American Journal of Transplantation

Background Delayed graft function (DGF) is among the most used metrics in transplant medicine, yet its prevailing definition-dialysis requirement within the first seven postoperative days lacks granularity and fails to capture the dynamic nature of graft recovery. It reflects a treatment decision rather than graft biology, varies by centre practice, and offers no temporal information about the pace or pattern of recovery. This study proposes a trajectory-based framework using serial serum creatinine measurements across three biologically defined time windows to capture the dynamic nature of early renal recovery. Methods We retrospectively analysed 205 adult kidney transplant recipients at Cleveland Clinic Weston Hospital in 2025. Donor groups included living donors, donation after brain death (DBD), donation after circulatory death with normothermic regional perfusion (DCD-NRP), and DCD without NRP. Creatinine slopes were estimated for Days 1-7, 7-30, and 30-90 using ordinary least-squares regression. Logistic regression assessed the predictive performance of each trajectory window for DGF, adjusting for Kidney Donor Profile Index, cold ischemia time, BMI, and donor type. Results DCD non-NRP kidneys showed negligible early creatinine decline (slope +0.02) compared to DBD (-0.71) and DCD-NRP (-0.57) grafts during Days 1-7. During Days 7-30, DCD-NRP kidneys showed accelerated recovery and converged toward DBD-level trajectories, whereas DCD non-NRP grafts remained sluggish. Predictive modelling identified the Day 7-30 trajectory had the strongest discrimination for DGF, with AUC 0.83, pseudo-R2 0.25, and the lowest AIC (181.73), outperforming Days 1-7 (AUC 0.75) and 30-90 (AUC 0.79). DGF rates were 0% in living donors, 25.5% in DBD, 20.7% in DCD-NRP, and 58.9% in DCD non-NRP recipients. Conclusions A trajectory-based creatinine model provides more informative prognostic value than the conventional binary DGF definition The Day 7-30 window periods offers the highest discriminatory power, and normothermic regional perfusion appears to favourably shift DCD kidney recovery trajectories in a manner the binary definition fails to detect.

Background: Histopathological diagnoses in kidney transplant biopsies, as described by the Banff classification, suffer from substantial inter-observer variability and misinterpretation, making them prone to diagnostic errors. Continuous indices based on BanffNET automated lesion scores are proposed to quantify the continuous phenotypic spectrum of kidney transplant biopsies, complementary to pathologist assessment of biopsies. Methods: The BanffNET model was used to obtain continuous lesion scoring for a training cohort of 2544 biopsies, a large validation cohort of 3863 biopsies, and a multi-reader cohort of 36 biopsies scored by 67 pathologists. A penalized regression approach was used to condense 17 automated lesion scores into four indices, representing the most important dimensions of graft injury: a TCMR/TI Index, an AMR/MVI Index, an Activity Index and a Chronicity Index. The BanffNET Indices were evaluated against Banff diagnoses and histological indices in the training cohort and validation cohort. Since pathologist-assigned Banff lesions and diagnoses suffer from inter-observer variability, associations were also assessed with diagnoses in a multi-reader study, with time to kidney graft failure in the training and validation cohort and with biopsy-based molecular signatures in the validation cohort. Results: The BanffNET TCMR/TI Index, AMR/MVI Index and Activity Index showed excellent discrimination of Banff TCMR, Banff MVI and Banff Any Diagnosis respectively, with validation AUCs ranging from 0.80 to 0.92. In addition, the BanffNET Indices explained large amounts of variability in multi-observer reference standards, time to graft failure and molecular biopsy-based diagnostics. In the large majority of cases, variability explained by BanffNET Indices matched or exceeded the variability explained by pathologist-assigned diagnoses and histological indices. Conclusions: BanffNET Indices are reproducible descriptors of whole slide images that could complement and augment kidney transplant biopsy evaluation by pathologists. Associations of BanffNET Indices with multi-observer diagnoses and related outcomes suggest that they capture additional information on tissue injury type and severity on top of pathologist-assigned Banff diagnoses and histological indices.

