Microvascular Inflammation of Kidney Allografts and Clinical Outcomes.

BACKGROUND: The heterogeneous clinical presentation of graft microvascular inflammation poses a major challenge to successful kidney transplantation. The effect of microvascular inflammation on allograft outcomes is unclear. METHODS: We conducted a cohort study that included kidney-transplant recipients from more than 30 transplantation centers in Europe and North America who had undergone allograft biopsy between 2004 and 2023. We integrated clinical and pathological data to classify biopsy specimens according to the 2022 Banff Classification of Renal Allograft Pathology, which includes two new diagnostic categories: probable antibody-mediated rejection and microvascular inflammation without evidence of an antibody-mediated response. We then assessed the association between the newly recognized microvascular inflammation phenotypes and allograft survival and disease progression. RESULTS: A total of 16,293 kidney-transplant biopsy specimens from 6798 patients were assessed. We identified the newly recognized microvascular inflammation phenotypes in 788 specimens, of which 641 were previously categorized as specimens with no evidence of rejection. As compared with patients without rejection, the hazard ratio for graft loss was 2.1 (95% confidence interval [CI], 1.5 to 3.1) among patients with microvascular inflammation without evidence of an antibody-mediated response and 2.7 (95% CI, 2.2 to 3.3) among patients with antibody-mediated rejection. Patients with a diagnosis of probable antibody-mediated rejection had a higher risk of graft failure beyond year 5 after biopsy than those without rejection (hazard ratio, 1.7; 95% CI, 0.8 to 3.5). Patients with a diagnosis of either newly recognized microvascular inflammation phenotype had a higher risk of progression of transplant glomerulopathy during follow-up than patients without microvascular inflammation. CONCLUSIONS: Microvascular inflammation in kidney allografts includes distinct phenotypes, with various disease progression and allograft outcomes. Our findings support the clinical use of additional rejection phenotypes to standardize diagnostics for kidney allografts. (Funded by OrganX. ClinicalTrials.gov number, NCT06496269.).

Archetypal Analysis of Kidney Allograft Biopsies Using Next-generation Sequencing Technology.

BACKGROUND: In kidney transplantation, molecular diagnostics may be a valuable approach to improve the precision of the diagnosis. Using next-generation sequencing (NGS), we aimed to identify clinically relevant archetypes. METHODS: We conducted an Illumina bulk RNA sequencing on 770 kidney biopsies (540 kidney recipients) collected between 2006 and 2021 from 11 European centers. Differentially expressed genes were determined for 11 Banff lesions. An ElasticNet model was used for feature selection, and 4 machine learning classifiers were trained to predict the probability of presence of the lesions. NGS-based classifiers were used in an unsupervised archetypal analysis to different archetypes. The association of the archetypes with allograft survival was assessed using the iBox risk prediction score. RESULTS: The ElasticNet feature selection reduced the number of the genes from a range of 859-10 830 to a range of 52-867 genes. NGS-based classifiers demonstrated robust performances (precision-recall area under the curves 0.708-0.980) in predicting the Banff lesions. Archetypal analysis revealed 8 distinct phenotypes, each characterized by distinct clinical, immunological, and histological features. Although the archetypes confirmed the well-defined Banff rejection phenotypes for T cell-mediated rejection and antibody-mediated rejection, equivocal histologic antibody-mediated rejection, and borderline diagnoses were reclassified into different archetypes based on their molecular signatures. The 8 NGS-based archetypes displayed distinct allograft survival profiles with incremental graft loss rates between archetypes, ranging from 90% to 56% rates 7 y after evaluation (P < 0.0001). CONCLUSIONS: Using molecular phenotyping, 8 archetypes were identified. These NGS-based archetypes might improve disease characterization, reclassify ambiguous Banff diagnoses, and enable patient-specific risk stratification.

Competing and Noncompeting Risk Models for Predicting Kidney Allograft Failure.

