Real Time Central Assessment of Kidney Transplant Indication Biopsies by Microarrays: The INTERCOMEX Study

Association of Ultrastructural Changes in Renal Allograft Biopsies With Diagnostic Elements of Antibody-Mediated Rejection and Graft Outcomes

BACKGROUND

The role of electron microscopy (EM) in the diagnosis of kidney allograft pathologies, particularly immunologic injury has not been well studied.

METHODS

In this retrospective, single-center cohort study, we examined EM features in 796 biopsies from 623 patients at high risk for antibody-mediated rejection, with glomerular abnormalities in light microscopy, presence of donor-specific antibody (DSA), or any degree of albuminuria/proteinuria.

RESULTS

Glomerular endothelial cell enlargement (GECE) > 50% was present in 29.1%, subendothelial expansion/basement membrane duplication in 24.5%, and peritubular basement membrane multilamellation > 4 (PTCML) in 18.5%. There was an incremental odds of worsening GECE from no DSA to class I DSA (odds ratio [OR], 2.75, P < 0.001; 95% confidence interval [CI], 1.7-4.5), class II DSA (OR, 3.44, P < 0.001, 95% CI, 2.5-4.7) and both classes (OR, 6.3, P < 0.001; 95% CI, 4.1-9.8). Moreover, the increase in number of antibodies was predictive of higher likelihood of worsening GECE (OR, 2.81, P < 0.001; 95% CI, 2.1-3.8 for 1 DSA; OR, 5.29, P < 0.001; 95% CI, 3.5-7.9 for 2-3; and OR, 8.45, P < 0.001; 95% CI, 4.7-15.3 for ≥4). Similar association was observed with PTCML. In multivariate analysis including DSA, subendothelial expansion/basement membrane duplication, and GECE >50%, but not PTCML were independently predictive of graft failure over mean follow-up of 63 mo (hazard ratio [HR], 1.6, P = 0.006, 95% CI, 1.2-2.3; HR, 2.0, P < 0.001; 95% CI, 1.4-2.9, respectively). Among a cohort with g, ptc, cg, and C4d scores 0, GECE >50% was independently associated with graft failure (HR, 2.58, P < 0.001, 95% CI, 1.6-4.3).

CONCLUSIONS

These observations support the wider use of EM in kidney transplant biopsies to help with earlier diagnosis of antibody-mediated rejection and to risk stratify the graft outcome.

Chronic Allograft Nephropathy-A Narrative Review of Its Pathogenesis, Diagnosis, and Evolving Management Strategies

Chronic allograft nephropathy is the leading cause of kidney allograft failure. Clinically, it is characterized by a progressive decline in kidney function, often in combination with proteinuria and hypertension. Histologically, interstitial fibrosis and tubular atrophy, along with features of glomerulosclerosis with occasional double contour appearance, arteriolar hyalinosis, and arteriosclerosis, are characteristic findings. The pathophysiology, though complex and incompletely understood, is thought to involve a sequence of immunologic and non-immunologic injuries eventually leading to tissue remodeling and scarring within the graft. The optimal strategy to prevent chronic allograft nephropathy is to minimize both immune- and non-immune-mediated graft injury.

Relating the molecular phenotype of ulcerative colitis to the clinical course

The expanding portfolio of targeted therapies for ulcerative colitis (UC) suggests that a more precise approach to defining disease activity will aid clinical decision-making. This prospective study used genome-wide microarrays to characterize gene expression in biopsies from the most inflamed colon segments from patients with UC and analyzed associations between molecular changes and short-term outcomes while on standard-of-care treatment. We analyzed 141 biopsies-128 biopsies from 112 UC patients and 13 biopsies from eight inflammatory bowel disease unclassified (IBDU) patients. Endoscopic disease was associated with expression of innate immunity transcripts, e.g. complement factor B (CFB); inflammasome genes (ZBP1 and PIM2); calprotectin (S100A8 and S100A9); and inflammation-, injury-, and innate immunity-associated pathway analysis terms. A cross-validated molecular machine learning classifier trained on the endoscopic Mayo subscore predicted the endoscopic Mayo subscore with area-under-the-curve of 0.85. A molecular calprotectin transcript score showed strong associations with fecal calprotectin and the endoscopic Mayo subscore. Logistic regression models showed that molecular features (e.g. molecular classifier and molecular calprotectin scores) improved the prediction of disease progression over conventional, clinical features alone (e.g. total Mayo score, fecal calprotectin, physician global assessment). The molecular features of UC showed strong correlations with disease activity and permitted development of machine-learning predictive disease classifiers that can be applied to expanded testing in diverse cohorts.

Additional Diagnoses Other Than Rejection in the Kidney Allograft Biopsy: Pitfalls for Biopsy-based Transcript Diagnostics

Background

Biopsy-based transcripts associated with antibody-mediated rejection (AMR) hold promise as substitutes for C4d positivity. However, their utility in cases with additional diagnoses other than rejection remains inadequately studied.

Methods

In our comprehensive analysis of 326 kidney allograft biopsies, assessed by histology and the Molecular Microscope Diagnostic System, we identified 68 cases characterized by additional pathologies, including pyelonephritis (n = 15), BK nephropathy (n = 20), acute interstitial nephritis (n = 5), and glomerular diseases (n = 28).

Results

Among cases with pyelonephritis, 7 of 15 cases (46%) showed a rejection-like signal, 4 above (16%) and 3 (20%) below diagnostic thresholds. Notably, the T cell-mediated rejection (TCMR) archetype score R2 (median, 0.13; interquartile range [IQR], 0.04-0.34) predominantly contributed to this observation. In BK nephropathy, 13 of 20 cases (65%) showed a rejection-like signal, 10 (50%) above and 3 (15%) below diagnostic thresholds. Elevated TCMR R2 (median, 0.07; IQR, 0.00-0.41) and all AMR archetype scores R4-6 (median, 0.23; IQR, 0.07-0.53) were driving factors. Among cases with acute interstitial nephritis, 3 of 5 cases (60%) showed TCMR-like signal with elevated R2 scores (median, 0.13; IQR, 0.00-0.54). Conversely, only 5 of 28 cases (18%) showed a rejection-like signal in glomerular disease cases, whereas 57% displayed all AMR archetype scores of ≥0.30.

Conclusions

Additional pathologies can affect the Molecular Microscope Diagnostic System output, giving a molecular rejection-like signal. The prevalence of rejection-like signals below diagnostic thresholds is noteworthy, warranting caution and prompting further investigation.

