Search

In kidney transplant recipients, urine CXCL9 and CXCL10 (uCXCL9/10) chemokines have reached a sufficiently high level of evidence to be recommended by the European Society of Organ Transplantation for the monitoring of immune quiescence. To assess the risk of acute rejection (AR), the advantage of uCXCL9/10 is their cost-effectiveness and their high diagnostic performance. Here, we evaluated the feasibility of a next-generation immunoassay for quantifying uCXCL9/10 levels. It demonstrated high efficiency with minimal workflow and a 90-min time to result. Preanalytical studies indicated stability of uCXCL9/10 levels and analytical studies confirmed excellent linearity and precision. In a cohort of 1048 samples collected at biopsy, the results correlated significantly with ELISA quantification and were integrated into a previously validated 8-parameter urine chemokine model. The next generation immunoassay achieved an accuracy of 0.84 for AR diagnosis. This study validates this technology as a robust, locally available and unexpensive platform and marks a significant step towards the widespread implementation of uCXCL9/10, for immune quiescence monitoring. Therefore, we developed an open-access web application using uCXCL9/10 to calculate AR risk and improve clinical decision-making to perform biopsy, ushering in a new era in kidney transplantation, where personalized, data-driven care becomes the norm., (© 2024. The Author(s).)

Introduction: The successes in the field of pediatric kidney transplantation over the past 60 years have been extraordinary. Year over year, there have been significant improvements in short-term graft survival. However, improvements in longer-term outcomes have been much less apparent. One important contributor has been the phenomenon of low-level rejection in the absence of clinical manifestations-so-called subclinical rejection (SCR)., Methods: Traditionally, rejection has been diagnosed by changes in clinical parameters, including but not limited to serum creatinine and proteinuria. This review examines the shortcomings of this approach, the effects of SCR on kidney allograft outcome, the benefits and drawbacks of surveillance biopsies to identify SCR, and new urine and blood biomarkers that define the presence or absence of SCR., Results: Serum creatinine is an unreliable index of SCR. Surveillance biopsies are the method most utilized to detect SCR. However, these have significant drawbacks. New biomarkers show promise. These biomarkers include blood gene expression profiles and donor derived-cell free DNA; urine gene expression profiles; urinary cytokines, chemokines, and metabolomics; and other promising blood and urine tests., Conclusion: Specific emphasis is placed on studies carried out in pediatric kidney transplant recipients., Trial Registration: ClinicalTrials.gov: NCT03719339., (© 2024 The Author(s). Pediatric Transplantation published by Wiley Periodicals LLC.)

Endomyocardial biopsies for rejection monitoring after heart transplantation are generally performed through the right internal jugular vein. We aimed to assess the feasibility and safety of using the left internal jugular vein approach as a valid alternative to a femoral vein for endomyocardial biopsies whenever thrombosis of the right internal jugular vein precludes insertion of a bioptome. We have reviewed our experience with heart transplantation in the last 2 decades to identify patients in whom surveillance endomyocardial biopsy was performed through the left internal jugular vein. We herein describe the step-by-step procedure and report the preliminary results. From May 1, 2000 to January 31, 2024, 561 orthotopic heart transplants have been performed in our unit. In 49 patients (8.7%), the right internal jugular vein access was found to be unsuitable or occluded at eco-Doppler evaluation; in 15 of them (30%) a total of 206 endomyocardial biopsies have been performed, using the left internal jugular vein, without complications. Our experience demonstrates that the left internal jugular vein is a valid alternative approach for endomyocardial biopsies when the right internal jugular vein is not available. This technique is feasible, safe and reproducible and allows adequate rejection monitoring after heart transplantation., (Copyright © 2024 Italian Federation of Cardiology - I.F.C. All rights reserved.)

Introduction: Acute rejection (AR) undermines the life-extending benefits of kidney transplantation and is diagnosed using the invasive biopsy procedure. T cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR), or concurrent TCMR + ABMR (Mixed Rejection [MR]) are the three major types of AR. Development of noninvasive biomarkers diagnostic of AR due to any of the three types is a useful addition to the diagnostic armamentarium., Methods: We developed customized RT-qPCR assays and measured urinary cell mRNA copy numbers in 145 biopsy-matched urine samples from 126 kidney allograft recipients. We determined whether the urinary cell three-gene signature diagnostic of TCMR (Suthanthiran et al., 2013) discriminates patients with no rejection biopsies (NR, n = 50) from those with ABMR (n = 28) or MR (n = 20) biopsies., Results: The urinary cell three-gene signature discriminated all three types of rejection biopsies from NR biopsies (P < 0.0001, One-way ANOVA). Dunnett's multiple comparisons test yielded P < 0.0001 for NR vs. TCMR; P < 0.001 for NR vs. ABMR; and P < 0.0001 for NR vs. MR. By bootstrap resampling, optimism-corrected area under the receiver operating characteristic curve (AUC) was 0.749 (bias-corrected 95% confidence interval [CI], 0.638 to 0.840) for NR vs. TCMR (P < 0.0001); 0.780 (95% CI, 0.656 to 0.878) for NR vs. ABMR (P < 0.0001); and 0.857 (95% CI, 0.727 to 0.947) for NR vs. MR (P < 0.0001). All three rejection categories were distinguished from NR biopsies with similar accuracy (all AUC comparisons P > 0.05)., Conclusion: The urinary cell three-gene signature score discriminates AR due to TCMR, ABMR or MR from NR biopsies in human kidney allograft recipients., Competing Interests: Declaration of competing interest M. Suthanthiran has a Consultancy Agreement with CareDx, Inc. Brisbane, CA. D.M. Dadhania D.M.D. has participated in industry sponsored studies organized by AlloVir Inc., CSL Behring, and Memo Therapeutics AG and served as consultant for CareDx, Inc. The other authors of this manuscript declare no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Pathologic antibody mediated rejection (pAMR) remains a major driver of graft failure in cardiac transplant patients. The endomyocardial biopsy remains the primary diagnostic tool but presents with challenges, particularly in distinguishing the histologic component (pAMR-H) defined by 1) intravascular macrophage accumulation in capillaries and 2) activated endothelial cells that expand the cytoplasm to narrow or occlude the vascular lumen. Frequently, pAMR-H is difficult to distinguish from acute cellular rejection (ACR) and healing injury. With the advent of digital slide scanning and advances in machine deep learning, artificial intelligence technology is widely under investigation in the areas of oncologic pathology, but in its infancy in transplant pathology. For the first time, we determined if a machine learning algorithm could distinguish pAMR-H from normal myocardium, healing injury and ACR., Materials and Methods: A total of 4,212 annotations (1,053 regions of normal, 1,053 pAMR-H, 1,053 healing injury and 1,053 ACR) were completed from 300 hematoxylin and eosin slides scanned using a Leica Aperio GT450 digital whole slide scanner at 40X magnification. All regions of pAMR-H were annotated from patients confirmed with a previous diagnosis of pAMR2 (>50% positive C4d immunofluorescence and/or >10% CD68 positive intravascular macrophages). Annotations were imported into a Python 3.7 development environment using the OpenSlide™ package and a convolutional neural network approach utilizing transfer learning was performed., Results: The machine learning algorithm showed 98% overall validation accuracy and pAMR-H was correctly distinguished from specific categories with the following accuracies: normal myocardium (99.2%), healing injury (99.5%) and ACR (99.5%)., Conclusion: Our novel deep learning algorithm can reach acceptable, and possibly surpass, performance of current diagnostic standards of identifying pAMR-H. Such a tool may serve as an adjunct diagnostic aid for improving the pathologist's accuracy and reproducibility, especially in difficult cases with high inter-observer variability. This is one of the first studies that provides evidence that an artificial intelligence machine learning algorithm can be trained and validated to diagnose pAMR-H in cardiac transplant patients. Ongoing studies include multi-institutional verification testing to ensure generalizability., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Plasma donor-derived cell-free DNA (dd-cfDNA) is used to screen for rejection in heart transplants. We launched the Trifecta-Heart study ( ClinicalTrials.gov No. NCT04707872), an investigator-initiated, prospective trial, to examine the correlations between genome-wide molecular changes in endomyocardial biopsies (EMBs) and plasma dd-cfDNA. The present report analyzes the correlation of plasma dd-cfDNA with gene expression in EMBs from 4 vanguard centers and compared these correlations with those in 604 kidney transplant biopsies in the Trifecta-Kidney study ( ClinicalTrials.gov No. NCT04239703)., Methods: We analyzed 137 consecutive dd-cfDNA-EMB pairs from 70 patients. Plasma %dd-cfDNA was measured by the Prospera test (Natera Inc), and gene expression in EMBs was assessed by Molecular Microscope Diagnostic System using machine-learning algorithms to interpret rejection and injury states., Results: Top transcripts correlating with dd-cfDNA were related to genes increased in rejection such as interferon gamma-inducible genes (eg, HLA-DMA ) but also with genes induced by injury and expressed in macrophages (eg, SERPINA1 and HMOX1 ). In gene enrichment analysis, the top dd-cfDNA-correlated genes reflected inflammation and rejection pathways. Dd-cfDNA correlations with rejection genes in EMB were similar to those seen in kidney transplant biopsies, with somewhat stronger correlations for TCMR genes in hearts and ABMR genes in kidneys. However, the correlations with parenchymal injury-induced genes and macrophage genes were much stronger in hearts., Conclusions: In this first analysis of Trifecta-Heart study, dd-cfDNA correlates significantly with molecular rejection but also with injury and macrophage infiltration, reflecting the proinflammatory properties of injured cardiomyocytes. The relationship supports the utility of dd-cfDNA in clinical management of heart transplant recipients., Competing Interests: The Trifecta study is an investigator-initiated study supported by a grant from Natera Inc to Transcriptome Sciences Inc/Alberta Transplant Applied Genomics Centre. P.F.H. reports having shares in Transcriptome Sciences Inc, a University of Alberta research company with an interest in molecular diagnostics and is a consultant to Natera Inc; all Natera Inc authors are employees and own equity at Natera Inc. The other authors declare no conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

