties. Confirmed abnormalities in these traditional biomarkers raise the suspicion for rejection and guide the indication for graft biopsy, which is still considered the gold standard for rejection monitoring. Rapidly evolving new "omic" technologies have led to the identification of several novel biomarkers, which may change the landscape of transplant monitoring should their potential be confirmed. Among them, urinary chemokines and measurement of cell-free DNA of donor origin are perhaps the most promising. However, at the moment, these approaches remain highly expensive and cost-prohibitive in most settings, with limited clinical applicability; approachable costs upon technology investments would speed their integration. In addition, transcriptomics, metabolomics, proteomics, and the study of blood and urinary extracellular vesicles have the potential for early identification of subclinical rejection with high sensitivity and specificity, good reproducibility, and for gaining predictive value in an affordable cost setting. In the near future, information derived from these new biomarkers is expected to integrate traditional tools in routine use, allowing identification of rejection prior to clinical manifestations and timely therapeutic intervention. This review will discuss traditional, novel, and invasive and non-invasive biomarkers, underlining their strengths, limitations, and present or future applications in children.

Molecular immune monitoring in kidney transplant rejection: a state-of-the-art review

Although current regimens of immunosuppressive drugs are effective in renal transplant recipients, long-term renal allograft outcomes remain suboptimal. For many years, the diagnosis of renal allograft rejection and of several causes of renal allograft dysfunction, such as chronic subclinical inflammation and infection, was mostly based on renal allograft biopsy, which is not only invasive but also possibly performed too late for proper management. In addition, certain allograft dysfunctions are difficult to differentiate from renal histology due to their similar pathogenesis and immune responses. As such, non-invasive assays and biomarkers may be more beneficial than conventional renal biopsy for enhancing graft survival and optimizing immunosuppressive drug regimens during long-term care. This paper discusses recent biomarker candidates, including donor-derived cell-free DNA, transcriptomics, microRNAs, exosomes (or other extracellular vesicles), urine chemokines, and nucleosomes, that show high potential for clinical use in determining the prognosis of long-term outcomes of kidney transplantation, along with their limitations.

Multiple abnormal peripheral blood gene expression assay results are correlated with subsequent graft loss after kidney transplantation

BACKGROUND

The aim of this study was to correlate peripheral blood gene expression profile (GEP) results during the first post-transplant year with outcomes after kidney transplantation.

METHODS

We conducted a prospective, multicenter observational study of obtaining peripheral blood at five timepoints during the first post-transplant year to perform a GEP assay. The cohort was stratified based on the pattern of the peripheral blood GEP results: Tx-all GEP results normal, 1 Not-TX had one GEP result abnormal and >1 Not-TX two or more abnormal GEP results. We correlated the GEP results with outcomes after transplantation.

RESULTS

We enrolled 240 kidney transplant recipients. The cohort was stratified into the three groups: TX n = 117 (47%), 1 Not-TX n = 59 (25%) and >1 Not-TX n = 64 (27%). Compared to the TX group, the >1 Not-TX group had lower eGFR (p < .001) and more chronic changes on 1-year surveillance biopsy (p = .007). Death censored graft survival showed inferior graft survival in the >1 Not-TX group (p < .001) but not in the 1 Not-TX group. All graft losses in the >1 Not-TX group occurred after 1-year post-transplant.

CONCLUSIONS

We conclude that a pattern of persistently Not-TX GEP assay correlates with inferior graft survival.

Contemporary Biomarkers for Renal Transplantation: A Narrative Overview

Renal transplantation (RT) is the preferred treatment for end-stage renal disease. However, clinical challenges persist, i.e., early detection of graft dysfunction, timely identification of rejection episodes, personalization of immunosuppressive therapy, and prediction of long-term graft survival. Biomarkers have emerged as valuable tools to address these challenges and revolutionize RT patient care. Our review synthesizes the existing scientific literature to highlight promising biomarkers, their biological characteristics, and their potential roles in enhancing clinical decision-making and patient outcomes. Emerging non-invasive biomarkers seemingly provide valuable insights into the immunopathology of nephron injury and allograft rejection. Moreover, we analyzed biomarkers with intra-nephron specificities, i.e., glomerular vs. tubular (proximal vs. distal), which can localize an injury in different nephron areas. Additionally, this paper provides a comprehensive analysis of the potential clinical applications of biomarkers in the prediction, detection, differential diagnosis and assessment of post-RT non-surgical allograft complications. Lastly, we focus on the pursuit of immune tolerance biomarkers, which aims to reclassify transplant recipients based on immune risk thresholds, guide personalized immunosuppression strategies, and ultimately identify patients for whom immunosuppression may safely be reduced. Further research, validation, standardization, and prospective studies are necessary to fully harness the clinical utility of RT biomarkers and guide the development of targeted therapies.

Multicenter Validation of a Urine CXCL10 Assay for Noninvasive Monitoring of Renal Transplants

BACKGROUND

Urine CXCL10 (C-X-C motif chemokine ligand 10, interferon gamma-induced protein 10 [IP10]) outperforms standard-of-care monitoring for detecting subclinical and early clinical T-cell-mediated rejection (TCMR) and may advance TCMR therapy development through biomarker-enriched trials. The goal was to perform an international multicenter validation of a CXCL10 bead-based immunoassay (Luminex) for transplant surveillance and compare with an electrochemiluminescence-based (Meso Scale Discovery [MSD]) assay used in transplant trials.

METHODS

Four laboratories participated in the Luminex assay development and evaluation. Urine CXCL10 was measured by Luminex and MSD in 2 independent adult kidney transplant trial cohorts (Basel and TMCT04). In an independent test and validation set, a linear mixed-effects model to predict (log 10 -transformed) MSD CXCL10 from Luminex CXCL10 was developed to determine the conversion between assays. Net reclassification was determined after mathematical conversion.