The Microscope and Beyond: Current Trends in the Characterization of Kidney Allograft Rejection From Tissue Samples

The Banff classification is regularly updated to integrate recent advances in the characterization of kidney allograft rejection, gathering novel diagnostic, prognostic, and theragnostic data into a diagnostic and pathogenesis-based framework. Despite ongoing research on noninvasive biomarkers of kidney rejection, the Banff classification remains, to date, biopsy-centered, primarily relying on a semiquantitative histological scoring system that overall lacks reproducibility and granularity. Besides, the ability of histopathological injuries and transcriptomics analyses from bulk tissue to accurately infer the pathogenesis of rejection is questioned. This review discusses findings from past, current, and emerging innovative tools that have the potential to enhance the characterization of allograft rejection from tissue samples. First, the digitalization of pathological workflows and the rise of deep learning should yield more reproducible and quantitative results from routine slides. Additionally, novel histomorphometric features of kidney rejection could be discovered with an overall genuine clinical implementation perspective. Second, multiplex immunohistochemistry enables in-depth in situ phenotyping of cells from formalin-fixed samples, which can decipher the heterogeneity of the immune infiltrate during kidney allograft rejection. Third, transcriptomics from bulk tissue is gradually integrated into the Banff classification, and its specific context of use is currently under extensive consideration. Finally, single-cell transcriptomics and spatial transcriptomics from formalin-fixed and paraffin-embedded samples are emerging techniques capable of producing up to genome-wide data with unprecedented precision levels. Combining all these approaches gives us hope for novel advances that will address the current blind spots of the Banff system.

Integration of FTIR Spectroscopy and Machine Learning for Kidney Allograft Rejection: A Complementary Diagnostic Tool

Background: Kidney transplantation is a life-saving treatment for end-stage kidney disease, but allograft rejection remains a critical challenge, requiring accurate and timely diagnosis. The study aims to evaluate the integration of Fourier Transform Infrared (FTIR) spectroscopy and machine learning algorithms as a minimally invasive method to detect kidney allograft rejection and differentiate between T Cell-Mediated Rejection (TCMR) and Antibody-Mediated Rejection (AMR). Additionally, the goal is to discriminate these rejection types aiming to develop a reliable decision-making support tool. Methods: This retrospective study included 41 kidney transplant recipients and analyzed 81 serum samples matched to corresponding allograft biopsies. FTIR spectroscopy was applied to pre-biopsy serum samples, and Naïve Bayes classification models were developed to distinguish rejection from non-rejection and classify rejection types. Data preprocessing involved, e.g., atmospheric compensation, second derivative, and feature selection using Fast Correlation-Based Filter for spectral regions 600-1900 cm-1 and 2800-3400 cm-1. Model performance was assessed via area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and accuracy. Results: The Naïve Bayes model achieved an AUC-ROC of 0.945 in classifying rejection versus non-rejection and AUC-ROC of 0.989 in distinguishing TCMR from AMR. Feature selection significantly improved model performance, identifying key spectral wavenumbers associated with rejection mechanisms. This approach demonstrated high sensitivity and specificity for both classification tasks. Conclusions: The integration of FTIR spectroscopy with machine learning may provide a promising, minimally invasive method for early detection and precise classification of kidney allograft rejection. Further validation in larger, more diverse populations is needed to confirm these findings' reliability.

Defining an NK Cell-enriched Rejection-like Phenotype in Liver Transplant Biopsies From the INTERLIVER Study

BACKGROUND

Initial analysis of liver transplant biopsies in the INTERLIVER study (ClinicalTrials.gov; unique identifier NCT03193151) using rejection-associated transcripts failed to find an antibody-mediated rejection state (ie, rich in natural killer [NK] cells and with interferon-gamma effects). We recently developed an optimization strategy in lung transplants that isolated an NK cell-enriched rejection-like (NKRL) state that was molecularly distinct from T cell-mediated rejection (TCMR). Here we apply the same strategy to a liver transplant biopsy population.

METHODS

We used this strategy to search for a molecular NKRL state in 765 consented liver transplant biopsies collected at participating international centers for gold-standard histology and molecular assessment by genome-wide microarrays. Validation through a training set-test set approach of an optimized selection of variables as inputs into unsupervised rejection classification identified an NKRL state in livers.

RESULTS

The full model classified 765 biopsies into the following molecular phenotypes, characterized by their gene expression: no-rejection 54%, TCMR 16%, NKRL 13%, and injury 16%. Top TCMR transcripts were expressed in effector T cells; top NKRL transcripts were almost exclusively expressed in NK cells; and both had increased interferon-γ-inducible transcripts, which were more pronounced in TCMR. Most TCMR biopsies had significant parenchymal injury, molecular fibrosis, and abnormal biochemistry. NKRL biopsies had no excess of injury, fibrosis, or biochemistry abnormalities.

CONCLUSIONS

Optimized rejection algorithms indicate that some liver transplants manifest an NKRL state that is well tolerated in the short term postbiopsy and with minimal injury and relatively normal biochemistry, while also underscoring the potential of TCMR to produce extensive parenchymal injury.

Subthreshold rejection activity in many kidney transplants currently classified as having no rejection

Most kidney transplant patients who undergo biopsies are classified as having no rejection based on consensus thresholds. However, we hypothesized that because these patients have normal adaptive immune systems, T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR) may exist as subthreshold activity in some transplants currently classified as no rejection. To examine this question, we studied genome-wide microarray results from 5086 kidney transplant biopsies (from 4170 patients). An updated molecular archetypal analysis designated 56% of biopsies as no rejection. Subthreshold molecular TCMR and/or ABMR activity molecular activity was detectable as elevated classifier scores in many biopsies classified as no rejection, with ABMR activity in many TCMR biopsies and TCMR activity in many ABMR biopsies. In biopsies classified as no rejection histologically and molecularly, molecular TCMR classifier scores correlated with increases in histologic TCMR features and molecular injury, lower estimated glomerular filtration rate, and higher risk of graft loss, and molecular ABMR activity correlated with increased glomerulitis and donor-specific antibody. No rejection biopsies with high subthreshold TCMR or ABMR activity had a higher probability of having TCMR or ABMR, respectively, diagnosed in a future biopsy. We conclude that many kidney transplant recipients have unrecognized subthreshold TCMR or ABMR activity, with significant implications for future problems.

Transcriptomic Signatures of Antibody-mediated Rejection in Early Biopsies With Negative Histology in HLA-incompatible Kidney Transplantation

Background

Presensitized patients with circulating donor-specific antibodies (DSAs) before transplantation are at risk for antibody-mediated rejection (AMR). Peritransplant desensitization mitigates but does not eliminate the alloimmune response. We examined the possibility that subthreshold AMR activity undetected by histology could be operating in some early biopsies.

