Mining the human urine proteome for monitoring renal transplant injury. Kidney Int. 2016;89:1244-1252. [PMID: 27165815 DOI: 10.1016/j.kint.2015.12.049]

Advancing kidney transplant outcomes: the role of urinary proteomics in graft function monitoring and rejection detection

INTRODUCTION

Kidney transplantation significantly improves the lives of those with end-stage kidney disease, offering best alternative to dialysis. However, transplant success is threatened by the acute and chronic rejection mechanisms due to complex immune responses against the new organ.

AREAS COVERED

The ongoing research into biomarkers holds promise for revolutionizing the early detection and monitoring of the graft health. Liquid biopsy techniques offer a new avenue, with several diagnostic, predictive, and prognostic biomarkers showing promise in detecting and monitoring kidney diseases and an early and chronic allograft rejection.

EXPERT OPINIONS

Evaluating the protein composition related to kidney transplant results could lead to identifying biomarkers that provide insights into the graft functionality. Non-invasive proteomic biomarkers can drastically enhance clinical outcomes and change the way how kidney transplants are evaluated for patients and physicians if they succeed in this transition. Hence, the advancement in proteomic technologies, leads toward a significant improvement in understanding of the protein markers and molecular mechanisms linked to the outcomes of kidney transplants. However, the road from discovery to the use of such proteins in clinical practice is long, with a need for continuous validation and beyond the singular research team with comprehensive infrastructure and across research groups collaboration.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Mass spectrometry-based proteomics for advancing solid organ transplantation research

Scarcity of high-quality organs, suboptimal organ quality assessment, unsatisfactory pre-implantation procedures, and poor long-term organ and patient survival are the main challenges currently faced by the solid organ transplant (SOT) field. New biomarkers for assessing graft quality pre-implantation, detecting, and predicting graft injury, rejection, dysfunction, and survival are critical to provide clinicians with invaluable prediction tools and guidance for personalized patients' treatment. Additionally, new therapeutic targets are also needed to reduce injury and rejection and improve transplant outcomes. Proteins, which underlie phenotypes, are ideal candidate biomarkers of health and disease statuses and therapeutic targets. A protein can exist in different molecular forms, called proteoforms. As the function of a protein depends on its exact composition, proteoforms can offer a more accurate basis for connection to complex phenotypes than protein from which they derive. Mass spectrometry-based proteomics has been largely used in SOT research for identification of candidate biomarkers and therapeutic intervention targets by so-called "bottom-up" proteomics (BUP). However, such BUP approaches analyze small peptides in lieu of intact proteins and provide incomplete information on the exact molecular composition of the proteins of interest. In contrast, "Top-down" proteomics (TDP), which analyze intact proteins retaining proteoform-level information, have been only recently adopted in transplantation studies and already led to the identification of promising proteoforms as biomarkers for organ rejection and dysfunction. We anticipate that the use of top-down strategies in combination with new technological advancements in single-cell and spatial proteomics could drive future breakthroughs in biomarker and therapeutic target discovery in SOT.

Proteomic analysis investigating kidney transplantation outcomes- a scoping review

BACKGROUND

Kidney transplantation is the optimal treatment option for most patients with end-stage kidney disease given the significantly lower morbidity and mortality rates compared to remaining on dialysis. Rejection and graft failure remain common in transplant recipients with limited improvement in long-term transplant outcomes despite therapeutic advances. There is an unmet need in the development of non-invasive biomarkers that specifically monitor graft function and predict transplant pathologies that affect outcomes. Despite the potential of proteomic investigatory approaches, up to now, no candidate biomarkers of sufficient sensitivity or specificity have translated into clinical use. The aim of this review was to collate and summarise protein findings and protein pathways implicated in the literature to date, and potentially flag putative biomarkers worth validating in independent patient cohorts.

METHODS

This review followed the Joanna Briggs' Institute Methodology for a scoping review. MedlineALL, Embase, Web of Science Core Collection, Scopus and Google Scholar databases were searched from inception until December 2022. Abstract and full text review were undertaken independently by two reviewers. Data was collated using a pre-designed data extraction tool.

RESULTS

One hundred one articles met the inclusion criteria. The majority were single-centre retrospective studies of small sample size. Mass spectrometry was the most used technique to evaluate differentially expressed proteins between diagnostic groups and studies identified various candidate biomarkers such as immune or structural proteins.

DISCUSSION

Putative immune or structural protein candidate biomarkers have been identified using proteomic techniques in multiple sample types including urine, serum and fluid used to perfuse donor kidneys. The most consistent findings implicated proteins associated with tubular dysfunction and immunological regulatory pathways such as leukocyte trafficking. However, clinical translation and adoption of candidate biomarkers is limited, and these will require comprehensive evaluation in larger prospective, multicentre trials.

Targeted protein quantitation in human body fluids by mass spectrometry

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)-based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS-based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS-based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS-based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.

Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

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.

Exploring the mechanism of BK polyomavirus-associated nephropathy through consensus gene network approach

BK polyomavirus-associated nephropathy occurs in kidney transplant recipients under immunosuppressive treatment. BK polyomavirus is implicated in cancer development and invasion, and case reports of renal cell carcinoma and urothelial carcinoma possibly associated with BK polyomavirus has been reported. Further, it has been suggested that the immune responses of KT-related diseases could play a role in the pathogenesis and progression of renal cell carcinoma. Thus, we thought to examine the relationship between BK polyomavirus-associated nephropathy and renal cell carcinoma in terms of gene expression. To identify the common and specific immune responses involved in kidney transplantation-related diseases with a specific focus on BK polyomavirus-associated nephropathy, we performed consensus weighted gene co-expression network analysis on gene profile datasets of renal biopsy samples from different institutions. After the identification of gene modules and validation of the obtained network by immunohistochemistry of the marker across kidney transplantation-related diseases, the relationship between prognosis of renal cell carcinoma and modules was assessed. We included the data from 248 patients and identified the 14 gene clusters across the datasets. We revealed that one cluster related to the translation regulating process and DNA damage response was specifically upregulated in BK polyomavirus-associated nephropathy. There was a significant association between the expression value of hub genes of the identified cluster including those related to cGAS-STING pathway and DNA damage response, and the prognosis of renal cell carcinoma. The study suggested the potential link between kidney transplantation-related diseases, especially specific transcriptomic signature of BK polyomavirus associated nephropathy and renal cell carcinoma.

Approach to acute kidney injury following paediatric kidney transplant

PURPOSE OF REVIEW

In a child with evidence of acute kidney injury (AKI) following renal transplantation, it is important to quickly and accurately diagnose the cause to enable timely initiation of therapeutic interventions. The following article will discuss the differential diagnosis of acute graft dysfunction in paediatric kidney transplant recipients. This review will systematically guide the clinician through the common and less common causes and provide updates on current treatments.

