International variation in the interpretation of renal transplant biopsies: report of the CERTPAP Project

A universal urinary cell gene signature of acute rejection in kidney allografts

INTRODUCTION

Acute rejection (AR) undermines the life-extending benefits of kidney transplantation and is diagnosed using the invasive biopsy procedure. T cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR), or concurrent TCMR + ABMR (Mixed Rejection [MR]) are the three major types of AR. Development of noninvasive biomarkers diagnostic of AR due to any of the three types is a useful addition to the diagnostic armamentarium.

METHODS

We developed customized RT-qPCR assays and measured urinary cell mRNA copy numbers in 145 biopsy-matched urine samples from 126 kidney allograft recipients. We determined whether the urinary cell three-gene signature diagnostic of TCMR (Suthanthiran et al., 2013) discriminates patients with no rejection biopsies (NR, n = 50) from those with ABMR (n = 28) or MR (n = 20) biopsies.

RESULTS

The urinary cell three-gene signature discriminated all three types of rejection biopsies from NR biopsies (P < 0.0001, One-way ANOVA). Dunnett's multiple comparisons test yielded P < 0.0001 for NR vs. TCMR; P < 0.001 for NR vs. ABMR; and P < 0.0001 for NR vs. MR. By bootstrap resampling, optimism-corrected area under the receiver operating characteristic curve (AUC) was 0.749 (bias-corrected 95% confidence interval [CI], 0.638 to 0.840) for NR vs. TCMR (P < 0.0001); 0.780 (95% CI, 0.656 to 0.878) for NR vs. ABMR (P < 0.0001); and 0.857 (95% CI, 0.727 to 0.947) for NR vs. MR (P < 0.0001). All three rejection categories were distinguished from NR biopsies with similar accuracy (all AUC comparisons P > 0.05).

CONCLUSION

The urinary cell three-gene signature score discriminates AR due to TCMR, ABMR or MR from NR biopsies in human kidney allograft recipients.

Development of a suitable vibration pad for renal MR elastography

The aim of this study was to develop a vibration pad suitable for renal MR elastography (MRE). Chronic kidney disease (CKD) is a progressive condition affecting >800 million people worldwide. Renal fibrosis is a common pathological feature of CKD that causes fibrotic regions to be much stiffer than those in normal renal tissues. Therefore, MRE can be used to diagnose CKD because it can image organ stiffness. In MRE, the shear modulus is obtained from the wavelength of the shear waves. Therefore, it is highly important to propagate shear waves with sufficient vibration strength in the tissue. By using a three-dimensional (3D) printer, we created a "Flexible Pad" suitable for renal MRE. The Flexible Pad was placed under the back of the participant in the supine position and deformed in response to the participant's weight, adhering closely to the body surface. Six healthy volunteers participated in this study. Our Flexible Pad allowed for coherent shear waves (clear waves with little scattering and interference) to be efficiently transmitted to the kidney deep-lying tissues in the abdomen. The shear moduli of the kidney (n = 6) were 8.95 ± 0.84 kPa in the right kidney and 9.70 ± 0.99 kPa in the left kidney. Our results indicate that using our Flexible Pad for renal MRE can provide a more reliable measurement of renal shear modulus.

Biopsy-based transcriptomics in the diagnosis of kidney transplant rejection

PURPOSE OF REVIEW

The last year has seen considerable progress in translational research exploring the clinical utility of biopsy-based transcriptomics of kidney transplant biopsies to enhance the diagnosis of rejection. This review will summarize recent findings with a focus on different platforms, potential clinical applications, and barriers to clinical adoption.

RECENT FINDINGS

Recent literature has focussed on using biopsy-based transcriptomics to improve diagnosis of rejection, in particular antibody-mediated rejection. Different techniques of gene expression analysis (reverse transcriptase quantitative PCR, microarrays, probe-based techniques) have been used either on separate samples with ideally preserved RNA, or on left over tissue from routine biopsy processing. Despite remarkable consistency in overall patterns of gene expression, there is no consensus on acceptable indications, or whether biopsy-based transcriptomics adds significant value at reasonable cost to current diagnostic practice.

SUMMARY

Access to biopsy-based transcriptomics will widen as regulatory approvals for platforms and gene expression models develop. Clinicians need more evidence and guidance to inform decisions on how to use precious biopsy samples for biopsy-based transcriptomics, and how to integrate results with standard histology-based diagnosis.

Urinary Cell Gene Signature of Acute Rejection in Kidney Allografts

Introduction

A kidney allograft biopsy may display acute T cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR), or concurrent TCMR + ABMR (MR). Development of noninvasive biomarkers diagnostic of all three types of acute rejection is a useful addition to the diagnostic armamentarium.

Methods

We developed customized RT-qPCR assays and measured urinary cell mRNA copy number in 145 biopsy-matched urine samples from 126 kidney allograft recipients and calculated urinary cell three-gene signature score from log 10 -transformed values for the 18S-normalized CD3E mRNA, 18S-normalized CXCL10 mRNA and 18S rRNA. We determined whether the signature score in biopsy-matched urine specimens discriminates biopsies without rejection (NR, n=50) from biopsies displaying TCMR (n=47), ABMR (n=28) or MR (n=20).

Results

Urinary cell three-gene signature discriminated TCMR, ABMR or MR biopsies from NR biopsies (P <0.0001, One-way ANOVA). Dunnett's multiple comparisons test yielded P<0.0001 for NR vs. TCMR; P <0.001 for NR vs. ABMR; and P <0.0001 for NR vs. MR. By bootstrap resampling, optimism-corrected area under the receiver operating characteristic curve (AUC) was 0.749 (bias-corrected 95% confidence interval [CI], 0.638 to 0.840) for NR vs. TCMR (P<0.0001); 0.780 (95% CI, 0.656 to 0.878) for NR vs. ABMR (P<0.0001); and 0.857 (95% CI, 0.727 to 0.947) for NR vs. MR (P<0.0001). All three rejection biopsy categories were distinguished from NR biopsies with similar accuracy (all AUC comparisons P>0.05).

Conclusion

Urinary cell three-gene signature score may serve as a universal diagnostic signature of acute rejection due to TCMR, ABMR or MR in human kidney allografts with similar performance characteristics.

Plasma protein signatures reflect systemic immunity and allograft function in kidney transplantation

Kidney transplantation causes large perturbations of the immune system. While many studies focus on the allograft, insights into systemic effects are largely missing. Here, we analyzed the systemic immune response in 3 cohorts of kidney transplanted patients. Using serum proteomics, laboratory values, mass cytometry, histological and clinical parameters, inter-patient heterogeneity was leveraged for multi-omic co-variation analysis. We identified circulating immune modules (CIM) that describe extra-renal signatures of co-regulated plasma proteins. CIM are present in nontransplanted controls, in transplant conditions and during rejection. They are enriched in pathways linked to kidney function, extracellular matrix, signaling, and cellular activation. A complex leukocyte response in the blood during allograft quiescence and rejection is associated with CIM activity and CIM-specific cytokines. CIM activity correlates with kidney function including a 2-month prediction. Together, the data suggest a systemic and multi-layered response of transplant immunity that might be insightful for understanding allograft dysfunction and developing translational biomarkers.

Update on current and potential application of extracellular vesicles in kidney transplantation

Kidney transplantation (KT) is the best treatment for end-stage kidney disease. However, early diagnosis of graft injury remains challenging, mainly because of the lack of accurate and noninvasive diagnostic techniques. Improving graft outcomes is equally demanding, as is the development of innovative therapies. Many research efforts are focusing on extracellular vesicles, cellular particles free in each body fluid that have shown promising results as precise markers of damage and potential therapeutic targets in many diseases, including the renal field. In fact, through their receptors and cargo, they act in damage response and immune modulation. In transplantation, they may be used to determine organ quality and aging, the presence of delayed graft function, rejection, and many other transplant-related pathologies. Moreover, their low immunogenicity and safe profile make them ideal for drug delivery and the development of therapies to improve KT outcomes. In this review, we summarize current evidence about extracellular vesicles in KT, starting with their characteristics and major laboratory techniques for isolation and characterization. Then, we discuss their use as potential markers of damage and as therapeutic targets, discussing their promising use in clinical practice as a form of liquid biopsy.

Reproducibility of Rejection Grading in Uterus Transplantation: A Multicenter Study

Background

Diagnosis of rejection after uterus transplantation is based on histopathological examination of ectocervical biopsies. Inflammation at the stromal-epithelial interface is the backbone of the histopathological classification proposed by our group in 2017. However, the reproducibility of this grading scheme has not been tested, and it is unclear whether it covers the full morphological spectrum of rejection.