Methods

Transcriptome of kidney allograft biopsies performed within the first month in presensitized patients (DSA+) who had received desensitization and did not develop active/probable AMR by histology (R-) was compared with biopsies showing active/probable AMR (R+/DSA+). As negative controls, biopsies without rejection by histology in patients without DSA at transplantation were used (R-/DSA-). RNA sequencing from biopsies selected from the biobank was used in cohort 1 (n = 32) and microarray, including the molecular microscope (Molecular Microscope Diagnostic System [MMDx]) algorithm, in recent cohort 2 (n = 30).

Results

The transcriptome of R-/DSA+ was similar to R+/DSA+ as these groups differed in 14 transcripts only. Contrarily, large differences were found between both DSA+ groups and negative controls. Fast gene set enrichment analyses showed upregulation of the immune system in both DSA+ groups (gene ontology terms: adaptive immune response, humoral immune response, antigen receptor-mediated signaling, and B-cell receptor signaling or complement activation) when compared with negative controls. MMDx assessment in cohort 2 classified 50% of R-/DSA+ samples as AMR and found no differences in AMR molecular scores between R+ and R- DSA+ groups. In imlifidase desensitization, MMDx series showed a gradual increase in AMR scores over time.

Conclusions

Presensitized kidney transplant recipients exhibited frequent molecular calls of AMR in biopsy-based transcript diagnostics despite desensitization therapy and negative histology.

Tissue-based Gene Expression Diagnosis of Mild and Moderate T-cell-mediated Rejection to Guide Therapy in Kidney Transplants

BACKGROUND

Mild histologic lesions of tubulo-interstitial inflammation could represent a "response-to-wounding" rather than allorecognition. Tissue gene expression may complement histopathology for T-cell-mediated rejection (TCMR) diagnostics.

METHODS

We report on the incorporation of tissue gene expression testing using a Molecular Microscope Diagnostic System into the management of kidney transplant biopsies with suspected TCMR. Patients (N = 209) were divided into 3 groups based upon diagnosis and TCMR therapy (with high-dose steroids and/or anti-thymocyte globulin): Group 1: Untreated histologic TCMR with molecular quiescence (H+M-); Group 2: Treated histologic and molecular TCMR (H+M+); and Group 3: Controls, with no histologic or molecular (H-M-) rejection.

RESULTS

At biopsy, estimated glomerular filtration rate was worse (P = 0.006) in H+M+ (N = 35; 33 ± 22 mL/min/1.73 m2) and H+M- (N = 30; 40 ± 18 mL/min/1.73 m2) groups; compared with H-M- (N = 144; 47 ± 24 mL/min/1.73 m2) group. In H+M- biopsies, mean molecular acute kidney injury scores (0.33 versus 0.10; P = 0.03) were higher than in H-M-; while molecular TCMR was lower compared with H+M+ (0.04 versus 0.54; P < 0.001). At 12 m postbiopsy estimated glomerular filtration rate remained low (P < 0.001) in H+M+ (38 ± 22 mL/min/1.73 m2) but improved in untreated H+M- (44 ± 22 mL/min/1.73 m2) and H-M- (50 ± 23 mL/min/1.73 m2) groups. At a mean follow-up of 2.1 ± 1.2 y post-index biopsy, death-censored graft survival was lower in H+M+ (74%) than in H+M- (90%) and H-M- (92%; P = 0.001). H+M+ cases had numerically higher rejection on follow-up biopsy (20%) than H+M- (7%) (P = 0.12) and de novo donor-specific antibody formation (H+M+ 24%; H+M- 10%; P = 0.13).

CONCLUSIONS

In this large single-center study, biopsies with untreated histological TCMR and molecular quiescence had comparable clinical outcomes to cases with no rejection, whereas those with histologic and tissue gene expression confirmed TCMR had inferior outcomes.

The Use of Machine Learning in the Diagnosis of Kidney Allograft Rejection: Current Knowledge and Applications

Kidney allograft rejection is one of the main limitations to long-term kidney transplant survival. The diagnostic gold standard for detecting rejection is a kidney biopsy, an invasive procedure that can often give imprecise results due to complex diagnostic criteria and high interobserver variability. In recent years, several additional diagnostic approaches to rejection have been investigated, some of them with the aid of machine learning (ML). In this review, we addressed studies that investigated the detection of kidney allograft rejection over the last decade using various ML algorithms. Various ML techniques were used in three main categories: (a) histopathologic assessment of kidney tissue with the aim to improve the diagnostic accuracy of a kidney biopsy, (b) assessment of gene expression in rejected kidney tissue or peripheral blood and the development of diagnostic classifiers based on these data, (c) radiologic assessment of kidney tissue using diffusion-weighted magnetic resonance imaging and the construction of a computer-aided diagnostic system. In histopathology, ML algorithms could serve as a support to the pathologist to avoid misclassifications and overcome interobserver variability. Diagnostic platforms based on biopsy-based transcripts serve as a supplement to a kidney biopsy, especially in cases where histopathologic diagnosis is inconclusive. ML models based on radiologic evaluation or gene signature in peripheral blood may be useful in cases where kidney biopsy is contraindicated in addition to other non-invasive biomarkers. The implementation of ML-based diagnostic methods is usually slow and undertaken with caution considering ethical and legal issues. In summary, the approach to the diagnosis of rejection should be individualized and based on all available diagnostic tools (including ML-based), leaving the responsibility for over- and under-treatment in the hands of the clinician.

Elevation of Donor-derived Cell-free DNA Before Biopsy-proven Rejection in Kidney Transplant

BACKGROUND

Standard-of-care biomarkers for renal allograft rejection are lagging indicators, signaling existing organ injury. This precludes early intervention, when immunological cascades leading to rejection are most susceptible. Donor-derived cell-free DNA (dd-cfDNA) shows promise as an early indicator of rejection, allowing earlier and possibly more effective treatment. This analysis was designed to assess this promise using real-world dd-cfDNA testing evidence.

METHODS

This retrospective analysis of the prospective, observational ProActive registry study (NCT04091984) assessed dd-cfDNA and serum creatinine levels before biopsy in 424 patients with ≥1 dd-cfDNA test (n = 1013) in the 6 mo before biopsy.

RESULTS

Of 4667 enrolled patients, 1631 patients had ≥18 mo of follow-up data, of which 424 had a biopsy and were included in this analysis. Twenty-six biopsies showed antibody-mediated rejection (ABMR), 62 showed T cell-mediated rejection, and 336 showed nonrejection; each from a unique patient. dd-cfDNA fractions were significantly elevated 5 mo before ABMR biopsies, and 2 mo before T cell-mediated rejection biopsies, compared with nonrejection biopsies. In contrast, serum creatinine did not discriminate between rejection and nonrejection in advance, or concurrent with biopsy. Among patients with nonrejection biopsies, estimated glomerular filtration rate was significantly lower in cases with ≥2 increased dd-cfDNA results (≥1%), compared with those with 0 or 1 increased dd-cfDNA result.