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., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Molecular testing with gene-expression profiling (GEP) and donor-derived cell-free DNA (dd-cfDNA) is increasingly used in the surveillance for acute cellular rejection (ACR) after heart transplant. However, the performance of dual testing over each test individually has not been established. Further, the impact of dual noninvasive surveillance on clinical decision-making has not been widely investigated., Methods: We evaluated 2,077 subjects from the Surveillance HeartCare Outcomes Registry registry who were enrolled between 2018 and 2021 and had verified biopsy data and were categorized as dual negative, GEP positive/dd-cfDNA negative, GEP negative/dd-cfDNA positive, or dual positive. The incidence of ACR and follow-up testing rates for each group were evaluated. Positive likelihood ratios (LRs+) were calculated, and biopsy rates over time were analyzed., Results: The incidence of ACR was 1.5% for dual negative, 1.9% for GEP positive/dd-cfDNA negative, 4.3% for GEP negative/dd-cfDNA positive, and 9.2% for dual-positive groups. Follow-up biopsies were performed after 8.8% for dual negative, 14.2% for GEP positive/dd-cfDNA negative, 22.8% for GEP negative/dd-cfDNA positive, and 35.4% for dual-positive results. The LR+ for ACR was 1.37, 2.91, and 3.90 for GEP positive, dd-cfDNA positive, and dual-positive testing, respectively. From 2018 to 2021, biopsies performed between 2 and 12-months post-transplant declined from 5.9 to 5.3 biopsies/patient, and second-year biopsy rates declined from 1.5 to 0.9 biopsies/patient. At 2 years, survival was 94.9%, and only 2.7% had graft dysfunction., Conclusions: Dual molecular testing demonstrated improved performance for ACR surveillance compared to single molecular testing. The use of dual noninvasive testing was associated with lower biopsy rates over time, excellent survival, and low incidence of graft dysfunction., (Copyright © 2024 International Society for the Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.)

Antibody-mediated rejection (AMR) is a major cause of graft failure limiting long-term graft survival after kidney transplantation. Current diagnostic strategy to detect AMR is suboptimal and requires further improvement. Previously suggested treatment regimens for AMR could not demonstrate efficacy, however novel therapeutic agents are currently under investigation. Donor-derived cell-free DNA (dd-cfDNA) is a novel non-invasive biomarker for allograft injury, that has been mainly studied in the context of rejection. Its short-half-life in circulation and injury-dependent release are its key advantages that contribute to its superior diagnostic accuracy, compared to traditional biomarkers. Moreover, previous studies showed that dd-cfDNA-release is well-linked to histological and molecular features of AMR, and thus able to reflect real-time injury. Further observations suggest that dd-cfDNA can be used as a suitable screening tool for early detection of AMR in patients with donor-specific-anti-HLA-antibodies (DSA), as well as for monitoring AMR activity after anti-rejection treatment. The weight of evidence suggests that the integration of dd-cfDNA in the graft surveillance of patients with AMR, or those suspicious of AMR (e.g., due to the presence of donor-specific anti-HLA-antibodies) has an added value and might have a positive impact on outcomes in this specific cohort., Competing Interests: Authors JB, KB-K, and ES were employed by Chronix Biomedical GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Akifova, Budde, Oellerich, Beck, Bornemann-Kolatzki, Schütz and Osmanodja.)

Introduction: Understanding immune cell dynamics in kidney transplantation may provide insight into the mechanisms of rejection and improve patient management. B cells have gained interest with a special relevance of the "regulatory" subsets and their graft outcome prognostic value. In this study, we aimed to prove that the direct immunophenotyping and target gene expression analysis of kidney transplant patients' fresh whole blood will help to identify graft rejection risk and assist in the monitoring of kidney transplanted patients., Methods: We employed flow cytometry and qPCR techniques to characterize B and T cell subsets within fresh whole blood samples, with particular emphasis on transitional B cells (TrB) identified as CD19 + CD24 hi CD38 hi . TrB are a relevant population in the context of kidney transplantation and are closely associated with regulatory B cells (Bregs) in humans. Patients were monitored, tracking pertinent clinical parameters and kidney-related events, including alterations in graft function and episodes of biopsy proven rejection., Results: Higher percentages of TrB cells at 3 months after transplantation were positively associated with better graft outcomes and lower biopsy-proven acute rejection risk. Furthermore, a novel panel of B cell regulatory associated genes was validated at 3 months post-transplantation by qPCR analysis of peripheral blood mononuclear cell (PBMC) mRNA, showing high predictive power of graft events and prognostic value., Discussion: These findings suggest that monitoring TrB may provide interesting patient management information, improve transplant outcomes, and allow for personalized drug regimens to minimize clinical complications., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author MF declares that they were an editorial board member of Frontiers, at the time of submission. Thishad no impact on the peer review process and the final decision., (Copyright © 2024 Perezpayá, Garcia, Clos-Sansalvador, Sanroque-Muñoz, Font-Morón, Rodríguez-Martínez, Vila-Santandreu, Bover, Borràs, Cañas and Franquesa.)

Humoral immunity is a major waypoint towards chronic allograft dysfunction in lung transplantation (LT) recipients. Though allo-immunization and antibody-mediated rejection (AMR) are well-known entities, some diagnostic gaps need to be addressed. Morphological analysis could be enhanced by digital pathology and artificial intelligence-based companion tools. Graft transcriptomics can help to identify graft failure phenotypes or endotypes. Donor-derived cell free DNA is being evaluated for graft-loss risk stratification and tailored surveillance. Preventative therapies should be tailored according to risk. The donor pool can be enlarged for candidates with HLA sensitization, with strategies combining plasma exchange, intravenous immunoglobulin and immune cell depletion, or with emerging or innovative therapies such as imlifidase or immunoadsorption. In cases of insufficient pre-transplant desensitization, the effects of antibodies on the allograft can be prevented by targeting the complement cascade, although evidence for this strategy in LT is limited. In LT recipients with a humoral response, strategies are combined, including depletion of immune cells (plasmapheresis or immunoadsorption), inhibition of immune pathways, or modulation of the inflammatory cascade, which can be achieved with photopheresis. Altogether, these innovative techniques offer promising perspectives for LT recipients and shape the 21st century's armamentarium against AMR., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Messika, Belousova, Parquin and Roux.)

The QuantiFERON CMV (QCMV) test evaluates specific adaptive immune system activity against CMV by measuring IFN-γ released by activated CD8+ T lymphocytes. We aimed to evaluate the QCMV test as a predictive tool for CMV manifestations and acute or chronic lung allograft rejection (AR and CLAD) in lung transplant (LTx) patients. A total of 73 patients were divided into four groups based on donor and recipient (D/R) serology for CMV and QCMV assay: group A low-risk for CMV infection and disease (D-/R-); group B and C at intermediate-risk (R+), group B with non-reactive QCMV and group C with reactive QCMV; group D at high-risk (D+/R-). Group D patients experienced higher viral replication; no differences were observed among R+ patients of groups B and C. D+/R- patients had a higher number of AR events and group C presented a lower incidence of AR. Prevalence of CLAD at 24 months was higher in group B with a higher risk of CLAD development (OR 6.33). The QCMV test allows us to identify R+ non-reactive QCMV population as the most exposed to onset of CLAD. This population had a higher, although non-significant, susceptibility to AR compared to the R+ population with reactive QCMV.