RESULTS

The Luminex assay was precise, with an intra- and interassay coefficient of variation 8.1% and 9.3%; showed modest agreement between 4 laboratories (R 0.96 to 0.99, P < 0.001); and correlated with known CXCL10 in a single- (n = 100 urines, R 0.94 to 0.98, P < 0.001) and multicenter cohort (n = 468 urines, R 0.92, P < 0.001) but the 2 assays were not equivalent by Passing-Bablok regression. Linear mixed-effects modeling demonstrated an intercept of -0.490 and coefficient of 1.028, showing Luminex CXCL10 are slightly higher than MSD CXCL10, but the agreement is close to 1.0. After conversion of the biopsy thresholds, the decision to biopsy would be changed for only 6% (5/85) patients showing acceptable reclassification.

CONCLUSIONS

These data demonstrate this urine CXCL10 Luminex immunoassay is robust, reproducible, and accurate, indicating it can be readily translated into clinical HLA laboratories for serial posttransplant surveillance.

The IMBG Test for Evaluating the Pharmacodynamic Response to Immunosuppressive Therapy in Kidney Transplant Patients: Current Evidence and Future Applications

Immunosuppressive drugs are widely used to prevent rejection after kidney transplantation. However, the pharmacological response to a given immunosuppressant can vary markedly between individuals, with some showing poor treatment responses and/or experiencing serious side effects. There is an unmet need for diagnostic tools that allow clinicians to individually tailor immunosuppressive therapy to a patient’s immunological profile. The Immunobiogram (IMBG) is a novel blood-based in vitro diagnostic test that provides a pharmacodynamic readout of the immune response of individual patients to a range of immunosuppressants commonly used in kidney transplant recipients. Here, we discuss the current approaches used to measure the pharmacodynamic responses of individual patients to specific immunosuppressive drugs in vitro, which can then be correlated with patient’s clinical outcomes. We also describe the procedure of the IMBG assay, and summarize the results obtained using the IMBG in different kidney transplant populations. Finally, we outline future directions and other novel applications of the IMBG, both in kidney transplant patients and other autoimmune diseases.

Diagnostic Potential of Minimally Invasive Biomarkers: A Biopsy-centered Viewpoint From the Banff Minimally Invasive Diagnostics Working Group

With recent advances and commercial implementation of minimally invasive biomarkers in kidney transplantation, new strategies for the surveillance of allograft health are emerging. Blood and urine-based biomarkers can be used to detect the presence of rejection, but their applicability as diagnostic tests has not been studied. A Banff working group was recently formed to consider the potential of minimally invasive biomarkers for integration into the Banff classification for kidney allograft pathology. We review the existing data on donor-derived cell-free DNA, blood and urine transcriptomics, urinary protein chemokines, and next-generation diagnostics and conclude that the available data do not support their use as stand-alone diagnostic tests at this point. Future studies assessing their ability to distinguish complex phenotypes, differentiate T cell-mediated rejection from antibody-mediated rejection, and function as an adjunct to histology are needed to elevate these minimally invasive biomarkers from surveillance tests to diagnostic tests.

Progress in kidney transplantation: The role for systems immunology

The development of systems biology represents an immense breakthrough in our ability to perform translational research and deliver personalized and precision medicine. A multidisciplinary approach in combination with use of novel techniques allows for the extraction and analysis of vast quantities of data even from the volume and source limited samples that can be obtained from human subjects. Continued advances in microfluidics, scalability and affordability of sequencing technologies, and development of data analysis tools have made the application of a multi-omics, or systems, approach more accessible for use outside of specialized centers. The study of alloimmune and protective immune responses after solid organ transplant offers innumerable opportunities for a multi-omics approach, however, transplant immunology labs are only just beginning to adopt the systems methodology. In this review, we focus on advances in biological techniques and how they are improving our understanding of the immune system and its interactions, highlighting potential applications in transplant immunology. First, we describe the techniques that are available, with emphasis on major advances that allow for increased scalability. Then, we review initial applications in the field of transplantation with a focus on topics that are nearing clinical integration. Finally, we examine major barriers to adapting these methods and discuss potential future developments.

STXBP3 and GOT2 predict immunological activity in acute allograft rejection

Background

Acute allograft rejection (AR) following renal transplantation contributes to chronic rejection and allograft dysfunction. The current diagnosis of AR remains dependent on renal allograft biopsy which cannot immediately detect renal allograft injury in the presence of AR. In this study, sensitive biomarkers for AR diagnosis were investigated and developed to protect renal function.

Methods

We analyzed pre- and postoperative data from five databases combined with our own data to identify the key differently expressed genes (DEGs). Furthermore, we performed a bioinformatics analysis to determine the immune characteristics of DEGs. The expression of key DEGs was further confirmed using the real-time quantitative PCR (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), and immunohistochemical (IHC) staining in patients with AR. ROC curves analysis was used to estimate the performance of key DEGs in the early diagnosis of AR.

Results

We identified glutamic-oxaloacetic transaminase 2 (GOT2) and syntaxin binding protein 3 (STXBP3) as key DEGs. The higher expression of STXBP3 and GOT2 in patients with AR was confirmed using RT-qPCR, ELISA, and IHC staining. ROC curve analysis also showed favorable values of STXBP3 and GOT2 for the diagnosis of early stage AR.

Conclusions

STXBP3 and GOT2 could reflect the immunological status of patients with AR and have strong potential for the diagnosis of early-stage AR.

The Immunobiogram, a novel in vitro diagnostic test to measure the pharmacodynamic response to immunosuppressive therapy in kidney transplant patients

BACKGROUND

Diagnostic tools to measure the response to individual immunosuppressive drugs for transplant patients are currently lacking. We previously developed the blood-based Immunobiogram bioassay for in-vitro characterization of the pharmacodynamic response of patients' own immune cells to a range of immunosuppressants. We used Immunobiogram to examine the association between patients' sensitivity to their prescribed immunosuppressants and clinical outcome.

METHODS

We conducted an international, multicenter, observational study in a kidney transplant population undergoing maintenance immunosuppressive therapy. Patients were selected by clinical course poor [PCC] N = 53 (with renal dysfunction, and rejection signs in biopsy or/and an increase in DSA strength in last 12 months) versus good [GCC] N = 50 (with stable renal function and treatment, no rejection and no DSA titers). Immunobiogram dose-response curve parameters were compared between both subgroups in patients treated with mycophenolate, tacrolimus, corticosteroids, cyclosporine A or everolimus. Parameters for which significant inter-group differences were observed were further analyzed by univariate and subsequent multivariate logistic regression.