Kidney transplant recipients experience a higher burden of several malignancies, yet the factors associated with prostate cancer presentation after transplantation remain poorly understood. Unlike malignancies strongly associated with impaired immune surveillance, prostate cancer has not consistently demonstrated an increased incidence after transplantation, suggesting that different mechanisms may underlie disease presentation. This study evaluated recipient, donor, transplant, immunologic, and immunosuppressive factors associated with prostate cancer phenotype after kidney transplantation. A retrospective cohort study was conducted using national transplant registry data from adult kidney transplant recipients diagnosed with post-transplant prostate cancer between 2015 and 2024. Cases were classified as de novo (no pre-transplant history of prostate cancer) or recurrent (documented pre-transplant history). Multivariable Firth penalized logistic regression was used to evaluate factors associated with recurrent phenotype. Prespecified sensitivity analyses included deceased donor restricted models, incorporation of donor organ quality variables, and adjustment for time from transplantation to cancer diagnosis. Exploratory machine learning analyses included elastic net logistic regression, random forest, and extreme gradient boosting. The cohort included 660 recipients, of whom 623 (94.4%) had de novo disease and 37 (5.6%) had recurrent disease. Recipient age was the only variable consistently associated with recurrent phenotype across primary and sensitivity analyses (adjusted odds ratio per year 1.11, 95% CI 1.05-1.17; p<0.001). Immunosuppressive regimen, donor characteristics, immunologic variables, and time from transplantation to cancer diagnosis were not independently associated with phenotype in the primary cohort. In deceased donor restricted analyses, alemtuzumab induction showed an exploratory association with recurrent phenotype, although estimates were imprecise. Machine learning models demonstrated modest discrimination and calibration and did not outperform penalized regression approaches. These findings suggest that, among kidney transplant recipients with prostate cancer, differences between recurrent and de novo presentation are more closely associated with recipient age and underlying disease characteristics than with transplant exposures or specific immunosuppressive regimens.

Background. Fluid collections are common after kidney transplantation, but their prevalence at scheduled imaging and their management are inconsistent from canter to canter. We describe the cross sectional prevalence and management of perigraft collections, including an exploratory deepdrain subgroup. Methods. In this retrospective single center cohort, 146 consecutive adult kidney transplant recipients (Cleveland Clinic Weston Hospital, July 2024 to June 2025) were imaged on postoperative day 0/1 and at approximately 1 and 3 months. Routine deep drainage was avoided (n=124), 22 clinically selected recipients with perioperative anticoagulation received a deep drain. The primary outcome was cross sectional prevalence of a perigraft collection at each visit. Secondary outcomes were management among patients with a collection. Drain group comparisons were exploratory. Results. Collections were present in 29 of 146 recipients at postoperative day 0/1 (19.9%; 95% CI, 14.2 to 27.1), 71 of 146 at 1 month (48.6%; 95% CI, 40.7 to 56.7), and 34 of 146 at 3 months (23.3%; 95% CI, 17.2 to 30.8). Prevalence in the no drain group was 21.0%, 50.0%, and 23.4%, respectively; corresponding prevalence in the deep drain group was 13.6%, 40.9%, and 22.7%. Between group prevalence comparisons were not statistically significant at any time point. BMI was higher in the deep-drain group than in the no-drain group (30.04 vs 27.1 kg/m2; P=0.01). Among patients with a 1-month collection, management did not differ significantly between groups (any invasive management, 11.1% vs 16.1%; P=1.00). Among patients with a 3month collection, invasive management was more common in the deep drain group than in the no drain group (80.0% vs 13.8%; P=0.007). This comparison included only five deep-drain recipients and was confounded by clinical selection, perioperative anticoagulation, and BMI imbalance. Conclusions. Perigraft collection prevalence was highest at 1 month and lower at 3 months in this predominantly no drain cohort. Most collections were managed conservatively, and invasive treatment was uncommon in the no-drain group. The deep drain subgroup provides clinically relevant information about high risk recipients selected for drainage but cannot support causal conclusions regarding drain benefit or harm. Patient level linkage is required to distinguish persistence, resolution, and new collection formation.