Background: Delayed graft function (DGF) after kidney transplantation is associated with adverse patients and allograft outcomes. A longer duration of DGF is predictive of worse graft outcomes compared to a shorter duration. Posttransplant serum β2-microglobulin (B2M) is associated with long-term graft outcomes, but its relationship with DGF recovery is unknown., Methods: We included all kidney-only transplant recipients with DGF enrolled in the E-DGF trial. Duration of DGF was defined as the interval between the transplant and the last dialysis session. We analyzed the association of standardized serum creatinine (Scr) and B2M on postoperative Days (POD) 1-7 during the subsequent days of DGF with the recovery of DGF., Results: A total of 97 recipients with DGF were included. The mean duration of DGF was 11.0 ± 11.2 days. Higher Scr was not associated with the duration of DGF in unadjusted or adjusted models. Higher standardized B2M, in contrast, was associated with a prolonged duration of DGF. This association remained in models adjusting for baseline characteristics from POD 2 (3.19 days longer, 95% CI: 0.46-5.93; p = 0.02) through Day 6 of DGF (4.97 days longer, 95% CI: 0.75-9.20; p = 0.02). There was minimal change in mean Scr (0.01 ± 0. 10 mg/dL per day; p = 0.32), while B2M significantly decreased as the time to recovery approached (-0.14 ± 0.05 mg/L per day; p = 0.006), among recipients with DGF., Conclusion: B2M is more strongly associated with DGF recovery than Scr. Posttransplant B2M may be an important biomarker to monitor during DGF., Trial Registration: ClinicalTrials.gov identifier: NCT03864926., (© 2024 The Author(s). Clinical Transplantation published by Wiley Periodicals LLC.)

Background: There seems to be a close link between the changing levels of selenoproteins, which are important for maintaining redox homeostasis in the body, and acute rejection of kidney transplants. The aim of this study was to explore the diagnostic value of selenoprotein change characteristics in renal tissues for acute rejection of kidney transplantation., Methods: We first explored the potential biological functions of 25 selenoproteins in the human body by enrichment analysis and used the HPA database to clarify the expression levels of selenoproteins in kidney tissues; We then constructed a diagnostic model using "Logistic regression analysis" and "Nomogram model"; Calibration curves and ROC curves were used to evaluate the diagnostic models, and clinical decision curves (DCA) were used to assess the diagnostic value of selenoprotein changes to the clinic; Single-gene GSEA enrichment analysis to further explore the potential regulatory mechanisms of selenoproteins; The Cibersort algorithm explores the level of immune cell infiltration and uses correlation analysis to clarify the correlation between selenoproteins and immune cells; We further assessed the diagnostic value of selenoproteins in kidney transplantation ABMR and TCMR, respectively. Finally, we validated the expression level of selenoproteins in kidney tissues by constructing a rat model of acute rejection of kidney transplantation using transcriptome sequencing., Results: Our enrichment analysis revealed that selenoproteins are mainly closely associated with biological functions such as oxidative stress, inflammation, and immune regulation (P<0.05); The HPA database suggests that a total of 23 selenoproteins can be expressed in kidney tissue. We constructed a diagnostic model using these 23 selenoproteins, and both calibration curves and ROC curves proved that their change levels have good diagnostic value for acute rejection of kidney transplantation, and DCA curves proved the role of selenoproteins in clinical decision-making; Single-gene GSEA enrichment analysis revealed that selenoproteins are closely associated with immune regulation-related pathways (P<0.05); The Cibersort algorithm identified 10 immune cell infiltration levels that were significantly altered during acute rejection of kidney transplantation (P<0.05), while correlation analyses indicated that selenoproteins correlate with multiple immune cell infiltrations; In ABMR and TCMR, we again verified the diagnostic value of selenoprotein changes in acute rejection of kidney transplantation. Finally, we found significant differences in the expression levels of nine selenoproteins in a rat model of acute rejection of kidney transplantation (P<0.05)., Conclusion: Changes in selenoproteins in renal tissues have good diagnostic value for acute rejection of kidneyl transplantation, and selenoproteins may be able to be a potential target for alleviating acute rejection of kidney transplantation., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: Despite significant progress over the last decades in the survival of kidney allografts, several risk factors remain contributing to worsening kidney function or even loss of transplants. We aimed to evaluate a new machine learning method to identify these variables which may predict the early graft loss in kidney transplant patients and to assess their usefulness for improving clinical decisions., Material and Methods: A retrospective cohort study was carried out with 627 kidney transplant patients followed at least three months. All these data were pre-processed, and their selected features were used to develop an automatically working a machine learning algorithm; this algorithm was then applied for training and parameterization of the model; and finally, the tested model was then used for the analysis of patients' features that were the most impactful for the prediction of clinical outcomes. Our models were evaluated using the Area Under the Curve (AUC), and the SHapley Additive exPlanations (SHAP) algorithm was used to interpret its predictions., Results: The final selected model achieved a precision of 0.81, a sensitivity of 0.61, a specificity of 0.89, and an AUC value of 0.84. In our model, serum creatinine levels of kidney transplant patients, evaluated at the hospital discharge, proved to be the most important factor in the decision-making for the allograft loss. Patients with a weight equivalent to a BMI closer to the normal range prior to a kidney transplant are less likely to experience graft loss compared to patients with a BMI below the normal range. The age of patients at transplantation and Polyomavirus (BKPyV) infection had significant impact on clinical outcomes in our model., Conclusions: Our algorithm suggests that the main characteristics that impacted early allograft loss were serum creatinine levels at the hospital discharge, as well as the pre-transplant values such as body weight, age of patients, and their BKPyV infection. We propose that machine learning tools can be developed to effectively assist medical decision-making in kidney transplantation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing personal relationships or financial interests that could have appeared to influence this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: The aim of this study was to investigate the incidence and clinical features of immunologic rejection after deep anterior lamellar keratoplasty (DALK)., Methods: This study included 411 patients (464 eyes, median age [interquartile range; IQR] 55.8 years [36.1-69.5]) who underwent DALK at Tokyo Dental College between June 1997 and 2021. Of 411 patients, 24 (24 eyes [5.2%], 51.9 years [IQR 31.6-65.4]) developed immunologic rejection. We characterized the clinical features, risk factors associated with immunologic rejection, and prognosis., Results: The interval between DALK and immunologic rejection was 14.5 (range, 5-78) months. Immunologic rejection occurred after cessation/reduction of topical steroid in 9 (47.4%) and suture removal in 4 eyes (21.1%). The postoperative duration of topical steroid use in eyes with immunologic rejection was significantly shorter (10.0 months, [IQR 6.0-14.0]) than those without immunologic rejection (28.3 [IQR 15.8-42.7], P = 0.001). Immunologic rejection manifested as stromal edema in 19 (100.0%), ciliary hyperemia in 17 (89.5%), keratic precipitates in 13 (68.4%), epithelial edema in 13 (68.4%), infiltration in 9 (47.4%), corneal opacity in 4 (21.1%), and Descemet membrane detachment in 2 eyes (10.5%). After treatment, corneal clarity was restored in 17 eyes (89.5%); however, immunologic rejection led to corneal endothelial decompensation in 2 eyes (10.5%). Endothelial cell density decreased from 1795.7 ± 722.6 to 1651.6 ± 655.6 cells/mm 2 after immunologic rejection ( P = 0.074)., Conclusions: Post-DALK immunologic rejection was associated with specific clinical triggers such as reduction/cessation of topical steroids or suture removal., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Graft survival is a critical end point in adult-to-adult living donor liver transplantation (ALDLT), where graft procurement endangers the lives of healthy individuals. Therefore, ALDLT must be responsibly performed in the perspective of a positive harm-to-benefit ratio. This study aimed to develop a risk prediction model for early (3 months) graft failure (EGF) following ALDLT. Donor and recipient factors associated with EGF in ALDLT were studied using data from the European Liver Transplant Registry. An artificial neural network classification algorithm was trained on a set of 2073 ALDLTs, validated using cross-validation, tested on an independent random-split sample (n=518), and externally validated on United Network for Organ Sharing Standard Transplant Analysis and Research data. Model performance was assessed using the AUC, calibration plots, and decision curve analysis. Graft type, graft weight, level of hospitalization, and the severity of liver disease were associated with EGF. The model ( http://ldlt.shinyapps.io/eltr&#95;app ) presented AUC values at cross-validation, in the independent test set, and at external validation of 0.69, 0.70, and 0.68, respectively. Model calibration was fair. The decision curve analysis indicated a positive net benefit of the model, with an estimated net reduction of 5-15 EGF per 100 ALDLTs. Estimated risks>40% and<5% had a specificity of 0.96 and sensitivity of 0.99 in predicting and excluding EGF, respectively. The model also stratified long-term graft survival ( p <0.001), which ranged from 87% in the low-risk group to 60% in the high-risk group. In conclusion, based on a panel of donor and recipient variables, an artificial neural network can contribute to decision-making in ALDLT by predicting EGF risk., (Copyright © 2023 American Association for the Study of Liver Diseases.)