RECENT FINDINGS

In patients with signs of graft dysfunction, rejection is an important cause to consider. Diagnosis of rejection relies on biopsy findings, an invasive and costly technique. Over the past 5 years, there has been a focus on noninvasive methods of diagnosing rejection, including serum and urinary biomarkers.

SUMMARY

This review discusses the differential diagnosis of acute graft dysfunction following transplant, with a focus on acute rejection, urinary tract infections and common viral causes, prerenal and postrenal causes, nephrotoxic medications, specifically calcineurin inhibitor toxicity, thrombotic microangiopathy and recurrence of the underlying disease. Each condition is discussed in detail, with a focus on clinical clues to the cause, incidence in the paediatric population, workup and treatment.

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.

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent studies have shown that defective function of hepatocyte nuclear factor 4 alpha (HNF4a) and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein, an integrative analysis of hepatic RNA sequencing and liquid chromatography-tandem mass spectrometry was performed to identify plasma protein signatures for patients with mild and severe AH. Alcohol-related liver disease cirrhosis, nonalcoholic fatty liver disease, and healthy subjects were used as comparator groups. Levels of identified proteins primarily involved in hepatocellular function were decreased in patients with AH, which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified, including thrombin, hepatocyte growth factor α, clusterin, human serum factor H-related protein, and kallistatin, which exhibited large abundance shifts between severe and nonsevere AH. The combination of thrombin and hepatocyte growth factor α discriminated between severe and nonsevere AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

The Impact of Donor and Recipient Genetic Variation on Outcomes After Solid Organ Transplantation: A Scoping Review and Future Perspectives

At the outset of solid organ transplantation, genetic variation between donors and recipients was recognized as a major player in mechanisms such as allograft tolerance and rejection. Genome-wide association studies have been very successful in identifying novel variant-trait associations, but have been difficult to perform in the field of solid organ transplantation due to complex covariates, era effects, and poor statistical power for detecting donor-recipient interactions. To overcome a lack of statistical power, consortia such as the International Genetics and Translational Research in Transplantation Network have been established. Studies have focused on the consequences of genetic dissimilarities between donors and recipients and have reported associations between polymorphisms in candidate genes or their regulatory regions with transplantation outcomes. However, knowledge on the exact influence of genetic variation is limited due to a lack of comprehensive characterization and harmonization of recipients' or donors' phenotypes and validation using an experimental approach. Causal research in genetics has evolved from agnostic discovery in genome-wide association studies to functional annotation and clarification of underlying molecular mechanisms in translational studies. In this overview, we summarize how the recent advances and progresses in the field of genetics and genomics have improved the understanding of outcomes after solid organ transplantation.

Identifying RBBP7 as a Promising Diagnostic Biomarker for BK Virus-Associated Nephropathy

BK virus-associated nephropathy (BKVN) remains a major infectious complication due to powerful immunosuppression in kidney transplant recipients, and its histologic appearance can mimic rejection, leading to diagnostic and treatment dilemmas thus molecular diagnostic methods would be beneficial. We collected gene expression profiles of 169 kidney biopsies taken from BKVN, rejection, and stable functioning allografts, based on single sample gene set enrichment analysis and random forest algorithm, and three hallmark activities associated with DNA damage and proliferation were found to be relatively specific in BKVN. Subsequently, weighted gene co-expression network analysis and support vector machines (SVM) algorithm identified RBBP7 as a robust and promising biomarker with high accuracy in both training and validation cohorts (AUC =0.938, 0.977, respectively). Besides, potential drugs for BKVN treatment such as mepacrine were discovered, which may contribute to targeted antiviral therapy and effective patient management rather than simply reducing the doses of immunosuppressive agents in clinical practice. RBBP7 (retinoblastoma binding protein 7) serves as component of serval complexes that regulate chromatin metabolism and functions in affecting DNA replication and controlling cell proliferation. In this research, upregulation of RBBP7 was found to be associated with the higher infiltration of CD8 naïve T, iTreg, and neutrophil cells and the lower amounts of Th1, central memory T, NKT, CD8 T, and dendritic cells. Moreover, the infiltration of Th1, Th17, and NKT cells was steadily different between BKVN and rejection allografts through immune cell assessment. In conclusion, we identified and verified RBBP7 as a molecular biomarker for BKVN diagnosis, which demonstrated great distinguishing ability with allograft rejection and would support clinical decision-making.

Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection

Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.

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.

Preliminary Investigation of the Biomarkers of Acute Renal Transplant Rejection Using Integrated Proteomics Studies, Gene Expression Omnibus Datasets, and RNA Sequencing

A kidney transplant is often the best treatment for end-stage renal disease. Although immunosuppressive therapy sharply reduces the occurrence of acute allograft rejection (AR), it remains the main cause of allograft dysfunction. We aimed to identify effective biomarkers for AR instead of invasive kidney transplant biopsy. We integrated the results of several proteomics studies related to AR and utilized public data sources. Gene ontology (GO) and pathway analyses were used to identify important biological processes and pathways. The performance of the identified proteins was validated using several public gene expression omnibus (GEO) datasets. Samples that performed well were selected for further validation through RNA sequencing of peripheral blood mononuclear cells of patients with AR (n = 16) and non-rejection (n = 19) from our medical center. A total of 25 differentially expressed proteins (DEPs) overlapped in proteomic studies of urine and blood samples. GO analysis showed that the DEPs were mainly involved in the immune system and blood coagulation. Pathway analysis showed that the complement and coagulation cascade pathways were well enriched. We found that immunoglobulin heavy constant alpha 1 (IGHA1) and immunoglobulin κ constant (IGKC) showed good performance in distinguishing AR from non-rejection groups validated with several GEO datasets. Through RNA sequencing, the combination of IGHA1, IGKC, glomerular filtration rate, and donor age showed good performance in the diagnosis of AR with ROC AUC 91.4% (95% CI: 82–100%). Our findings may contribute to the discovery of potential biomarkers for AR monitoring.

Ischemia-Reperfusion Injury and Immunosuppressants Promote Polyomavirus Replication Through Common Molecular Mechanisms

Background

BK polyomavirus (BKPyV)-associated nephropathy (BKPyVAN) causes renal allograft dysfunction and graft loss. However, the mechanism of BKPyV replication after kidney transplantation is unclear. Clinical studies have demonstrated that immunosuppressants and renal ischemia–reperfusion injury (IRI) are risk factors for BKPyV infection. Studying the pathogenic mechanism of BKPyV is limited by the inability of BKPyV to infect the animal. Mouse polyomavirus (MPyV) is a close homolog of BKPyV. We used a model of MPyV infection to investigate the core genes and underlying mechanism of IRI and immunosuppressants to promote polyomavirus replication.

