Proteomics for rejection diagnosis in renal transplant patients: Where are we now?

Predicting Cellular Rejection of Renal Allograft Based on the Serum Proteomic Fingerprint

Kidney transplantation is an essential medical procedure that significantly enhances the survival rates and quality of life for patients with end-stage kidney disease. However, despite advancements in immunosuppressive therapies, allograft rejection remains a leading cause of organ loss. Notably, predictions of cellular rejection processes primarily rely on biopsy analysis, which is not routinely performed due to its invasive nature. The present work evaluates if the serum proteomic fingerprint, as acquired by Fourier Transform Infrared (FTIR) spectroscopy, can predict cellular rejection processes. We analyzed 28 serum samples, corresponding to 17 without cellular rejection processes and 11 associated with cellular rejection processes, as based on biopsy analyses. The leave-one-out-cross validation procedure of a Naïve Bayes model enabled the prediction of cellular rejection processes with high sensitivity and specificity (AUC > 0.984). The serum proteomic profile was obtained in a high-throughput mode and based on a simple, rapid, and economical procedure, making it suitable for routine analyses and large-scale studies. Consequently, the current method presents a high potential to predict cellular rejection processes translatable to clinical scenarios, and that should continue to be explored.

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.

Prognostic value of protein biomarkers in liver transplantation: A systematic review

Liver transplantation is currently the preferred method for the treatment of advanced liver disease and early-stage hepatocellular carcinoma (HCC). Although advances in surgical techniques, immunosuppressive drugs and postoperative management have reduced the incidence of postoperative complications, how to effectively predict or diagnose postoperative complications earlier and reduce their incidence is still a clinical concern. We performed a comprehensive proteomics literature research to identified protein biomarkers in complications after liver transplantation. Seventeen studies met the inclusion criteria including ischemia reperfusion injury (IRI) (n = 4), acute rejection (AR) (n = 4), renal dysfunction (n = 4), HCC recurrence (n = 2), primary graft dysfunction (PGD) (n = 1), infection (n = 1), and liver fibrosis (n = 1). A total of 625 differentially expressed proteins (DEPs) have been reported between postoperative complications and controls, of which 63 have been validated by quantitative protein expression and 26 have been reported by at least two studies and showed consistently changes. The results of the bioinformation analysis show that the immune system, especially the innate immune system and cytokine signaling in immune system, is an important protein-mediated pathway that affects the prognosis of liver transplantation.

Noninvasive Diagnosis of Acute Rejection in Renal Transplant Patients Using Mass Spectrometric Analysis of Urine Samples: A Multicenter Diagnostic Phase III Trial

Timely recognition and treatment of acute kidney graft rejection is important to prevent premature graft failure. A predefined urinary marker set for acute T cell–mediated rejection (TCMR) containing 14 peptides was tested for this purpose in a multicenter in-place validation study.

A Prospective Multicenter Trial to Evaluate Urinary Metabolomics for Non-invasive Detection of Renal Allograft Rejection (PARASOL): Study Protocol and Patient Recruitment

Background: In an earlier monocentric study, we have developed a novel non-invasive test system for the prediction of renal allograft rejection, based on the detection of a specific urine metabolite constellation. To further validate our results in a large real-world patient cohort, we designed a multicentric observational prospective study (PARASOL) including six independent European transplant centers. This article describes the study protocol and characteristics of recruited better patients as subjects. Methods: Within the PARASOL study, urine samples were taken from renal transplant recipients when kidney biopsies were performed. According to the Banff classification, urine samples were assigned to a case group (renal allograft rejection), a control group (normal renal histology), or an additional group (kidney damage other than rejection). Results: Between June 2017 and March 2020, 972 transplant recipients were included in the trial (1,230 urine samples and matched biopsies, respectively). Overall, 237 samples (19.3%) were assigned to the case group, 541 (44.0%) to the control group, and 452 (36.7%) samples to the additional group. About 65.9% were obtained from male patients, the mean age of transplant recipients participating in the study was 53.7 ± 13.8 years. The most frequently used immunosuppressive drugs were tacrolimus (92.8%), mycophenolate mofetil (88.0%), and steroids (79.3%). Antihypertensives and antidiabetics were used in 88.0 and 27.4% of the patients, respectively. Approximately 20.9% of patients showed the presence of circulating donor-specific anti-HLA IgG antibodies at time of biopsy. Most of the samples (51.1%) were collected within the first 6 months after transplantation, 48.0% were protocol biopsies, followed by event-driven (43.6%), and follow-up biopsies (8.5%). Over time the proportion of biopsies classified into the categories Banff 4 (T-cell-mediated rejection [TCMR]) and Banff 1 (normal tissue) decreased whereas Banff 2 (antibody-mediated rejection [ABMR]) and Banff 5I (mild interstitial fibrosis and tubular atrophy) increased to 84.2 and 74.5%, respectively, after 4 years post transplantation. Patients with rejection showed worse kidney function than patients without rejection. Conclusion: The clinical characteristics of subjects recruited indicate a patient cohort typical for routine renal transplantation all over Europe. A typical shift from T-cellular early rejections episodes to later antibody mediated allograft damage over time after renal transplantation further strengthens the usefulness of our cohort for the evaluation of novel biomarkers for allograft damage.