Until now, the ability to predict or retard immune-mediated rejection events after lung transplantation is still limited due to the lack of specific biomarkers. The pressing need remains to early diagnose or predict the onset of chronic lung allograft dysfunction (CLAD) and its differential phenotypes that is the leading cause of death. Omics technologies (mainly genomics, epigenomics, and transcriptomics) combined with advanced bioinformatic platforms are clarifying the key immune-related molecular routes that trigger early and late events of lung allograft rejection supporting the biomarker discovery. The most promising biomarkers came from genomics. Both unregistered and NIH-registered clinical trials demonstrated that the increased percentage of donor-derived cell-free DNA in both plasma and bronchoalveolar lavage fluid showed a good diagnostic performance for clinically silent acute rejection events and CLAD differential phenotypes. A further success arose from transcriptomics that led to development of Molecular Microscope® Diagnostic System (MMDx) to interpret the relationship between molecular signatures of lung biopsies and rejection events. Other immune-related biomarkers of rejection events may be exosomes, telomer length, DNA methylation, and histone-mediated neutrophil extracellular traps (NETs) but none of them entered in registered clinical trials. Here, we discuss novel and existing technologies for revealing new immune-mediated mechanisms underlying acute and chronic rejection events, with a particular focus on emerging biomarkers for improving precision medicine of lung transplantation field., Competing Interests: Declaration of Competing Interest Nothing to disclose., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Heart transplantation is an effective treatment for end-stage congestive heart failure, however, achieving the right balance of immunosuppression to maintain graft function while minimising adverse effects is challenging. Serial endomyocardial biopsies (EMBs) are currently the standard for rejection surveillance, despite being invasive. Replacing EMB-based surveillance with cardiac magnetic resonance (CMR)-based surveillance for acute cardiac allograft rejection has shown feasibility. This study aimed to assess the cost-effectiveness of CMR-based surveillance in the first year after heart transplantation., Method: A prospective clinical trial was conducted with 40 orthotopic heart transplant (OHT) recipients. Participants were randomly allocated into two surveillance groups: EMB-based, and CMR-based. The trial included economic evaluations, comparing the frequency and cost of surveillance modalities in relation to quality-adjusted life years (QALYs) within the first year post-transplantation. Sensitivity analysis encompassed modelled data from observed EMB and CMR arms, integrating two hypothetical models of expedited CMR-based surveillance., Results: In the CMR cohort, 238 CMR scans and 15 EMBs were conducted, versus (vs) 235 EMBs in the EMB group. CMR surveillance yielded comparable rejection rates (CMR 74 vs EMB 94 events, p=0.10) and did not increase hospitalisation risk (CMR 32 vs EMB 46 events, p=0.031). It significantly reduced the necessity for invasive EMBs by 94%, lowered costs by an average of AUD$32,878.61, and enhanced cumulative QALY by 0.588 compared with EMB. Sensitivity analysis showed that increased surveillance with expedited CMR Models 1 and 2 were more cost-effective than EMB (all p<0.01), with CMR Model 1 achieving the greatest cost savings (AUD$34,091.12±AUD$23,271.86 less) and utility increase (+0.62±1.49 QALYs, p=0.011), signifying an optimal cost-utility ratio. Model 2 showed comparable utility to the base CMR model (p=0.900) while offering the benefit of heightened surveillance frequency during periods of elevated rejection risk., Conclusions: CMR-based rejection surveillance in orthotopic heart transplant recipients provides a cost-effective alternative to EMB-based surveillance. Furthermore, it reduces the need for invasive procedures, without increased risk of rejection or hospitalisation for patients, and can be incorporated economically for expedited surveillance. These findings have important implications for improving patient care and optimising resource allocation in post-transplant management., Competing Interests: Conflicts of Interest There are no conflicts of interest to disclose., (Copyright © 2024 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). All rights reserved.)

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 ., (© 2024. The Author(s).)

Background: Macrophage type 1 (M1) cells are associated with both acute kidney injury (AKI) during kidney transplantation and acute rejection (AR) after kidney transplantation. Our study explored M1-related biomarkers involved in both AKI and AR and their potential biological functions., Methods: Based on the Gene Expression Omnibus (GEO) database, the immune cell infiltration levels and differentially expressed genes were examined in AKI and AR in the kidney transplantation; M1-related genes shared in AKI and AR were identified using weighted gene co-expression analysis (WGCNA) system. Subsequently, protein-protein interaction (PPI) networks and machine learning methods to identify Hub genes and construct diagnostic models. Both AKI model and AR rat models were built to validate the expressions of Hub genes and test the injury phenotype, oxidative stress markers, and inflammatory factors. Finally, the transcription factor (TF)-Hub gene and micro-RNA (miRNA)-Hub gene regulatory networks were constructed based on identified Hub genes., Results: Out of 2167 differential expression genes (DEGs) in AKI and 2100 DEGs in AR, four M1-related Hub genes were obtained by PPI networks and machine learning methods, namely GBP2, TYROBP, CCR5, and TLR8. The calibration curves in the nomogram diagnostic model for these four Hub genes suggested the same predictive probability as an ideal model for AKI and AR after kidney transplantation (AUC values of the area under the ROC curve were all >0.7). The same observations were confirmed in ischemia reperfusion injury (IRI) and AR rat models by identifying common four Hub genes (GBP2, TYROBP, TLR8, and CCR5). Western blots showed that these four Hub genes were significantly different in rat models of IRI and AR (all p<0.05). Compared with the control group, IRI and AR groups showed aggravated histopathological damage and increased secretion of oxidative stress markers and inflammatory factors in rat kidneys (all p<0.05). Finally, TF-Hub and miRNA-Hub gene regulatory networks were constructed to provide a theoretical basis for the regulation of Hub genes., Conclusion: We identified four macrophage M1-related Hub genes shared among AKI and AR after kidney transplantation. These genes may be considered for diagnosis of AKI and AR after kidney transplantation., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023. Published by Elsevier B.V.)

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., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Histologic evaluation of allograft biopsies after lung transplantation has several limitations, suggesting that molecular assessment using tissue transcriptomics could improve biopsy interpretation. This single-center, retrospective cohort study evaluated discrepancies between the histology of transbronchial biopsies (TBBs) with no rejection (NR) and T-cell mediated rejection (TCMR) by molecular diagnosis. The accuracy of diagnosis was assessed based on response to treatment. 54 TBBs from Prague Lung Transplant Program obtained between December 2015 and January 2020 were included. Patients with acute cellular rejection (ACR) grade ≥ 1 by histology received anti-rejection treatment. Response to therapy was defined as an increase in FEV1 of ≥ 10% 4 weeks post-biopsy compared to the pre-biopsy value. Among the 54 analyzed TBBs, 25 (46%) were concordant with histology, while 29 (54%) showed discrepancies. ACR grade 0 was found in 12 TBBs (22%) and grade A1 ≥ 1 in 42 TBBs (78%). Treatment response was present in 14% in the NR group and in 50% in the TCMR group ( p = 0.024). Our findings suggest that low-grade acute cellular rejection is less likely to be associated with molecular TCMR, which might better identify lung transplant recipients who benefit from therapy., Competing Interests: PH holds shares in Transcriptome Sciences Inc. (TSI), a University of Alberta research company dedicated to developing molecular diagnostics, supported in part by a licensing agreement between TSI and Thermo Fisher Scientific, and by a research grant from Natera, Inc. PH is a consultant to Natera, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zajacova, Mackova, Halloran, Gauthier, Balko, Guney, Rakita, Svorcova, Kolarik, Vachtenheim, Pozniak, Simonek, Fila, Lischke, Halloran and Havlin.)

During the last few years, cell-free DNA (cfDNA) has emerged as a possible non-invasive biomarker for prediction of complications after lung transplantation. We previously published a proof-of-concept study using a digital droplet polymerase chain reaction (ddPCR)-based method for detection of cfDNA. In the current study, we aimed to further evaluate the potential clinical usefulness of detecting chronic lung allograft dysfunction (CLAD) using three different ddPCR applications measuring and calculating the donor fraction (DF) of cfDNA as well as one method using the absolute amount of donor-derived cfDNA. We analyzed 246 serum samples collected from 26 lung transplant recipients. Nine of the patients had ongoing CLAD at some point during follow-up. All four methods showed statistically significant elevation of the measured variable in the CLAD samples compared to the non-CLAD samples. The results support the use of ddPCR-detected cfDNA as a potential biomarker for prediction of CLAD. These findings need to be validated in a subsequent prospective study., Competing Interests: Unrelated to the current study JM discloses consulting fees from Boehringer Ingelheim, AstraZeneca, GlaxoSmithKline, Takeda Pharma, Vicore Pharma, and Mallinckrodt. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Novo, Nordén, Westin, Dellgren, Böhmer, Ricksten and Magnusson.)