Methods

We present a multicenter study in which 5 pathologists from 4 uterus transplantation centers performed 2 rounds of grading on 145 and 48 cervical biopsies, respectively. Three of the centers provided biopsies. Additionally, the presence of perivascular stromal inflammation was recorded. During discussions after the first round, further histological lesions (venous endothelial inflammation and apoptosis) were identified for closer evaluation and added to the panel of lesions to score in the second round. All participants completed a questionnaire to explore current practices in handling and reporting uterus transplant biopsies.

Results

Cervical biopsies were commonly performed in all centers to monitor rejection. Intraobserver reproducibility of rejection grading (performed by 1 rater) was excellent, whereas interobserver reproducibility was moderate and did not improve in the second round. Reproducibility of perivascular stromal inflammation was moderate but unsatisfactory for venous endothelial inflammation and apoptosis. All lesions were more frequent in, but not restricted to, biopsies with rejection patterns.

Conclusions

Grading of rejection in cervical biopsies is reproducible and applicable to biopsies from different centers. Diagnosis of rejection may be improved by adding further histological lesions to the grading system; however, lesions require rigorous consensus definition.

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.

Learning more from the inter-rater reliability of interstitial fibrosis assessment beyond just a statistic

Interstitial fibrosis assessment by renal pathologists lacks good agreement, and we aimed to investigate its hidden properties and infer possible clinical impact. Fifty kidney biopsies were assessed by 9 renal pathologists and evaluated by intraclass correlation coefficients (ICCs) and kappa statistics. Probabilities of pathologists' assessments that would deviate far from true values were derived from quadratic regression and multilayer perceptron nonlinear regression. Likely causes of variation in interstitial fibrosis assessment were investigated. Possible misclassification rates were inferred on reported large cohorts. We found inter-rater reliabilities ranged from poor to good (ICCs 0.48 to 0.90), and pathologists' assessments had the worst agreements when the extent of interstitial fibrosis was moderate. 33.5% of pathologists' assessments were expected to deviate far from the true values. Variation in interstitial fibrosis assessment was found to be correlated with variation in interstitial inflammation assessment (r2 = 32.1%). Taking IgA nephropathy as an example, the Oxford T scores for interstitial fibrosis were expected to be misclassified in 21.9% of patients. This study demonstrated the complexity of the inter-rater reliability of interstitial fibrosis assessment, and our proposed approaches discovered previously unknown properties in pathologists' practice and inferred a possible clinical impact on patients.

Understanding Donor-derived Cell-free DNA in Kidney Transplantation: An Overview and Case-based Guide for Clinicians

Kidney transplant recipients undergo lifelong monitoring of allograft function and evaluation for transplant complications. The current monitoring paradigm utilizes blood, urine, and tissue markers that are insensitive, nonspecific, or invasive to obtain. As a result, problems are detected late, after significant damage has accrued, and often beyond the time at which complete resolution is possible. Indeed, most kidney transplants eventually fail, usually because of chronic rejection and other undetected injury. There is a clear need for a transplant-specific biomarker that enables a proactive approach to monitoring via early detection of reversible pathology. A biomarker that supports timely and personalized treatment would assist in achieving the ultimate goal of improving allograft survival and limiting therapeutic toxicity to the recipient. Donor-derived cell-free DNA (ddcfDNA) has been proposed as one such transplant biomarker. Although the test is presently utilized most in the United States, it is conceivable that its use will become more widespread. This review covers aspects of ddcfDNA that support informed use of the test by general nephrologists, including the basic biology of ddcfDNA, methodological nuances of testing, and general recommendations for use in the kidney transplant population. Clinical contexts are used to illustrate evidence-supported interpretation of ddcfDNA results and subsequent management. Finally, knowledge gaps and areas for further study are discussed.

Systematic Review of the Oxford Classification of IgA Nephropathy: Reproducibility and Prognostic Value

Key Points

The Oxford classification of IgA nephropathy defined five features scored subjectively in renal biopsies, identified by the initials MESTC. Two large studies with independent observers showed reproducibility was moderate for T, moderate or poor for M and S, and poor for E and C. In multivariate analyses including clinical features, T was related to 58% of outcomes, with no correlation of MESTC with 24% of outcomes.

Background

The Oxford classification of IgA nephropathy defined five prognostic features scored subjectively in renal biopsies: mesangial cellularity (M), endocapillary hypercellularity (E), segmental sclerosis (S), interstitial fibrosis/tubular atrophy (T), and (fibro)cellular crescents (C). Pathological scoring systems should be reproducible and have prognostic value independently of clinical features. Reproducibility of the classification was not previously investigated in a systematic review, and the most recent systematic reviews of prognostic value were in 2017.

Methods

This systematic review followed PRISMA 2020 guidelines. MEDLINE, PUBMED, and EMBASE databases were searched using the terms “IgA nephropathy” and “Oxford.” Eligible papers applied the classification and mentioned statistical analysis of interobserver reproducibility and/or included multivariate analysis of outcomes related to individual Oxford scores and clinical features, including treatment with corticosteroids or other immunosuppressive drugs.

Results

There were 99 suitable papers before September 23, 2022. Of 12 papers that mentioned reproducibility, only six reported statistics for MEST/MESTC scoring. Four of these were small studies and/or had observers at the same institution. These were considered less representative of application of the classification than two large studies with independent observers, in which agreement was moderate for T, either moderate or poor for M and S, and poor for E and C. In 92 papers with 125 multivariate analyses of various outcomes, the commonest Oxford element associated with outcomes was T (73 of 125, 58%), with no correlation of any element with outcomes in 30 analyses (24%). Treatment with immunosuppression was often related to scores, particularly C and E, without consistent relations between Oxford scores and outcomes in immunosuppressed patients.

Conclusions

This systematic review showed limitations of the Oxford classification in practice, particularly the moderate or poor reproducibility of scores. T was the Oxford score most often related to clinical outcomes, but even this was not consistently reliable as a prognostic indicator.

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.

Kidney Allograft Monitoring by Combining Donor-Derived Cell-Free DNA and Molecular Gene Expression: A Clinical Management Perspective

Donor-derived cell-free DNA (dd-cfDNA) may safely assess kidney allograft rejection. Molecular Microscope (MMDx®) gene expression may offer increased precision to histology. This single-center retrospective study monitored kidney transplant recipients for rejection at specified time intervals by utilizing creatinine (SCr), proteinuria, donor-specific antibodies (DSAs), and dd-cfDNA. A clinically indicated biopsy sample was sent for histopathology and MMDx®. Patients were categorized into rejection (Rej) and non-rejection (NRej) groups, and further grouped according to antibody-mediated rejection (ABMR) subtypes. Rej and NRej groups included 52 and 37 biopsies, respectively. Median follow-up duration was 506 days. DSAs were positive in 53% and 22% of patients in both groups, respectively (p = 0.01). Among these groups, pre- and post-intervention median SCr, proteinuria, and dd-cfDNA at 1 month, 2 months, and at the last follow-up revealed significant difference for dd-cfDNA (all p = 0.01), however, no difference was found for SCr and proteinuria (p > 0.05). The AUC was 0.80 (95% CI: 0.69-0.91), with an optimal dd-cfDNA criterion of 2.2%. Compared to histology, MMDx® was more likely to diagnose ABMR (79% vs. 100%) with either C4d positivity or negativity and/or DSA positivity or negativity. Hence, a pre- and post-intervention allograft monitoring protocol in combination with dd-cfDNA, MMDx®, and histology has aided in early diagnosis and timely individualized intervention.

Unsatisfactory reproducibility of interstitial inflammation scoring in allograft kidney biopsy

Interstitial inflammation scoring is incorporated into the Banff Classification of Renal Allograft Pathology and is essential for the diagnosis of T-cell mediated rejection. However, its reproducibility, including inter-rater and intra-rater reliabilities, has not been carefully investigated. In this study, eight renal pathologists from different hospitals independently scored 45 kidney allograft biopsies with varying extents of interstitial inflammation. Inter-rater reliabilities and intra-rater reliabilities were investigated by kappa statistics and conditional agreement probabilities. Individual pathologists' scoring patterns were examined by chi-squared tests and proportions tests. The mean pairwise kappa values for inter-rater reliability were 0.27, 0.30, and 0.26 for the Banff i score, ti score, and i-IFTA, respectively. No rater pair performed consistently better or worse than others on all three scorings. After dichotomizing the scores into two groups (none/mild and moderate/severe inflammation), the averaged conditional agreements ranged from 47.1% to 50.0%. The distributions of the scores differed, but some pathologists persistently scored higher or lower than others. Given the important role of interstitial inflammation scoring in the diagnosis of T-cell mediated rejection, transplant practitioners should be aware of the possible clinical implications of the far-from-optimal reproducibility.