Prediction of acute rejection in kidney transplanted patients based on the point-of-care isothermal molecular diagnostics platform

In this study, we proposed an advanced point-of-care molecular diagnostic technology to evaluate the acute rejection (AR) in kidney transplanted patients. On the contrary to the conventional PCR method, we developed a colorimetric loop mediated isothermal amplification (LAMP) for quantitative analysis of the six biomarkers related to AR (CD3ϵ, IP-10, Tim-3-HAVCR2, CXCL9, PSMB9, C1QB) with a reference gene (18S rRNA). Using urinary cDNA samples of transplanted patients, it turned out that three biomarkers among six, namely IP-10, Tim-3-HAVCR2 and C1QB, have significant discrepancy in quantity between the stable graft (STA) patient and the AR patient. The AR prediction model using these three biomarkers was established, which could estimate the immune-rejection in the patients with 93.3% of accuracy. For the point-of-care (POC) molecular diagnostics for the AR evaluation, we constructed a centrifugal microfluidic platform, in which the RNA extraction from the clinical urinary samples, the quantitative reverse-transcription (RT)-LAMP reaction, and the data analysis based on the AR prediction model could be performed in a serial order. Ten blind clinical samples were analyzed on the POC genetic analyzer, showing 100% match with the validated qPCR data. Thus, the proposed advanced molecular diagnostic platform enables us to perform the timely treatment for the transplanted patients who are suffering from the allograft failure and side effects such as infection and malignancy.

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.

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.

Biomarkers of rejection in kidney transplantation

PURPOSE OF REVIEW

To provide an update of the literature on the use of new biomarkers of rejection in kidney transplant recipients.

RECENT FINDINGS

The kidney allograft biopsy is currently considered the gold standard for the diagnosis of rejection. However, the kidney biopsy is invasive and could be indeterminate. A significant progress has been made in discovery of new biomarkers of rejection, and some of them have been introduced recently for potential use in clinical practice including measurement of serum donor-derived cell free DNA, allo-specific CD154 + T-cytotoxic memory cells, and gene-expression 'signatures'. The literature supports that these biomarkers provide fair and reliable diagnostic accuracy and may be helpful in clinical decision-making when the kidney biopsy is contraindicated or is inconclusive.

SUMMARY

The new biomarkers provide a promising approach to detect acute rejections in a noninvasive way.

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.

A urinary metabolite constellation to detect acute rejection in kidney allografts

BACKGROUND

To validate a novel method for post-transplant surveillance to detect kidney allograft rejection via a characteristic constellation of the urine metabolites alanine, citrate, lactate, and urea investigated by nuclear magnetic resonance (NMR) spectroscopy a first prospective, observational study was performed.

METHODS

Within the UMBRELLA study 986 urine specimens were collected from 109 consecutively enrolled renal transplant recipients, and metabolite constellations were analyzed. A metabolite rejection score was calculated and compared to histopathological results of corresponding indication and protocol allograft biopsies (n = 206).

FINDINGS

The metabolite constellation was found to be a useful biomarker to non-invasively detect acute allograft rejection (AUC = 0.75; 95% confidence interval (CI) 0.68-0.83; based on 46 cases and 520 control samples). Combined analysis of the metabolite rejection score and the estimated glomerular filtration rate (eGFR) at the time of urine sampling further improved the overall test performance significantly (AUC = 0.84; 95% CI 0.76-0.91; based on 42 cases and 468 controls). Regarding the time course analysis in patients without rejection episodes the test results remained well below a diagnostic threshold associated with high risk of acute rejection. In other cases, a marked increase above this threshold indicated acute allograft rejection already six to ten days before diagnostic renal biopsies were performed.

INTERPRETATION

A combination of an NMR-based urine metabolite analysis and eGFR is promising as a non-invasive test for post-transplant surveillance and to support decision making whether renal allografts need histopathological evaluation.