CONCLUSIONS

These data indicate that dd-cfDNA is an early indicator of biopsy-proven rejection, especially ABMR, suggesting a greater role for dd-cfDNA in surveillance to identify patients at high risk of ongoing or future rejection, thus requiring closer monitoring, biopsy, or other management changes.

Redefining the molecular rejection states in 3230 heart transplant biopsies: Relationships to parenchymal injury and graft survival

The first-generation Molecular Microscope (MMDx) system for heart transplant endomyocardial biopsies used expression of rejection-associated transcripts (RATs) to diagnose not only T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR) but also acute injury. However, the ideal system should detect rejection without being influenced by injury, to permit analysis of the relationship between rejection and parenchymal injury. To achieve this, we developed a new rejection classification in an expanded cohort of 3230 biopsies: 1641 from INTERHEART (ClinicalTrials.gov NCT02670408), plus 1589 service biopsies added to improve the power of the machine learning algorithms. The new system used 6 rejection classifiers instead of RATs and generated 7 rejection archetypes: No rejection, 48%; Minor, 24%; TCMR1, 2.3%; TCMR2, 2.7%; TCMR/mixed, 2.7%; early-stage ABMR, 3.9%; and fully developed ABMR, 16%. Using rejection classifiers eliminated cross-reactions with acute injury, permitting separate assessment of rejection and injury. TCMR was associated with severe-recent injury and late atrophy-fibrosis and rarely had normal parenchyma. ABMR was better tolerated, seldom producing severe injury, but in later biopsies was often associated with atrophy-fibrosis, indicating long-term risk. Graft survival and left ventricular ejection fraction were reduced not only in hearts with TCMR but also in hearts with severe-recent injury and atrophy-fibrosis, even without rejection.

Iguratimod ameliorates antibody-mediated rejection after renal transplant by modulating the Th17/Treg paradigm

BACKGROUND

Iguratimod (IGU) is widely used in clinical practice due to its stable anti-inflammatory effects. Our previous studies have confirmed that the proportion of Th17/Treg balance in patients taking IGU altered significantly. This study aims to explore the role of IGU in antibody-mediated rejection (ABMR) and its potential mechanisms.

METHODS

We conducted bioinformatics analysis of sequencing data from the GEO database to analyze the abundance of immune cell infiltration in transplanted kidney tissues. In vivo, IGU was intervened in a mice secondary skin transplantation model and a mice kidney transplantation ABMR model, and histological morphology of the grafts were examined by pathological staining, while relevant indicators were determined through qRT-PCR, immunohistochemistry, and enzyme-linked immunosorbent assay, observed T cell differentiation by flow cytometry, and preliminarily assessed the immunosuppressive effect of IGU. In vitro, we established Th17 and Treg cell induction and stimulation differentiation culture systems and added IGU for intervention to explore its effects on their differentiation.

RESULTS

Through bioinformatics analysis, we found that Th17 and Treg may play important roles in the occurrence and development of ABMR. In vivo, we found that IGU could effectively reduce the damage caused by ABMR to the grafts, alleviate the infiltration of inflammatory cells in the graft tissues, and reduce the deposition of C4d in the grafts. Moreover, it is also found that IGU regulated the differentiation of Th17 and Treg cells in the spleen and peripheral blood and reduced the expression of IL-17A in the grafts and serum. In addition, same changes were observed in the induction and differentiation culture system of Th17 and Treg cells in vitro after the addition of IGU.

CONCLUSION

IGU can inhibit the progression of ABMR by regulating the differentiation of Th17 and Treg cells, providing novel insights for optimizing clinical immunosuppressive treatment regimens.

[Update kidney allograft pathology : A better depiction of microvascular inflammation]

BACKGROUND

The Banff Foundation produces recommendations for classifying various lesions in renal allografts. Experts gather to update the classification every other year based on new scientific and clinical evidence.

OBJECTIVES

This article presents the most important changes incorporated into the new recommendations after the last Banff conference.

MATERIALS AND METHODS

The author of this article personally took part in the Banff conference and the subsequent survey, reported on the activities of a Banff working group (peritubular capillaritis) on-site, and contributed to drafting the recently published meeting report.

RESULTS

Lesions of antibody-mediated kidney allograft rejection (AMR), especially microvascular inflammation, have been part of the diagnostic algorithm for over 20 years. Experts advocated for a simplified AMR algorithm and mindful inclusion of molecular pathological data in the clinicopathological reflection regarding therapeutic decision. A new, more descriptive diagnostic entity-microvascular inflammation, C4d negative and DSA negative-has been introduced into the AMR category to acknowledge this histological constellation and motivate research into this pathophysiologically and immunologically probably different phenotype.

CONCLUSIONS

The Banff classification provides a structure for diagnosing kidney transplant pathology. Regular updates serve to adapt to ever-growing knowledge about alloimmunity. Particular challenges are capturing the complexity of various immunological scenarios and ensuring an understandable representation of these in a pathology report.

Challenges and opportunities for designing clinical trials for antibody mediated rejection

Significant progress has been made in kidney transplantation, with 1-year graft survival nearing 95%. However, long-term allograft survival remains suboptimal, with a 10-year overall graft survival rate of only 53.6% for deceased donor transplant recipients. Chronic active antibody-mediated rejection (ABMR) is a leading cause of death-censored graft loss, yet no therapy has demonstrated efficacy in large, randomized trials, despite substantial investment from pharmaceutical companies. Several clinical trials aimed to treat chronic ABMR in the past decade have yielded disappointing results or were prematurely terminated, attributed to factors including incomplete understanding of disease mechanisms, heterogeneous patient populations with comorbidities, slow disease progression, and limited patient numbers. This review aims to discuss opportunities for improving retrospective and prospective studies of ABMR, focusing on addressing heterogeneity, outcome measurement, and strategies to enhance patient enrollment to inform study design, data collection, and reporting.