RESULTS

Clinical outcome was associated with following parameters: area over the curve (AOC) and 25% (ID25) and 50% (ID50) inhibitory response in mycophenolate, tacrolimus, and corticosteroid-treated subgroups, respectively. These statistically significant associations persisted in mycophenolate (OR 0.003, CI95% <0.001-0.258; p = 0.01) and tacrolimus (OR < 0.0001, CI95% <0.00001-0.202; p = 0.016) subgroups after adjusting for concomitant corticosteroid treatment, and in corticosteroid subgroup after adjusting for concomitant mycophenolate or tacrolimus treatment (OR 0.003; CI95% <0.0001-0.499; p = 0.026).

CONCLUSIONS

Our results highlight the potential of Immunobiogram as a tool to test the pharmacodynamic response to individual immunosuppressive drugs.

T Cells With Activated STAT4 Drive the High-Risk Rejection State to Renal Allograft Failure After Kidney Transplantation

In kidney transplantation, deteriorated progression of rejection is considered to be a leading course of postoperative mortality. However, the conventional histologic diagnosis is limited in reading the rejection status at the molecular level, thereby triggering mismatched pathogenesis with clinical phenotypes. Here, by applying uniform manifold approximation and projection and Leiden algorithms to 2,611 publicly available microarray datasets of renal transplantation, we uncovered six rejection states with corresponding signature genes and revealed a high-risk (HR) state that was essential in promoting allograft loss. By identifying cell populations from single-cell RNA sequencing data that were associated with the six rejection states, we identified a T-cell population to be the pathogenesis-triggering cells associated with the HR rejection state. Additionally, by constructing gene regulatory networks, we identified that activated STAT4, as a core transcription factor that was regulated by PTPN6 in T cells, was closely linked to poor allograft function and prognosis. Taken together, our study provides a novel strategy to help with the precise diagnosis of kidney allograft rejection progression, which is powerful in investigating the underlying molecular pathogenesis, and therefore, for further clinical intervention.

Molecular Markers of Kidney Transplantation Outcome: Current Omics Tools and Future Developments

Purpose of review: The emerging field of molecular predictive medicine is aiming to change the traditional medical approach in renal transplantation. Many studies have explored potential biomarker molecules with predictive properties in renal transplantation, issued from omics research. Herein, we review the biomarker molecules of four technologies (i.e., Genomics, Transcriptomics, Proteomics, and Metabolomics) associated with favorable kidney transplant outcomes. Recent findings: Several panels of molecules have been associated with the outcome that the majority of markers are related to inflammation and immune response; although. other molecular ontologies are also represented, such as proteasome, growth, regeneration, and drug metabolism. Throughout this review, we highlight the lack of properly validated statistical demonstration. Indeed, the most preeminent molecular panels either remain at the limited size study stage or are not confirmed during large-scale studies. At the core of this problem, we identify the methodological shortcomings and propose a comprehensive workflow for discovery and validation of molecular biomarkers that aims to improve the relevance of these tools in the future. Summary: Overall, adopting a patient management through omics approach could bring remarkable improvement to transplantation success. An increased effort and investment between scientists, medical biologists, and clinicians seem to be the path toward a proper solution.

Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection

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.

Validation of a gene expression signature to measure immune quiescence in kidney transplant recipients in the CLIA setting

Aim: Allograft rejection remains a major cause of graft failure in kidney transplantation. Here the authors report the validation of a non-invasive molecular diagnostic assay, AlloMap Kidney, using peripheral blood. Methods: The AlloMap Kidney test is a gene expression profile utilizing the RNA-seq platform to measure immune quiescence in kidney transplant patients. Results/Conclusions: Analytical validation showed robust performance characteristics with an accuracy correlation coefficient of 0.997 and a precision coefficient of variation of 0.049 across testing. Clinical validation from the prospective, multi-center studies of 235 samples (66 rejection and 169 quiescence specimens) demonstrated the sensitivity of 70% and specificity of 66% for allograft rejection, while the negative predictive value was 95% to discriminate rejection from quiescence at 10% prevalence of rejection.

Single-Cell RNA Sequencing Identifies Intra-Graft Population Heterogeneity in Acute Heart Allograft Rejection in Mouse

Transplant rejection remains a major barrier to graft survival and involves a diversity of cell types. However, the heterogeneity of each cell type in the allograft remains poorly defined. In the present study, we used single-cell RNA sequencing technology to analyze graft-infiltrating cells to describe cell types and states associated with acute rejection in a mouse heart transplant model. Unsupervised clustering analysis revealed 21 distinct cell populations. Macrophages formed five cell clusters: two resident macrophage groups, two infiltrating macrophage groups and one dendritic cell-like monocyte group. Infiltrating macrophages were predominantly from allogeneic grafts. Nevertheless, only one infiltrating macrophage cluster was in an active state with the upregulation of CD40, Fam26f and Pira2, while the other was metabolically silent. Re-clustering of endothelial cells identified five subclusters. Interestingly, one of the endothelial cell populations was almost exclusively from allogeneic grafts. Further analysis of this population showed activation of antigen processing and presentation pathway and upregulation of MHC class II molecules. In addition, Ubiquitin D was specifically expressed in such endothelial cell population. The upregulation of Ubiquitin D in rejection was validated by staining of mouse heart grafts and human kidney biopsy specimens. Our findings present a comprehensive analysis of intra-graft cell heterogeneity, describe specific macrophage and endothelial cell populations which mediate rejection, and provide a potential predictive biomarker for rejection in the clinic.

High PIRCHE Scores May Allow Risk Stratification of Borderline Rejection in Kidney Transplant Recipients

Background

The diagnosis of borderline rejection (BLR) ranges from mild inflammation to clinically significant TCMR and is associated with an increased risk of allograft dysfunction. Currently, there is no consensus regarding its treatment due in part to a lack of biomarkers to identify cases with increased risk for immune-mediated injury.