Materials and Methods

One-day-old male C57BL/6 mice were intraperitoneally injected with MPyV. At week 9 post-infection, all mice were randomly divided into IRI, immunosuppressant, and control groups and treated accordingly. IRI was established by clamping the left renal pedicle. Subsequently, kidney specimens were collected for detecting MPyV DNA, histopathological observation, and high-throughput RNA sequencing. Weighted gene correlation network analysis (WGCNA), protein–protein interaction network analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to screen for core genes and common signaling pathways involved in promoting MPyV replication by IRI and immunosuppressants.

Results

After primary infection, MPyV established persistent infection in kidneys and subsequently was significantly increased by IRI or immunosuppressant treatment individually. In the IRI group, viral loads peaked on day 3 in the left kidney, which were significantly higher than those in the right kidney and the control group. In the immunosuppressant group, viral loads in the left kidney were significantly increased on day 3, which were significantly higher than those in the control group. Protein–protein interaction network analysis and WGCNA screened complement C3, epidermal growth factor receptor (EGFR), and FN1 as core genes. Pathway enrichment analysis based on the IRI- or immunosuppressant-related genes selected by WGCNA indicated that the NF-κB signaling pathway was the main pathway involved in promoting MPyV replication. The core genes were further confirmed using published datasets GSE47199 and GSE75693 in human polyomavirus-associated nephropathy.

Conclusions

Our study demonstrated that IRI and immunosuppressants promote polyomavirus replication through common molecular mechanisms. In future studies, knockdown or specific inhibition of C3, EGFR, FN1, and NF-κB signaling pathway will further validate their critical roles in promoting polyomavirus replication.

Pre-transplant Transcriptional Signature in Peripheral Blood Mononuclear Cells of Acute Renal Allograft Rejection

Acute rejection (AR) is closely associated with renal allograft dysfunction. Here, we utilised RNA sequencing (RNA-Seq) and bioinformatic methods to characterise the peripheral blood mononuclear cells (PBMCs) of patients with acute renal allograft rejection. Pretransplant blood samples were collected from 32 kidney allograft donors and 42 corresponding recipients with biopsies classified as T cell-mediated rejection (TCMR, n = 18), antibody-mediated rejection (ABMR, n = 5), and normal/non-specific changes (non-AR, n = 19). The patients with TCMR and ABMR were assigned to the AR group, and the patients with normal/non-specific changes (n = 19) were assigned to the non-AR group. We analysed RNA-Seq data for identifying differentially expressed genes (DEGs), and then gene ontology (GO) analysis, Reactome, and ingenuity pathway analysis (IPA), protein—protein interaction (PPI) network, and cell-type enrichment analysis were utilised for bioinformatics analysis. We identified DEGs in the PBMCs of the non-AR group when compared with the AR, ABMR, and TCMR groups. Pathway and GO analysis showed significant inflammatory responses, complement activation, interleukin-10 (IL-10) signalling pathways, classical antibody-mediated complement activation pathways, etc., which were significantly enriched in the DEGs. PPI analysis showed that IL-10, VEGFA, CXCL8, MMP9, and several histone-related genes were the hub genes with the highest degree scores. Moreover, IPA analysis showed that several proinflammatory pathways were upregulated, whereas antiinflammatory pathways were downregulated. The combination of NFSF14+TANK+ANKRD 33 B +HSPA1B was able to discriminate between AR and non-AR with an AUC of 92.3% (95% CI 82.8–100). Characterisation of PBMCs by RNA-Seq and bioinformatics analysis demonstrated gene signatures and biological pathways associated with AR. Our study may provide the foundation for the discovery of biomarkers and an in-depth understanding of acute renal allograft rejection.

Urinary Biomarkers for Kidney Allograft Injury

The current standard of serum creatinine and biopsy to monitor allograft health has many limitations. The most significant drawback of the current standard is the lack of sensitivity and specificity to allograft injuries, which are diagnosed only after significant damage to the allograft. Thus, it is of critical need to identify a biomarker that is sensitive and specific to the early detection of allograft injuries. Urine, as the direct renal ultrafiltrate that can be obtained noninvasively, directly reflects intrarenal processes in the allograft at greater accuracy than analysis of peripheral blood. We review transcriptomic, metabolomic, genomic, and proteomic discovery-based approaches to identifying urinary biomarkers for the noninvasive detection of allograft injuries, as well as the use of urine cell-free DNA in the QSant urine assay as a sensitive surrogate for the renal allograft biopsy for rejection diagnosis.

Endoplasmic Reticulum Stress Mediates Renal Tubular Vacuolation in BK Polyomavirus-Associated Nephropathy

OBJECTIVE

This study aimed to explore the molecular mechanism of cytoplasmic vacuolation caused by BK polyomavirus (BKPyV) and thus search for potential target for drug repurposing.

METHODS

Morphological features of BK polyomavirus-associated nephropathy (BKPyVAN) were studied under light and electron microscopes. Microarray datasets GSE75693, GSE47199, and GSE72925 were integrated by ComBat, and differentially expressed genes (DEGs) were analyzed using limma. Furthermore, the endoplasmic reticulum (ER)-related genes obtained from GenCLiP 2.0 were intersected with DEGs. GO and KEGG enrichment pathways were performed with intersection genes by R package clusterProfiler. The single-cell RNA sequencing (scRNA-seq) from a BKPyVAN recipient was analyzed with a dataset (GSE140989) downloaded from Gene Expression Omnibus (GEO) as control for gene set variation analysis (GSVA). Immunohistochemistry and electron microscopy of kidney sections from drug-induced ERS mouse models were performed to explore the association of ERS and renal tubular vacuolation. Protein-protein interaction (PPI) network of the intersection genes was constructed to identify hub target. AutoDock was used to screen Food and Drug Administration (FDA)-approved drugs that potentially targeted hub gene.

RESULTS

Light and electron microscopes exhibited obvious intranuclear inclusions, vacuoles, and virus particles in BKPyV-infected renal tubular cells. Transcriptome analysis revealed 629 DEGs between samples of BKPyVAN and stable transplanted kidneys, of which 16 were ER-associated genes. GO analysis with the intersection genes illustrated that ERS-related pathways were significantly involved, and KEGG analysis showed a prominent enrichment of MAPK, Toll-like receptor, and chemokine signaling pathways. GSVA analysis of the proximal tubule revealed similar pathways enrichment. An electron microscope image of the kidney from ERS mouse models showed an obvious renal tubular vacuolation with prominent activation of ERS markers verified by immunohistochemistry. Furthermore, DDIT3 was identified as the hub gene based on PPI analysis, and ZINCOOOOO1531009 (Risedronate) was indicated to be a potential drug for DDIT3.

