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

Gene Expression-based Molecular Scoring of Pancreas Transplant Rejection for a Quantitative Assessment of Rejection Severity and Resistance to Treatment

Pancreas transplantation improves glycemic control and mortality in patients with diabetes but requires aggressive immunosuppression to control the alloimmune and autoimmune response. Recent developments in "omics' methods have provided gene transcript-based biomarkers for organ transplant rejection. The tissue Common Response Module (tCRM) score is developed to identify the severity of rejection in kidney, heart, liver, and lung transplants. Still, it has not yet been validated in pancreas transplants (PT). We evaluated the tCRM score's relevance in PT and additional markers of acute cellular rejection (ACR) for PT. An analysis on 51 pancreas biopsies with ACR identified 37 genes and 56 genes significantly upregulated in the case of grade 3 and grade 2 ACR respectively (P<0.05). Significant differences were seen with higher grades of rejection among several transcripts. Of the 22 genes differentially expressed in Grade 3 ACR, 18 were also differentially expressed in Grade 2 ACR. The rejection signal was attributable to activated leukocytes' infiltration. Significantly higher tCRM scores were found in grade 3 ACR (p = 0.007) and grade 2 ACR (p = 0.004), compared to normal samples. The tCRM score was able to distinguish treatment-resistant cases from those successfully treated for rejection.

Transforming kidney transplant monitoring with urine CXCL9 and CXCL10: practical clinical implementation

In kidney transplant recipients, urine CXCL9 and CXCL10 (uCXCL9/10) chemokines have reached a sufficiently high level of evidence to be recommended by the European Society of Organ Transplantation for the monitoring of immune quiescence. To assess the risk of acute rejection (AR), the advantage of uCXCL9/10 is their cost-effectiveness and their high diagnostic performance. Here, we evaluated the feasibility of a next-generation immunoassay for quantifying uCXCL9/10 levels. It demonstrated high efficiency with minimal workflow and a 90-min time to result. Preanalytical studies indicated stability of uCXCL9/10 levels and analytical studies confirmed excellent linearity and precision. In a cohort of 1048 samples collected at biopsy, the results correlated significantly with ELISA quantification and were integrated into a previously validated 8-parameter urine chemokine model. The next generation immunoassay achieved an accuracy of 0.84 for AR diagnosis. This study validates this technology as a robust, locally available and unexpensive platform and marks a significant step towards the widespread implementation of uCXCL9/10, for immune quiescence monitoring. Therefore, we developed an open-access web application using uCXCL9/10 to calculate AR risk and improve clinical decision-making to perform biopsy, ushering in a new era in kidney transplantation, where personalized, data-driven care becomes the norm.

Detection of Subclinical Rejection in Pediatric Kidney Transplantation: Current and Future Practices

INTRODUCTION

The successes in the field of pediatric kidney transplantation over the past 60 years have been extraordinary. Year over year, there have been significant improvements in short-term graft survival. However, improvements in longer-term outcomes have been much less apparent. One important contributor has been the phenomenon of low-level rejection in the absence of clinical manifestations-so-called subclinical rejection (SCR).

METHODS

Traditionally, rejection has been diagnosed by changes in clinical parameters, including but not limited to serum creatinine and proteinuria. This review examines the shortcomings of this approach, the effects of SCR on kidney allograft outcome, the benefits and drawbacks of surveillance biopsies to identify SCR, and new urine and blood biomarkers that define the presence or absence of SCR.

RESULTS

Serum creatinine is an unreliable index of SCR. Surveillance biopsies are the method most utilized to detect SCR. However, these have significant drawbacks. New biomarkers show promise. These biomarkers include blood gene expression profiles and donor derived-cell free DNA; urine gene expression profiles; urinary cytokines, chemokines, and metabolomics; and other promising blood and urine tests.

CONCLUSION

Specific emphasis is placed on studies carried out in pediatric kidney transplant recipients.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT03719339.

Improving liver transplant outcomes with transplant-omics and network biology

PURPOSE OF REVIEW

Molecular omics data is increasingly ubiquitous throughout medicine. In organ transplantation, recent large-scale research efforts are generating the 'transplant-ome' - the entire set of molecular omics data, including the genome, transcriptome, proteome, and metabolome. Importantly, early studies in anesthesiology have demonstrated how perioperative interventions alter molecular profiles in various patient populations. The next step for anesthesiologists and intensivists will be to tailor perioperative care to the transplant-ome of individual liver transplant patients.

RECENT FINDINGS

In liver transplant patients, elements of the transplant-ome predict complications and point to novel interventions. Importantly, molecular profiles of both the donor organ and recipient contribute to this risk, and interventions like normothermic machine perfusion influence these profiles. As we can now measure various omics molecules simultaneously, we can begin to understand how these molecules interact to form molecular networks and emerging technologies offer noninvasive and continuous ways to measure these networks throughout the perioperative period. Molecules that regulate these networks are likely mediators of complications and actionable clinical targets throughout the perioperative period.

SUMMARY

The transplant-ome can be used to tailor perioperative care to the individual liver transplant patient. Monitoring molecular networks continuously and noninvasively would provide new opportunities to optimize perioperative management.