Circulating microvesicle protein is associated with renal transplant outcome

Renal transplantation is an effective therapy with improved long-term outcomes compared with other therapies for end stage renal disease. Present methods for evaluating kidney allograft function, such as serum creatinine or allograft biopsy, are not sensitive and identify pathological changes only after any potential intervention would be effective. Thus, there is a necessity for biomarkers that would provide early prognostic information about kidney transplant outcomes. Circulating microvesicles represent an attractive source of biomarkers for different diseases including renal failure. We have studied the proteins of the circulating microvesicles from two populations of kidney transplant recipients (n = 20) with poor transplant outcomes (n = 10) or good transplant outcome (n = 10), according to their estimated glomerular filtration rate (eGFR). Microvesicles from age-matched healthy subjects (n = 10) were used as a control. Also, we performed a pilot study to assess the microvesicle protein in kidney transplant recipients before and six months after kidney transplant (n = 6), compared to healthy subjects. Proteomic analysis of microvesicles could discriminate between transplant recipients and healthy subjects, and between transplant patients based on eGFR. Our results shed light on the potential of blood microvesicles to provide a novel tool for the prediction of the outcome of kidney transplants.

Increased levels of circulating MMP3 correlate with severe rejection in face transplantation

Face transplantation is a viable treatment option for carefully selected patients with devastating injuries to the face. However, acute rejection episodes occur in more than 80% of recipients in the first postoperative year. Unfortunately, neither a correlation between histological grades of rejection and anti-rejection treatment nor systemic surrogate markers of rejection in face transplantation are established in clinical routine. Therefore, we utilized next generation aptamer-based SOMAscan proteomics platform for non-invasive rejection biomarker discovery. Longitudinal serum samples from face transplant recipients with long-term follow-up were included in this study. From the 1,310 proteins analyzed by SOMAscan, a 5-protein signature (MMP3, ACY1, IL1R2, SERPINA4, CPB2) was able to discriminate severe rejection from both no-rejection and nonsevere rejection samples. Technical validation on ELISA platform showed high correlation with the SOMAscan data for the MMP3 protein (r_s = 0.99). Additionally, MMP3 levels were significantly increased during severe rejection as compared to no-rejection (p = 0.0009) and nonsevere rejection (p = 0.0173) episodes. Pathway analyses revealed significant activation of the metallopeptidase activity during severe face transplant rejection. This pilot study demonstrates the feasibility of SOMAscan to identify non-invasive candidate biomarkers of rejection in face transplantation. Further validation in a larger independent patient cohort is needed.

GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection

BACKGROUND

Acute renal allograft rejection is a common complication after renal transplantation that often leads to chronic rejection and ultimate graft loss. While renal allograft biopsy remains the gold standard for diagnosis of acute rejection, the possibility of biopsy-associated complications cannot be overlooked. The development of noninvasive methods for accurate detection of acute renal allograft rejection is thus of significant clinical importance.

METHODS

Gas chromatography-mass spectrometry (GC/MS) was employed for analysis of urine metabolites in 15 renal allograft recipients with acute rejection and 15 stable renal transplant recipients. Partial least squares (PLS) regression and leave-one-out analyses were performed to ascertain whether the metabolites identified could be exploited to distinguish acute rejection from stable groups as well as their sensitivity and specificity.

RESULTS

Overall, 14 metabolites were significantly altered in the acute rejection group (11 and 3 metabolites displayed higher and lower levels, respectively) relative to the stable transplant group. Data from PLS and leave-one-out analyses revealed that the differential metabolites identified not only distinguished acute rejection from stable transplant recipients but also showed high sensitivity and specificity for diagnosis of renal allograft recipients with acute rejection.

CONCLUSION

Urine metabolites identified with GC/MS can effectively distinguish acute rejection from stable transplant recipients, supporting the potential utility of metabolome analysis in non-invasive diagnosis of acute rejection.

Plasma Exosomes From HLA-Sensitized Kidney Transplant Recipients Contain mRNA Transcripts Which Predict Development of Antibody-Mediated Rejection

BACKGROUND

Sensitization to HLA remains a significant immunologic barrier to successful transplantation. Identifying immune mechanisms responsible for antibody-mediated rejection (AMR) is an important goal. Here, we explored the possibility of predicting the risk for AMR by measuring mRNA transcripts of AMR-associated genes in plasma exosomes from kidney transplant patients.

METHODS

Total RNA was extracted from exosomes purified from 152 ethylenediaminetetraacetic acid-plasma samples of 64 patients (18 AMR, 8 cell-mediated rejection [CMR], 38 no rejection in desensitized [DES] and non-DES control groups) for reverse transcription into cDNA, preamplification and then real time quantitative polymerase chain reaction (qPCR) for 21 candidate genes. The mRNA transcript levels of each gene were calculated. Comparisons were made among 4 patient groups for each gene and also for a gene combination score based on selected genes.