BACKGROUND: Prognostic models are becoming increasingly relevant in clinical trials as potential surrogate endpoints, and for patient management as clinical decision support tools. However, the impact of competing risks on model performance remains poorly investigated. We aimed to carefully assess the performance of competing risk and noncompeting risk models in the context of kidney transplantation, where allograft failure and death with a functioning graft are two competing outcomes. METHODS: We included 11,046 kidney transplant recipients enrolled in 10 countries. We developed prediction models for long-term kidney graft failure prediction, without accounting (i.e., censoring) and accounting for the competing risk of death with a functioning graft, using Cox, Fine-Gray, and cause-specific Cox regression models. To this aim, we followed a detailed and transparent analytical framework for competing and noncompeting risk modelling, and carefully assessed the models' development, stability, discrimination, calibration, overall fit, clinical utility, and generalizability in external validation cohorts and subpopulations. More than 15 metrics were used to provide an exhaustive assessment of model performance. RESULTS: Among 11,046 recipients in the derivation and validation cohorts, 1,497 (14%) lost their graft and 1,003 (9%) died with a functioning graft after a median follow-up post-risk evaluation of 4.7 years (IQR 2.7-7.0). The cumulative incidence of graft loss was similarly estimated by Kaplan-Meier and Aalen-Johansen methods (17% versus 16% in the derivation cohort). Cox and competing risk models showed similar and stable risk estimates for predicting long-term graft failure (average mean absolute prediction error of 0.0140, 0.0138 and 0.0135 for Cox, Fine-Gray, and cause-specific Cox models, respectively). Discrimination and overall fit were comparable in the validation cohorts, with concordance index ranging from 0.76 to 0.87. Across various subpopulations and clinical scenarios, the models performed well and similarly, although in some high-risk groups (such as donors over 65 years old), the findings suggest a trend towards moderately improved calibration when using a competing risk approach. CONCLUSIONS: Competing and noncompeting risk models performed similarly in predicting long-term kidney graft failure.

Successful prevention of BK-polyomavirus nephropathy using extracorporeal photopheresis for immunosuppression minimisation following severe BK polyomavirus replication after kidney transplantation in a double lung transplant recipient, a case report.

BACKGROUND: BK-polyomavirus (BKpyV) nephropathy (BKVN) is associated with end-stage kidney disease in kidney and non-kidney solid organ transplantation, with no curative treatment. CASE PRESENTATION: A 45-year-old woman with a past medical history of double lung transplantation subsequently developed end-stage kidney disease, of undetermined origin. One month after receiving a kidney transplant, a diagnosis of early BKVN was suspected, and in retrospect was a reasonable cause for the loss of her native kidneys. Minimisation of immunosuppression, achieved through extracorporeal photopheresis, allowed clearance of BKpyV and so prevented nephropathy. Both lung and kidney grafts had a satisfactory and stable function after one year of follow-up, with no rejection. CONCLUSIONS: Extracorporeal photopheresis may have facilitated minimisation of immunosuppression and BKpyV clearance without lung allograft rejection.

Concepts and applications of digital twins in healthcare and medicine.

The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the digital entity. It can predict perturbations related to the physical object's function. The obvious applications of DTs in healthcare and medicine are extremely attractive prospects that have the potential to revolutionize patient diagnosis and treatment. However, challenges including technical obstacles, biological heterogeneity, and ethical considerations make it difficult to achieve the desired goal. Advances in multi-modal deep learning methods, embodied AI agents, and the metaverse may mitigate some difficulties. Here, we discuss the basic concepts underlying DTs, the requirements for implementing DTs in medicine, and their current and potential healthcare uses. We also provide our perspective on five hallmarks for a healthcare DT system to advance research in this field.

Evaluation of non-invasive biomarkers of kidney allograft rejection in a prospective multicenter unselected cohort study (EU-TRAIN).

Non-invasive biomarkers are promising tools for improving kidney allograft rejection monitoring, but their clinical adoption requires more evidence in specifically designed studies. To address this unmet need, we designed the EU-TRAIN study, a large prospective multicentric unselected cohort funded by the European Commission. Here, we included consecutive adult patients who received a kidney allograft in nine European transplant centers between November 2018 and June 2020. We prospectively assessed gene expression levels of 19 blood messenger RNAs, four antibodies targeting non-human leukocyte antigen (HLA) endothelial antigens, together with circulating anti-HLA donor-specific antibodies (DSA). The primary outcome was allograft rejection (antibody-mediated, T cell-mediated, or mixed) in the first year post-transplantation. Overall, 412 patients were included, with 812 biopsies paired with a blood sample. CD4 gene expression was significantly associated with rejection, while circulating anti-HLA DSA had a significant association with allograft rejection and a strong association with antibody-mediated rejection. All other tested biomarkers, including AKR1C3, CD3E, CD40, CD8A, CD9, CTLA4, ENTPD1, FOXP3, GZMB, ID3, IL7R, MS4A1, MZB1, POU2AF1, POU2F1, TCL1A, TLR4, and TRIB1, as well as antibodies against angiotensin II type 1 receptor, endothelin 1 type A receptor, C3a and C5a receptors, did not show significant associations with allograft rejection. The blood messenger RNAs and non-HLA antibodies did not show an additional value beyond standard of care monitoring parameters and circulating anti-HLA DSA to predict allograft rejection in the first year post-transplantation. Thus, our results open avenues for specifically designed studies to demonstrate the clinical relevance and implementation of other candidate non-invasive biomarkers in kidney transplantation practice.