Precision diagnostics in transplanted organs using microarray-assessed gene expression: concepts and technical methods of the Molecular Microscope® Diagnostic System (MMDx)

There is a major unmet need for improved accuracy and precision in the assessment of transplant rejection and tissue injury. Diagnoses relying on histologic and visual assessments demonstrate significant variation between expert observers (as represented by low kappa values) and have limited ability to assess many biological processes that produce little histologic changes, for example, acute injury. Consensus rules and guidelines for histologic diagnosis are useful but may have errors. Risks of over- or under-treatment can be serious: many therapies for transplant rejection or primary diseases are expensive and carry risk for significant adverse effects. Improved diagnostic methods could alleviate healthcare costs by reducing treatment errors, increase treatment efficacy, and serve as useful endpoints for clinical trials of new agents that can improve outcomes. Molecular diagnostic assessments using microarrays combined with machine learning algorithms for interpretation have shown promise for increasing diagnostic precision via probabilistic assessments, recalibrating standard of care diagnostic methods, clarifying ambiguous cases, and identifying potentially missed cases of rejection. This review describes the development and application of the Molecular Microscope® Diagnostic System (MMDx), and discusses the history and reasoning behind many common methods, statistical practices, and computational decisions employed to ensure that MMDx scores are as accurate and precise as possible. MMDx provides insights on disease processes and highly reproducible results from a comparatively small amount of tissue and constitutes a general approach that is useful in many areas of medicine, including kidney, heart, lung, and liver transplants, with the possibility of extrapolating lessons for understanding native organ disease states.

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.

Molecular states associated with dysfunction and graft loss in heart transplants

BACKGROUND

We explored the changes in gene expression correlating with dysfunction and graft failure in endomyocardial biopsies.

METHODS

Genome-wide microarrays (19,462 genes) were used to define mRNA changes correlating with dysfunction (left ventricular ejection fraction [LVEF] ≤ 55) and risk of graft loss within 3 years postbiopsy. LVEF data was available for 1,013 biopsies and survival data for 779 patients (74 losses). Molecular classifiers were built for predicting dysfunction (LVEF ≤ 55) and postbiopsy 3-year survival.

RESULTS

Dysfunction is correlated with dedifferentiation-decreased expression of normal heart transcripts, for example, solute carriers, along with increased expression of inflammation genes. Many genes with reduced expression in dysfunction were matrix genes such as fibulin 1 and decorin. Gene ontology (GO) categories suggested matrix remodeling and inflammation, not rejection. Genes associated with the risk of failure postbiopsy overlapped dysfunction genes but also included genes affecting microcirculation, for example, arginase 2, which reduces NO production, and endothelin 1. GO terms also reflected increased glycolysis and response to hypoxia, but decreased VEGF and angiogenesis pathways. T cell-mediated rejection was associated with reduced survival and antibody-mediated rejection with relatively good survival, but the main determinants of survival were features of parenchymal injury. Both dysfunction and graft loss were correlated with increased biopsy expression of BNP (gene NPPB). Survival probability classifiers divided hearts into risk quintiles, with actuarial 3-year postbiopsy survival >95% for the highest versus 50% for the lowest.

CONCLUSIONS

Dysfunction in transplanted hearts reflects dedifferentiation, decreased matrix genes, injury, and inflammation. The risk of short-term loss includes these changes but is also associated with microcirculation abnormalities, glycolysis, and response to hypoxia.

Using Regression Equations to Enhance Interpretation of Histology Lesions of Kidney Transplant Rejection

BACKGROUND

The Banff system for histologic diagnosis of rejection in kidney transplant biopsies uses guidelines to assess designated features-lesions, donor-specific antibody (DSA), and C4d staining. We explored whether using regression equations to interpret the features as well as current guidelines could establish the relative importance of each feature and improve histologic interpretation.

METHODS

We developed logistic regression equations using the designated features to predict antibody-mediated rejection (AMR/mixed) and T-cell-mediated rejection (TCMR/mixed) in 1679 indication biopsies from the INTERCOMEX study ( ClinicalTrials.gov NCT01299168). Equations were trained on molecular diagnoses independent of the designated features.

RESULTS

In regression and random forests, the important features predicting molecular rejection were as follows: for AMR, ptc and g, followed by cg; for TCMR, t > i. V-lesions were relatively unimportant. C4d and DSA were also relatively unimportant for predicting AMR: by AUC, the model excluding them (0.853) was nearly as good as the model including them (0.860). Including time posttransplant slightly but significantly improved all models. By AUC, regression predicted molecular AMR and TCMR better than Banff histologic diagnoses. More importantly, in biopsies called "no rejection" by Banff guidelines, regression equations based on histology features identified histologic and molecular rejection-related changes in some biopsies and improved survival predictions. Thus, regression can screen for missed rejection.

CONCLUSIONS

Using lesion-based regression equations in addition to Banff histology guidelines defines the relative important of histology features for identifying rejection, allows screening for potential missed diagnoses, and permits early estimates of AMR when C4d and DSA are not available.

Immune landscape of the kidney allograft in response to rejection

Preventing kidney graft dysfunction and rejection is a critical step in addressing the nationwide organ shortage and improving patient outcomes. While kidney transplants (KT) are performed more frequently, the overall number of patients on the waitlist consistently exceeds organ availability. Despite improved short-term outcomes in KT, comparable progress in long-term allograft survival has not been achieved. Major cause of graft loss at 5 years post-KT is chronic allograft dysfunction (CAD) characterized by interstitial fibrosis and tubular atrophy (IFTA). Accordingly, proactive prevention of CAD requires a comprehensive understanding of the immune mechanisms associated with either further dysfunction or impaired repair. Allograft rejection is primed by innate immune cells and carried out by adaptive immune cells. The rejection process is primarily facilitated by antibody-mediated rejection (ABMR) and T cell-mediated rejection (TCMR). It is essential to better elucidate the actions of individual immune cell subclasses (e.g. B memory, Tregs, Macrophage type 1 and 2) throughout the rejection process, rather than limiting our understanding to broad classes of immune cells. Embracing multi-omic approaches may be the solution in acknowledging these intricacies and decoding these enigmatic pathways. A transition alongside advancing technology will better allow organ biology to find its place in this era of precision and personalized medicine.

The utilization of molecular microscope in management of heart transplant recipients in the era of noninvasive monitoring

INTRODUCTION

Monitoring for graft rejection is a fundamental tenet of post-transplant follow-up. In heart transplantation (HT) in particular, rejection has been traditionally assessed with endomyocardial biopsy (EMB). EMB has potential complications and noted limitations, including interobserver variability in interpretation. Additional tests, such as basic cardiac biomarkers, cardiac imaging, gene expression profiling (GEP) scores, donor-derived cell-free DNA (dd-cfDNA) and the novel molecular microscope diagnostic system (MMDx) have become critical tools in rejection surveillance beyond standard EMB.

METHODS

This paper describes an illustrative case followed by a review of MMDx within the context of other noninvasive screening modalities for rejection.

CONCLUSIONS

We suggest MMDx be used to assist with early detection of rejection in cases of discordance between EMB and other noninvasive studies.

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.