Introduction: The aim of this study is to investigate the clinical validity of donor-derived cell-free DNA (dd-cfDNA) in comparison with that of donor specific anti-HLA antibody (DSA) for predicting biopsy-proven rejection (BPR)and severe microvascular inflammation (severe MVI) in kidney transplant recipients (KTRs)., Methods: In this prospective observational investigation, 64 KTRs who underwent the indicated biopsies were included. Blood samples collected prior to biopsy were tested for dd-cfDNA and DSA. Biopsy specimens were classified by a renal pathologist according to the Banff classification. The predictive performance of dd-cfDNA and DSA for histological allograft diagnosis was assessed., Results: KTRs were categorized into the high and low dd-cfDNA groups based on a level of 0.4%. Eighteen patients (28.1%) had positive DSA at biopsy, exhibiting higher dd-cfDNA levels than the DSA-negative patients. BPR and severe MVI incidences were elevated in the high dd-cfDNA group (BPR: 42.9% vs. 3.4%, P <0.001; severe MVI: 37.1% vs. 3.4%, P = 0.001). Also, elevated glomerulitis and MVI scores were observed in the high dd-cfDNA group. DSA showed the highest predictive value for BPR (AUC = 0.880), whereas dd-cfDNA alone excelled in predicting severe MVI (AUC = 0.855). Combination of DSA and dd-cfDNA (>0.4%) yielded sensitivities of 80.0% and 50.0% with specificities of 90.7% and 88.0% for antibody-mediated rejection and severe MVI detection, respectively., Conclusion: The dd-cfDNA test is a predictive tool for BPR and severe MVI, and it can improve the performance, especially when combined with DSA for BPR., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Kim, Bae, Kang, Lee, Eum, Yang, Choi, Chung and Oh.)

Background: Diagnosis of kidney transplant rejection currently relies on manual histopathological assessment, which is subjective and susceptible to inter-observer variability, leading to limited reproducibility. We aim to develop a deep learning system for automated assessment of whole-slide images (WSIs) from kidney allograft biopsies to enable detection and subtyping of rejection and to predict the prognosis of rejection., Method: We collected H&E-stained WSIs of kidney allograft biopsies at 400x magnification from January 2015 to September 2023 at two hospitals. These biopsy specimens were classified as T cell-mediated rejection, antibody-mediated rejection, and other lesions based on the consensus reached by two experienced transplant pathologists. To achieve feature extraction, feature aggregation, and global classification, we employed multi-instance learning and common convolution neural networks (CNNs). The performance of the developed models was evaluated using various metrics, including confusion matrix, receiver operating characteristic curves, the area under the curve (AUC), classification map, heat map, and pathologist-machine confrontations., Results: In total, 906 WSIs from 302 kidney allograft biopsies were included for analysis. The model based on multi-instance learning enables detection and subtyping of rejection, named renal rejection artificial intelligence model (RRAIM), with the overall 3-category AUC of 0.798 in the independent test set, which is superior to that of three transplant pathologists under nearly routine assessment conditions. Moreover, the prognosis models accurately predicted graft loss within 1 year following rejection and treatment response for rejection, achieving AUC of 0.936 and 0.756, respectively., Conclusion: We first developed deep-learning models utilizing multi-instance learning for the detection and subtyping of rejection and prediction of rejection prognosis in kidney allograft biopsies. These models performed well and may be useful in assisting the pathological diagnosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ye, Xia, Yang, Luo, Tang, Li, Han, Xie, Ren and Na.)

The kidney allograft has been under continuous attack from diverse injuries since the very beginning of organ procurement, leading to a gradual decline in function, chronic fibrosis, and allograft loss. It is vital to routinely and precisely monitor the risk of injuries after renal transplantation, which is difficult to achieve because the traditional laboratory tests lack sensitivity and specificity, and graft biopsies are invasive with the risk of many complications and time-consuming. Herein, a novel method for the diagnosis of graft injury is demonstrated, using deep learning-assisted surface-enhanced Raman spectroscopy (SERS) of the urine analysis. Specifically, we developed a hybrid SERS substrate composed of gold and silver with high sensitivity to the urine composition under test, eliminating the need for labels, which makes measurements easy to perform and meanwhile results in extremely abundant and complex Raman vibrational bands. Deep learning algorithms were then developed to improve the interpretation of the SERS spectral fingerprints. The deep learning model was trained with SERS signals of urine samples of recipients with different injury types including delayed graft function (DGF), calcineurin-inhibitor toxicity (CNIT), T cell-mediated rejection (TCMR), antibody-mediated rejection (AMR), and BK virus nephropathy (BKVN), which explored the features of these types and achieved the injury differentiation with an overall accuracy of 93.03%. The results highlight the potential of combining label-free SERS spectroscopy with deep learning as a method for liquid biopsy of kidney allograft injuries, which can provide great potential to diagnose and evaluate allograft injuries, and thus extend the life of kidney allografts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Objectives: Primary sclerosing cholangitis is an autoimmune illness affecting the intrahepatic and/or extrahepatic bile ducts that has a varying clinical history and no clear therapy. Recurrence of primary sclerosing cholangitis after transplantation can cause recurring liver failure, decreased survival, and the necessity for retransplant. Here, we explored the incidence of recurrence while also identifying the risk factors of primary sclerosing cholangitis., Materials and Methods: In this retrospective cohort study, we collected demographic and clinical data from patients with a history of primary sclerosing cholangitis after liver transplant between 2011 and 2021. With SPSS software, we compared results in 2 groups of patients (with and without recurrent sclerosing biliary cholangitis) in terms of demographic and clinical variables., Results: The study included 408 patients. Lower donor age and the occurrence of acute cellularrejection were shown to be key risk factors for recurrence of primary sclerosing cholangitis. Acute cellularrejection showed the best likelihood of predicting primary sclerosing cholangitis recurrence. As the number of acute cellular rejection episodes increased, so did the chance of primary sclerosing cholangitis. Death rate of patients with recurrence of primary sclerosing cholangitis was 40.8% (n = 20 patients) compared with 18.9% (n = 68 patients) in those without recurrence (significant at P < .001)., Conclusions: The recurrence of primary sclerosing cholangitis had a detrimental effect on survival after liver transplant. Modifiable risk variables have the potentialto affecttherapies on care and prevention of primary sclerosing cholangitis recurrence. Donor age and acute cellular rejection were risk factors for decreased survival and higher primary sclerosing cholangitis recurrence. The use of mycophenolate (Cellcept) increased recurrence, but tacrolimus reduced mortality.