Antibody Mediated Rejection and T-cell Mediated Rejection Molecular Signatures Using Next-Generation Sequencing in Kidney Transplant Biopsies.

Recently, interest in transcriptomic assessment of kidney biopsies has been growing. This study investigates the use of NGS to identify gene expression changes and analyse the pathways involved in rejection. An Illumina bulk RNA sequencing on the polyadenylated RNA of 770 kidney biopsies was conducted. Differentially-expressed genes (DEGs) were determined for AMR and TCMR using DESeq2. Genes were segregated according to their previous descriptions in known panels (microarray or the Banff Human Organ Transplant (B-HOT) panel) to obtain NGS-specific genes. Pathway enrichment analysis was performed using the Reactome and Kyoto Encyclopaedia of Genes and Genomes (KEGG) public repositories. The differential gene expression using NGS analysis identified 6,141 and 8,478 transcripts associated with AMR and TCMR. While most of the genes identified were included in the microarray and the B-HOT panels, NGS analysis identified 603 (9.8%) and 1,186 (14%) new specific genes. Pathways analysis showed that the B-HOT panel was associated with the main immunological processes involved during AMR and TCMR. The microarrays specifically integrated metabolic functions and cell cycle progression processes. Novel NGS-specific based transcripts associated with AMR and TCMR were discovered, which might represent a novel source of targets for drug designing and repurposing.

Cell-free DNA for the detection of kidney allograft rejection.

Donor-derived cell-free DNA (dd-cfDNA) is an emerging noninvasive biomarker that has the potential to detect allograft injury. The capacity of dd-cfDNA to detect kidney allograft rejection and its added clinical value beyond standard of care patient monitoring is unclear. We enrolled 2,882 kidney allograft recipients from 14 transplantation centers in Europe and the United States in an observational population-based study. The primary analysis included 1,134 patients. Donor-derived cell-free DNA levels strongly correlated with allograft rejection, including antibody-mediated rejection (P < 0.0001), T cell-mediated rejection (P < 0.0001) and mixed rejection (P < 0.0001). In multivariable analysis, circulating dd-cfDNA was significantly associated with allograft rejection (odds ratio 2.275; 95% confidence interval (CI) 1.902-2.739; P < 0.0001) independently of standard of care patient monitoring parameters. The inclusion of dd-cfDNA to a standard of care prediction model showed improved discrimination (area under the curve 0.777 (95% CI 0.741-0.811) to 0.821 (95% CI 0.784-0.852); P = 0.0011) and calibration. These results were confirmed in the external validation cohorts (n = 1,748) including a cohort of African American patients (n = 439). Finally, dd-cfDNA showed high predictive value to detect subclinical rejection in stable patients. Our study provides insights on the potential value of assessing dd-cfDNA, in addition to standard of care monitoring, to improve the detection of allograft rejection. ClinicalTrials.gov registration: NCT05995379 .

Integrative multi-omics profiling in human decedents receiving pig heart xenografts.

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

Design, cohort profile and comparison of the KTD-Innov study: a prospective multidimensional biomarker validation study in kidney allograft rejection.

There is an unmet need for robust and clinically validated biomarkers of kidney allograft rejection. Here we present the KTD-Innov study (ClinicalTrials.gov, NCT03582436), an unselected deeply phenotyped cohort of kidney transplant recipients with a holistic approach to validate the clinical utility of precision diagnostic biomarkers. In 2018-2019, we prospectively enrolled consecutive adult patients who received a kidney allograft at seven French centers and followed them for a year. We performed multimodal phenotyping at follow-up visits, by collecting clinical, biological, immunological, and histological parameters, and analyzing a panel of 147 blood, urinary and kidney tissue biomarkers. The primary outcome was allograft rejection, assessed at each visit according to the international Banff 2019 classification. We evaluated the representativeness of participants by comparing them with patients from French, European, and American transplant programs transplanted during the same period. A total of 733 kidney transplant recipients (64.1% male and 35.9% female) were included during the study. The median follow-up after transplantation was 12.3 months (interquartile range, 11.9-13.1 months). The cumulative incidence of rejection was 9.7% at one year post-transplant. We developed a distributed and secured data repository in compliance with the general data protection regulation. We established a multimodal biomarker biobank of 16,736 samples, including 9331 blood, 4425 urinary and 2980 kidney tissue samples, managed and secured in a collaborative network involving 7 clinical centers, 4 analytical platforms and 2 industrial partners. Patients' characteristics, immune profiles and treatments closely resembled those of 41,238 French, European and American kidney transplant recipients. The KTD-Innov study is a unique holistic and multidimensional biomarker validation cohort of kidney transplant recipients representative of the real-world transplant population. Future findings from this cohort are likely to be robust and generalizable.