CONCLUSION

ERS was involved in renal tubular cytoplasmic vacuolation in BKPyVAN recipients. Risedronate was screened as a potential drug for BKPyVAN by targeting DDIT3.

Urinary Proteomics in Kidney Transplantation

Although kidney transplantation is the best treatment option for end stage kidney disease, it is still associated with long-term graft failure. One of the greater challenges for transplant professionals is the ability to identify grafts with a high risk of failure before initial decline of eGFR with irreversible graft changes. Transplantation medicine is facing an emerging need for novel disease end point-specific biomarkers, with practical application in preventive screening, early diagnostic, and improved prognostic and therapeutic utility. The aim of our review was to evaluate the clinical application of urinary proteomics in kidney transplant recipients at risk for any type of future graft failure.

Urinary donor-derived cell-free DNA as a non-invasive biomarker for BK polyomavirus-associated nephropathy

BK polyomavirus-associated nephropathy (BKPyVAN) is a common cause of allograft failure. However, differentiation between BKPyVAN and type I T cell-mediated rejection (TCMR) is challenging when simian virus 40 (SV40) staining is negative, because of the similarities in histopathology. This study investigated whether donor-derived cell-free DNA (ddcfDNA) can be used to differentiate BKPyVAN. Target region capture sequencing was applied to detect the ddcfDNAs of 12 recipients with stable graft function, 22 with type I TCMR, 21 with proven BKPyVAN, and 5 with possible PyVAN. We found that urinary ddcfDNA levels were upregulated in recipients with graft injury, whereas plasma ddcfDNA levels were comparable for all groups. The median urinary concentrations and fractions of ddcfDNA in proven BKPyVAN recipients were significantly higher than those in type I TCMR recipients (10.4 vs. 6.1 ng/mL, P<0.001 and 68.4% vs. 55.3%, P=0.013, respectively). Urinary ddcfDNA fractions (not concentrations) were higher in the BKPyVAN-pure subgroup than in the BKPyVAN-rejection-like subgroup (81.30% vs. 56.64%, P=0.025). With a cut-off value of 7.81 ng/mL, urinary ddcfDNA concentrations distinguished proven BKPyVAN from type I TCMR (area under the curve (AUC)=0.848, 95% confidence interval (95% CI): 0.734 to 0.963). These findings suggest that urinary ddcfDNA is a non-invasive biomarker which can reliably differentiate BKPyVAN from type I TCMR.

Urinary mRNA Expression of Glomerular Podocyte Markers in Glomerular Disease and Renal Transplant

The research of novel markers in urinary samples, for the description of renal damage, is of high interest, and several works demonstrated the value of urinary mRNA quantification for the search of events related to renal disease or affecting the outcome of transplant kidneys. In the present pilot study, a comparison of the urine mRNA expression of specific podocyte markers among patients who had undergone clinical indication to renal transplanted (RTx, n = 20) and native (N, n = 18) renal biopsy was performed. The aim of this work was to identify genes involved in podocytes signaling and cytoskeletal regulation (NPHS1, NPHS2, SYNPO, WT1, TRPC6, GRM1, and NEUROD) in respect to glomerular pathology. We considered some genes relevant for podocytes signaling and for the function of the glomerular filter applying an alternative normalization approach. Our results demonstrate the WT1 urinary mRNA increases in both groups and it is helpful for podocyte normalization. Furthermore, an increase in the expression of TRPC6 after all kinds of normalizations was observed. According to our data, WT1 normalization might be considered an alternative approach to correct the expression of urinary mRNA. In addition, our study underlines the importance of slit diaphragm proteins involved in calcium disequilibrium, such as TRPC6.

A new lateral flow assay to detect sIL-2R during T-cell mediated rejection after kidney transplantation

Kidney is the most frequently transplanted among all solid organs worldwide. Kidney transplant recipients (KTRs) undergo regular follow-up examinations for the early detection of acute rejections. The gold standard for proving a T-cell mediated rejection (TCMR) is a biopsy of the renal graft often occurring as indication biopsy, in parallel to an increased serum creatinine that may indicate deterioration of renal transplant function. The goal of the current work was to establish a lateral flow assay (LFA) for diagnosing acute TCMR to avoid harmful, invasive biopsies. Soluble interleukin-2 (IL-2) receptor (sIl-2R) is a potential biomarker representing the α-subunit of the IL-2 receptor produced by activated T-cells, e.g., after allogen contact. To explore the diagnostic potential of sIL-2R as a biomarker for TCMR and borderline TCMR, plasma and urine samples were collected from three independent KTR cohorts with various distinct histopathological diagnostic findings according to BANFF (containing 112 rsp. 71 rsp. 61 KTRs). Samples were analyzed by a Luminex-based multiplex technique and cut off-ranges were determined. An LFA was established with two specific sIL-2R-antibodies immobilized on a nitrocellulose membrane. A significant association between TCMR, borderline TCMR and sIL-2R in plasma and between TCMR and sIL-2R in urine of KTRs was confirmed using the Mann-Whitney U test. The LFA was tested with sIL-2R-spiked buffer samples establishing a detection limit of 25 pM. The performance of the new LFA was confirmed by analyzing urine samples of the 2^nd and 3^rd patient cohort with 35 KTRs with biopsy proven TCMRs, 3 KTRs diagnosed with borderline TCMR, 1 mixed AMR/TCMR rsp. AMR/borderline TCMR and 13 control patients with a rejection-free kidney graft proven by protocol biopsies. The new point-of-care assay showed a specificity of 84.6% and sensitivity of 87.5%, and a superior estimated glomerular filtration rate (eGFR) at the time point of biopsy (specificity 30.8%, sensitivity 85%).

Urinary proteomics for kidney dysfunction: insights and trends

Introduction: Kidney dysfunction poses a high burden on patients and health care systems. Early detection and accurate prediction of kidney disease progression remains a major challenge. Compared to existing clinical parameters, urinary proteomics has the potential to reveal molecular alterations within the kidney that may alter its function before the onset of clinical symptoms. Thus, urinary proteomics has greater prognostic potential for assessment of kidney dysfunction progression.Areas covered: Advances in urinary proteomics for major causes of kidney dysfunction are discussed. The application of urinary extracellular vesicles for studying kidney dysfunction are discussed. Technological advances in urinary proteomics are discussed. The literature was identified using a database search for titles containing 'proteom*' and 'urin*' and published within the past 5 years. Retrieved literature was manually filtered to retain kidney dysfunctions-related studies.Expert opinion: Despite major advances, diagnosis by urinary proteomics has not been fully applied in any clinical settings. This could be attributed to the complex nature of kidney diseases, in addition to the constraints on study power and feasibility of incorporating mass spectrometry techniques in daily routine analysis. Nevertheless, we are confident that advances in urinary proteomics will soon provide superior insights into kidney disease beyond existing clinical parameters.