Discrepancy Analysis between Histology and Molecular Diagnoses in Kidney Allograft Biopsies: A Single-Center Experience

Histology diagnosis is essential for the monitoring and management of kidney transplant patients. Nowadays, the accuracy and reproducibility of histology have been criticized when compared with molecular microscopy diagnostic system (MMDx). Our cohort included 95 renal allograft biopsies with both histology and molecular diagnoses. Discrepancies between histology and molecular diagnosis were assessed for each biopsy. Among the 95 kidney allograft biopsies, a total of 6 cases (6%) showed clear (n = 4) or borderline (n = 2) discrepancies between histology and molecular diagnoses. Four out of the six (67%) were cases with pathologically and clinically confirmed active infections that were diagnosed as mild to moderate T-cell-mediated rejection (TCMR) with MMDx. Two cases showed pathological changes that were not sufficient to make a definitive diagnosis of active rejection via histology, while MMDx results showed antibody-mediated rejection (ABMR). In addition, there were six cases with recurrent or de novo glomerular diseases diagnosed only via histology. All other biopsy results were in an agreement. Our results indicate that histology diagnosis of kidney allograft biopsy is superior to molecular diagnosis in the setting of infections and glomerular diseases; however, MMDx can provide helpful information to confirm the diagnosis of active ABMR.

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.

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.

The Clinical Utility of Post-Transplant Monitoring of Donor-Specific Antibodies in Stable Renal Transplant Recipients: A Consensus Report With Guideline Statements for Clinical Practice

Solid phase immunoassays improved the detection and determination of the antigen-specificity of donor-specific antibodies (DSA) to human leukocyte antigens (HLA). The widespread use of SPI in kidney transplantation also introduced new clinical dilemmas, such as whether patients should be monitored for DSA pre- or post-transplantation. Pretransplant screening through SPI has become standard practice and DSA are readily determined in case of suspected rejection. However, DSA monitoring in recipients with stable graft function has not been universally established as standard of care. This may be related to uncertainty regarding the clinical utility of DSA monitoring as a screening tool. This consensus report aims to appraise the clinical utility of DSA monitoring in recipients without overt signs of graft dysfunction, using the Wilson & Junger criteria for assessing the validity of a screening practice. To assess the evidence on DSA monitoring, the European Society for Organ Transplantation (ESOT) convened a dedicated workgroup, comprised of experts in transplantation nephrology and immunology, to review relevant literature. Guidelines and statements were developed during a consensus conference by Delphi methodology that took place in person in November 2022 in Prague. The findings and recommendations of the workgroup on subclinical DSA monitoring are presented in this article.

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.

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.

On a Long and Winding Road: Alloantibodies in Organ Transplantation

Today we know that both the humoral and the cellular arm of the immune system are engaged in severe immunological challenges. A close interaction between B and T cells can be observed in most "natural" challenges, including infections, malignancies, and autoimmune diseases. The importance and power of humoral immunity are impressively demonstrated by the current coronavirus disease 2019 pandemic. Organ transplant rejection is a normal immune response to a completely "artificial" challenge. It took a long time before the multifaceted action of different immunological forces was recognized and a unified, generally accepted opinion could be formed. Here, we address prominent paradigms and paradigm shifts in the field of transplantation immunology. We identify several instances in which the transplant community missed a timely paradigm shift because essential, available knowledge was ignored. Moreover, we discuss key findings that critically contributed to our understanding of transplant immunology but sometimes developed with delay and in a roundabout way, as was the case with antibody-mediated rejection-a main focus of this article. These include the discovery of the molecular principles of histocompatibility, the recognition of the microcirculation as a key interface of immune damage, the refinement of alloantibody detection, the description of C4d as a footmark of endothelium-bound antibody, and last but not least, the developments in biopsy-based diagnostics beyond conventional morphology, which only now give us a glimpse of the enormous complexity and pathogenetic diversity of rejection.

Antibody-mediated Rejection Without Detectable Donor-specific Antibody Releases Donor-derived Cell-free DNA: Results From the Trifecta Study

BACKGROUND

Trifecta (ClinicalTrials.gov #NCT04239703) is a prospective trial defining relationships between donor-derived cell-free DNA (dd-cfDNA), donor-specific antibody (DSA), and molecular findings in kidney transplant biopsies. Previous analyses of double results showed dd-cfDNA was strongly associated with rejection-associated molecules in the biopsy. The present study analyzed the triple results in 280 biopsies, focusing on the question of dd-cfDNA levels in DSA-negative antibody-mediated rejection (AMR).

METHODS

Molecular Microscope Diagnostic System biopsy testing was performed at Alberta Transplant Applied Genomics Centre, dd-cfDNA testing at Natera, Inc, and central HLA antibody testing at One Lambda Inc. Local DSA and histologic diagnoses were assigned per center standard-of-care.

RESULTS

DSA was frequently negative in both molecular (56%) and histologic (51%) AMR. DSA-negative AMR had slightly less molecular AMR activity and histologic peritubular capillaritis than DSA-positive AMR. However, all AMRs-DSA-positive or -negative-showed elevated %dd-cfDNA. There was no association between dd-cfDNA and DSA in biopsies without rejection. In AMR, %dd-cfDNA ≥1.0 was more frequent (75%) than DSA positivity (44%). In logistic regression, dd-cfDNA percent (area under the curve [AUC] 0.85) or quantity (AUC 0.86) predicted molecular AMR better than DSA (AUC 0.66). However, the best predictions incorporated both dd-cfDNA and DSA, plus time posttransplant (AUC 0.88).

CONCLUSIONS

DSA-negative AMR has moderately decreased mean molecular and histologic AMR-associated features compared with DSA-positive AMR, though similarly elevated dd-cfDNA levels. In predicting AMR at the time of indication biopsies in this population, dd-cfDNA is superior to DSA, reflecting the prevalence of DSA-negative AMR, but the optimal predictions incorporated both dd-cfDNA and DSA.

Monitoring of Serological, Cellular and Genomic Biomarkers in Transplantation, Computational Prediction Models and Role of Cell-Free DNA in Transplant Outcome

The process and evolution of an organ transplant procedure has evolved in terms of the prevention of immunological rejection with the improvement in the determination of immune response genes. These techniques include considering more important genes, more polymorphism detection, more refinement of the response motifs, as well as the analysis of epitopes and eplets, its capacity to fix complement, the PIRCHE algorithm and post-transplant monitoring with promising new biomarkers that surpass the classic serum markers such as creatine and other similar parameters of renal function. Among these new biomarkers, we analyze new serological, urine, cellular, genomic and transcriptomic biomarkers and computational prediction, with particular attention to the analysis of donor free circulating DNA as an optimal marker of kidney damage.