Methods

We identified 60 of 924 kidney transplant recipients (KTRs) with isolated and untreated BLR. We analyzed the impact of predicted indirectly recognizable HLA epitopes (PIRCHE) score on future rejection, de novo DSA development, and recovery to baseline allograft function. Additionally, we compared the outcomes of different Banff rejection phenotypes.

Results

Total PIRCHE scores were significantly higher in KTRs with BLR compared to the entire study population (p=0.016). Among KTRs with BLR total PIRCHE scores were significantly higher in KTRs who developed TCMR/ABMR in follow-up biopsies (p=0.029). Notably, the most significant difference was found in PIRCHE scores for the HLA-A locus (p=0.010). PIRCHE scores were not associated with the development of de novo DSA or recovery to baseline allograft function among KTRs with BLR (p>0.05). However, KTRs under cyclosporine-based immunosuppression were more likely to develop de novo DSA (p=0.033) than those with tacrolimus, whereas KTRs undergoing retransplantation were less likely to recover to baseline allograft function (p=0.003).

Conclusions

High PIRCHE scores put KTRs with BLR at an increased risk for future TCMR/ABMR and contribute to improved immunological risk stratification. The benefit of anti-rejection treatment, however, needs to be evaluated in future studies.

Emerging biomarkers in kidney transplantation and challenge of clinical implementation

PURPOSE OF REVIEW

Despite improvement in short-term outcomes after kidney transplantation, long-term outcomes remain suboptimal. Conventional biomarkers are limited in their ability to reliably identify early immunologic and nonimmunologic injury. Novel biomarkers are needed for noninvasive diagnosis of subclinical injury, prediction of response to treatment, and personalization of the care of kidney transplant recipients.

RECENT FINDINGS

Recent biotechnological advances have led to the discovery of promising molecular biomarker candidates. However, translating potential biomarkers from bench to clinic is challenging, and many potential biomarkers are abandoned prior to clinical implementation. Despite these challenges, several promising urine, blood, and tissue novel molecular biomarkers have emerged and are approaching incorporation into clinical practice.

SUMMARY

This article highlights the challenges in adopting biomarker-driven posttransplant management and reviews several promising emerging novel biomarkers that are approaching clinical implementation.

Emerging role of cell-free DNA in kidney transplantation

Monitoring kidney transplants for rejection conventionally includes serum creatinine, immunosuppressive drug levels, proteinuria, and donor-specific antibody (DSA). Serum creatinine is a late marker of allograft injury, and the predictive ability of DSA regarding risk of rejection is variable. Histological analysis of an allograft biopsy is the standard method for diagnosing rejection but is invasive, inconvenient, and carries risk of complications. There has been a long quest to find a perfect biomarker that noninvasively predicts tissue injury caused by rejection at an early stage, so that diagnosis and treatment could be pursued without delay in order to minimize irreversible damage to the allograft. In this review, we discuss relatively novel research on identifying biomarkers of tissue injury, specifically elaborating on donor-derived cell-free DNA, and its clinical utility.

Noninvasive Assessment of the Alloimmune Response in Kidney Transplantation

Transplantation remains the optimal mode of kidney replacement therapy, but unfortunately long-term graft survival after 1 year remains suboptimal. The main mechanism of chronic allograft injury is alloimmune, and current clinical monitoring of kidney transplants includes measuring serum creatinine, proteinuria, and immunosuppressive drug levels. The most important biomarker routinely monitored is human leukocyte antigen (HLA) donor-specific antibodies (DSAs) with the frequency based on underlying immunologic risk. HLA-DSA should be measured if there is graft dysfunction, immunosuppression minimization, or nonadherence. Antibody strength is semiquantitatively estimated as mean fluorescence intensity, with titration studies for equivocal cases and for following response to treatment. Determination of in vitro C1q or C3d positivity or HLA-DSA IgG subclass analysis remains of uncertain significance, but we do not recommend these for routine use. Current evidence does not support routine monitoring of non-HLA antibodies except anti-angiotensin II type 1 receptor antibodies when the phenotype is appropriate. The monitoring of both donor-derived cell-free DNA in blood or gene expression profiling of serum and/or urine may detect subclinical rejection, although mainly as a supplement and not as a replacement for biopsy. The optimal frequency and cost-effectiveness of using these noninvasive assays remain to be determined. We review the available literature and make recommendations.

Emerging monitoring technologies in kidney transplantation

Non-invasive technologies to monitor kidney allograft health utilizing high-throughput assays of blood and urine specimens are emerging out of the research realm and slowly becoming part of everyday clinical practice. HLA epitope analysis and eplet mismatch score determination promise a more refined approach to the pre-transplant recipient-donor HLA matching that may lead to reduced rejection risk. High-resolution HLA typing and multiplex single antigen bead assays are identifying potential new offending HLA antibody subtypes. There is increasing recognition of the deleterious role non-HLA antibodies play in post-transplant outcomes. Donor-derived cell-free DNA detected by next-generation sequencing is a promising biomarker for kidney transplant rejection. Multi-omics techniques are shedding light on discrete genomic, transcriptomic, proteomic, and metabolomic signatures that correlate with and predict allograft outcomes. Over the next decade, a comprehensive approach to optimize kidney matching and monitor transplant recipients for acute and chronic graft dysfunction will likely involve a combination of those emerging technologies summarized in this review.

Advances in single-cell sequencing: insights from organ transplantation

Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.

Beyond the Biopsy: Monitoring Immune Status in Kidney Recipients

Improved long-term kidney allograft survival is largely related to better outcomes at 12 months, in association with declining acute rejection rates and more efficacious immunosuppression. Finding the right balance between under- and overimmunosuppression or rejection versus immunosuppression toxicity remains one of transplant's holy grails. In the absence of precise measures of immunosuppression burden, transplant clinicians rely on nonspecific, noninvasive tests and kidney allograft biopsy generally performed for cause. This review appraises recent advances of conventional monitoring strategies and critically examines the plethora of emerging tests utilizing tissue, urine, and blood samples to improve upon the diagnostic precision of allograft surveillance.