Tackling Chronic Kidney Transplant Rejection: Challenges and Promises

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.

Proteomics reveals urine apolipoprotein A-I as a potential biomarker of acute kidney injury following percutaneous coronary intervention in elderly patients

The aim of the present study was to investigate how changes in the lipid composition are involved in early stages of acute kidney injury (AKI) following percutaneous coronary intervention (PCI-AKI) in elderly patients. A prospective nested case-control study was performed. Alterations in the urine protein accumulation were investigated in patients with and without PCI-AKI using isobaric tags for relative and absolute quantitation (iTRAQ). In addition, differentially expressed proteins (DEPs) related to lipids were confirmed using parallel reaction monitoring (PRM)-based targeted proteomics. From the cohort of elderly patients (>60 years of age), 14 (12.28%) developed AKI within 48 h after PCI. No significant differences were detected between the AKI and control (CON) groups for serum creatinine at 24 h following treatment (P=0.27). Among the DEPs that overlapped in both the AKI-24 h/AKI-Pre (AKI group at 24 h post-PCI vs. pre-PCI) and AKI-24 h/CON-24 h groups (AKI group vs. CON group at 24 h post-PCI), only apolipoprotein A-I (apoA-I) was related to lipids, which displayed a significant upregulation in expression levels. The protein expression levels of apoA-I displayed a 5.98-fold increase at 24 h after PCI from the baseline and a 2.09-fold increase compared with the control group as determined using PRM, which exhibited a similar trend to the iTRAQ results. Using protein-protein interaction analyses, apoA-I was determined to be functionally linked to the complement and coagulation cascades, the renin-angiotensin system and the hypoxia-inducible factor-1 signaling pathway. Using the pathway analysis tool from the Kyoto Encyclopedia of Genes and Genomes, several pathways were identified to be associated with apoA-I, including fat digestion and absorption, vitamin digestion and absorption, as well as the peroxisome proliferator activated receptor signaling pathway. In conclusion, apoA-I may be a promising biomarker for the early diagnosis of PCI-AKI in elderly patients. The role of apoA-I in the pathobiology of PCI-AKI requires further exploration.

A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

Urinary Biomarkers for Diagnosis and Prediction of Acute Kidney Allograft Rejection: A Systematic Review

Noninvasive tools for diagnosis or prediction of acute kidney allograft rejection have been extensively investigated in recent years. Biochemical and molecular analyses of blood and urine provide a liquid biopsy that could offer new possibilities for rejection prevention, monitoring, and therefore, treatment. Nevertheless, these tools are not yet available for routine use in clinical practice. In this systematic review, MEDLINE was searched for articles assessing urinary biomarkers for diagnosis or prediction of kidney allograft acute rejection published in the last five years (from 1 January 2015 to 31 May 2020). This review follows the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Articles providing targeted or unbiased urine sample analysis for the diagnosis or prediction of both acute cellular and antibody-mediated kidney allograft rejection were included, analyzed, and graded for methodological quality with a particular focus on study design and diagnostic test accuracy measures. Urinary C-X-C motif chemokine ligands were the most promising and frequently studied biomarkers. The combination of precise diagnostic reference in training sets with accurate validation in real-life cohorts provided the most relevant results and exciting groundwork for future studies.

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.

Urinary Protein Biomarker Panel for the Diagnosis of Antibody-Mediated Rejection in Kidney Transplant Recipients

Introduction

Antibody-mediated rejection (ABMR) impacts kidney allograft outcome. The diagnosis is made based on findings from invasive kidney transplant biopsy specimens. The aim of this study was to identify a noninvasive urinary protein biomarker for ABMR after kidney transplantation.

Methods

We performed a multicenter case-control study to identify a urinary biomarker for ABMR (training cohort, n = 249) and an independent, prospective multicenter cohort study for validation (n = 391). We used concomitant biopsies to classify the samples according to the Banff classification. After untargeted protein identification and quantification, we used a support vector machine to train the model in the training cohort. The primary endpoint was the diagnostic accuracy of the urinary biomarker for ABMR in the validation cohort.

Results

We identified a set of 10 urinary proteins that accurately discriminated patients with (n = 60) and without (n = 189) ABMR in the training cohort with an area under the curve (AUC) of 0.98 (95% confidence interval [CI], 0.96–1.00). The diagnostic accuracy was maintained in the validation cohort (AUC, 0.88; 95% CI, 0.8–0.93) for discriminating the presence (n = 43) from the absence (n = 348) of ABMR. The negative predictive value of the 10-protein marker set for exclusion of ABMR was 0.99, and the positive predictive value was 0.33. The diagnostic accuracy was independent of the reason for performing the biopsy, time after transplantation, and better than the accuracy of gross proteinuria (AUC, 0.76).

Conclusions

We identified and validated a urinary protein biomarker set that can be used to exclude ABMR.

Activity-based protein profiling guided identification of urine proteinase 3 activity in subclinical rejection after renal transplantation

Background

The pathophysiology of subclinical versus clinical rejection remains incompletely understood given their equivalent histological severity but discordant graft function. The goal was to evaluate serine hydrolase enzyme activities to explore if there were any underlying differences in activities during subclinical versus clinical rejection.

Methods

Serine hydrolase activity-based protein profiling (ABPP) was performed on the urines of a case control cohort of patients with biopsy confirmed subclinical or clinical transplant rejection. In-gel analysis and affinity purification with mass spectrometry were used to demonstrate and identify active serine hydrolase activity. An assay for proteinase 3 (PR3/PRTN3) was adapted for the quantitation of activity in urine.

Results

In-gel ABPP profiles suggested increased intensity and diversity of serine hydrolase activities in urine from patients undergoing subclinical versus clinical rejection. Serine hydrolases (n = 30) were identified by mass spectrometry in subclinical and clinical rejection patients with 4 non-overlapping candidates between the two groups (i.e. ABHD14B, LTF, PR3/PRTN3 and PRSS12). Western blot and the use of a specific inhibitor confirmed the presence of active PR3/PRTN3 in samples from patients undergoing subclinical rejection. Analysis of samples from normal donors or from several serial post-transplant urines indicated that although PR3/PRTN3 activity may be highly associated with low-grade subclinical inflammation, the enzyme activity was not restricted to this patient group.