An automated histological classification system for precision diagnostics of kidney allografts

For three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has become complex over time with the integration of multimodal data and rules, leading to misclassifications that can have deleterious therapeutic consequences for patients. To improve diagnosis, we developed a decision-support system, based on an algorithm covering all classification rules and diagnostic scenarios, that automatically assigns kidney allograft diagnoses. We then tested its ability to reclassify rejection diagnoses for adult and pediatric kidney transplant recipients in three international multicentric cohorts and two large prospective clinical trials, including 4,409 biopsies from 3,054 patients (62.05% male and 37.95% female) followed in 20 transplant referral centers in Europe and North America. In the adult kidney transplant population, the Banff Automation System reclassified 83 out of 279 (29.75%) antibody-mediated rejection cases and 57 out of 105 (54.29%) T cell-mediated rejection cases, whereas 237 out of 3,239 (7.32%) biopsies diagnosed as non-rejection by pathologists were reclassified as rejection. In the pediatric population, the reclassification rates were 8 out of 26 (30.77%) for antibody-mediated rejection and 12 out of 39 (30.77%) for T cell-mediated rejection. Finally, we found that reclassification of the initial diagnoses by the Banff Automation System was associated with an improved risk stratification of long-term allograft outcomes. This study demonstrates the potential of an automated histological classification to improve transplant patient care by correcting diagnostic errors and standardizing allograft rejection diagnoses.ClinicalTrials.gov registration: NCT05306795 .

Relating Molecular T Cell-mediated Rejection Activity in Kidney Transplant Biopsies to Time and to Histologic Tubulitis and Atrophy-fibrosis

BACKGROUND

We studied the variation in molecular T cell-mediated rejection (TCMR) activity in kidney transplant indication biopsies and its relationship with histologic lesions (particularly tubulitis and atrophy-fibrosis) and time posttransplant.

METHODS

We examined 175 kidney transplant biopsies with molecular TCMR as defined by archetypal analysis in the INTERCOMEX study ( ClinicalTrials.gov #NCT01299168). TCMR activity was defined by a molecular classifier.

RESULTS

Archetypal analysis identified 2 TCMR classes, TCMR1 and TCMR2: TCMR1 had higher TCMR activity and more antibody-mediated rejection ("mixed") activity and arteritis but little hyalinosis, whereas TCMR2 had less TCMR activity but more atrophy-fibrosis. TCMR1 and TCMR2 had similar levels of molecular injury and tubulitis. Both TCMR1 and TCMR2 biopsies were uncommon after 2 y posttransplant and were rare after 10 y, particularly TCMR1. Within late TCMR biopsies, TCMR classifier activity and activity molecules such as IFNG fell progressively with time, but tubulitis and molecular injury were sustained. Atrophy-fibrosis was increased in TCMR biopsies, even in the first year posttransplant, and rose with time posttransplant. TCMR1 and TCMR2 both reduced graft survival, but in random forests, the strongest determinant of survival after biopsies with TCMR was molecular injury, not TCMR activity.

CONCLUSIONS

TCMR varies in intensity but is always strongly related to molecular injury and atrophy-fibrosis, which ultimately explains its effect on survival. We hypothesize, based on the reciprocal relationship with hyalinosis, that the TCMR1-TCMR2 gradient reflects calcineurin inhibitor drug underexposure, whereas the time-dependent decline in TCMR activity and frequency after the first year reflects T-cell exhaustion.

Allograft tissue under the microscope: only the beginning

PURPOSE OF REVIEW

To review novel modalities for interrogating a kidney allograft biopsy to complement the current Banff schema.

RECENT FINDINGS

Newer approaches of Artificial Intelligence (AI), Machine Learning (ML), digital pathology including Ex Vivo Microscopy, evaluation of the biopsy gene expression using bulk, single cell, and spatial transcriptomics and spatial proteomics are now available for tissue interrogation.

SUMMARY

Banff Schema of classification of allograft histology has standardized reporting of tissue pathology internationally greatly impacting clinical care and research. Inherent sampling error of biopsies, and lack of automated morphometric analysis with ordinal outputs limit its performance in prognostication of allograft health. Over the last decade, there has been an explosion of newer methods of evaluation of allograft tissue under the microscope. Digital pathology along with the application of AI and ML algorithms could revolutionize histopathological analyses. Novel molecular diagnostics such as spatially resolved single cell transcriptomics are identifying newer mechanisms underlying the pathologic diagnosis to delineate pathways of immunological activation, tissue injury, repair, and regeneration in allograft tissues. While these techniques are the future of tissue analysis, costs and complex logistics currently limit their clinical use.

Visual interstitial fibrosis assessment as continuous variable in protocol renal transplant biopsies

AIMS

In current renal transplant pathology practice, interstitial fibrosis is visually assessed in categories according to the Banff classification. As this has a moderate reproducibility, which is little ameliorated by morphometric analysis, we investigated whether visual renal fibrosis assessment is feasible on a continuous scale, i.e. as a percentage of affected area of the cortex.

METHODS AND RESULTS

Protocol renal biopsies taken at transplantation (n = 125), three (n = 73) and 12 months (n = 88) after transplantation were visually scored in categories (Banff) and percentages for interstitial fibrosis (ci). Interobserver variation (ICC and weighted κ) was assessed, and morphometric analysis on Sirius red-stained sections was performed. Correlations between the different methods and their association with donor age and eGFR 1 and 5 years post-transplant were analysed using Pearson's or Spearman's rho. Interobserver agreement was equivalent for Banff and %ci (κ = 0.713 versus ICC = 0.792), and for Banff IF/TA and %IF/TA (κ = 0.615 versus ICC = 0.743). Both Banff and %ci were associated with Sirius red morphometry in 3 and 12 months. With all three methods, a significant correlation was found between donor age and fibrosis in the implantation biopsy and between fibrosis in the 12 months' biopsy and eGFR at 1 and 5 years (eGFR at 1 year: Sirius red ρ = 0.487, %ci ρ = 0.393, Banff ρ = 0.413, all P < 0.01, eGFR at 5 years: Sirius red ρ = 0.392, %ci ρ = 0.333, Banff ρ = 0.435, all P < 0.01).

CONCLUSION

Interstitial fibrosis assessment on a continuous scale can be used next to scoring in categories according to the Banff classification in protocol renal transplant biopsies.

Urine as liquid gold: the transcriptional landscape of acute rejection defined by urinary cell mRNA profiling of kidney allograft recipients

PURPOSE OF REVIEW

Because all functioning nephrons contribute to urine formation, we reasoned that urine would be a suitable substitute to kidney allograft biopsy to discern human kidney allograft status. In view of compelling data that ribonucleic acid (RNA) sequencing outperforms microarray-based profiling, we performed RNA sequencing of urinary cells and kidney allograft biopsies to define the transcriptional landscape of allograft rejection.

RECENT FINDINGS

Whole genome transcriptome profiling identified unique and shared gene signatures of acute T cell mediated rejection (TCMR) and antibody mediated rejection (AMR). We found that biopsy rejection signatures are enriched in urinary cells and that the immune cellular landscape is more diverse and enriched in urine compared to biopsies. Towards a patient friendly protocol for urinary cell messenger RNA (mRNA) profiling, we developed a filtration-based protocol for the initial processing of urine at home and demonstrated excellent performance characteristics of the filter- based protocol.

SUMMARY

Acute rejection signatures are enriched in urinary cells. Urinary cell mRNA profiles are diagnostic and prognostic of acute rejection and could serve as yardsticks of in-vivo immune status. RNA sequencing yields insights into mechanisms of rejection and helps prioritize therapeutic targets. The filtration protocol for home processing of urine may optimize immune surveillance.

A Simple Molecular Tool for the Assessment of Kidney Transplant Biopsies

BACKGROUND

The Banff Classification for Allograft Pathology recommendations for the diagnosis of kidney transplant rejection includes molecular assessment of the transplant biopsy. However, implementation of molecular tools in clinical practice is still limited, partly due to the required expertise and financial investment. The reverse transcriptase multiplex ligation-dependent probe amplification (RT-MLPA) assay is a simple, rapid, and inexpensive assay that permits simultaneous evaluation of a restricted gene panel using paraffin-embedded tissue blocks. The aim of this study was to develop and validate a RT-MLPA assay for diagnosis and classification of rejection.