Transitional B cell cytokines predict renal allograft outcomes

Early immunological biomarkers that predict rejection and chronic allograft loss are needed to inform preemptive therapy and improve long-term outcomes. Here, we prospectively examined the ratio of interleukin-10 (IL-10) to tumor necrosis factor-α (TNFα) produced by transitional-1 B cells (T1B) 3 months after transplantation as a predictive biomarker for clinical and subclinical renal allograft rejection and subsequent clinical course. In both Training (n = 162) and Internal Validation (n = 82) Sets, the T1B IL-10/TNFα ratio 3 months after transplantation predicted both clinical and subclinical rejection anytime in the first year. The biomarker also predicted subsequent late rejection with a lead time averaging 8 months. Among biomarker high-risk patients, 60% had early rejection, of which 48% recurred later in the first posttransplant year. Among high-risk patients without early rejection, 74% developed rejection later in the first year. In contrast, only 5% of low-risk patients had early and 5% late rejection. The biomarker also predicted rejection in an External Validation Set (n = 95) and in key patient subgroups, confirming generalizability. Biomarker high-risk patients exhibited progressively worse renal function and decreased 5-year graft survival compared to low-risk patients. Treatment of B cells with anti-TNFα in vitro augmented the IL-10/TNFα ratio, restored regulatory activity, and inhibited plasmablast differentiation. To conclude, the T1B IL-10/TNFα ratio was validated as a strong predictive biomarker of renal allograft outcomes and provides a rationale for preemptive therapeutic intervention with TNF blockade.

Role of the IL-33/ST2 pathway in renal allograft rejection

The interleukin-33 (IL-33)/suppression of tumorigenicity 2 (ST2) pathway modulates immune response and inflammation, associated with allograft dysfunction and rejection. We hypothesized that IL-33/ST2 is a marker of renal allograft rejection and IL-33/ST2 expression may differ according to rejection type. IL-33/ST2 expression was measured in sera and kidney tissues from recipients with acute antibody-mediated rejection (AAMR), acute cell-mediated rejection (ACMR), chronic antibody-mediated rejection (CAMR), and healthy controls. The soluble ST2 and IL-33/ST2 expression levels were higher in participants with all three rejection types than in controls. Although the expression levels in recipients with AAMR and ACMR were significantly higher than those with CAMR, there was no significant difference between the expression levels in AAMR and ACMR. Although IL-33, IL-8, and fibronectin expression were significantly increased after the addition of the recipients' serum in primary cultured human renal proximal tubular epithelial cells, the levels decreased after treatment with an anti-ST2 antibody. Furthermore, the anti-ST2 antibody specifically suppressed the upregulation of the mixed lymphocyte reaction. Boyden chamber assays demonstrated that anti-ST2 antibody abrogated chemotaxis induced by recombinant IL-33. Thus, IL-33 and ST2 are potent mediators of rejection. Treatment with an anti-ST2 antibody ameliorates rejection and could be a potential therapeutic strategy for renal allograft rejection.

Non-invasive imaging for the diagnosis of acute rejection in transplantation: The next frontier

Acute rejection is a leading cause of organ transplant failure and the most common indication for re-transplantation. Clinically, suspicion of acute rejection is often dependent upon serum laboratory values which may only manifest after organ injury. The gold standard for diagnosis requires an invasive biopsy which can carry serious clinical risks including bleeding and graft loss as well as the possibility of sampling error. The use of noninvasive imaging modalities to monitor transplanted organs is of great clinical value, particularly as a tool for early detection of graft dysfunction or acute rejection. Herein, we provide an overview of the existing literature evaluating noninvasive imaging modalities of solid organ and cellular allografts after transplantation, including both preclinical and clinical studies.

Challenges of Diagnosing Antibody-Mediated Rejection: The Role of Invasive and Non-Invasive Biomarkers

Kidney transplantation is the best treatment modality for end-stage kidney disease, leading to improvement in a patient’s quality and quantity of life. With significant improvements in short-term outcomes, prolonging long-term allograft and patient survival remain ongoing challenges. The ability to monitor allograft function, immune tolerance and predict rejection accurately would enable personalization and better prognostication during post-transplant care. Though kidney biopsy remains the backbone of transplant diagnostics, emerging biomarkers can help detecting kidney allograft injury early enough to prevent permanent damage and detect injury before it is clinically apparent. In this review, we summarize the recent biomarkers that have shown promise in the prediction of acute rejection with a focus on antibody-mediated rejection in kidney transplantation.

Blood transcriptomics as non-invasive marker for kidney transplant rejection

In the last decade, a plenitude of potential molecular peripheral blood biomarkers has been developed. In assessing the utility of these markers for clinical practice, it is important to evaluate their diagnostic performance in different clinical scenarios. The higher probability of diagnosing rejection in indication compared to protocol biopsies illustrates that kidney functional parameters (estimated glomerular filtration rate evolution, proteinuria) are inherently already non-invasive biomarkers for rejection, with evident clinical utility. However, by definition, graft functional assessment will miss subclinical rejection. In this paper, we review how some of the most promising peripheral blood molecular biomarkers, like blood transcriptomic markers and donor-derived cell-free DNA measurement, perform in relation to graft functional evaluation. Since the definition of graft dysfunction is relatively arbitrary, we propose using a standardized clinical model for non-invasive diagnosis of allograft rejection, as benchmark and for integration with novel molecular biomarkers.