High-dimensional mass cytometry identified circulating natural killer T-cell subsets associated with protection from cytomegalovirus infection in kidney transplant recipients.

Cytomegalovirus (CMV) infection is associated with poor kidney transplant outcomes. While innate and adaptive immune cells have been implicated in its prevention, an in-depth characterization of the in vivo kinetics of multiple cell subsets and their role in protecting against CMV infection has not been achieved. Here, we performed high-dimensional immune phenotyping by mass cytometry, and functional assays, on 112 serially collected samples from CMV seropositive kidney transplant recipients. Advanced unsupervised deep learning analysis was used to assess immune cell populations that significantly correlated with prevention against CMV infection and anti-viral immune function. Prior to infection, kidney transplant recipients who developed CMV infection showed significantly lower CMV-specific cell-mediated immune (CMI) frequencies than those that did not. A broad diversity of circulating cell subsets within innate and adaptive immune compartments were associated with CMV infection or protective CMV-specific CMI. While percentages of CMV (tetramer-stained)-specific T cells associated with high CMI responses and clinical protection, circulating CD3+CD8midCD56+ NK-T cells overall strongly associated with low CMI and subsequent infection. However, three NK-T cell subsets sharing the CD11b surface marker associated with CMV protection and correlated with strong anti-viral CMI frequencies in vitro. These data were validated in two external independent cohorts of kidney transplant recipients. Thus, we newly describe the kinetics of a novel NK-T cell subset that may have a protective role in post-transplantation CMV infection. Our findings pave the way to more mechanistic studies aimed at understanding the function of these cells in protection against CMV infection.

Comparing the prognostic performance of iBOX and biopsy-proven acute rejection for long-term kidney graft survival.

Biopsy-proven acute rejection (BPAR) occurs in approximately 10% of kidney transplant recipients in the first year, making superiority trials unfeasible. iBOX, a quantitative composite of estimated glomerular filtration rate, proteinuria, antihuman leukocyte antigen donor-specific antibody, and + full/- abbreviated kidney histopathology, is a new proposed surrogate endpoint. BPAR's prognostic ability was compared with iBOX in a pooled cohort of 1534 kidney transplant recipients from 4 data sets, including 2 prospective randomized controlled trials. Discrimination analyses showed mean c-statistic differences between both iBOX compared with BPAR of 0.25 (95% confidence interval: 0.17-0.32) for full iBOX and 0.24 (95% confidence interval: 0.16-0.32) for abbreviated iBOX, indicating statistically significantly higher c-statistic values for the iBOX prognosis of death-censored graft survival. Mean (± standard error) c-statistics were 0.81 ± 0.03 for full iBOX, 0.80 ± 0.03 for abbreviated iBOX, and 0.57 ± 0.03 for BPAR. In calibration analyses, predicted graft loss events from both iBOX models were not significantly different from those observed. However, for BPAR, the predicted events were significantly (P < .01) different (observed: 64; predicted: 70; full iBOX: 76; abbreviated iBOX: 173 BPAR). IBOX at 1-year posttransplant is superior to BPAR in the first year posttransplant in graft loss prognostic performance, providing valuable additional information and facilitating the demonstration of superiority of novel immunosuppressive regimens.

Long-term Kidney Transplant Survival Across the Globe.