METHODS

A retrospective cohort of 220 kidney transplant biopsies from two centers, which included 52 antibody-mediated rejection, 51 T-cell-mediated rejection, and 117 no-rejection controls, was assessed. A 17-gene panel was identified on the basis of relevant pathophysiological pathways. A support vector machine classifier was developed. A subset of 109 biopsies was also assessed using the Nanostring Banff Human Organ Transplant panel to compare the two assays.

RESULTS

The support vector machine classifier train and test accuracy scores were 0.84 and 0.83, respectively. In the test cohort, the F1 score for antibody-mediated rejection, T-cell-mediated rejection, and control were 0.88, 0.86, and 0.69, respectively. Using receiver-operating characteristic curves, the area under the curve for class predictions was 0.96, 0.89, and 0.91, respectively, with a weighted average at 0.94. Classifiers' performances were highest for antibody-mediated rejection diagnosis with 94% correct predictions, compared with 88% correct predictions for control biopsies and 60% for T-cell-mediated rejection biopsies. Gene expression levels assessed by RT-MLPA and Nanostring were correlated: r = 0.68, P < 0.001. Equivalent gene expression profiles were obtained with both assays in 81% of the samples.

CONCLUSIONS

The 17-gene panel RT-MLPA assay, developed here for formalin-fixed paraffin-embedded kidney transplant biopsies, classified kidney transplant rejection with an overall accurate prediction ratio of 0.83.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_04_10_CJN10100822.mp3.

The Molecular Diagnosis Might Be Clinically Useful in Discrepant Kidney Allograft Biopsy Findings: An Analysis of Clinical Outcomes

BACKGROUND

The Molecular Microscope Diagnostic System (MMDx) may overcome histology shortcomings. Previous studies have simply examined discrepant findings but have not attempted to determine clinical endpoints. To measure performance, clinical outcomes are strongly required.

METHODS

This single-center cohort study described discrepancies between MMDx and histology from 51 kidney transplant recipients (KTRs) and analyzed 72 indication biopsies, including 21 follow-up biopsies. Clinical performance was assessed by a combined endpoint of graft failure, rejection on follow-up biopsy, de novo donor-specific antibody, and improvement of kidney allograft function upon antirejection treatment.

RESULTS

MMDx agreed in 33 (65%) and differed in 18 (35%) of 51 KTRs. Most discrepancies occurred in biopsies called no rejection by MMDx and rejection by histology (15/24, 63%). In contrast, in biopsies called rejection by MMDx, 3 were classified as no rejection by histology (3/27, 11%). Discrepant findings between MMDx and histology occurred following delayed graft function and MMDx from biopsies with a low percentage of cortex. Among 15 biopsies classified as no rejection by MMDx but rejection by histology, the clinical course suggested no rejection in 9 cases. Six KTRs reached the endpoint, showing predominant t ≥ 2 lesions.

CONCLUSIONS

The most often occurring discrepancy is rejection by histology but no rejection by MMDx. As more KTRs do not meet the combined endpoint for rejection, MMDx might be clinically useful in these discrepant cases. Although strong histological findings have priority in indicating the treatment, clinical implementation of MMDx could strengthen treatment strategies.

An Assessment of the Value of Donor-derived Cell-free DNA Surveillance in Patients With Preserved Kidney Allograft Function

BACKGROUND

Donor-derived cell-free DNA (dd-cfDNA) is a biomarker validated to detect rejection when measured to assess kidney allograft dysfunction. However, it remains unclear whether routine surveillance with dd-cfDNA provides additional information over standard monitoring of kidney allografts with creatinine and donor-specific antibodies (DSAs), particularly among those with little suspicion of rejection or injury. We investigated the value of measuring dd-cfDNA in patients with preserved allograft function and describe its association with future events.

METHODS

Three-hundred seventeen kidney transplant recipients with a creatinine ≤1.5 mg/dL, no current DSA, and no prior rejection were assessed with dd-cfDNA and categorized into low (dd-cfDNA <0.5%; n = 239), moderate (dd-cfDNA 0.5% to <1.0%; n = 43), and high (dd-cfDNA ≥1.0%; n = 35) groups. The occurrence of rejection, DSA, graft loss, and change in estimated glomerular filtration rate over time after dd-cfDNA assessment was compared.

RESULTS

Over follow-up, rejections were more commonly found among patients with high vs low dd-cfDNA (17% versus 5%; P = 0.01); a similar nonsignificant trend was observed among patients with moderate compared to low dd-cfDNA (12% versus 5%; P = 0.13). DSA development was uncommon and not different between groups (low: 4%; moderate: 3%; high: 0%; P = 0.52). There was only 1 graft loss in a patient with low dd-cfDNA, and dd-cfDNA was not associated with graft dysfunction over time.

CONCLUSIONS

Most patients with elevated dd-cfDNA in conjunction with preserved allograft function remained stable over follow-up without deterioration in function or graft loss. Studies are needed to differentiate patients with elevated dd-cfDNA who will develop adverse outcomes from those who will remain clinically stable.

Urinary cell mRNA profiling of kidney allograft recipients: Development of a portable protocol for noninvasive diagnosis of T cell mediated rejection and BK virus nephropathy

BACKGROUND

We developed urinary cell mRNA profiling for noninvasive diagnosis of acute T cell mediated rejection (TCMR) and BK virus nephropathy (BKVN), two significant post-transplant complications. Our profiling protocol for the multicenter Clinical Trial of Transplantation-04 (CTOT-04) study consisted of centrifugation of urine to prepare cell pellets, washes, addition of an RNA preservative, storage at 800C and shipment in cold containers to our Gene Expression Monitoring (GEM) Core for RNA isolation and quantification of mRNA in RT-qPCR assays. To simplify profiling, we developed a filter-based protocol (ZFBP) that eliminated the need for centrifugation, RNA preservative, storage at 800C, and shipment in cold containers for mRNA profiling. Furthermore, we trained kidney allograft recipients to perform the filtration of urine at home using the filter and post the urinary cell lysate containing the RNA at ambient temperature to our GEM Core for profiling. Here, we report our refinement of ZFBP and investigation of its diagnostic performance characteristics.

METHODS

Total RNA was isolated from kidney allograft biopsy-matched urines using a filter-based protocol complemented by a silica-membrane-based cartridge for mRNA enrichment, the Weill Cornell Hybrid Protocol (WCHP). Absolute copy numbers of CD3ε mRNA, CXCL10 mRNA, and 18S rRNA, components of the CTOT-04 three-gene TCMR diagnostic signature, and urinary cell BKV VP 1 mRNA copy number were measured using RT-qPCR assays. Mann-Whitney test, Fischer exact test, and receiver operating characteristic (ROC) curve analysis were used for data analyses.

RESULTS

Urinary cell three-gene TCMR diagnostic signature scores in urines processed using the WCHP discriminated kidney allograft recipients with TCMR (12 TCMR biopsies from 11 patients) from those without TCMR or BKVN (29 No TCMR/No BKVN biopsies from 29 patients). The median (25th and 75th percentiles) score of the CTOT-04 three-gene TCMR diagnostic signature was -0.448 (-1.664, 0.204) in the TCMR group and - 2.542 (-3.267, -1.365) in the No TCMR/ No BKVN group (P = 0.0005, Mann-Whitney test). ROC curve analysis discriminated the TCMR group from the No TCMR/ No BKVN group; the area under the ROC curve (AUROC) was 0.84 (95% Confidence Intervals [CI], 0.69 to 0.98) (P < 0.001), and TCMR was diagnosed with a sensitivity of 67% (95% CI, 35 to 89) at a specificity of 86% (95% CI, 67 to 95) using the CTOT-04 validated cutpoint of -1.213 (P = 0.0016, Fisher exact test). BKV VP1 mRNA copy number in urines processed using the WCHP discriminated patients with BKVN (n = 7) from patients without TCMR or BKVN (n = 29) and the AUROC was 1.0 (95% CI, 1.00 to 1.00) (P < 0.0001) and BKVN was diagnosed with a sensitivity of 86% (95% CI, 42 to 99) at a specificity of 100% (95% CI, 85 to 100) with the previously validated cutpoint of 6.5 × 108 BKV-VP1 mRNA copies per microgram of RNA (P < 0.0001, Fisher exact test).

CONCLUSION

Urine processed using the WCHP predicted TCMR and BKVN in kidney allograft recipients. WCHP represents not only a significant advance toward the portability of urinary cell mRNA profiling but also improved patient management by minimizing their visits for urine collection.