Use of the Tissue Common Rejection Module Score in Kidney Transplant as an Objective Measure of Allograft Inflammation

Long-term kidney transplant (KT) allograft outcomes have not improved as expected despite a better understanding of rejection and improved immunosuppression. Previous work had validated a computed rejection score, the tissue common rejection module (tCRM), measured by amplification-based assessment of 11 genes from formalin-fixed paraffin-embedded (FFPE) biopsy specimens, which allows for quantitative, unbiased assessment of immune injury. We applied tCRM in a prospective trial of 124 KT recipients, and contrasted assessment by tCRM and histology reads from 2 independent pathologists on protocol and cause biopsies post-transplant. Four 10-μm shaves from FFPE biopsy specimens were used for RNA extraction and amplification by qPCR of the 11 tCRM genes, from which the tCRM score was calculated. Biopsy diagnoses of either acute rejection (AR) or borderline rejection (BL) were considered to have inflammation present, while stable biopsies had no inflammation. Of the 77 biopsies that were read by both pathologists, a total of 40 mismatches in the diagnosis were present. The median tCRM scores for AR, BL, and stable diagnoses were 4.87, 1.85, and 1.27, respectively, with an overall significant difference among all histologic groups (Kruskal-Wallis, p < 0.0001). There were significant differences in tCRM scores between pathologists both finding inflammation vs. disagreement (p = 0.003), and both finding inflammation vs. both finding no inflammation (p < 0.001), along with overall significance between all scores (Kruskal-Wallis, p < 0.001). A logistic regression model predicting graft inflammation using various clinical predictor variables and tCRM revealed the tCRM score as the only significant predictor of graft inflammation (OR: 1.90, 95% CI: 1.40–2.68, p < 0.0001). Accurate, quantitative, and unbiased assessment of rejection of the clinical sample is critical. Given the discrepant diagnoses between pathologists on the same samples, individuals could utilize the tCRM score as a tiebreaker in unclear situations. We propose that the tCRM quantitative score can provide unbiased quantification of graft inflammation, and its rapid evaluation by PCR on the FFPE shave can become a critical adjunct to help drive clinical decision making and immunosuppression delivery.

Diagnostic performance of kSORT, a blood-based mRNA assay for noninvasive detection of rejection after kidney transplantation: A retrospective multicenter cohort study

The Kidney Solid Organ Response Test (kSORT) blood gene expression assay was developed to noninvasively detect acute rejection (AR) after kidney transplantation. Its performance in a setting with natural disease prevalence has not been evaluated. A retrospective, multicenter cohort study was conducted across all single kidney transplant recipients, transplanted between 2011 and 2015, with samples within the first year after transplantation available in existing biobanks. The primary objective was to determine the diagnostic performance of the kSORT assay to detect AR (T cell-mediated and/or antibody-mediated rejection) as compared to a concomitant renal biopsy. AR was reported on the concomitant biopsy in 188 of 1763 (10.7%) blood samples and any rejection (including borderline changes) in 614 of 1763 (34.8%) blood samples. In 320 of 1763 samples (18.2%) the kSORT risk category was indeterminate. The kSORT assay had no diagnostic value for AR (area under the curve [AUC] 0.51, 95% confidence interval [CI] 0.50-0.56; P = .46) overall, or when considering indication biopsies (N = 487) and protocol-specified biopsies (N = 1276) separately (AUC of 0.53, 95% CI 0.50-0.59, P = .44 and 0.55, 95% CI 0.50-0.61, P = .09, respectively). This large retrospective study utilizing samples obtained under real-world clinical conditions, was unable to validate the kSORT assay for detection of AR in the first year after transplantation.

Kidney allograft rejection: Diagnosis and treatment practices in USA- A UNOS survey

We studied diverse rejection management strategies across centers by conducting a UNOS survey of kidney transplant program directors in 2017. There were 104 total responses from 235 kidney transplant programs representing 88 unique transplant programs (response rate 37%). Information was collected on center-specific management practices. Pertinent center-specific data were obtained from the OPTN database. Of the respondents, 33% were considered large centers (>100 transplants/year). Thymoglobulin was the most commonly used induction agent at 84%, 72% responders do rapid steroid withdrawal, and mycophenolic acid (MPA) is the major antimetabolite (100%). For diagnosing TCMR, 100% used indication biopsy, 28% used protocol biopsy, 2% used serum biomarkers, and none used urine cytokines. For ABMR, 99% used indication biopsy, 34% used protocol biopsy, 72% used DSA, 21% used C1q positive DSA, and none used gene profiling (ENDATS). The treatment of subclinical and clinical TCMR included iv/PO steroids. PP/IVIG were the commonest treatments for ABMR. The use of rituximab, bortezomib, and eculizumab increased from C4D-ABMR to recurrent ABMR. There are diverse management practices for diagnosing and treating rejection. An effort to harmonize these diverse practices for management of TCMR and ABMR will give an opportunity to pool data for evaluating clinical outcomes.

Application of Contrast-Enhanced Sonography on the Diagnosis of Acute and Chronic Rejection After Renal Transplantation

To test the reliability of CEUS on the diagnosis of acute (AR) or chronic rejection (CR) after renal transplantation, patients who received renal transplantation in our center from January 2011 and December 2015 were retrospectively included in the current study. All the included patients underwent contrast-enhanced ultrasonography tests. Two regions of interests were chosen to carry out time-intensity curves (TICs). The main indexes include time indexes, intensity indexes, and difference indexes. Separation of TIC1 and TIC2 was evaluated by the authors. Results revealed that time to peak 1 (TTP-1), TTP-2, absolute time to peak 1 (ATTP-1), and ATTP-2 in the CR group were significantly later than those in the graft function stable group. Peak intensity 2 is smaller in the AR group than that in the GFS group, velocity of intensity ascending 2 is slower in the CR group than that in the GFS group, terminal intensity 1 (TI-1) and TI-2 are lower in the CR group than those in the GFS group, and Vd-1 is faster in the CR group than that in the GFS group (P < 0.05). Those results indicated that contrast-enhanced ultrasonography test can satisfactorily reflect the microcirculation of transplanted kidney and can be used to assist in the early diagnosis of graft rejection.