Conclusions

There appear to be limited qualitative and quantitative differences in serine hydrolase activity in patients with subclinical versus clinical renal transplant rejection. The majority of enzymes identified were present in samples from both groups implying that in-gel quantitative differences may largely relate to the activity status of shared enzymes. However qualitative compositional differences were also observed indicating differential activities. The PR3/PRTN3 analyses indicate that the activity status of urine in transplant patients is dynamic possibly reflecting changes in the underlying processes in the transplant. These data suggest that differential serine hydrolase pathways may be active in subclinical versus clinical rejection which requires further exploration in larger patient cohorts. Although this study focused on PR3/PRTN3, this does not preclude the possibility that other enzymes may play critical roles in the rejection process.

Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring

Traditional histopathological allograft biopsy evaluation provides, within hours, diagnoses, prognostic information, and mechanistic insights into disease processes. However, proponents of an array of alternative monitoring platforms, broadly classified as "invasive" or "noninvasive" depending on whether allograft tissue is needed, question the value proposition of tissue histopathology. The authors explore the pros and cons of current analytical methods relative to the value of traditional and illustrate advancements of next-generation histopathological evaluation of tissue biopsies. We describe the continuing value of traditional histopathological tissue assessment and "next-generation pathology (NGP)," broadly defined as staining/labeling techniques coupled with digital imaging and automated image analysis. Noninvasive imaging and fluid (blood and urine) analyses promote low-risk, global organ assessment, and "molecular" data output, respectively; invasive alternatives promote objective, "mechanistic" insights by creating gene lists with variably increased/decreased expression compared with steady state/baseline. Proponents of alternative approaches contrast their preferred methods with traditional histopathology and: (1) fail to cite the main value of traditional and NGP-retention of spatial and inferred temporal context available for innumerable objective analyses and (2) belie an unfamiliarity with the impact of advances in imaging and software-guided analytics on emerging histopathology practices. Illustrative NGP examples demonstrate the value of multidimensional data that preserve tissue-based spatial and temporal contexts. We outline a path forward for clinical NGP implementation where "software-assisted sign-out" will enable pathologists to conduct objective analyses that can be incorporated into their final reports and improve patient care.

Advances in Detection of Kidney Transplant Injury

Early detection of graft injury after kidney transplantation is key to maintaining long-term good graft function. Graft injury could be due to a multitude of factors including ischaemia reperfusion injury, cell or antibody-mediated rejection, progressive interstitial fibrosis and tubular atrophy, infections and toxicity from the immunosuppressive drugs themselves. The current gold standard for assessing renal graft dysfunction is renal biopsy. However, biopsy is usually late when triggered by a change in serum creatinine and of limited utility in diagnosis of early injury when histological changes are equivocal. Therefore, there is a need for timely, objective and non-invasive diagnostic techniques with good early predictive value to determine graft injury and provide precision in titrating immunosuppression. We review potential novel plasma and urine biomarkers that offer sensitive new strategies for early detection and provide major insights into mechanisms of graft injury. This is a rapidly expanding field, but it is likely that a combination of biomarkers will be required to provide adequate sensitivity and specificity for detecting graft injury.

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

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

Analysis of Spatiotemporal Urine Protein Dynamics to Identify New Biomarkers for Sepsis-Induced Acute Kidney Injury

Acute kidney injury (AKI) is a frequent complication of sepsis and contributes to increased mortality. Discovery of reliable biomarkers could enable identification of individuals with high AKI risk as well as early AKI detection and AKI progression monitoring. However, the current methods are insensitive and non-specific. This study aimed to identify new biomarkers through label-free mass spectrometry (MS) analysis of a sepsis model induced by cecal ligation and puncture (CLP). Urine samples were collected from septic rats at 0, 3, 6, 12, 24, and 48 h. Protein isolated from urine was subjected to MS. Immunoregulatory biological processes, including immunoglobin production and wounding and defense responses, were upregulated at early time points. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses identified 77 significantly changed pathways. We further examined the consistently differentially expressed proteins to seek biomarkers that can be used for early diagnosis. Notably, the expression of PARK7 and CDH16 were changed in a continuous manner and related to the level of Scr in urine from patients. Therefore, PARK7 and CDH16 were confirmed to be novel biomarkers after validation in sepsis human patients. In summary, our study analyzed the proteomics of AKI at multiple time points, elucidated the related biological processes, and identified novel biomarkers for early diagnosis of sepsis-induced AKI, and our findings provide a theoretical basis for further research on the molecular mechanisms.

Quantitative Proteomics for Monitoring Renal Transplant Injury

PURPOSE

This study is aimed at developing a molecular diagnostics platform to enhance the interpretation of renal allograft biopsies using quantitative proteomic profiling of formalin-fixed and paraffin-embedded (FFPE) specimens.

EXPERIMENTAL DESIGN

A quantitative proteomics platform composed of 1) an optimized FFPE protein sample preparation method, 2) a tandem mass tag TMT10-plex-based proteomic workflow, and 3) a systematic statistical analysis pipeline to reveal differentially expressed proteins has been developed. This platform is then tested on a small sample set (five samples per phenotype) to reveal proteomic signatures that can differentiate T-cell mediated rejection (TCMR) and polyomavirus BK nephropathy (BKPyVN) from healthy functionally stable kidney tissue (STA).

RESULTS

Among 2798 quantified proteins, the expression levels of 740 BKPyVN and 638 TCMR associated proteins are significantly changed compared to STA specimens. Principal component analysis demonstrated good segregation of all three phenotypes investigated. Protein detection and quantitation are highly reproducible: replicate comparative analyses demonstrated 71-84% overlap of detected proteins, and the coefficient of variation for protein measurements is <15% in triplicate liquid chromatography-tandem mass spectrometry runs.

CONCLUSIONS AND CLINICAL RELEVANCE

Quantitative proteomics can be applied to archived FFPE specimens to differentiate different causes of renal allograft injury.

Identifying 4 Novel lncRNAs as Potential Biomarkers for Acute Rejection and Graft Loss of Renal Allograft

Acute rejection (AR) after kidney transplant is one of the major obstacles to obtain ideal graft survival. Reliable molecular biomarkers for AR and renal allograft loss are lacking. This study was performed to identify novel long noncoding RNAs (lncRNAs) for diagnosing AR and predicting the risk of graft loss. The several microarray datasets with AR and nonrejection specimens of renal allograft downloaded from Gene Expression Omnibus database were analyzed to screen differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). Univariate and multivariate Cox regression analyses were used to identify optimal prognosis-related DElncRNAs for constructing a risk score model. 39 common DElncRNAs and 185 common DEmRNAs were identified to construct a lncRNA-mRNA regulatory relationship network. DElncRNAs were revealed to regulate immune cell activation and proliferation. Then, 4 optimal DElncRNAs, ATP1A1-AS1, CTD-3080P12.3, EMX2OS, and LINC00645, were selected from 17 prognostic DElncRNAs to establish the 4-lncRNA risk score model. In the training set, the high-risk patients were more inclined to graft loss than the low-risk patients. Time-dependent receiver operating characteristics analysis revealed the model had good sensitivity and specificity in prediction of 1-, 2-, and 3-year graft survival after biopsy (AUC = 0.891, 0.836, and 0.733, respectively). The internal testing set verified the result well. Gene set enrichment analysis which expounded NOD-like receptor, the Toll-like receptor signaling pathways, and other else playing important role in immune response was enriched by the 4 lncRNAs. Allograft-infiltrating immune cells analysis elucidated the expression of 4 lncRNAs correlated with gamma delta T cells and eosinophils, etc. Our study identified 4 novel lncRNAs as potential biomarkers for AR of renal allograft and constructed a lncRNA-based model for predicting the risk of graft loss, which would provide new insights into mechanisms of AR.