Evolution of human kidney allograft pathology diagnostics through 30 years of the Banff classification process

The second half of the previous century witnessed a tremendous rise in the number of clinical kidney transplants worldwide. This activity was, however, accompanied by many issues and challenges. An accurate diagnosis and appropriate management of causes of graft dysfunction were and still are, a big challenge. Kidney allograft biopsy played a vital role in addressing the above challenge. However, its interpretation was not standardized for many years until, in 1991, the Banff process was started to fill this void. Thereafter, regular Banff meetings took place every 2 years for the past 30 years. Marked changes have taken place in the interpretation of kidney allograft biopsies, diagnosis, and classification of rejection and other non-rejection pathologies from the original Banff 93 classification. This review attempts to summarize those changes for increasing the awareness and understanding of kidney allograft pathology through the eyes of the Banff process. It will interest the transplant surgeons, physicians, pathologists, and allied professionals associated with the care of kidney transplant patients.

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

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

A plasmatic score using a miRNA signature and CXCL-10 for accurate prediction and diagnosis of liver allograft rejection

Introduction

The use of noninvasive biomarkers may avoid the need for liver biopsy (LB) and could guide immunosuppression adjustment in liver transplantation (LT). The aims of this study were: to confirm the predictive and diagnostic capacity of plasmatic expression of miR-155-5p, miR-181a-5p, miR-122-5p and CXCL-10 for assessing T-cell mediated rejection (TCMR) risk; to develop a score based on a panel of noninvasive biomarkers to predict graft rejection risk and to validate this score in a separate cohort.

Methods

A prospective, observational study was conducted with a cohort of 79 patients followed during the first year after LT. Plasma samples were collected at predetermined time points for the analysis of miRNAs and the CXCL-10. Patients with LFTs abnormalities were submitted to a LB to rule out rejection, assessing previous and concurrent expression of the biomarkers to evaluate their predictive and diagnostic ability. Information from 86 patients included in a previous study was collected and used as a validation cohort.

Results

Twenty-four rejection episodes were diagnosed in 22 patients. Plasmatic CXCL-10 concentration and the expression of the three miRNAs were significantly elevated prior to and at the moment of the diagnosis of rejection. We developed a logistic model for rejection prediction and diagnosis, which included CXCL-10, miR-155-5p and miR-181a-5p. The area under the ROC curve (AUROC) for rejection prediction was 0.975 (79.6% sensitivity, 99.1% specificity, 90,7% PPV; 97.7% NPV; 97.1% correctly classified) and 0.99 for diagnosis (87.5% sensitivity, 99.5% specificity, 91.3% PPV; 99.3% NPV; 98.9% correctly classified). In the validation cohort (n=86; 14 rejections), the same cut-off points were used obtaining AUROCs for rejection prediction and diagnosis of 0.89 and 0.92 respectively. In patients with graft dysfunction in both cohorts the score could discriminate those with rejection regarding other causes with an AUROC of 0.98 (97.3% sensitivity, 94.1%specificity).

Conclusion

These results suggest that the clinical implementation of the monitoring of this noninvasive plasmatic score may allow the prediction and diagnosis of rejection and identify patients with graft dysfunction due to rejection, helping with a more efficient guide for immunosuppressive therapy adjustment. This finding warrants the development of prospective biomarker-guided clinical trials.

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

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

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.

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.

Noninvasive Assessment of the Alloimmune Response in Kidney Transplantation

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

Are borderline changes real rejection? Current viewpoints

PURPOSE OF REVIEW

The clinical significance and treatment of borderline changes are controversial. The lowest detectable margin for rejection on histology is unclear. We review recent evidence about borderline changes and related biomarkers.

RECENT FINDINGS

Borderline change (Banff ≥ t1i1) is associated with progressive fibrosis, a greater propensity to form de-novo DSA, and reduced graft survival. Isolated tubulitis appears to have similar kidney allograft outcomes with normal controls, but this finding should be validated in a larger, diverse population. When borderline change was treated, a higher chance of kidney function recovery and better clinical outcomes were observed. However, spontaneous borderline changes resolution without treatment was also observed. Various noninvasive diagnostic biomarkers have been developed to diagnose subclinical acute rejection, including borderline changes and ≥ Banff 1A TCMR. Biomarkers using gene expression and donor-derived cell-free DNA, and HLA DR/DQ eplet mismatch show potential to diagnose subclinical acute rejection (borderline change and ≥Banff 1A TCMR), to avoid surveillance biopsy, or to predict poor kidney allograft outcomes.

SUMMARY

Borderline changes are associated with poor kidney allograft outcomes, but it remains unclear if all cases of borderline changes should be treated. Novel biomarkers may inform physicians to aid in the diagnosis and treatment.