Background: Immune checkpoint inhibitors (ICIs) can provide effective treatment for advanced cutaneous squamous cell carcinoma (CSCC) in solid organ transplant recipients (SOTRs), but long-term oncologic and allograft outcomes remain poorly characterized. Objective: To evaluate long-term efficacy and allograft outcomes after ICI therapy in SOTRs with advanced CSCC. Methods: We conducted a retrospective cohort study of SOTRs with advanced CSCC treated with systemic ICI at Mass General Brigham from 2016-2025. Tumor response, survival, immune-related adverse events, immunosuppression modifications, rejection rate, and graft loss were assessed. Kidney graft failure was analyzed using competing-risk methods with death as a competing event. Results: Among 36 SOTRs, objective response rate was 44.4% (95% CI, 27.9%-61.9%), including 9 complete responses. At 3 years, progression-free, disease-specific, and overall survival were 18.6%, 65.8%, and 32.5%, respectively. Median follow-up was 42.1 months. Five patients experienced graft loss, all kidney recipients; 4 had biopsy-confirmed rejection. The 3-year cumulative incidence of kidney graft failure was 16.7% (95% CI, 2.9%-30.5%). Limitations: Retrospective design, modest sample size, and heterogeneous immunosuppression limited risk-factor analyses. Conclusion: ICI provided long-term CSCC control with a low rate of allograft loss, highlighting the need for longitudinal multidisciplinary management balancing oncologic benefit, graft preservation, and competing mortality risk.

Background: Noninvasive biomarkers capable of detecting kidney allograft injury and distinguishing rejection from infection remain an important clinical need. Torque teno virus (TTV) reflects host immune status, but its utility in urine has not been well established. We evaluated urinary TTV, total cell-free DNA (cfDNA), cfDNA fragmentation, and BK polyomavirus (BKV) as potential biomarkers of kidney transplant rejection and BK polyomavirus-associated nephropathy (BKPyVAN). Methods: Urine samples from 334 kidney transplant recipients were analyzed in association with kidney biopsies performed within 30 days of sample collection. TTV and cfDNA were measured by multiplex quantitative PCR (qPCR), with a subset analyzed by digital PCR (dPCR), and BKV was quantified by qPCR. Associations with biopsy results were evaluated using group comparisons and nominal logistic regression. Changes associated with outcomes of consecutive biopsies were assessed by matched pairs analysis. Results: Among 544 unique urine samples, the urinary TTV/cfDNA ratio was significantly lower in rejection than in non-rejection samples (P<0.0001). Logistic regression adjusted for demographic factors confirmed an inverse association between the qPCR-derived TTV/cfDNA metric and rejection (adjusted odds ratio per delta Cq, 0.91; 95% CI, 0.88-0.94; P<0.00001). Significant differences were observed for all types of rejection. Association was confirmed by dPCR: higher TTV was associated with lower rejection odds, whereas higher cfDNA was associated with greater rejection odds. A nominal logistic model incorporating dPCR measurements achieved an AUROC of 0.76 (95% CI, 0.69-0.82). Matched pairs analysis showed a significant decrease in TTV/cfDNA when rejection developed and an increase following recovery from rejection, with no significant changes when biopsy status remained unchanged. BKV levels were strongly associated with BKPyVAN. No correlation between TTV and BKV was observed. Nominal logistic regression integrating TTV, cfDNA, and BKV measurements yielded AUROCs of 0.75, 0.97, and 0.73 for rejection, BKPyVAN, and non-rejection, respectively. Conclusions: A reduced urinary TTV/cfDNA ratio is associated with biopsy-defined kidney transplant rejection, and changes in the ratio correlate with transitions in biopsy results. Combined TTV, cfDNA, and BKV measurements showed differential associations with rejection and BKPyVAN, supporting further evaluation as complementary urinary biomarkers.