"Transplantomics" for predicting allograft rejection: real-life applications and new strategies from Network Medicine

Although decades of the reductionist approach achieved great milestones in optimizing the immunosuppression therapy, traditional clinical parameters still fail in predicting both acute and chronic (mainly) rejection events leading to higher rates across all solid organ transplants. To clarify the underlying immune-related cellular and molecular mechanisms, current biomedical research is increasingly focusing on "transplantomics" which relies on a huge quantity of big data deriving from genomics, transcriptomics, epigenomics, proteomics, and metabolomics platforms. The AlloMap (gene expression) and the AlloSure (donor-derived cell-free DNA) tests represent two successful examples of how omics and liquid biopsy can really improve the precision medicine of heart and kidney transplantation. One of the major challenges in translating big data in clinically useful biomarkers is the integration and interpretation of the different layers of omics datasets. Network Medicine offers advanced bioinformatic-molecular strategies which were widely used to integrate large omics datasets and clinical information in end-stage patients to prioritize potential biomarkers and drug targets. The application of network-oriented approaches to clarify the complex nature of graft rejection is still in its infancy. Here, we briefly discuss the real-life clinical applications derived from omics datasets as well as novel opportunities for establishing predictive tests in solid organ transplantation. Also, we provide an original "graft rejection interactome" and propose network-oriented strategies which can be useful to improve precision medicine of solid organ transplantation.

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.

Applications of Transcriptomics in the Research of Antibody-Mediated Rejection in Kidney Transplantation: Progress and Perspectives

Antibody-mediated rejection (ABMR) is the major cause of chronic allograft dysfunction and loss in kidney transplantation. The immunological mechanisms of ABMR that have been featured in the latest studies indicate a highly complex interplay between various immune and nonimmune cell types. Clinical diagnostic standards have long been criticized for being arbitrary and the lack of accuracy. Transcriptomic approaches, including microarray and RNA sequencing of allograft biopsies, enable the identification of differential gene expression and the continuous improvement of diagnostics. Given that conventional bulk transcriptomic approaches only reflect the average gene expression but not the status at the single-cell level, thereby ignoring the heterogeneity of the transcriptome across individual cells, single-cell RNA sequencing is rising as a powerful tool to provide a high-resolution transcriptome map of immune cells, which allows the elucidation of the pathogenesis and may facilitate the development of novel strategies for clinical treatment of ABMR.

Combining Donor-derived Cell-free DNA Fraction and Quantity to Detect Kidney Transplant Rejection Using Molecular Diagnoses and Histology as Confirmation

BACKGROUND

Donor-derived cell-free DNA (dd-cfDNA) fraction and quantity have both been shown to be associated with allograft rejection. The present study compared the relative predictive power of each of these variables to the combination of the two, and developed an algorithm incorporating both variables to detect active rejection in renal allograft biopsies.

METHODS

The first 426 sequential indication biopsy samples collected from the Trifecta study ( ClinicalTrials.gov # NCT04239703) with microarray-derived gene expression and dd-cfDNA results were included. After exclusions to simulate intended clinical use, 367 samples were analyzed. Biopsies were assessed using the molecular microscope diagnostic system and histology (Banff 2019). Logistic regression analysis examined whether combining dd-cfDNA fraction and quantity adds predictive value to either alone. The first 149 sequential samples were used to develop a two-threshold algorithm and the next 218 to validate the algorithm.

RESULTS

In regression, the combination of dd-cfDNA fraction and quantity was found to be significantly more predictive than either variable alone ( P = 0.009 and P < 0.0001). In the test set, the area under the receiver operating characteristic curve of the two-variable system was 0.88, and performance of the two-threshold algorithm showed a sensitivity of 83.1% and specificity of 81.0% for molecular diagnoses and a sensitivity of 73.5% and specificity of 80.8% for histology diagnoses.

CONCLUSIONS

This prospective, biopsy-matched, multisite dd-cfDNA study in kidney transplant patients found that the combination of dd-cfDNA fraction and quantity was more powerful than either dd-cfDNA fraction or quantity alone and validated a novel two-threshold algorithm incorporating both variables.

Individualised immunosuppression with intravenously administered donor-derived modified immune cells compared with standard of care in living donor kidney transplantation (TOL-2 Study): protocol for a multicentre, open-label, phase II, randomised controlled trial

INTRODUCTION

Donor-derived modified immune cells (MIC) induced long-term specific immunosuppression against the allogeneic donor in preclinical models of transplantation. In a phase I clinical trial (TOL-1 Study), MIC treatment resulted in a cellular phenotype that was directly and indirectly suppressive to the recipient's immune system allowing for reduction of conventional immunosuppressive therapy. Here, we describe a protocol for a randomised controlled, multicentre phase-IIb clinical trial of individualised immunosuppression with intravenously administered donor MIC compared with standard-of-care (SoC) in living donor kidney transplantation (TOL-2 Study).

METHODS AND ANALYSIS

Sixty-three living donor kidney transplant recipients from six German transplant centres are randomised 2:1 to treatment with MIC (MIC group, N=42) or no treatment with MIC (control arm, N=21). MIC are manufactured from donor peripheral blood mononuclear cells under Good Manufacturing Practice conditions. The primary objective of this trial is to determine the efficacy of MIC treatment together with reduced conventional immunosuppressive therapy in terms of achieving an operational tolerance-like phenotype compared with SoC 12 months after MIC administration. Key secondary endpoints are the number of patient-relevant infections as well as a composite of biopsy-proven acute rejection, graft loss, graft dysfunction or death. Immunosuppressive therapy of MIC-treated patients is reduced during follow-up under an extended immunological monitoring including human leucocyte antigen-antibody testing, and determination of lymphocyte subsets, for example, regulatory B lymphocytes (Breg) and antidonor T cell response. A Data Safety Monitoring Board has been established to allow an independent assessment of safety and efficacy.

ETHICS AND DISSEMINATION

Ethical approval has been provided by the Ethics Committee of the Medical Faculty of the University of Heidelberg, Heidelberg, Germany (AFmu-580/2021, 17 March 2022) and from the Federal Institute for Vaccines and Biomedicines, Paul-Ehrlich-Institute, Langen, Germany (Vorlage-Nr. 4586/02, 21 March 2022). Written informed consent will be obtained from all patients and respective donors prior to enrolment in the study. The results from the TOL-2 Study will be published in peer-reviewed medical journals and will be presented at symposia and scientific meetings.

TRIAL REGISTRATION NUMBER

NCT05365672.

Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies

BACKGROUND

Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ Transplant (B-HOT) panel and a customized antibody-mediated rejection (AMR)-specific NanoString nCounter Elements (Elements) panel. Additionally, we explored the potential for the classification of KTx rejection building and testing a classifier within our dataset.