The Histological Spectrum and Clinical Significance of T Cell-mediated Rejection of Kidney Allografts

T cell-mediated rejection (TCMR) remains a significant cause of long-term kidney allograft loss, either indirectly through induction of donor-specific anti-HLA alloantibodies or directly through chronic active TCMR. Whether found by indication or protocol biopsy, Banff defined acute TCMR should be treated with antirejection therapy and maximized maintenance immunosuppression. Neither isolated interstitial inflammation in the absence of tubulitis nor isolated tubulitis in the absence of interstitial inflammation results in adverse outcomes, and neither requires antirejection treatment. RNA gene expression analysis of biopsy material may supplement conventional histology, especially in ambiguous cases. Lesser degrees of tubular and interstitial inflammation (Banff borderline) may portend adverse outcomes and should be treated when found on an indication biopsy. Borderline lesions on protocol biopsies may resolve spontaneously but require close follow-up if untreated. Following antirejection therapy of acute TCMR, surveillance protocol biopsies should be considered. Minimally invasive blood-borne assays (donor-derived cell-free DNA and gene expression profiling) are being increasingly studied as a means of following stable patients in lieu of biopsy. The clinical benefit and cost-effectiveness require confirmation in randomized controlled trials. Treatment of acute TCMR is not standardized but involves bolus corticosteroids with lymphocyte depleting antibodies for severe, refractory, or relapsing cases. Arteritis may be found with acute TCMR, active antibody-mediated rejection, or mixed rejections and should be treated accordingly. The optimal treatment ofchronic active TCMR is uncertain. Randomized controlled trials are necessary to optimally define therapy.

Machine learning-supported interpretation of kidney graft elementary lesions in combination with clinical data

Interpretation of kidney graft biopsies using the Banff classification is still heterogeneous. In this study, extreme gradient boosting classifiers learned from two large training datasets (n = 631 and 304 cases) where the "reference diagnoses" were not strictly defined following the Banff rules but from central reading by expert pathologists and further interpreted consensually by experienced transplant nephrologists, in light of the clinical context. In three external validation datasets (n = 3744, 589, and 360), the classifiers yielded a mean ROC curve AUC (95%CI) of: 0.97 (0.92-1.00), 0.97 (0.96-0.97), and 0.95 (0.93-0.97) for antibody-mediated rejection (ABMR); 0.94 (0.91-0.96), 0.94 (0.92-0.95), and 0.91 (0.88-0.95) for T cell-mediated rejection; >0.96 (0.90-1.00) with all three for interstitial fibrosis-tubular atrophy. We also developed a classifier to discriminate active and chronic active ABMR with 95% accuracy. In conclusion, we built highly sensitive and specific artificial intelligence classifiers able to interpret kidney graft scoring together with a few clinical data and automatically diagnose rejection, with excellent concordance with the Banff rules and reference diagnoses made by a group of experts. Some discrepancies may point toward possible improvements that could be made to the Banff classification.

Convolutional Neural Networks for the Evaluation of Chronic and Inflammatory Lesions in Kidney Transplant Biopsies

In kidney transplant biopsies, both inflammation and chronic changes are important features that predict long-term graft survival. Quantitative scoring of these features is important for transplant diagnostics and kidney research. However, visual scoring is poorly reproducible and labor intensive. The goal of this study was to investigate the potential of convolutional neural networks (CNNs) to quantify inflammation and chronic features in kidney transplant biopsies. A structure segmentation CNN and a lymphocyte detection CNN were applied on 125 whole-slide image pairs of periodic acid-Schiff- and CD3-stained slides. The CNN results were used to quantify healthy and sclerotic glomeruli, interstitial fibrosis, tubular atrophy, and inflammation within both nonatrophic and atrophic tubuli, and in areas of interstitial fibrosis. The computed tissue features showed high correlation with Banff lesion scores of five pathologists (A.A., A.Dend., J.H.B., J.K., and T.N.). Analyses on a small subset showed a moderate correlation toward higher CD3⁺ cell density within scarred regions and higher CD3⁺ cell count inside atrophic tubuli correlated with long-term change of estimated glomerular filtration rate. The presented CNNs are valid tools to yield objective quantitative information on glomeruli number, fibrotic tissue, and inflammation within scarred and non-scarred kidney parenchyma in a reproducible manner. CNNs have the potential to improve kidney transplant diagnostics and will benefit the community as a novel method to generate surrogate end points for large-scale clinical studies.

AIM2 as a putative target in acute kidney graft rejection

Acute rejection (AR) is a process triggered via the recognition of grafted organ-derived antigens by the immune system, which could present as a life-threatening condition. In the context of a kidney transplant, despite improvement with immunosuppressive therapies, AR maintains a significant incidence of 10%, and currently available drugs generally act in similar and canonical pathways of lymphocyte activation. This prompted the research for different approaches to identify potential novel targets that could improve therapeutic interventions. Here, we conducted a transcriptome analysis comparing groups of acute rejection (including T cell-mediated rejection and antibody-mediated rejection) to stable grafts that included differentially expressed genes, transcription factor and kinase enrichment, and Gene Set Enrichment Analysis. These analyses revealed inflammasome enhancement in rejected grafts and AIM2 as a potential component linked to acute rejection, presenting a positive correlation to T-cell activation and a negative correlation to oxidative phosphorylation metabolism. Also, the AIM2 expression showed a global accuracy in discerning acute rejection grafts (area under the curve (AUC) = 0.755 and 0.894, p &lt; 0.0001), and meta-analysis comprising different studies indicated a considerable enhancement of AIM2 in rejection (standardized mean difference (SMD) = 1.45, [CI 95%, 1.18 to 1.71]), especially for T cell-mediated rejection (TCMR) (SMD = 2.01, [CI 95%, 1.58 to 2.45]). These findings could guide future studies of AIM2 as either an adjuvant target for immunosuppression or a potential biomarker for acute rejection and graft survival.

Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects

Digital imaging and advanced microscopy play a pivotal role in the diagnosis of kidney diseases. In recent years, great achievements have been made in digital imaging, providing novel approaches for precise quantitative assessments of nephropathology and relieving burdens of renal pathologists. Developing novel methods of artificial intelligence (AI)-assisted technology through multidisciplinary interaction among computer engineers, renal specialists, and nephropathologists could prove beneficial for renal pathology diagnoses. An increasing number of publications has demonstrated the rapid growth of AI-based technology in nephrology. In this review, we offer an overview of AI-assisted renal pathology, including AI concepts and the workflow of processing digital image data, focusing on the impressive advances of AI application in disease-specific backgrounds. In particular, this review describes the applied computer vision algorithms for the segmentation of kidney structures, diagnosis of specific pathological changes, and prognosis prediction based on images. Lastly, we discuss challenges and prospects to provide an objective view of this topic.

Shifting Clinical Trial Endpoints in Kidney Transplantation: The Rise of Composite Endpoints and Machine Learning to Refine Prognostication

The measurement of outcomes in kidney transplantation has been more accurately documented than almost any other surgical procedure result in recent decades. With significant improvements in short- and long-term outcomes related to optimized immunosuppression, outcomes have gradually shifted away from conventional clinical endpoints (ie, patient and graft survival) to surrogate and composite endpoints. This article reviews how outcomes measurements have evolved in the past 2 decades in the setting of increased data collection and summarizes recent advances in outcomes measurements pertaining to clinical, histopathological, and immune outcomes. Finally, we discuss the use of composite endpoints and Bayesian concepts, specifically focusing on the integrative box risk prediction score, in conjunction with machine learning to refine prognostication.

Common Glomerular Diseases in Adult Jordanians: A Single-Center Experience

The pattern of glomerular diseases has been reported previously with contradictory results. Our primary objective is to assess the relative frequencies of glomerular disease in adult Jordanians and compare it with other institutes. A secondary objective is to assess the contribution of environmental factors, in an industrial city Zarqa, to kidney disease patterns. Methods. A retrospective study was conducted at a referral hospital center in the central region of Jordan. Assessment of native kidney biopsies, pathological reports, and the patients' characteristics were obtained from electronic medical records. Results. Our study assessed a total of 178 biopsies, of which 106 patients were included achieving the age criterion for adults. The mean age of our patient was 34 ± 12.7. The number of females (53.7%) was slightly more than males (46.3%). The average creatinine at presentation was 198 umol/L. Almost half of the patients had mild renal impairment (50.9%), while the remaining were divided between moderate (26.1%) and severe (27.3%). The indications of kidney biopsy were proteinuria (11.3%), proteinuria (54.7%), and unexplained renal impairment (34%). The leading common glomerular diseases were represented as a group with a relative frequency ranging between 11% and 13%. Both IgA nephropathy (13.2%) and lupus nephritis (12.2%) were the top conditions causing the nephritic syndrome, while focal segmental glomerulosclerosis (12.2%) and minimal change disease (11.3%) were the conditions leading to nephrotic syndrome. Our secondary analysis showed nonstatistically significantly higher glomerular filtration rates in the city of Zarqa, when compared to Amman (median 94 and 54, respectively, U = 469.5, r = 0.08, p = 0.491). Additionally, Zarqa had higher frequency rates of interstitial/tubular nephritis (χ 2(1) = 1.17, p = 0.279, Cramér's V = 0.13. Conclusion. Common glomerular diseases, as reported internationally, were common among Jordanian adults.