Cardiac allograft vasculopathy (CAV) is a leading cause of death after heart transplantation (HT). We evaluated donor-derived cell-free DNA (dd-cfDNA) as a noninvasive biomarker of CAV development after HT. The INSPIRE registry at the Intermountain Medical Center was queried for stored plasma samples from HT patients with and without CAV. At Stanford University, HT patients with CAV (cases) and without CAV (controls) were enrolled prospectively, and blood samples were collected. All the samples were analyzed for dd-cfDNA using the AlloSure assay (CareDx, Inc.). CAV was defined per the ISHLT 2010 standardized classification system. Univariate associations between patient demographics and clinical characteristics and their CAV grade were tested using chi-square and Wilcoxon rank sum tests. Associations between their dd-cfDNA levels and CAV grades were examined using a nonparametric Kruskal-Wallis test. A total of 69 pts were included, and 101 samples were analyzed for dd-cfDNA. The mean age at sample collection was 58.6 ± 13.7 years; 66.7% of the patients were male, and 81% were White. CAV 0, 1, 2, and 3 were present in 37.6%, 22.8%, 22.8%, and 16.8% of included samples, respectively. The median dd-cfDNA level was 0.13% (0.06, 0.33). The median dd-cfDNA level was not significantly different between CAV (-) and CAV (+): 0.09% (0.05%-0.32%) and 0.15% (0.07%-0.33%), respectively, p = 0.25 and with similar results across all CAV grades. In our study, dd-cfDNA levels did not correlate with the presence of CAV and did not differ across CAV grades. As such, dd-cfDNA does not appear to be a reliable noninvasive biomarker for CAV surveillance., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: Microvascular inflammation (MVI) can occur in biopsies showing T-cell mediated rejection (TCMR), but it is not well established that T-cells can directly mediate microvascular injury (TCMR-MVI)., Methods: This was a cross sectional RNAseq based Banff Human Organ Transplant (BHOT) gene expression (GE) analysis. The objective of this study was to probe the molecular signature of TCMR-MVI in comparison with C4d+, DSA+ antibody mediated rejection (ABMR), stable renal function (STA), and TCMR without MVI. Transcriptome analysis utilized CLC genomic workbench and R-studio software., Results: No gene set was specific for any diagnostic category, and all were expressed at low levels in STA biopsies. BHOT gene set scores could differentiate ABMR from TCMR and TCMR-MVI, but not TCMR from TCMR-MVI. TCMR-MVI underexpressed several genes associated with ABMR including DSATs, ENDAT, immunoglobulin genes, ADAMDEC1, PECAM1 and NK cell transcripts (MYBL1, GNLY), but overexpressed C3, NKBBIZ, and LTF. On the other hand, there was no significant difference in the expression of these genes in TCMR-MVI versus TCMR. This indicates that the GE profile of TCMR MVI aligns more closely with TCMR than ABMR. The limitations of classifying biopsies using the binary ABMR-TCMR algorithm, and the occurrence of common pathogenesis mechanisms amongst different rejection phenotype was highlighted by the frequent presence of molecular mixed rejection., Conclusions: T-cell mediated mechanisms play a significant role in the pathogenesis of MVI. GE was broadly different between rejection phenotypes, but molecular scores varied substantially between biopsies with the same Banff grade. It was not always possible to achieve precise molecular score-based diagnostic categorization of individual patients., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: Transcriptomic kidney profile testing and donor-derived cell-free DNA (dd-cfDNA) testing are new methods shown to provide early markers of graft inflammation during the post-transplant period. This study focused on utilizing clinical data to evaluate the application of these tests in detecting transplant rejection by comparing tests results to biopsy reports., Material and Methods: We conducted a retrospective analysis of a prospectively collected database of all adult kidney transplant patients at SUNY Upstate Medical Hospital from 1 January 2014 to 1 December 2022. Inclusion criteria were patients with concurrent transcriptomic kidney profile test and kidney biopsy results., Results: Biopsies identified 33 kidney transplant rejections. For diagnosis of kidney rejection, transcriptomic kidney profile testing had a 52.83% positive predictive value and 92.77% negative predicative value, while dd-cfDNA testing had a 54.83% positive predictive value and 86.45% negative predictive value. Transcriptomic kidney profile testing showed an 82.35% sensitivity and 75.49% specificity, while dd-cfDNA testing showed a 56.66% sensitivity and 85.56% specificity. Positive transcriptomic kidney profile and dd-cfDNA tests detected 51.51% of rejections. Combined negative tests were observed in 70.21% of biopsies without rejection., Conclusions: Despite certain discrepancies and limitations, we believe transcriptomic profile testing and dd-cfDNA testing are useful for detecting early-stage rejections and can guide patient care. Additionally, dd-cfDNA testing avoids invasive screening biopsies. Following negative test results, the probability patients are not having rejection is 86.45%. The transcriptomic profile test's high sensitivity and specificity allow possible detection of transplant rejections that may have otherwise not been identified by biopsy., Competing Interests: Declaration of competing interest The authors declare they do not have any personal or financial conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Kidney transplant recipients require potent immunosuppression and are predisposed to opportunistic infections, many of which have a viral etiology. Currently, viral assays detect and quantify single pathogens using PCR or qPCR. An unbiased sequencing method with comparable accuracy would allow simultaneous monitoring of multiple viral pathogens and nonpathogenic Anelloviridae. The quantification of donor-derived cell-free DNA (dd-cfDNA) is an established method for the detection of allograft rejection, and a single workflow combining dd-cfDNA quantification and viral detection represents an opportunity to improve patient monitoring and management., Methods: Whole genome sequencing of cell-free DNA was performed using 1,980 plasma samples from 256 subjects enrolled in a multi-center study. Non-human sequences underwent reference-assisted assembly and taxonomic annotation of the viral DNA pathogens., Results: Of the 1,980 samples tested, 1,453 (73.4%) had ≥1 viral detection(s), either a known viral pathogen or torque teno virus (TTV), with positivity rates generally declining 12-18 months post-transplant. Concordance of metagenomic NGS (mNGS) viral detection with qPCR detection was 97.7% (94.1% sensitivity, 98.2% specificity), and a linear relationship was demonstrated between mNGS viral quantitation and qPCR results. BK virus, cytomegalovirus, and Epstein-Barr virus were detected by sequencing up to 60 days prior to independently established clinical diagnoses., Conclusions: Whole-genome sequencing allows simultaneous quantification of dd-cfDNA as well as sensitive and early detection of viral infection through secondary analysis of the same sequencing results. In combination with dd-cfDNA, mNGS viral detection may provide additional pathogen surveillance results and serve as a useful biomarker for both over- and under-immunosuppression., Competing Interests: Declaration of competing interest Rohita Sinha, Zixuan Zhu and Steven Kleiboeker are employees of Eurofins Viracor Clinical Diagnostics., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Donor-specific antibodies (DSAs) are common following lung transplantation (LuTx), yet their role in graft damage is inconclusive. Mean fluorescent intensity (MFI) is the main read-out of DSA diagnostics; however its value is often disregarded when analyzing unwanted post-transplant outcomes such as graft loss or chronic lung allograft dysfunction (CLAD). Here we aim to evaluate an MFI stratification method in these outcomes., Methods: A cohort of 87 LuTx recipients has been analyzed, in which a cutoff of 8000 MFI has been determined for high MFI based on clinically relevant data. Accordingly, recipients were divided into DSA-negative, DSA-low and DSA-high subgroups. Both graft survival and CLAD-free survival were evaluated. Among factors that may contribute to DSA development we analyzed Pseudomonas aeruginosa (P. aeruginosa) infection in bronchoalveolar lavage (BAL) specimens., Results: High MFI DSAs contributed to clinical antibody-mediated rejection (AMR) and were associated with significantly worse graft (HR: 5.77, p < 0.0001) and CLAD-free survival (HR: 6.47, p = 0.019) compared to low or negative MFI DSA levels. Analysis of BAL specimens revealed a strong correlation between DSA status, P. aeruginosa infection and BAL neutrophilia. DSA-high status and clinical AMR were both independent prognosticators for decreased graft and CLAD-free survival in our multivariate Cox-regression models, whereas BAL neutrophilia was associated with worse graft survival., Conclusions: P. aeruginosa infection rates are elevated in recipients with a strong DSA response. Our results indicate that the simultaneous interpretation of MFI values and BAL neutrophilia is a feasible approach for risk evaluation and may help clinicians when to initiate DSA desensitization therapy, as early intervention could improve prognosis., (© 2024. The Author(s).)

Histologic separation of injury, T cell-mediated rejection, or antibody-mediated rejection in allograft heart biopsies is difficult. A critical review of publications was performed to evaluate the caveats of using molecular diagnostics (MDX) to distinguish between these entities. Typically, only 1 to 2 fragments of unknown histologic appearance are evaluated. Archetype and molecular classifier analyses use gene lists derived from histologic labels and associated reproducibility issues influence the accuracy of the derived MDX classes. Archetypes A1, A2, and A3 archetypes created by bioinformatics were renamed no rejection, T cell-mediated rejection, and antibody-mediated rejection despite as little as 40% concordance with histologic diagnoses and overlapping archetype scores. Additional archetypes S4 and minor injury were created using arbitrary cutoffs based on visual examination of principal component analysis plots. Therapeutic implications of the numerous discrepancies with histology remain unexplored. Many MDX-derived observations are ambiguous and open to alternate logical explanations. Better molecular methods and more rigorous validation studies are needed to advance the field. Ideally, these methods should analyze all available biopsy fragments to minimize sampling issues. It is also desirable to incorporate spatial transcriptomics into the workflow, so that gene expression data can be directly compared with the underlying histology lesions., Competing Interests: The author declares no funding or conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Endomyocardial biopsy (EMB)-based traditional microscopy remains the gold standard for the detection of cardiac allograft rejection, despite its limitation of inherent subjectivity leading to inter-reader variability. Alternative techniques now exist to surveil for allograft injury and classify rejection. Donor-derived cell-free DNA (dd-cfDNA) testing is now a validated blood-based assay used to surveil for allograft injury. The molecular microscope diagnostic system (MMDx) utilizes intragraft rejection-associated transcripts (RATs) to classify allograft rejection and identify injury. The use of dd-cfDNA and MMDx together provides objective molecular insight into allograft injury and rejection. The aim of this study was to measure the diagnostic agreement between dd-cfDNA and MMDx and assess the relationship between dd-cfDNA and MMDx-derived RATs, which may provide further insight into the pathophysiology of allograft rejection and injury., Methods: This is a retrospective observational study of 156 EMB evaluated with traditional microscopy and MMDx. All samples were paired with dd-cfDNA from peripheral blood before EMB (up to 9 days). Diagnostic agreement between traditional histopathology, MMDx, and dd-cfDNA (threshold of 0.20%) was compared for assessment of allograft injury. In addition, the relationship between dd-cfDNA and individual RAT expression levels from MMDx was evaluated., Results: MMDx characterized allograft tissue as no rejection (62.8%), antibody-mediated rejection (ABMR) (26.9%), T-cell-mediated rejection (TCMR) (5.8%), and mixed ABMR/TCMR (4.5%). For the diagnosis of any type of rejection (TCMR, ABMR, and mixed rejection), there was substantial agreement between MMDx and dd-cfDNA (76.3% agreement). All transcript clusters (group of gene sets designated by MMDx) and individual transcripts considered abnormal from MMDx had significantly elevated dd-cfDNA. In addition, a positive correlation between dd-cfDNA levels and certain MMDx-derived RATs was observed. Tissue transcript clusters were correlated with dd-cfDNA scores, including DSAST, GRIT, HT1, QCMAT, and S4. For individual transcripts, tissue ROBO4 was significantly correlated with dd-cfDNA in both nonrejection and rejection as assessed by MMDx., Conclusions: Collectively, we have shown substantial diagnostic agreement between dd-cfDNA and MMDx. Furthermore, based on the findings presented, we postulate a common pathway between the release of dd-cfDNA and expression of ROBO4 (a vascular endothelial-specific gene that stabilizes the vasculature) in the setting of antibody-mediated rejection, which may provide a mechanistic rationale for observed elevations in dd-cfDNA in AMR, compared to acute cellular rejection., (Copyright © 2024. Published by Elsevier Inc.)