Urinary Peptidomic Biomarkers in Kidney Diseases

In order to effectively develop personalized medicine for kidney diseases we urgently need to develop highly accurate biomarkers for use in the clinic, since current biomarkers of kidney damage (changes in serum creatinine and/or urine albumin excretion) apply to a later stage of disease, lack accuracy, and are not connected with molecular pathophysiology. Analysis of urine peptide content (urinary peptidomics) has emerged as one of the most attractive areas in disease biomarker discovery. Urinary peptidome analysis allows the detection of short and long-term physiological or pathological changes occurring within the kidney. Urinary peptidomics has been applied extensively for several years now in renal patients, and may greatly improve kidney disease management by supporting earlier and more accurate detection, prognostic assessment, and prediction of response to treatment. It also promises better understanding of kidney disease pathophysiology, and has been proposed as a "liquid biopsy" to discriminate various types of renal disorders. Furthermore, proteins being the major drug targets, peptidome analysis may allow one to evaluate the effects of therapies at the protein signaling pathway level. We here review the most recent findings on urinary peptidomics in the setting of the most common kidney diseases.

Noninvasive Urinary Monitoring of Progression in IgA Nephropathy

Standard methods for detecting and monitoring of IgA nephropathy (IgAN) have conventionally required kidney biopsies or suffer from poor sensitivity and specificity. The Kidney Injury Test (KIT) Assay of urinary biomarkers has previously been shown to distinguish between various kidney pathologies, including chronic kidney disease, nephrolithiasis, and transplant rejection. This validation study uses the KIT Assay to investigate the clinical utility of the non-invasive detection of IgAN and predicting the progression of renal damage over time. The study design benefits from longitudinally collected urine samples from an investigator-initiated, multicenter, prospective study, evaluating the efficacy of corticosteroids versus Rituximab for preventing progressive IgAN. A total of 131 urine samples were processed for this study; 64 urine samples were collected from 34 IgAN patients, and urine samples from 64 demographically matched healthy controls were also collected; multiple urinary biomarkers consisting of cell-free DNA, methylated cell-free DNA, DMAIMO, MAMIMO, total protein, clusterin, creatinine, and CXCL10 were measured by the microwell-based KIT Assay. An IgA risk score (KIT-IgA) was significantly higher in IgAN patients as compared to healthy control (87.76 vs. 14.03, p < 0.0001) and performed better than proteinuria in discriminating between the two groups. The KIT Assay biomarkers, measured on a spot random urine sample at study entry could distinguish patients likely to have progressive renal dysfunction a year later. These data support the pursuit of larger prospective studies to evaluate the predictive performance of the KIT-IgA score in both screening for non-invasive diagnosis of IgAN, and for predicting risk of progressive renal disease from IgA and utilizing the KIT score for potentially evaluating the efficacy of IgAN-targeted therapies.

Cellular and viral miRNA expression in polyomavirus BK infection

Polyomavirus BK (BKV) is an important pathogen in kidney transplant patients. Regulation of BKV encoded microRNAs (miRNAs) is not well understood. Therefore, tubular epithelial cells infected with BKV were examined for changes in small RNA expression. The observed changes were further evaluated by real-time PCR and RNA-seq analysis of renal allograft biopsies. BKV-miR-B1-5p and BKV-miR-B1-3p showed a 1000-fold increase over 12 days but did not prevent cell lysis. Downregulation of host miR-10b and miR-30a could be confirmed on all three platforms evaluated. Whereas, the BKV genome expressed more 3p than 5p miRNA species, the reverse was true for the human genome. Decreased expression of TP53INP2, and increased expression of BCL2A1, IL-6, IL8 and other proinflammatory cytokines were shown in biopsies with BKV nephropathy. No change in expression was seen in miR-10a dependent expression of NKG2D ligands ULBP3, MICA, or MICB. In conclusion, BKV infection results in regulation of cellular genes regulated by and possibly amenable to therapies targeting miR-10 and miR-30.

Subclinical Changes in Deceased Donor Kidney Proteomes Are Associated With 12-month Allograft Function Posttransplantation-A Preliminary Study

Background

Cerebral injury during donation after brain death may induce systemic damage affecting long-term kidney function posttransplantation. Conventional evaluation of donor organ quality as a triage for transplantation is of limited utility.

Methods

We compared donor kidneys yielding opposing extremes of the continuum of posttransplantation outcomes by several common kidney biopsy evaluation techniques, including Kidney Donor Profile Index and Remuzzi scoring, and analyzed tissue from a minimal sample cohort using label-free quantitation mass spectrometry. Further assessment of the proteomic results was performed by orthogonal quantitative comparisons of selected key proteins by immunoblotting.

Results

We show that common evaluation techniques of kidney biopsies were not predictive for posttransplantation outcomes. In contrast, despite the limited cohort size, the proteomic analysis was able to clearly differentiate between kidneys yielding extreme posttransplantation outcome differences. Pathway analysis of the proteomic data suggested that outcome-related variance in protein abundance associated with profibrotic, apoptosis, and antioxidant proteins. Immunoblotting confirmation further supported this observation.

Conclusions

We present preliminary data indicating that there is scope for existing evaluation approaches to be supplemented by the analysis of proteomic differences. Furthermore, the observed outcome-related variance in a limited cohort was supported by immunoblotting and is consistent with mechanisms previously implicated in the development of injury and cytoprotection in kidney transplantation.

Proteomic analyses using mass spectrometry and immunoblot of a small cohort of kidneys from brain death donors is superior to predict graft function (estimated glomerular filtration rate at 3 and 12 months) versus clinical and histological standard classifications. Supplemental digital content is available in the text.