Harnessing the B Cell Response in Kidney Transplantation - Current State and Future Directions

Despite dramatic improvement in kidney transplantation outcomes over the last decades due to advent of modern immunosuppressive agents, long-term outcomes remain poor. Antibody-mediated rejection (ABMR), a B cell driven process, accounts for the majority of chronic graft failures. There are currently no FDA-approved regimens for ABMR; however, several clinical trials are currently on-going. In this review, we present current mechanisms of B cell response in kidney transplantation, the clinical impact of sensitization and ABMR, the B cell response under current immunosuppressive regimens, and ongoing clinical trials for ABMR and desensitization treatment.

A Decentralized Kidney Transplant Biopsy Classifier for Transplant Rejection Developed Using Genes of the Banff-Human Organ Transplant Panel

Introduction

A decentralized and multi-platform-compatible molecular diagnostic tool for kidney transplant biopsies could improve the dissemination and exploitation of this technology, increasing its clinical impact. As a first step towards this molecular diagnostic tool, we developed and validated a classifier using the genes of the Banff-Human Organ Transplant (B-HOT) panel extracted from a historical Molecular Microscope^® Diagnostic system microarray dataset. Furthermore, we evaluated the discriminative power of the B-HOT panel in a clinical scenario.

Materials and Methods

Gene expression data from 1,181 kidney transplant biopsies were used as training data for three random forest models to predict kidney transplant biopsy Banff categories, including non-rejection (NR), antibody-mediated rejection (ABMR), and T-cell-mediated rejection (TCMR). Performance was evaluated using nested cross-validation. The three models used different sets of input features: the first model (B-HOT Model) was trained on only the genes included in the B-HOT panel, the second model (Feature Selection Model) was based on sequential forward feature selection from all available genes, and the third model (B-HOT+ Model) was based on the combination of the two models, i.e. B-HOT panel genes plus highly predictive genes from the sequential forward feature selection. After performance assessment on cross-validation, the best-performing model was validated on an external independent dataset based on a different microarray version.

Results

The best performances were achieved by the B-HOT+ Model, a multilabel random forest model trained on B-HOT panel genes with the addition of the 6 most predictive genes of the Feature Selection Model (ST7, KLRC4-KLRK1, TRBC1, TRBV6-5, TRBV19, and ZFX), with a mean accuracy of 92.1% during cross-validation. On the validation set, the same model achieved Area Under the ROC Curve (AUC) of 0.965 and 0.982 for NR and ABMR respectively.

Discussion

This kidney transplant biopsy classifier is one step closer to the development of a decentralized kidney transplant biopsy classifier that is effective on data derived from different gene expression platforms. The B-HOT panel proved to be a reliable highly-predictive panel for kidney transplant rejection classification. Furthermore, we propose to include the aforementioned 6 genes in the B-HOT panel for further optimization of this commercially available panel.

US payer budget impact of a microarray assay with machine learning to evaluate kidney transplant rejection in for-cause biopsies

AIM

This study evaluates the economic impact to US commercial payers of MMDx-Kidney used in conjunction with histologic evaluation of for-cause kidney transplant biopsies.

MATERIALS AND METHODS

An Excel-based model was developed to assess the cost impact of histology plus MMDx-Kidney versus histology alone for the evaluation of potential rejection in kidney transplant patients who receive a for-cause biopsy. Different model time periods were assessed, ranging from 1 to 5 years post-biopsy. A targeted literature review was used to identify parameter estimates, validated by two external clinicians with expertise in managing kidney transplant rejection. A sensitivity analysis was conducted to evaluate the relative impact of key clinical and cost parameters. In particular, the model identified the magnitude of MMDx-Kidney's impact on graft failure from rejection that would be required for MMDx-Kidney to be cost-neutral.

RESULTS

By more accurately characterizing rejection, MMDx-Kidney is estimated to increase antirejection treatment costs by $1,126 per test. Nevertheless, a break-even analysis shows that the costs of MMDx-Kidney and anti-rejection medication, as well as the costs associated with an increase in the number of patients with functioning transplants, may be offset by reductions in costs associated with graft failure (i.e. costs of hospitalizations, dialysis, and repeat transplants) over 5 years, assuming MMDx-Kidney reduces annual graft failure from rejection by at least 5%. For the base case, with a 25% relative reduction in annual rate of graft failures from rejection, MMDx-Kidney increases overall costs incurred in the first year of the model but starts generating savings by the second year of the model.

CONCLUSIONS

Compared with histologic evaluation of for-cause kidney transplant biopsies alone, the use of MMDx-Kidney in conjunction with histologic evaluation improves the diagnoses of graft dysfunction and may have the potential to generate overall savings from reductions in rejection-related graft failure.

Soluble Tim-3/Gal-9 as predictors of adverse outcomes after kidney transplantation: a cohort study

BACKGROUND

In our previous study, serum soluble T-cell immunoglobulin and mucin structure-3 (stim-3) and galactosin-9 (sGal-9) were found to be associated with renal function after kidney transplantation. However, it is unclear whether these two indicators can predict adverse outcomes after transplantation.

METHODS

Ninety-one recipients of kidney transplantation were enrolled and divided into a stable group and an adverse outcome group (consisting of biopsy-proven rejection, graft loss, death and clinically diagnosed rejection). The expression levels of sTim-3 and sGal-9 before (pre-Tim-3 and pre-Gal-9) and one month after transplantation (post-Tim-3 and post-Gal-9) were measured by ELISA.

RESULTS

The level of pre-Tim-3 was significantly higher in the stable group than in the adverse outcome group [median (range), 2275 (840-4236) pg/mL vs. 1589 (353-3094) pg/mL, P=0.002]. The level of post-Gal-9 was significantly lower in the stable group than in the adverse outcome group [median (range), 4869 (1418-13080) pg/mL vs. 6852: (4128-10760) pg/mL, P=0.003]. The areas under the curve (AUCs) for pre-Tim-3 and post-Gal-9 were 0.737 (P=0.002) and 0.751 (P=0.003), respectively, better than AUC of post-eGFR (0.633) (P=0.071), according to the receiver operating characteristic (ROC) curve. Through Cox regression analysis, including pre-Tim-3, post-Gal-9, post-eGFR, sex, age, BMI of recipients and donors, pre-Tim-3 and post-Gal-9 were independent risk factors for adverse outcomes after kidney transplantation (P=0.016, P=0.033, respectively).

CONCLUSION

Serum sTim-3 and sGal-9 can predict adverse outcomes within two years after kidney transplantation.

Urinary cell mRNA profiling of kidney allograft recipients: A systematic investigation of a filtration based protocol for the simplification of urine processing

BACKGROUND

Kidney transplantation is a life-restorative therapy, but immune rejection undermines allograft survival. Urinary cell mRNA profiles offer a noninvasive means of diagnosing kidney allograft rejection, but urine processing protocols have logistical constraints. We aimed to determine whether the centrifugation-based method for urinary cell mRNA profiling could be replaced with a simpler filtration-based method without undermining quality.

METHODS

We isolated RNA from urine collected from kidney allograft recipients using the Cornell centrifugation-based protocol (CCBP) or the Zymo filter-based protocol (ZFBP) and compared RNA purity and yield using a spectrophotometer or a fluorometer and measured absolute copy number of transcripts using customized real-time quantitative PCR assays. We investigated the performance characteristics of RNA isolated using ZFBP and stored either at -80 °C or at ambient temperature for 2 to 4 days and also when shipped to our Gene Expression Monitoring (GEM) Core at ambient temperature. We examined the feasibility of initial processing of urine samples by kidney allograft recipients trained by the GEM Core staff and the diagnostic utility for acute rejection, of urine processed using the ZFBP.