RESULTS

Among 21 candidate genes, we identified multiple genes (gp130, CCL4, TNFα, SH2D1B, CAV1, atypical chemokine receptor 1 [duffy blood group]) whose mRNA transcript levels in plasma exosomes significantly increased among AMR compared with CMR and/or control patients. A gene combination score calculated from 4 genes of gp130, SH2D1B, TNFα, and CCL4 was significantly higher in the AMR than the CMR (P < 0.0001) and no rejection control groups (P < 0.01 vs DES control, P < 0.05 vs non-DES control).

CONCLUSIONS

Our results suggest that plasma exosomes may contain information indicating clinical conditions of kidney transplant patients. mRNA transcript profiles based on gp130, SH2D1B, TNFα, and CCL4 in plasma exosomes may be used to predict on-going and/or imminent AMR.

Assessment of Circulating Protein Signatures for Kidney Transplantation in Pediatric Recipients

Identification and use of non-invasive biomarkers for kidney transplantation monitoring is an unmet need. A total of 121 biobanked sera collected from 111 unique kidney transplant (KT) patients (children and adolescent) and 10 age-matched healthy normal controls were used to profile serum proteins using semi-quantitative proteomics. The proteomics data were analyzed to identify panels of serum proteins that were specific to various transplant injuries, which included acute rejection (AR), BK virus nephropathy (BKVN), and chronic allograft nephropathy (CAN). Gene expression data from matching peripheral blood mononuclear cells were interrogated to investigate the association between soluble serum proteins and altered gene expression of corresponding genes in different injury phenotypes. Analysis of the proteomics data identified from different patient phenotypes, with criteria of false discovery rate <0.05 and at least twofold changes in either direction, resulted in a list of 10 proteins that distinguished KT injury from no injury. Similar analyses to identify proteins specific to chronic injury, acute injury, and AR after kidney transplantation identified 22, 6, and 10 proteins, respectively. Elastic-Net logistic regression method was applied on the 137 serum proteins to classify different transplant injuries. This algorithm has identified panels of 10 serum proteins specific for AR, BKVN, and CAN with classification rates 93, 93, and 95%, respectively. The identified proteins could prove to be potential surrogate biomarkers for routine monitoring of the injury status of pediatric KT patients.

Establishing Biomarkers in Transplant Medicine: A Critical Review of Current Approaches

Although the management of kidney transplant recipients has greatly improved over recent decades, the assessment of individual risks remains highly imperfect. Individualized strategies are necessary to recognize and prevent immune complications early and to fine-tune immunosuppression, with the overall goal to improve patient and graft outcomes. This review discusses current biomarkers and their limitations, and recent advancements in the field of noninvasive biomarker discovery. A wealth of noninvasive monitoring tools has been suggested that use easily accessible biological fluids such as urine and blood, allowing frequent and sequential assessments of recipient's immune status. This includes functional cell-based assays and the evaluation of molecular expression on a wide spectrum of platforms. Nevertheless, the translation and validation of exploratory findings and their implementation into standard clinical practice remain challenging. This requires dedicated prospective interventional trials demonstrating that the use of these biomarkers avoids invasive procedures and improves patient or transplant outcomes.

Non-invasive approaches in the diagnosis of acute rejection in kidney transplant recipients, part II: omics analyses of urine and blood samples

Kidney transplantation (KTx) represents the best available treatment for patients with end-stage renal disease. Still, the full benefits of KTx are undermined by acute rejection (AR). The diagnosis of AR ultimately relies on transplant needle biopsy. However, such an invasive procedure is associated with a significant risk of complications and is limited by sampling error and interobserver variability. In the present review, we summarize the current literature about non-invasive approaches for the diagnosis of AR in kidney transplant recipients (KTRs), including in vivo imaging, gene-expression profiling and omics analyses of blood and urine samples. Most imaging techniques, such as contrast-enhanced ultrasound and magnetic resonance, exploit the fact that blood flow is significantly lowered in case of AR-induced inflammation. In addition, AR-associated recruitment of activated leucocytes may be detectable by 18F-fluorodeoxyglucose positron emission tomography. In parallel, urine biomarkers, including CXCL9/CXCL10 or a three-gene signature of CD3ε, CXCL10 and 18S RNA levels, have been identified. None of these approaches has yet been adopted in the clinical follow-up of KTRs, but standardization of analysis procedures may help assess reproducibility and comparative diagnostic yield in large, prospective, multicentre trials.