BACKGROUND: The outcomes after kidney transplantation (KT), including access, wait time, and other issues around the globe, have been studied. However, issues do vary from one country to another. METHODS: We obtained data from several countries from North America, South America, Europe, Asia, and Australia, including the number of patients awaiting KT from 2015, transplant rate per million population (pmp), proportion of living donor and deceased donor (LD/DD) KT, and posttransplant survival. We also sought opinions on key difficulties faced by each of these countries with respect to KT and long-term survival. RESULTS: Variation in access to KT across the globe was noted. Countries with the highest rates of KT pmp included the United States (79%) and Spain (71%). A higher proportion of LD transplants was noted in Japan (93%), India (85%), Singapore (63%), and South Korea (63%). A higher proportion of DD KTs was noted in Spain (90%), Brazil (90%), France (85%), Italy (85%), Finland (85%), Australia-New Zealand (80%), and the United States (77%). The 5-y graft survival for LD was highest in South Korea (95%), Singapore (94%), Italy (93%), Finland (93%), and Japan (93%), whereas for DD, it was South Korea (93%), Italy (88%), Japan (86%), and Singapore (86%). The common issues surrounding KTs are access and a limited number of LDs and DDs. Key issues identified for long-term survival were increasing age of donors and recipients, higher recipient comorbidity, and posttransplant events, such as alloimmune injury to the kidney, infection, cancer, and suboptimal adherence to therapy. CONCLUSIONS: A unified approach is necessary to improve issues surrounding KT as the demand continues to increase.

Long-Term Outcomes after Conversion to a Belatacept-Based Immunosuppression in Kidney Transplant Recipients.

BACKGROUND: Conversion to a belatacept-based immunosuppression is currently used as a calcineurin inhibitor (CNI) avoidance strategy when the CNI-based standard-of-care immunosuppression is not tolerated after kidney transplantation. However, there is a lack of evidence on the long-term benefit and safety after conversion to belatacept. METHODS: We prospectively enrolled 311 kidney transplant recipients from 2007 to 2020 from two referral centers, converted from CNI to belatacept after transplant according to a prespecified protocol. Patients were matched at the time of conversion to patients maintained with CNIs, using optimal matching. The primary end point was death-censored allograft survival at 7 years. The secondary end points were patient survival, eGFR, and safety outcomes, including serious viral infections, immune-related complications, antibody-mediated rejection, T-cell-mediated rejection, de novo anti-HLA donor-specific antibody, de novo diabetes, cardiovascular events, and oncologic complications. RESULTS: A total of 243 patients converted to belatacept (belatacept group) were matched to 243 patients maintained on CNIs (CNI control group). All recipient, transplant, functional, histologic, and immunologic parameters were well balanced between the two groups with a standardized mean difference below 0.05. At 7 years post-conversion to belatacept, allograft survival was 78% compared with 63% in the CNI control group ( P < 0.001 for log-rank test). The safety outcomes showed a similar rate of patient death (28% in the belatacept group versus 36% in the CNI control group), active antibody-mediated rejection (6% versus 7%), T-cell-mediated rejection (4% versus 4%), major adverse cardiovascular events, and cancer occurrence (9% versus 11%). A significantly higher rate of de novo proteinuria was observed in the belatacept group as compared with the CNI control group (37% versus 21%, P < 0.001). CONCLUSIONS: This real-world evidence study shows that conversion to belatacept post-transplant was associated with lower risk of graft failure and acceptable safety outcomes compared with patients maintained on CNIs. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Long-term Outcomes after Conversion to Belatacept, NCT04733131 .

A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients.

In kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate between donor-inherited lesions and those acquired post-transplantation. However, many centers do not perform such biopsies since they are invasive, costly and may delay the transplant procedure. We aim to generate a non-invasive virtual biopsy system using routinely collected donor parameters. Using 14,032 day-zero kidney biopsies from 17 international centers, we develop a virtual biopsy system. 11 basic donor parameters are used to predict four Banff kidney lesions: arteriosclerosis, arteriolar hyalinosis, interstitial fibrosis and tubular atrophy, and the percentage of renal sclerotic glomeruli. Six machine learning models are aggregated into an ensemble model. The virtual biopsy system shows good performance in the internal and external validation sets. We confirm the generalizability of the system in various scenarios. This system could assist physicians in assessing organ quality, optimizing allograft allocation together with discriminating between donor derived and acquired lesions post-transplantation.

Report of the 2022 Banff Heart Concurrent: Focus on non-human leukocyte antigen antibodies in rejection and the pathology of "mixed" rejection.

The Banff Heart Concurrent Session, held as part of the 16th Banff Foundation for Allograft Pathology Conference at Banff, Alberta, Canada, on September 21, 2022, focused on 2 major topics: non-human leukocyte antigen (HLA) antibodies and mixed rejection. Each topic was addressed in a multidisciplinary fashion with clinical, immunological, and pathology perspectives and future developments and prospectives. Following the Banff organization model and principles, the collective aim of the speakers on each topic was to • Determine current knowledge gaps in heart transplant pathology • Identify limitations of current pathology classification systems • Discuss next steps in addressing gaps and refining classification system.