RESULTS

RNA purity (P = 0.0007, Wilcoxon matched paired signed-ranks test) and yield (P < 0.0001) were higher with ZFBP vs. CCBP, and absolute copy number of 18S rRNA was similar (P = 0.79) following normalization of RNA yield by reverse transcribing a constant amount of RNA isolated using either protocol. RNA purity, yield, and absolute copy numbers of 18S rRNA, TGF-β1 mRNA and microRNA-26a were not different (P > 0.05) in the filtrates containing RNA stored either at -80 °C or at ambient temperature for 2 to 4 days or shipped overnight at ambient temperature. RNA purity, yield, and absolute copy numbers of 18S rRNA and TGF-β1 mRNA were also not different (P > 0.05) between home processed and laboratory processed urine filtrates. Urinary cell levels of mRNA for granzyme B (P = 0.01) and perforin (P = 0.0002) in the filtrates were diagnostic of acute rejection in human kidney allografts.

CONCLUSIONS

Urinary cell mRNA profiling was simplified using the ZFBP without undermining RNA quality or diagnostic utility. Home processing by the kidney allograft recipients, the stability of RNA containing filtrates at ambient temperature, and the elimination of the need for centrifuges and freezers represent some of the advantages of ZFBP over the CCBP for urinary cell mRNA profiling.

Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies

Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft failure. Here we sought an objective, quantitative pathological assessment of these lesions to improve predictive utility and constructed a deep-learning-based pipeline recognizing normal vs. abnormal kidney tissue compartments and mononuclear leukocyte infiltrates. Periodic acid- Schiff stained slides of transplant biopsies (60 training and 33 testing) were used to quantify pathological lesions specific for interstitium, tubules and mononuclear leukocyte infiltration. The pipeline was applied to the whole slide images from 789 transplant biopsies (478 baseline [pre-implantation] and 311 post-transplant 12-month protocol biopsies) in two independent cohorts (GoCAR: 404 patients, AUSCAD: 212 patients) of transplant recipients to correlate composite lesion features with graft loss. Our model accurately recognized kidney tissue compartments and mononuclear leukocytes. The digital features significantly correlated with revised Banff 2007 scores but were more sensitive to subtle pathological changes below the thresholds in the Banff scores. The Interstitial and Tubular Abnormality Score (ITAS) in baseline samples was highly predictive of one-year graft loss, while a Composite Damage Score in 12-month post-transplant protocol biopsies predicted later graft loss. ITASs and Composite Damage Scores outperformed Banff scores or clinical predictors with superior graft loss prediction accuracy. High/intermediate risk groups stratified by ITASs or Composite Damage Scores also demonstrated significantly higher incidence of estimated glomerular filtration rate decline and subsequent graft damage. Thus, our deep-learning approach accurately detected and quantified pathological lesions from baseline or post-transplant biopsies and demonstrated superior ability for prediction of post-transplant graft loss with potential application as a prevention, risk stratification or monitoring tool.

Urinary Cell mRNA Profiles Predictive of Human Kidney Allograft Status

Immune monitoring of kidney allograft recipients and personalized therapeutics may help reach the aspirational goal of "one transplant for life." The invasive kidney biopsy procedure, the diagnostic tool of choice, has become safer and the biopsy classification more refined. Nevertheless, biopsy-associated complications, interobserver variability in biopsy specimen scoring, and costs continue to be significant concerns. The dynamics of the immune repertoire make frequent assessments of allograft status necessary, but repeat biopsies of the kidney are neither practical nor safe. To address the existing challenges, we developed urinary cell mRNA profiling and investigated the diagnostic, prognostic, and predictive accuracy of absolute levels of a hypothesis-based panel of mRNAs encoding immunoregulatory proteins. Enabled by our refinements of the PCR assay and by investigating mechanistic hypotheses, our single-center studies identified urinary cell mRNAs associated with T cell-mediated rejection, antibody-mediated rejection, interstitial fibrosis and tubular atrophy, and BK virus nephropathy. In the multicenter National Institutes of Health Clinical Trials in Organ Transplantation-04, we discovered and validated a urinary cell three-gene signature of T-cell CD3 ε chain mRNA, interferon gamma inducible protein 10 (IP-10) mRNA, and 18s ribosomal RNA that is diagnostic of subclinical acute cellular rejection and acute cellular rejection and prognostic of acute cellular rejection and graft function. The trajectory of the signature score remained flat and below the diagnostic threshold for acute cellular rejection in the patients with no rejection biopsy specimens, whereas a sharp rise was observed during the weeks before the biopsy specimen that showed acute cellular rejection. Our RNA sequencing and bioinformatics identified kidney allograft biopsy specimen gene signatures of acute rejection to be enriched in urinary cells matched to acute rejection biopsy specimens. The urinary cellular landscape was more diverse and more enriched for immune cell types compared with kidney allograft biopsy specimens. Urinary cell mRNA profile-guided clinical trials are needed to evaluate their value compared with current standard of care.

Glomerular Disease Classification and Lesion Identification by Machine Learning

Background

Classification of glomerular diseases and identification of glomerular lesions require careful morphological examination by experienced nephropathologists, which is labor-intensive, time-consuming, and prone to interobserver variability. In this regard, recent advance in machine learning-based image analysis is promising.

Methods

We combined Mask Region-based Convolutional Neural Networks (Mask R–CNN) with an additional classification step to build a glomerulus detection model using human kidney biopsy samples. A Long Short-Term Memory (LSTM) recurrent neural network was applied for glomerular disease classification, and another two-stage model using ResNeXt-101 was constructed for glomerular lesion identification in cases of lupus nephritis.

Results

The detection model showed state-of-the-art performance on variedly stained slides with F1 scores up to 0.944. The disease classification model showed good accuracies up to 0.940 on recognizing different glomerular diseases based on H&E whole slide images. The lesion identification model demonstrated high discriminating power with area under the receiver operating characteristic curve up to 0.947 for various glomerular lesions. Models showed good generalization on external testing datasets.

Conclusion

This study is the first-of-its-kind showing how each step of kidney biopsy interpretation carried out by nephropathologists can be captured and simulated by machine learning models. The models were integrated into a whole slide image viewing and annotating platform to enable nephropathologists to review, correct, and confirm the inference results. Further improvement on model performances and incorporating inputs from immunofluorescence, electron microscopy, and clinical data might realize actual clinical use.

Pure T-cell mediated rejection following kidney transplant according to response to treatment

The focus of studies on kidney transplantation (KT) has largely shifted from T-cell mediated rejection (TCMR) to antibody-mediated rejection (ABMR). However, there are still cases of pure acute TCMR in histological reports, even after a long time following transplant. We thus evaluated the impact of pure TCMR on graft survival (GS) according to treatment response. We also performed molecular diagnosis using a molecular microscope diagnostic system on a separate group of 23 patients. A total of 63 patients were divided into non-responders (N = 22) and responders (N = 44). Non-response to rejection treatment was significantly associated with the following factors: glomerular filtration rate (GFR) at biopsy, ΔGFR, TCMR within one year, t score, and IF/TA score. We also found that non-responder vs. responder (OR = 3.31; P = 0.036) and lower GFR at biopsy (OR = 0.56; P = 0.026) were independent risk factors of graft failure. The responders had a significantly superior overall GS rate compared with the non-responders (P = 0.004). Molecular assessment showed a good correlation with histologic diagnosis in ABMR, but not in TCMR. Solitary TCMR was a significant risk factor of graft failure in patients who did not respond to rejection treatment.

A ferroptosis-related gene signature for graft loss prediction following renal allograft

Allogeneic kidney transplantation (renal allograft) is the most effective treatment for advanced kidney disease. Previous studies have indicated that ferroptosis participates in the progression of acute kidney injury and renal transplant failure. However, few studies have evaluated the prognostic value of ferroptosis on renal transplantation outcomes. In this study, a total of 22 differentially expressed ferroptosis-related genes (DFGs) were identified, which were mainly enriched in infection-related pathways. Next, a ferroptosis-related gene signature, including GA-binding protein transcription factor subunit beta 1 (GABPB1), cyclin-dependent kinase inhibitor 1A (CDKN1A), Toll-like receptor 4 (TLR4), C-X-C motif chemokine ligand 2 (CXCL2), caveolin 1 (CAV1), and ribonucleotide reductase subunit M2 (RRM2), was constructed to predict graft loss following renal allograft. Moreover, receiver operating characteristic (ROC) curves (area under the ROC curve [AUC] > 0.8) demonstrated the accuracy of the gene signature and univariate Cox analysis suggested that the gene signature could play an independent role in graft loss (p < 0.05). Furthermore, the nomogram and calibration plots also indicated the good prognostic capability of the gene signature. Finally, immune-related and cytokine signaling pathways were mostly enriched in renal allograft patients with poor outcomes. Considered together, a ferroptosis-related gene signature and nomogram based on DFGs were created to predict the 1-, 2- and 3- year graft loss probability of renal allograft patients.The gene signature could serve as a valuable biomarker for predicting graft loss, contributing to improving the outcome of allogeneic kidney transplantation.