Background Pre-implantation biopsy utility for deceased-donor kidney acceptance is controversial due to processing limitations and interpretive variability. We evaluated whether systematic histological assessment, including expert evaluation and quantification with the BanffNET automated deep learning system (17 lesions), predicts post-transplant failure under optimal laboratory conditions. Methods Biopsies from deceased donor kidneys (N=733) underwent optimized laboratory processing, whole slide imaging, expert Banff 2024 pathologic assessment, and BanffNET lesion quantification. We assessed their incremental predictive value beyond clinical characteristics for early graft dysfunction, longitudinal eGFR/UPCR trajectories, need for indication biopsies, and death-censored graft failure. Results Histopathology improved clinical model discrimination by 1-4% and increased explained variance for longitudinal trajectories by 1-2%. Continuous bivariate surface analysis, however, revealed that while histology adds marginal overall predictive accuracy, mapping continuous composite and individual BanffNET scores against the Kidney Donor Risk Index (KDRI) uncovers distinct topological risk gradients for early graft dysfunction and long-term graft failure. Conclusion While pre-implantation biopsies add minimal overall prognostic value, continuous bivariate mapping of KDRI and BanffNET scores uncovers distinct synergistic risk gradients for graft failure. These continuous clinical-histological surfaces could optimize organ salvage by precisely identifying viable high-KDRI kidneys lacking critical compounded damage and vice versa.

Background Studies of the 2018 United Network for Organ Sharing (UNOS) policy revision suggest improved early transplantation access for the sickest patients. It remains unknown whether these benefits vary as a function of time on the waitlist. Thus, we evaluated potential time-dependent effects of the 2018 heart allocation policy revision on waitlist outcomes. Methods Using UNOS data, we analyzed adult heart transplant candidates listed five years before (pre-policy) and after (post-policy) policy change, categorized as high-acuity (Status 1-3 or 1A) or low-acuity (Status 4-6 or 1B/old 2). Landmark analysis at weeks 0, 1, 2, 4, 8, 16, 24 using a competing risks framework was performed to assess transplantation, death/deterioration, and myocardial recovery. Sub-distribution and cause-specific hazard ratios were calculated. Absolute number and proportion of far-away transplants (donor distance [&ge;]500 nautical miles) were calculated at each timepoint. Results High-acuity patients experienced significantly higher risk of transplantation within 2 weeks post-policy change but equivocal risk by week 16. Low-acuity patients exhibited increased rate/risk of myocardial recovery and equal or improved death/deterioration risk at all timepoints; early transplantation cumulative incidence was increased. At all timepoints, both groups experienced significantly increased far-away donor use, highest immediately after listing and progressively declining over time. Conclusions The 2018 heart allocation policy change resulted in an initial appearance of time-dependent benefits among high-acuity, post-policy patients, but this was likely due to rapid transplantation of Status 1 and 2 patients from broader geographic sharing rather than a true temporal phenomenon. Post-policy, low-acuity patients experience benefits in all waitlist outcomes.

BACKGROUND: Machine learning (ML) models have been used to evaluate one-year post-transplant mortality in donor-recipient pairs. Previous modeling utilizing noninterpretable ML methods (deep neural networks [DNN] and XGBoost) showed modest gains in area under the receiver operating curve (AUC) beyond logistic regression, but suffered a significant drop in predictive AUC applied to the subsequent years' data and lacked statistical significance in validating previously identified risk factors. METHODS: Using balanced SRTR datasets, we evaluated non-interpretable models against interpretable ML models (adaptive logistic regression with interaction terms [aLR], Classification and Regression tree [CART], and conditional inference tree [CIT]) for one-year mortality, including comprehensive clinician-supervised data curation and inclusion of variables describing pre- and post-2018 listing status changes. Models were trained/tested using rolling-window validation across years and further analyzed with repeated ten-fold crossvalidation. Interaction terms were obtained via Adaptive Best-Subset Selection (ABESS). RESULTS: Predictive validation before the listing policy change in 2018 showed similar AUCs between DNN (0.579), aLR (0.642), CART (0.579), and CIT (0.584), with XGBoost having a higher (0.763) AUC. However, in the post-2018 predictive analysis, aLR outperformed XGBoost (AUC 0.613 vs. 0.586). The interpretable ML models confirm the significance of previously reported risk factors (recipient bilirubin and creatinine) and identify risk factors not previously reported (donor pH, potential recipient distance, and recipient transfusion), as well as clinically relevant interaction terms. CONCLUSIONS: Carefully developed interpretable ML models of one-year transplant mortality have similar predictive performance to black-box models, while identifying novel risk factors, and showing improved performance after recent listing policy changes. With appropriate validation and additional data, interpretable ML modeling may allow real-time data-driven donor selection.