MetaMSD: meta analysis for mass spectrometry data

Mass spectrometry-based proteomics facilitate disease understanding by providing protein abundance information about disease progression. For the same type of disease studies, multiple mass spectrometry datasets may be generated. Integrating multiple mass spectrometry datasets can provide valuable information that a single dataset analysis cannot provide. In this article, we introduce a meta-analysis software, MetaMSD (Meta Analysis for Mass Spectrometry Data) that is specifically designed for mass spectrometry data. Using Stouffer’s or Pearson’s test, MetaMSD detects significantly more differential proteins than the analysis based on the single best experiment. We demonstrate the performance of MetaMSD using simulated data, urinary proteomic data of kidney transplant patients, and breast cancer proteomic data. Noting the common practice of performing a pilot study prior to a main study, this software will help proteomics researchers fully utilize the benefit of multiple studies (or datasets), thus optimizing biomarker discovery. MetaMSD is a command line tool that automatically outputs various graphs and differential proteins with confidence scores. It is implemented in R and is freely available for public use at https://github.com/soyoungryu/MetaMSD. The user manual and data are available at the site. The user manual is written in such a way that scientists who are not familiar with R software can use MetaMSD.

A Novel Multi-Biomarker Assay for Non-Invasive Quantitative Monitoring of Kidney Injury

The current standard of care measures for kidney function, proteinuria, and serum creatinine (SCr) are poor predictors of early-stage kidney disease. Measures that can detect chronic kidney disease in its earlier stages are needed to enable therapeutic intervention and reduce adverse outcomes of chronic kidney disease. We have developed the Kidney Injury Test (KIT) and a novel KIT Score based on the composite measurement and validation of multiple biomarkers across a unique set of 397 urine samples. The test is performed on urine samples that require no processing at the site of collection and without target sequencing or amplification. We sought to verify that the pre-defined KIT test, KIT Score, and clinical thresholds correlate with established chronic kidney disease (CKD) and may provide predictive information on early kidney injury status above and beyond proteinuria and renal function measurements alone. Statistical analyses across six DNA, protein, and metabolite markers were performed on a subset of residual spot urine samples with CKD that met assay performance quality controls from patients attending the clinical labs at the University of California, San Francisco (UCSF) as part of an ongoing IRB-approved prospective study. Inclusion criteria included selection of patients with confirmed CKD and normal healthy controls; exclusion criteria included incomplete or missing information for sample classification, logistical delays in transport/processing of urine samples or low sample volume, and acute kidney injury. Multivariate logistic regression of kidney injury status and likelihood ratio statistics were used to assess the contribution of the KIT Score for prediction of kidney injury status and stage of CKD as well as assess the potential contribution of the KIT Score for detection of early-stage CKD above and beyond traditional measures of renal function. Urine samples were processed by a proprietary immunoprobe for measuring cell-free DNA (cfDNA), methylated cfDNA, clusterin, CXCL10, total protein, and creatinine. The KIT Score and stratified KIT Score Risk Group (high versus low) had a sensitivity and specificity for detection of kidney injury status (healthy or CKD) of 97.3% (95% CI: 94.6-99.3%) and 94.1% (95% CI: 82.3-100%). In addition, in patients with normal renal function (estimated glomerular filtration rate (eGFR) ≥ 90), the KIT Score clearly identifies those with predisposing risk factors for CKD, which could not be detected by eGFR or proteinuria (p < 0.001). The KIT Score uncovers a burden of kidney injury that may yet be incompletely recognized, opening the door for earlier detection, intervention and preservation of renal function.

Urine Angiotensin II Signature Proteins as Markers of Fibrosis in Kidney Transplant Recipients

BACKGROUND

Interstitial fibrosis/tubular atrophy (IFTA) is an important cause of kidney allograft loss; however, noninvasive markers to identify IFTA or guide antifibrotic therapy are lacking. Using angiotensin II (AngII) as the prototypical inducer of IFTA, we previously identified 83 AngII-regulated proteins in vitro. We developed mass spectrometry-based assays for quantification of 6 AngII signature proteins (bone marrow stromal cell antigen 1, glutamine synthetase [GLNA], laminin subunit beta-2, lysophospholipase I, ras homolog family member B, and thrombospondin-I [TSP1]) and hypothesized that their urine excretion will correlate with IFTA in kidney transplant patients.

METHODS

Urine excretion of 6 AngII-regulated proteins was quantified using selected reaction monitoring and normalized by urine creatinine. Immunohistochemistry was used to assess protein expression of TSP1 and GLNA in kidney biopsies.

RESULTS

The urine excretion rates of AngII-regulated proteins were found to be increased in 15 kidney transplant recipients with IFTA compared with 20 matched controls with no IFTA (mean log2[fmol/µmol of creatinine], bone marrow stromal cell antigen 1: 3.8 versus 3.0, P = 0.03; GLNA: 1.2 versus -0.4, P = 0.03; laminin subunit beta-2: 6.1 versus 5.4, P = 0.06; lysophospholipase I: 2.1 versus 0.6, P = 0.002; ras homolog family member B: 1.2 versus -0.1, P = 0.006; TSP1_GGV: 2.5 versus 1.9; P = 0.15; and TSP1_TIV: 2.0 versus 0.6, P = 0.0006). Receiver operating characteristic curve analysis demonstrated an area under the curve = 0.86 for the ability of urine AngII signature proteins to discriminate IFTA from controls. Urine excretion of AngII signature proteins correlated strongly with chronic IFTA and total inflammation. In a separate cohort of 19 kidney transplant recipients, the urine excretion of these 6 proteins was significantly lower following therapy with AngII inhibitors (P < 0.05).

CONCLUSIONS

AngII-regulated proteins may represent markers of IFTA and guide antifibrotic therapies.

A urinary Common Rejection Module (uCRM) score for non-invasive kidney transplant monitoring

A Common Rejection Module (CRM) consisting of 11 genes expressed in allograft biopsies was previously reported to serve as a biomarker for acute rejection (AR), correlate with the extent of graft injury, and predict future allograft damage. We investigated the use of this gene panel on the urine cell pellet of kidney transplant patients. Urinary cell sediments collected from patients with biopsy-confirmed acute rejection, borderline AR (bAR), BK virus nephropathy (BKVN), and stable kidney grafts with normal protocol biopsies (STA) were analyzed for expression of these 11 genes using quantitative polymerase chain reaction (qPCR). We assessed these 11 CRM genes for their abundance, autocorrelation, and individual expression levels. Expression of 10/11 genes were elevated in AR when compared to STA. Psmb9 and Cxcl10could classify AR versus STA as accurately as the 11-gene model (sensitivity = 93.6%, specificity = 97.6%). A uCRM score, based on the geometric mean of the expression levels, could distinguish AR from STA with high accuracy (AUC = 0.9886) and correlated specifically with histologic measures of tubulitis and interstitial inflammation rather than tubular atrophy, glomerulosclerosis, intimal proliferation, tubular vacuolization or acute glomerulitis. This urine gene expression-based score may enable the non-invasive and quantitative monitoring of AR.