METHODS

Ninety-six formalin-fixed paraffin-embedded KTx biopsies were retrieved from the archives of the ErasmusMC Rotterdam and the University Hospital Cologne. Biopsies with AMR, borderline or T cell-mediated rejections (BLorTCMR), and no rejection were compared using the B-HOT and Elements panels.

RESULTS

High correlation between gene expression levels was found when comparing the 2 chemistries pairwise (r = 0.76-0.88). Differential gene expression (false discovery rate; P  < 0.05) was identified in biopsies diagnosed with AMR (B-HOT: 294; Elements: 76) and BLorTCMR (B-HOT: 353; Elements: 57) compared with no rejection. Using the most predictive genes from the B-HOT analysis and the Element analysis, 2 least absolute shrinkage and selection operators-based regression models to classify biopsies as AMR versus no AMR (BLorTCMR or no rejection) were developed achieving an receiver-operating-characteristic curve of 0.994 and 0.894, sensitivity of 0.821 and 0.480, and specificity of 1.00 and 0.979, respectively, during cross-validation.

CONCLUSIONS

Transcriptomic analysis is feasible on KTx biopsies previously used for diagnostic purposes. The B-HOT panel has the potential to differentiate AMR from BLorTCMR or no rejection and could prove valuable in aiding kidney transplant rejection classification.

New Approaches to the Diagnosis of Rejection and Prediction of Tolerance in Liver Transplantation

Immunosuppression after liver transplantation is essential for preventing allograft rejection. However, long-term drug toxicity and associated complications necessitate investigation of immunosuppression minimization and withdrawal protocols. Development of such protocols is hindered by reliance on current paradigms for monitoring allograft function and rejection status. The current standard of care for diagnosis of rejection is histopathologic assessment and grading of liver biopsies in accordance with the Banff Rejection Activity Index. However, this method is limited by cost, sampling variability, and interobserver variation. Moreover, the invasive nature of biopsy increases the risk of patient complications. Incorporating noninvasive techniques may supplement existing methods through improved understanding of rejection causes, hepatic spatial architecture, and the role of idiopathic fibroinflammatory regions. These techniques may also aid in quantification and help integrate emerging -omics analyses with current assessments. Alternatively, emerging noninvasive methods show potential to detect and distinguish between different types of rejection while minimizing risk of adverse advents. Although biomarkers have yet to replace biopsy, preliminary studies suggest that several classes of analytes may be used to detect rejection with greater sensitivity and in earlier stages than traditional methods, possibly when coupled with artificial intelligence. Here, we provide an overview of the latest efforts in optimizing the diagnosis of rejection in liver transplantation.

The Role of Complement Split-products as Biomarkers for Acute Antibody-mediated Rejection of Kidney Allografts

Acute antibody-mediated rejection (AMR) is mediated by the activation of the classical complement system in addition to noncomplement-dependent inflammatory pathways. Complement fixation by donor-specific antibodies leads to cleavage of the complement proteins C4, C3, and C5 to produce multiple complement split-products (CSP) and the end-effector membrane attack complex, C5b-9. In this study, we investigate CSP as potential biomarkers for AMR.

Assessing the Relationship Between Molecular Rejection and Parenchymal Injury in Heart Transplant Biopsies

BACKGROUND

The INTERHEART study (ClinicalTrials.gov #NCT02670408) used genome-wide microarrays to detect rejection in endomyocardial biopsies; however, many heart transplants with no rejection have late dysfunction and impaired survival. We used the microarray measurements to develop a molecular classification of parenchymal injury.

METHODS

In 1320 endomyocardial biopsies from 645 patients previously studied for rejection-associated transcripts, we measured the expression of 10 injury-induced transcript sets: 5 induced by recent injury; 2 reflecting macrophage infiltration; 2 normal heart transcript sets; and immunoglobulin transcripts, which correlate with time. We used archetypal clustering to assign injury groups.

RESULTS

Injury transcript sets correlated with impaired function. Archetypal clustering based on the expression of injury transcript sets assigned each biopsy to 1 of 5 injury groups: 87 Severe-injury, 221 Late-injury, and 3 with lesser degrees of injury, 376 No-injury, 526 Mild-injury, and 110 Moderate-injury. Severe-injury had extensive loss of normal transcripts (dedifferentiation) and increase in macrophage and injury-induced transcripts. Late-injury was characterized by high immunoglobulin transcript expression. In Severe- and Late-injury, function was depressed, and short-term graft failure was increased, even in hearts with no rejection. T cell-mediated rejection almost always had parenchymal injury, and 85% had Severe- or Late-injury. In contrast, early antibody-mediated rejection (ABMR) had little injury, but late ABMR often had the Late-injury state.

CONCLUSION

Characterizing heart transplants for their injury state provides new understanding of dysfunction and outcomes and demonstrates the differential impact of T cell-mediated rejection versus ABMR on the parenchyma. Slow deterioration from ABMR emerges as a major contributor to late dysfunction.

Molecular diagnosis of ABMR with or without donor-specific antibody in kidney transplant biopsies: Differences in timing and intensity but similar mechanisms and outcomes

We studied the clinical, histologic, and molecular features distinguishing DSA-negative from DSA-positive molecularly defined antibody-mediated rejection (mABMR). We analyzed mABMR biopsies with available DSA assessments from the INTERCOMEX study: 148 DSA-negative versus 248 DSA-positive, compared with 864 no rejection (excluding TCMR and Mixed). DSA-positivity varied with mABMR stage: early-stage (EABMR) 56%; fully developed (FABMR) 70%; and late-stage (LABMR) 58%. DSA-negative patients with mABMR were usually sensitized, 60% being HLA antibody-positive. Compared with DSA-positive mABMR, DSA-negative mABMR was more often C4d-negative; earlier by 1.5 years (average 2.4 vs. 3.9 years); and had lower ABMR activity and earlier stage in molecular and histology features. However, the top ABMR-associated transcripts were identical in DSA-negative versus DSA-positive mABMR, for example, NK-associated (e.g., KLRD1 and GZMB) and IFNG-inducible (e.g., PLA1A). Genome-wide class comparison between DSA-negative and DSA-positive mABMR showed no significant differences in transcript expression except those related to lower intensity and earlier time of DSA-negative ABMR. Three-year graft loss in DSA-negative mABMR was the same as DSA-positive mABMR, even after adjusting for ABMR stage. Thus, compared with DSA-positive mABMR, DSA-negative mABMR is on average earlier, less active, and more often C4d-negative but has similar graft loss, and genome-wide analysis suggests that it involves the same mechanisms. SUMMARY SENTENCE: In 398 kidney transplant biopsies with molecular antibody-mediated rejection, the 150 DSA-negative cases are earlier, less intense, and mostly C4d-negative, but use identical molecular mechanisms and have the same risk of graft loss as the 248 DSA-positive cases.

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.