Development and validation of an optimized integrative model using urinary chemokines for noninvasive diagnosis of acute allograft rejection

The urinary chemokines CXCL9 and CXCL10 are promising noninvasive diagnostic markers of acute rejection (AR) in kidney recipients, but their levels might be confounded by urinary tract infection (UTI) and BK virus (BKV) reactivation. Multiparametric model development and validation addressed these confounding factors in a training set of 391 samples, optimizing the diagnostic performance of urinary chemokines. CXCL9/creatinine increased in UTI and BKV viremia with or without nephropathy (BKVN) (no UTI/leukocyturia/UTI: -0.10/1.61/2.09, P = .0001 and no BKV/viremia/BKVN: -0.10/1.90/2.29, P < .001) as well as CXCL10/creatinine (1.17/2.09/1.98, P < .0001 and 1.13/2.21/2.51, P < .001, respectively). An optimized 8-parameter model (recipient age, sex, estimated glomerular filtration rate, donor specific antibodies, UTI, BKV blood viral load, CXCL9, and CXCL10) diagnosed AR with high accuracy (area under the curve [AUC]: 0.85, 95% confidence interval [CI]: 0.80-0.89) and remained highly accurate at the time of screening (AUC: 0.81, 95% CI: 0.48-1) or indication biopsies (AUC: 0.85, 95% CI: 0.81-0.90) and within the first year (AUC: 0.86, 95% CI: 0.80-0.91) or later (AUC: 0.90, 95% CI: 0.84-0.96), achieving AR diagnosis with an AUC of 0.85 and 0.92 (P < .0001) in 2 external validation cohorts. Decision curve analyses demonstrated the clinical utility of the model. Considering confounding factors rather than excluding them, we optimized a noninvasive multiparametric diagnostic model for AR of kidney allografts with unprecedented accuracy.

Noninvasive biomarkers for prediction and diagnosis of heart transplantation rejection

For most patients with end-stage heart failure, heart transplantation is the treatment of choice. Allograft rejection is one of the major post-transplantation complications affecting graft outcome and survival. Recent advancements in science and technology offer an opportunity to integrate genomic and other omics-based biomarkers into clinical practice, facilitating noninvasive evaluation of allograft for diagnostic and prognostic purposes. Omics, including gene expression profiling (GEP) of blood immune cell components and donor-derived cell-free DNA (dd-cfDNA) are of special interest to researchers. Several studies have investigated levels of dd-cfDNA and miroRNAs in blood as potential markers for early detection of allograft rejection. One of the achievements in the field of transcriptomics is AlloMap, GEP of peripheral blood mononuclear cells (PBMC), which can identify 11 differentially expressed genes and help with detection of moderate and severe acute cellular rejection in stable heart transplant recipients. In recent years, the utilization of GEP of PBMC for identifying differentially expressed genes to diagnose acute antibody-mediated rejection and cardiac allograft vasculopathy has yielded promising results. Advancements in the field of metabolomics and proteomics as well as their potential implications have been further discussed in this paper.

Future developments in kidney transplantation

PURPOSE OF REVIEW

This review summarises recent developments in monitoring and immunosuppressive management in kidney transplantation.

RECENT FINDINGS

Long-term kidney allograft outcomes have not changed substantially mainly as a result of acute and chronic antibody-mediated rejection. Several groups have recently attempted to determine peripheral molecular fingerprints of ongoing rejection. But while this research is promising, it is not generalised for further spreading among different cohorts. Measurements of donor-derived cell-free DNA levels in recent studies have revealed better predictive values for antibody-mediated rejection. The Molecular Microscope Diagnostic System for assessing kidney graft biopsies has been gradually introduced within clinical practice, especially in complicated cases aimed at improving histological diagnostics. Molecular studies on accommodation in ABO-incompatible transplantation have shown increased complement regulation and lower expression of epithelial transporters and class 1 metallothioneins. Additionally, in clinical studies of sensitised patients, imlifidase has been shown to enable transplantation across significant immunological barriers, while the co-stimulation blockade has been tested to prevent donor specific antibodies development. In low-risk patients, everolimus/tacrolimus-based regimens have also proven their antiviral effects in large clinical trials.

SUMMARY

Recent developments in non-invasive monitoring have paved the way for the introduction of future larger clinical trials with multiple patient cohorts.

Donor-derived cell-free DNA as a biomarker for rejection after kidney transplantation: a systematic review and meta-analysis

A systematic review and meta-analysis were performed to investigate the value of donor-derived cell-free DNA (dd-cfDNA) as a noninvasive biomarker in diagnosing kidney allograft rejection. We searched PubMed, Web of Science and the Cochrane Library for original research papers published between January 1994 and May 2020 on dd-cfDNA fractions in blood of kidney allograft recipients. A single-group meta-analysis was performed by computing pooled estimates for dd-cfDNA fractions using the weighted median of medians or quantile estimation (QE) approach. Weighted median differences in medians (WMDMs) and median differences based on the QE method were used for pairwise comparisons. Despite heterogeneity among the selected studies, the meta-analysis revealed significantly higher median dd-cfDNA fractions in patients with antibody-mediated rejection (ABMR) than patients without rejection or patients with stable graft function. When comparing patients with T cell-mediated rejection (TCMR) and patients with ABMR, our two statistical approaches revealed conflicting results. Patients with TCMR did not have different median dd-cfDNA fractions than patients without rejection or patients with stable graft function. dd-cfDNA may be a useful marker for ABMR, but probably not for TCMR.

A Practical Guide to the Clinical Implementation of Biomarkers for Subclinical Rejection Following Kidney Transplantation

Noninvasive biomarkers are needed to monitor stable patients following kidney transplantation (KT), as subclinical rejection, currently detectable only with invasive surveillance biopsies, can lead to chronic rejection and graft loss. Several biomarkers have recently been developed to detect rejection in KT recipients, using different technologies as well as varying clinical monitoring strategies defined as "context of use (COU)." The various metrics utilized to evaluate the performance of each biomarker can also vary, depending on their intended COU. As the use of molecular biomarkers in transplantation represents a new era in patient management, it is important for clinicians to better understand the process by which the incremental value of each biomarkers is evaluated to determine its potential role in clinical practice. This process includes but is not limited to an assessment of clinical validity and utility, but to define these, the clinician must first appreciate the trajectory of a biomarker from bench to bedside as well as the regulatory and other requirements needed to navigate this course successfully. This overview summarizes this process, providing a framework that can be used by clinicians as a practical guide in general, and more specifically in the context of subclinical rejection following KT. In addition, we have reviewed available as well as promising biomarkers for this purpose in terms of the clinical need, COU, assessment of biomarker performance relevant to both the need and COU, assessment of biomarker benefits and risks relevant to the COU, and the evidentiary criteria of the biomarker relevant to the COU compared with the current standard of care. We also provide an insight into the path required to make biomarkers commercially available once they have been developed and validated so that they used by clinicians outside the research context in every day clinical practice.