Background: Noninvasive methods for surveillance of acute rejection are increasingly used in heart transplantation (HT), including donor-derived cell-free DNA (dd-cfDNA). As other cardiac biomarkers differ by sex, we hypothesized that there may be sex-specific differences in the performance of dd-cfDNA for the detection of acute rejection. The purpose of the current study was to examine patterns of dd-cfDNA seen in quiescence and acute rejection in male and female transplant recipients., Methods: Patients enrolled in the Genomic Research Alliance for Transplantation who were ≥18 years at the time of HT were included. Rejection was defined by endomyocardial biopsy with acute cellular rejection (ACR) grade ≥2R and/or antibody-mediated rejection ≥ pAMR 1. dd-cfDNA was quantitated using shotgun sequencing. Median dd-cfDNA levels were compared between sexes during quiescence and rejection. The performance of dd-cfDNA by sex was assessed using area under the receiver operator characteristic (AUROC) curve. Allograft injury was defined as dd-cfDNA ≥0.25%., Results: One hundred fifty-one unique patients (49 female, 32%) were included in the analysis with 1,119 available dd-cfDNA measurements. Baseline characteristics including demographics and comorbidities were not significantly different between sexes. During quiescence, there were no significant sex differences in median dd-cfDNA level (0.04% [IQR 0.00, 0.16] in females vs 0.03% [IQR 0.00, 0.12] in males, p = 0.22). There were no significant sex differences in median dd-cfDNA for ACR (0.33% [0.21, 0.36] in females vs 0.32% [0.21, 1.10] in males, p = 0.57). Overall, median dd-cfDNA levels were higher in antibody-mediated rejection (AMR) than ACR but did not significantly differ by sex (0.50% [IQR 0.18, 0.82] in females vs 0.63% [IQR 0.32, 1.95] in males, p = 0.51). Elevated dd-cfDNA detected ACR/AMR with an AUROC of 0.83 in females and 0.89 in males, p-value for comparison = 0.16., Conclusions: There were no significant sex differences in dd-cfDNA levels during quiescence and rejection. Performance characteristics were similar, suggesting similar diagnostic thresholds can be used in men and women for rejection surveillance., (Copyright © 2024 International Society for the Heart and Lung Transplantation. All rights reserved.)

Purpose of Review: Chronic lung allograft dysfunction (CLAD) remains a life-threatening complication following lung transplantation. Different CLAD phenotypes have recently been defined, based on the combination of pulmonary function testing and chest computed tomography (CT) scanning and spurred renewed interests in differential diagnosis, risk factors and management of CLAD., Recent Findings: Given their crucial importance in the differential diagnosis, we will discuss the latest development in assessing the pulmonary function and chest CT scan, but also their limitations in proper CLAD phenotyping, especially with regards to patients with baseline allograft dysfunction. Since no definitive treatment exists, it remains important to timely identify clinical risk factors, but also to assess the presence of specific patterns or biomarkers in tissue or in broncho alveolar lavage in relation to CLAD (phenotypes). We will provide a comprehensive overview of the latest advances in risk factors and biomarker research in CLAD. Lastly, we will also review novel preventive and curative treatment strategies for CLAD., Summary: Although this knowledge has significantly advanced the field of lung transplantation, more research is warranted because CLAD remains a life-threatening complication for all lung transplant recipients., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose of Review: To review what is currently known about the pathogenesis, diagnosis, treatment, and prevention of acute rejection (AR) in lung transplantation., Recent Findings: Epigenomic and transcriptomic methods are gaining traction as tools for earlier detection of AR, which still remains primarily a histopathologic diagnosis., Summary: Acute rejection is a common cause of early posttransplant lung graft dysfunction and increases the risk of chronic rejection. Detection and diagnosis of AR is primarily based on histopathology, but noninvasive molecular methods are undergoing investigation. Two subtypes of AR exist: acute cellular rejection (ACR) and antibody-mediated rejection (AMR). Both can have varied clinical presentation, ranging from asymptomatic to fulminant ARDS, and can present simultaneously. Diagnosis of ACR requires transbronchial biopsy; AMR requires the additional measuring of circulating donor-specific antibody (DSA) levels. First-line treatment in ACR is increased immunosuppression (pulse-dose or tapered dose glucocorticoids); refractory cases may need antibody-based lymphodepletion therapy. First line treatment in AMR focuses on circulating DSA removal with B and plasma cell depletion; plasmapheresis, intravenous human immunoglobulin (IVIG), bortezomib, and rituximab are often employed., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Kidney transplantation is the preferred treatment for pediatric end-stage renal disease. However, pediatric recipients face unique challenges due to their prolonged need for kidney function to accommodate growth and development. The continual changes in the immune microenvironment during childhood development and the heightened risk of complications from long-term use of immunosuppressive drugs. The overwhelming majority of children may require more than one kidney transplant in their lifetime. Acute rejection (AR) stands as the primary cause of kidney transplant failure in children. While pathologic biopsy remains the "gold standard" for diagnosing renal rejection, its invasive nature raises concerns regarding potential functional impairment and the psychological impact on children due to repeated procedures. In this review, we outline the current research status of novel biomarkers associated with AR in urine and blood after pediatric kidney transplantation. These biomarkers exhibit superior diagnostic and prognostic performance compared to conventional ones, with the added advantages of being less invasive and highly reproducible for long-term graft monitoring. We also integrate the limitations of these novel biomarkers and propose a refined monitoring model to optimize the management of AR in pediatric kidney transplantation., Competing Interests: Declaration of competing interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, “Non-invasive biomarkers of acute rejection in pediatric kidney transplantation: New targets and Strategies”., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The quest to reduce kidney transplant rejection has emphasized the urgent requirement for the development of non-invasive, precise diagnostic technologies. These technologies aim to detect antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR), which are asymptomatic and pose a risk of potential kidney damage. The protocols for managing rejection caused by ABMR and TCMR differ, and diagnosis has traditionally relied on invasive biopsy procedures. Therefore, a convergence system using a nano-sensing chip, Raman spectroscopy, and AI technology was introduced to facilitate diagnosis using serum samples obtained from patients with no major abnormality, ABMR, and TCMR after kidney transplantation. Tissue biopsy and Banff score analysis were performed across the groups for validation, and 5 μL of serum obtained at the same time was added onto the Au-ZnO nanorod-based Surface-Enhanced Raman Scattering sensing chip to obtain Raman spectroscopy signals. The accuracy of machine learning algorithms for principal component-linear discriminant analysis and principal component-partial least squares discriminant analysis was 93.53% and 98.82%, respectively. The collagen (an indicative of kidney injury), creatinine, and amino acid-derived signals (markers of kidney function) contributed to this accuracy; however, the high accuracy was primarily due to the ability of the system to analyze a broad spectrum of various biomarkers., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jun Ki Kim reports financial support was provided by Asan Medical Center. Jun Ki Kim reports a relationship with Asan Medical Center that includes: employment. Jun Ki Kim has patent pending to Asan medical center. Non applicable., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

While allograft rejection (AR) continues to threaten the success of cardiothoracic transplantation, lack of accurate and repeatable surveillance tools to diagnose AR is a major unmet need in the clinical management of cardiothoracic transplant recipients. Endomyocardial biopsy (EMB) and transbronchial biopsy (TBBx) have been the cornerstone of rejection monitoring since the field's incipience, but both suffer from significant limitations, including poor concordance of biopsy interpretation among pathologists. In recent years, novel molecular tools for AR monitoring have emerged and their performance characteristics have been evaluated in multiple studies. An international working group convened by ESOT has reviewed the existing literature and provides a series of recommendations to guide the use of these biomarkers in clinical practice. While acknowledging some caveats, the group recognized that Gene-expression profiling and donor-derived cell-free DNA (dd-cfDNA) may be used to rule out rejection in heart transplant recipients, but they are not recommended for cardiac allograft vasculopathy screening. Other traditional biomarkers (NT-proBNP, BNP or troponin) do not have sufficient evidence to support their use to diagnose AR. Regarding lung transplant, dd-cfDNA could be used to rule out clinical rejection and infection, but its use to monitor treatment response is not recommended., Competing Interests: KK consulted for Care-Dx; MCL received speakers fees from Care-Dx; LP received lab material from Care-Dx; SB is PI of a Eurofins sponsored study MJB received institutional grant from Eurofins. All other authors declare no conflict of interest with the topic of current manuscript., (Copyright © 2024 Nikolova, Agbor-Enoh, Bos, Crespo-Leiro, Ensminger, Jimenez-Blanco, Minervini, Perch, Segovia, Vos, Khush and Potena.)

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., (© 2024 The Author(s).)