Non-Invasive Diagnosis for Acute Rejection Using Urinary mRNA Signature Reflecting Allograft Status in Kidney Transplantation

Urine has been regarded as a good resource based on the assumption that urine can directly reflect the state of the allograft or ongoing injury in kidney transplantation. Previous studies, suggesting the usefulness of urinary mRNA as a biomarker of acute rejection, imply that urinary mRNA mirrors the transcriptional activity of the kidneys. We selected 14 data-driven candidate genes through a meta-analysis and measured the candidate genes using quantitative PCR without pre-amplification in the cross-sectional specimens from Korean kidney transplant patients. Expression of 9/14 genes (CXCL9, CD3ϵ, IP-10, LCK, C1QB, PSMB9, Tim-3, Foxp3, and FAM26F) was significantly different between acute rejection and stable graft function with normal pathology and long-term graft survival in 103 training samples. CXCL9 was also distinctly expressed in allografts with acute rejection in in situ hybridization analysis. This result, consistent with the qPCR result, implies that urinary mRNA could reflect the magnitude of allograft injury. We developed an AR prediction model with the urinary mRNAs by a binary logistic regression and the AUC of the model was 0.89 in the training set. The model was validated in 391 independent samples, and the AUC value yielded 0.84 with a fixed manner. In addition, the decision curve analysis indicated a range of reasonable threshold probabilities for biopsy. Therefore, we suggest the urine mRNA signature could be used as a non-invasive monitoring tool of acute rejection for clinical application and could help determine whether to perform a biopsy in a recipient with increased creatinine.

[Urinary biomarkers in kidney transplant recipients: From technological innovations to clinical development]

In kidney transplantation, the assessment of individual risks remains highly imperfect and highlights the need for robust noninvasive biomarkers with the overall goal to improve patient and graft outcomes. In the field of noninvasive biomarkers discovery, urinary biomarkers are promising tools which use easily accessible biological fluid. During the past decades, the technical revolution in the fields of genetics and molecular biology, and advances in chemistry and data analysis have led to a wealth of studies using urinary cell pellets or supernatants from kidney transplant recipients. Transcriptomic, proteomic and metabonomic analyses have suggested numerous signatures for the diagnoses of acute rejection, delayed-graft function or interstitial fibrosis. 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.

Urinary C-X-C Motif Chemokine 10 Is Related to Acute Graft Lesions Secondary to T Cell- and Antibody-Mediated Damage

Background

Non-invasive biomarkers of graft rejection are needed to optimize the management and outcomes of kidney transplant recipients. Urinary excretion of IFN-γ-related chemokine CXCL10 is clearly associated with clinical and subclinical T cell-mediated graft inflammation, but its relationship with antibody-mediated damage has not been fully addressed. Further, the variables influencing levels of urinary CXCL10 excretion are unknown.

Material/Methods

A total of 151 kidney graft biopsies (92 surveillance and 59 indication biopsies) and 151 matched urine samples obtained before biopsy were prospectively analyzed. T cell-mediated rejection (TCMR) and antibody-mediated rejection (AbMR) were defined according to the 2017 Banff classification criteria. Urinary CXCL10 levels were measured by ELISA and corrected by urinary creatinine.

Results

Banff scores ‘t’, ‘i’, ‘g’, and ‘ptc’ were significantly related to urinary CXCL10 levels. Multivariate analysis showed that ‘t’ (β=0.107, P=0.001) and ‘ptc’ (β=0.093, P=0.002) were significantly associated with urinary CXCL10. Donor-specific antibodies (DSAs) were related to the high excretion of urinary CXCL10 at 1 year after transplantation (odds ratio [OR] 17.817, P=0.003). Urinary CXCL10 showed good discrimination ability for AbMR (AUC-ROC 0.760, P=0.001). The third tertile of urinary CXCL10 remained significantly associated with AbMR (OR 4.577, 95% confidence interval 1.799–11.646, P=0.001) after multivariate regression analysis.

Conclusions

DSA was the only variable clearly related to high urinary CXCL10 levels. Urinary CXCL10 is a good non-invasive candidate biomarker of AbMR and TCMR, supplying information independent of renal function and other variables normally used to monitor kidney transplants.

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

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

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

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

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.

Role of novel biomarkers in kidney transplantation

Clinical application of biomarkers is an integral component of transplant care. Clinicians and scientists alike are in search of better biomarkers than the current serologic (serum creatinine, donor-specific antibodies), urine-derived (urinalysis, urine protein), and histologic ones we now use. The science behind recent biomarker discovery spans across multiple molecular biologic disciplines, including transcriptomics, proteomics, and metabolomics. Innovative methodology and integration of basic and clinical approaches have allowed researchers to unearth molecular phenomena preceding clinical disease. Biomarkers can be classified in several ways. In this review, we have classified them via their origin and outcome: Primarily immunologic, i.e., representative of immune regulation and dysfunction and non-immunologic, pertaining to delayed graft function, cardiovascular events/mortality, infection, malignancy, post-transplant diabetes, graft, and patient survival. Novel biomarker uses to guide the diagnosis and management of transplant-related outcomes is a promising area of research. However, the use of biomarkers to predict outcomes after kidney transplantation is not well studied. In this review, we summarize the recent studies illustrating biomarker use and transplant outcomes.

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

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

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.

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.

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.