Immunological follow-up of patients with renal transplants: A proposal for clinical practice in Colombia

Graft damage is a process that starts at the moment of transplantation, due to comorbidities of receptor, donor status, ischemia time, ischemia-reperfusion phenomenon, among others, those induce metabolic and immune factors that ultimately trigger clinical manifestations of graft dysfunction. However, the preclinical progression between the time of transplantation and the appearance of signs and symptoms of graft damage can take weeks to years. Therefore, the implementation of rational monitoring approaches during the post-transplantation period is critical and should include not only the clinical follow-up but also anticipate immunological graft damage. In the present essay, we propose an immunological monitoring algorithm for the post-renal transplantation period.

Maintenance Immunosuppression in Solid Organ Transplantation: Integrating Novel Pharmacodynamic Biomarkers to Inform Calcineurin Inhibitor Dose Selection

Calcineurin inhibitors, the primary immunosuppressive therapy used to prevent alloreactivity of transplanted organs, have a narrow therapeutic index. Currently, treatment is individualized based on clinical assessment of the risk of rejection or toxicity guided by trough concentration monitoring. Advances in immune monitoring have identified potential markers that may have value in understanding calcineurin inhibitor pharmacodynamics. Integration of these markers has the potential to complement therapeutic drug monitoring. Existing pharmacokinetic-pharmacodynamic (PK-PD) data is largely limited to correlation between the biomarker and trough concentrations at single time points. Immune related gene expression currently has the most evidence supporting PK-PD integration. Novel biomarker-based approaches to pharmacodynamic monitoring including development of enhanced PK-PD models are proposed to realize the full clinical benefit.

Recent Advances on Biomarkers of Early and Late Kidney Graft Dysfunction

New biomarkers of early and late graft dysfunction are needed in renal transplant to improve management of complications and prolong graft survival. A wide range of potential diagnostic and prognostic biomarkers, measured in different biological fluids (serum, plasma, urine) and in renal tissues, have been proposed for post-transplant delayed graft function (DGF), acute rejection (AR), and chronic allograft dysfunction (CAD). This review investigates old and new potential biomarkers for each of these clinical domains, seeking to underline their limits and strengths. OMICs technology has allowed identifying many candidate biomarkers, providing diagnostic and prognostic information at very early stages of pathological processes, such as AR. Donor-derived cell-free DNA (ddcfDNA) and extracellular vesicles (EVs) are further promising tools. Although most of these biomarkers still need to be validated in multiple independent cohorts and standardized, they are paving the way for substantial advances, such as the possibility of accurately predicting risk of DGF before graft is implanted, of making a “molecular” diagnosis of subclinical rejection even before histological lesions develop, or of dissecting etiology of CAD. Identification of “immunoquiescent” or even tolerant patients to guide minimization of immunosuppressive therapy is another area of active research. The parallel progress in imaging techniques, bioinformatics, and artificial intelligence (AI) is helping to fully exploit the wealth of information provided by biomarkers, leading to improved disease nosology of old entities such as transplant glomerulopathy. Prospective studies are needed to assess whether introduction of these new sets of biomarkers into clinical practice could actually reduce the need for renal biopsy, integrate traditional tools, and ultimately improve graft survival compared to current management.

Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection

Introduction

Peripheral blood (PB) molecular patterns characterizing the different effector immune pathways driving distinct kidney rejection types remain to be fully elucidated. We hypothesized that transcriptome analysis using RNA sequencing (RNAseq) in samples of kidney transplant patients would enable the identification of unique protein-coding and noncoding genes that may be able to segregate different rejection phenotypes.

Methods

We evaluated 37 biopsy-paired PB samples from the discovery cohort, with stable (STA), antibody-mediated rejection (AMR), and T cell-mediated rejection (TCMR) by RNAseq. Advanced machine learning tools were used to perform 3-way differential gene expression analysis to identify gene signatures associated with rejection. We then performed functional in silico analysis and validation by Fluidigm (San Francisco, CA) in 62 samples from 2 independent kidney transplant cohorts.

Results

We found 102 genes (63 coding genes and 39 noncoding genes) associated with AMR (54 upregulated), TCMR (23 upregulated), and STA (25 upregulated) perfectly clustered with each rejection phenotype and highly correlated with main histologic lesions (ρ = 0.91). For the genes associated with AMR, we found enrichment in regulation of endoplasmic reticulum stress, adaptive immunity, and Ig class-switching. In the validation, we found that the SIGLEC17P pseudogene and 9 SIGLEC17P-related coding genes were highly expressed among AMR but not in TCMR and STA samples.

Conclusions

This analysis identifies a critical gene signature in PB in kidney transplant patients undergoing AMR, sufficient to differentiate them from patients with TCMR and immunologically quiescent kidney allografts. Our findings provide the basis for new studies dissecting the role of noncoding genes in the pathophysiology of kidney allograft rejection and their potential value as noninvasive biomarkers of the rejection process.

Targeted Urine Metabolomics for Monitoring Renal Allograft Injury and Immunosuppression in Pediatric Patients

Despite new advancements in surgical tools and therapies, exposure to immunosuppressive drugs related to non-immune and immune injuries can cause slow deterioration and premature failure of organ transplants. Diagnosis of these injuries by non-invasive urine monitoring would be a significant clinical advancement for patient management, especially in pediatric cohorts. We investigated the metabolomic profiles of biopsy matched urine samples from 310 unique kidney transplant recipients using gas chromatography-mass spectrometry (GC-MS). Focused metabolite panels were identified that could detect biopsy confirmed acute rejection with 92.9% sensitivity and 96.3% specificity (11 metabolites) and could differentiate BK viral nephritis (BKVN) from acute rejection with 88.9% sensitivity and 94.8% specificity (4 metabolites). Overall, targeted metabolomic analyses of biopsy-matched urine samples enabled the generation of refined metabolite panels that non-invasively detect graft injury phenotypes with high confidence. These urine biomarkers can be rapidly assessed for non-invasive diagnosis of specific transplant injuries, opening the window for precision transplant medicine.