FOXP3 mRNA Profile Prognostic of Acute T Cell-mediated Rejection and Human Kidney Allograft Survival

BACKGROUND

T cell-mediated rejection (TCMR) is the most frequent type of acute rejection and is associated with kidney allograft failure. Almost 40% of TCMR episodes are nonresponsive to therapy, and molecular mechanisms for the nonresponsiveness are unknown. Our single-center study identified that urinary cell FOXP3 mRNA abundance predicts TCMR reversibility and allograft survival.

METHODS

We developed PCR assays and measured absolute copy numbers of transcripts for FOXP3, CD25, CD3E, perforin, and 18S rRNA in 3559 urines from 480 kidney allograft recipients prospectively enrolled in the multicenter Clinical Trials in Organ Transplantation-04. In this replication study, we investigated the association between mRNA profile and TCMR diagnosis, TCMR reversibility, and allograft survival.

RESULTS

18S rRNA normalized levels of mRNA for FOXP3 (P = 0.01, Kruskal-Wallis test), CD25 (P = 0.01), CD3E (P < 0.0001), and perforin (P < 0.0001) were diagnostic of TCMR, but only FOXP3 mRNA level predicted TCMR reversibility (ROC AUC = 0.764; 95% confidence interval, 0.611-0.917; P = 0.008). Multivariable logistic regression analyses showed that urinary cell FOXP3 mRNA level predicted reversal, independent of clinical variables. A composite model of clinical variables and FOXP3 mRNA (AUC = 0.889; 95% CI, 0.781-0.997; P < 0.001) outperformed FOXP3 mRNA or clinical variables in predicting TCMR reversibility (P = 0.01, likelihood ratio test). Multivariable Cox proportional hazards regression analyses showed that FOXP3 mRNA level predicts kidney allograft survival (P = 0.047) but not after controlling for TCMR reversal (P = 0.477).

CONCLUSIONS

Urinary cell level of FOXP3 mRNA is diagnostic of TCMR, predicts TCMR reversibility, and is prognostic of kidney allograft survival via a mechanism involving TCMR reversal.

Image Analysis Pipeline for Renal Allograft Evaluation and Fibrosis Quantification

INTRODUCTION

Digital pathology improves the standardization and reproducibility of kidney biopsy specimen assessment. We developed a pipeline allowing the analysis of many images without requiring human preprocessing and illustrate its use with a simple algorithm for quantification of interstitial fibrosis on a large dataset of kidney allograft biopsy specimens.

METHODS

Masson trichrome-stained images from kidney allograft biopsy specimens were used to train and validate a glomeruli detection algorithm using a VGG19 convolutional neural network and an automatic cortical region of interest (ROI) selection algorithm including cortical regions containing all predicted glomeruli. A positive-pixel count algorithm was used to quantify interstitial fibrosis on the ROIs and the association between automatic fibrosis and pathologist evaluation, estimated glomerular filtration rate (GFR) and allograft survival was assessed.

RESULTS

The glomeruli detection (F1 score of 0.87) and ROIs selection (F1 score 0.83 [SD 0.13]) algorithms displayed high accuracy. The correlation between the automatic fibrosis quantification on manually and automatically selected ROIs was high (r = 1.00 [0.99-1.00]). Automatic fibrosis quantification was only moderately correlated with pathologists' assessment and was not significantly associated with eGFR or allograft survival.

CONCLUSION

This pipeline can automatically and accurately detect glomeruli and select cortical ROIs that can easily be used to develop, validate, and apply image analysis algorithms.

A Systematic Review of Renal Pathology in Chronic Kidney Disease of Uncertain Etiology

INTRODUCTION

Despite much research on chronic kidney disease of uncertain etiology (CKDu) in Sri Lanka and the Mesoamerican nephropathy, the etiology and pathogenesis of this disease remains elusive. The pathology has broadly been described as chronic tubulointerstitial nephritis and no specific signature lesions have been identified.

METHODS

A scoping review was conducted through MEDLINE and Google Scholar databases for peer-reviewed publications on biopsy studies related to CKDu - Sri Lanka and Mesoamerican nephropathy to develop a comparative and critical analysis of the renal pathology found in these patients.

RESULTS

Thirteen studies met the selection criteria. Interstitial fibrosis was the predominant lesion in all the studies. Tubulointerstitial and glomerular abnormalities showed a more variable distribution. No characteristic histopathological feature was reported other than a proximal tubular lysosomal inclusion body which was claimed to indicate a toxic etiology. Three main pathogenetic mechanisms were postulated: repeated acute insults leading to scarring, low-grade chronic insults leading to non-inflammatory fibrosis, and tubulointerstitial damage in combination with glomerular injury. The main limitations in the interpretation and comparative analysis of these studies were the heterogeneity in case selection and biopsy reporting.

CONCLUSIONS

Although no characteristic histopathological feature could be found in CKDu-Sri Lanka or Mesoamerican nephropathy, there are noticeable differences between these two groups in the frequency and severity of the glomerular and tubulointerstitial changes which warrant more explorative studies preferably on kidneys in early stages of the disease. Future strategies should ensure that more uniform selection criteria and reporting methods are used.

Correlation of Donor-Derived Cell-free DNA with Histology and Molecular Diagnoses of Kidney Transplant Biopsies

BACKGROUND

Circulating donor-derived cell free DNA (cfDNA), a minimally invasive diagnostic tool for kidney transplant rejection, was validated using traditional histology. The Molecular Microscope (MMDx) tissue gene expression platform may provide increased precision to traditional histology.

METHODS

In this single-center prospective study of 208 biopsies (median=5.8 months) post-transplant, we report on the calibration of cfDNA with simultaneous biopsy assessments using MMDx and histology by Area under the curve (AUC) analyses for optimal criterion, as well as for, previously published cfDNA cut-offs ≤0.21% to 'rule-out' rejection and ≥1% to 'rule-in' rejection.

RESULTS

There were significant discrepancies between histology and MMDx, with MMDx identifying more antibody-mediated rejection (65; 31%) than histology (43; 21%); the opposite was true for T-cell mediated rejection [TCMR; histology: 27 (13%) vs MMDx: 13 (6%)]. Most of the TCMR discrepancies were seen for histologic borderline/1A TCMR. AUC Curves for cfDNA and prediction of rejection were slightly better with MMDx (AUC=0.80; 95%CI: 0.74-0.86) vs. histology (AUC=0.75; 95%CI: 0.69-0.81). A cfDNA≤0.21% had similar sensitivity (~91%) to 'rule-out' rejection by histology and MMDx. Specificity was slightly higher with MMDx (92%) compared with histology (85%) to 'rule-in' rejection using cfDNA criterion≥1%. Strong positive quantitative correlations were observed between cfDNA scores and molecular acute kidney injury (AKI) for both 'rejection' and 'nonrejection' biopsies.

CONCLUSIONS

Molecular diagnostics using tissue gene expression and blood-based donor-derived cell-free DNA may add precision to some cases of traditional histology. The positive correlation of cfDNA with molecular AKI suggests a dose-dependent association with tissue injury irrespective of rejection characteristics.

An Integrated Transcriptomic Approach to Identify Molecular Markers of Calcineurin Inhibitor Nephrotoxicity in Pediatric Kidney Transplant Recipients

Calcineurin inhibitors are highly efficacious immunosuppressive agents used in pediatric kidney transplantation. However, calcineurin inhibitor nephrotoxicity (CNIT) has been associated with the development of chronic renal allograft dysfunction and decreased graft survival. This study evaluated 37 formalin-fixed paraffin-embedded biopsies from pediatric kidney transplant recipients using gene expression profiling. Normal allograft samples (n = 12) served as negative controls and were compared to biopsies exhibiting CNIT (n = 11). The remaining samples served as positive controls to validate CNIT marker specificity and were characterized by other common causes of graft failure such as acute rejection (n = 7) and interstitial fibrosis/tubular atrophy (n = 7). MiRNA profiles served as the platform for data integration. Oxidative phosphorylation and mitochondrial dysfunction were the top molecular pathways associated with overexpressed genes in CNIT samples. Decreased ATP synthesis was identified as a significant biological function in CNIT, while key toxicology pathways included NRF2-mediated oxidative stress response and increased permeability transition of mitochondria. An integrative analysis demonstrated a panel of 13 significant miRNAs and their 33 CNIT-specific gene targets involved with mitochondrial activity and function. We also identified a candidate panel of miRNAs/genes, which may serve as future molecular markers for CNIT diagnosis as well as potential therapeutic targets.