Objectives: Pathologists interpreting kidney allograft biopsies using the Banff system usually start by recording component scores (eg, i, t, cg) using histopathologic criteria committed to memory. Component scores are then melded into diagnoses using the same manual/mental processes. This approach to complex Banff rules during routine sign-out produces a lack of fidelity and needs improvement., Methods: We constructed a web-based "smart template" (software-assisted sign-out) system that uniquely starts with upstream Banff-defined additional diagnostic parameters (eg, infection) and histopathologic criteria (eg, percent interstitial inflammation) collectively referred to as feeder data that is then translated into component scores and integrated into final diagnoses using software-encoded decision trees., Results: Software-assisted sign-out enables pathologists to (1) accurately and uniformly apply Banff rules, thereby eliminating human inconsistencies (present in 25% of the cohort); (2) document areas of improvement; (3) show improved correlation with function; (4) examine t-Distributed Stochastic Neighbor Embedding clustering for diagnosis stratification; and (5) ready upstream incorporation of artificial intelligence-assisted scoring of biopsies., Conclusions: Compared with the legacy approach, software-assisted sign-out improves Banff accuracy and fidelity, more closely correlates with kidney function, is practical for routine clinical work and translational research studies, facilitates downstream integration with nonpathology data, and readies biopsy scoring for artificial intelligence algorithms., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society for Clinical Pathology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Describing risk factors and outcomes in kidney transplant recipients with oxalate nephropathy (ON) may help elucidate the pathogenesis and guide treatment strategies. We used a large single-center database to identify patients with ON and categorized them into delayed graft function with ON (DGF-ON) and late ON. Incidence density sampling was used to select controls. A total of 37 ON cases were diagnosed between 1/2011 and 1/2021. DGF-ON (n = 13) was diagnosed in 1.05% of the DGF population. Pancreatic atrophy on imaging (36.4% vs. 2.9%, p = 0.002) and gastric bypass history (7.7% vs. 0%; p = 0.06) were more common in DGF-ON than with controls with DGF requiring biopsy but without evidence of ON. DGF-ON was not associated with worse graft survival (p = 0.98) or death-censored graft survival (p = 0.48). Late ON (n = 24) was diagnosed after a mean of 78.2 months. Late ON patients were older (mean age 55.1 vs. 48.4 years; p = 0.02), more likely to be women (61.7% vs. 37.5%; p = 0.03), have gastric bypass history (8.3% vs. 0.8%; p = 0.02) and pancreatic atrophy on imaging (38.9% vs. 13.3%; p = 0.02). Late ON was associated with an increased risk of graft failure (HR 2.0; p = 0.07) and death-censored graft loss (HR 2.5; p = 0.10). We describe two phenotypes of ON after kidney transplantation: DGF-ON and late ON. Our study is the first to our knowledge to evaluate DGF-ON with DGF controls without ON. Although limited by small sample size, DGF-ON was not associated with adverse outcomes when compared with controls. Late ON predicted worse allograft outcomes., (© 2024 The Author(s). Clinical Transplantation published by John Wiley & Sons Ltd.)

Background: Immune-mediated rejection is the most common cause of allograft failure in kidney transplant (KT) patients. Exposure to alloantigen, including human leukocyte antigen (HLA), results in the production of donor-specific antibodies (DSA). There are limited data about low levels of mean fluorescence intensity (MFI) DSA, especially post-transplantation. This study evaluated allograft outcomes in KT patients with low MFI DSA., Methods: From January 2007 to December 2021, KT patients who were tested for post-transplant DSA at Ramathibodi Hospital, Bangkok, Thailand, with the DSA MFI ≤ 1000 were evaluated. These KT patients were categorized into two groups: very low DSA (VLL; MFI = 1-500) and low DSA (LL; MFI = 501-1000). All KT patients were evaluated for the primary outcomes, such as the incidence of acute rejection, serum creatinine levels at one and five years after transplantation as well as allograft and patient survivals., Results: Among 36 KT patients 25 were included as those with VLL and 11 as those with LL. The LL group had significantly higher T-cell mediated allograft rejection (TCMR) than the VLL group (45% vs. 12%, P = 0.04). In addition, 10 patients, 5 in the VLL group and 5 in the LL group developed antibody-mediated allograft rejection (ABMR). Both TCMR and ABMR were confirmed by biopsy results. There was a trend toward higher MFI in KT patients with ABMR than without ABMR (P = 0.22). At 5 post-transplant years, serum creatinine, allograft and patient survivals were comparable between these two groups. Furthermore, the univariate and multivariate analyzes revealed that the LL group was a high risk for rejection., Conclusion: Low MFI DSA values after transplantation may be associated with a higher incidence of rejection, but this finding did not show differences in allograft and patient survival in this study's analysis., Competing Interests: Declaration of competing interest None., (Copyright © 2023. Published by Elsevier B.V.)

Background: Corneal transplantation is the most common transplant procedure worldwide. Despite immune and angiogenic privilege of the cornea, 50% to 70% of corneal transplants fail in high-risk recipients, primarily because of immune rejection. Therefore, it is crucial to identify predictive biomarkers of rejection to improve transplant survival., Methods: In search for predictive biomarkers, we performed proteomics analysis of serum extracellular vesicles (EVs) in a fully major histocompatibility complex-mismatched (C57BL/6-to-BALB/c) murine corneal transplantation model, wherein 50% of transplants undergo rejection by day 28 following transplantation., Results: Our time course study revealed a decrease in the number of serum EVs on day 1, followed by a gradual increase by day 7. A comparative analysis of proteomics profiles of EVs from transplant recipients with rejection (rejectors) and without rejection (nonrejectors) found a distinct enrichment of histocompatibility 2, Q region locus 2, which is a part of major histocompatibility complex-class I of donor C57BL/6 mice, in day 7 EVs of rejectors, compared with nonrejectors, syngeneic controls, or naïve mice. In contrast, serum amyloid A2, a protein induced in response to injury, was increased in day 7 EVs of nonrejectors., Conclusions: Our findings offer noninvasive EV-based potential biomarkers for predicting corneal allograft rejection or tolerance., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Antibody-mediated rejection (AMR) often leads to chronic kidney allograft damage and is a critical cause of allograft failure. The Banff classification, used to diagnose AMR, has become complex and challenging for clinicians. A Banff-based histologic chronicity index (CI) was recently proposed as a simplified prognostic indicator. Its reliability and reproducibility have not been externally validated., Methods: This study investigated 71 kidney allograft biopsies diagnosed with AMR. Interobserver reproducibility of the recently proposed CI and its components (cg, cv, ct, and ci) were assessed. The association between CI and allograft failure was analyzed, and CI cut-off values were evaluated by Cox proportional hazards regression and Kaplan-Meier estimator with log-rank test., Results: The study confirmed the association of CI with allograft failure, but also revealed that the assessment of CI varied between pathologists, impacting its reproducibility as a prognostic tool. Only 49 (69.0%) of the biopsies showed complete agreement on the proposed cut-off value of CI < 4 or CI ≥ 4. Furthermore, this cut-off did not reliably stratify allograft failure. Notably, the cg score, which carries significant weight in the CI calculation, had the lowest agreement between observers (kappa = .281)., Conclusions: While a simplified prognostic indicator for AMR is needed, this study highlights the limitations of CI, particularly its poor interobserver reproducibility. Our findings suggest that clinicians should interpret CI cautiously and consider establishing their own cut-off values. This study underscores the need to address interobserver reproducibility before CI can be widely adopted for AMR management., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The intricate association between histologic lesions and circulating antihuman leucocyte antigen donor-specific antibodies (DSA) in liver transplantation (LT) requires further clarification. We conducted a probabilistic, unsupervised approach in a comprehensively well-annotated LT cohort to identify clinically relevant archetypes. We evaluated 490 pairs of LT biopsies with DSA testing from 325 recipients transplanted between 2010 and 2020 across 3 French centers and an external cohort of 202 biopsies from 128 recipients. Unsupervised archetypal analysis integrated all clinico-immuno-histologic parameters of each biopsy to identify biopsy archetypes. The median time after LT was 1.17 (interquartile range, 0.38-2.38) years. We identified 7 archetypes distinguished by clinico-immuno-histologic parameters: archetype #1: severe T cell-mediated rejection (15.9%); #2: chronic rejection with ductopenia (1.8%); #3: architectural and microvascular damages (3.5%); #4: (sub)normal (55.9%); #5: mild T cell-mediated rejection (4.9%); #6: acute antibody-mediated rejection (6.5%); and #7: chronic rejection with DSA (11.4%). Cell infiltrates vary in the archetype. These archetypes were associated with distinct liver biological markers and allograft outcomes. These findings remained consistent when stratified using the patient's age or indications for LT, with good performance in the external cohort (mean highest probability assignment = 0.58, standard deviation ± 0.17). In conclusion, we have identified clinically meaningful archetypes, providing valuable insights into the intricate DSA-histology association, which may help standardize liver allograft pathology classification., (Copyright © 2023 American Society of Transplantation & American Society of Transplant Surgeons. Published by Elsevier Inc. All rights reserved.)