Introduction Timely diagnosis of kidney allograft rejection is critical for post-transplant management, yet treatment decisions may need to be made empirically while awaiting the final pathology report. We previously demonstrated that biopsy transport medium (BTM) contains molecular signals reflective of allograft rejection. Building on these findings, we developed a rapid BTM qPCR workflow using a targeted gene panel for early molecular assessment of rejection. Methods Kidney transplant biopsies assessed at Leiden University Medical Center from April 2023 to November 2024 were eligible. A predefined gene panel was quantified in BTM by qPCR, while matched formalin-fixed paraffin-embedded tissues were profiled using Tempo-Seq. Elastic Net, Random Forest, and support vector machine models were developed to classify rejection and predict continuous histological indices directly from the BTM. Results A total of 134 paired BTM samples and biopsy tissues were analyzed. The best-performing BTM gene-panel models demonstrated good discrimination for rejection, with a median AUC of 0.80, and good calibration (median slope, 0.92; median intercept, 0.08). For continuous histological indices, the best-performing BTM gene-panel models achieved R square values of 0.33 for Activity, 0.31 for TCMR/TI, and 0.27 for AMR/MVI. Corresponding biopsy gene-panel models showed similar patterns across diagnostic outcomes. Conclusions The BTM qPCR workflow captures molecular features of kidney allograft rejection and enables prediction of rejection status along the spectrum of continuous activity indices. By providing same-day molecular information while definitive biopsy interpretation is pending, this rapid approach has the potential to complement conventional histopathological diagnostics and support early clinical decision-making.

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSLung donor-recipient matching requires balancing recipient medical urgency with expected post-transplant benefit. Conventional prediction models estimate outcomes for historical donor-recipient pairs but do not directly compare alternative candidates for the same donor. We developed an offline contextual-bandit framework to assess the feasibility of learning donor-centered lung-matching policies from historical registry data. MethodsWe used linked United Network for Organ Sharing (UNOS)/Organ Procurement and Transplantation Network (OPTN) Standard Transplant Analysis and Research files to identify 8,529 lung transplant allocation events from 2023 through 2025. Each event included the historical recipient and nine date-matched, ABO-compatible pseudo-candidates. The reward combined 72-hour respiratory-support-free survival (weight, 0.75) with a normalized initial Composite Allocation Score waitlist medical-urgency score (weight, 0.25). We trained a pessimistic neural lower-confidence-bound contextual-bandit policy (NeuraLCB) and evaluated it on held-out donor events using matched-action evaluation and self-normalized inverse propensity scoring (SNIPS). ResultsThe reconstructed dataset contained 85,290 donor-candidate rows. In the held-out set of 1,706 allocation events, the observed clinician reward was 0.534 (95% CI, 0.518-0.549). NeuraLCB agreed with the historical recipient in 174 events (10.2%), with a matched-action reward of 0.616. The SNIPS-estimated value of the NeuraLCB policy was 0.649 (95% CI, 0.568-0.717), corresponding to a paired difference of +0.116 (95% CI, +0.035 to +0.181) relative to observed clinician reward. However, the effective sample size was 51.5 events, indicating limited overlap between the learned and estimated historical policies. ConclusionsThis study demonstrates the feasibility of constructing and evaluating an offline contextual-bandit framework for lung donor-recipient matching using registry data. The estimated policy value was higher than the observed historical reward, but this finding is exploratory because candidate sets were reconstructed and off-policy evaluation had limited overlap. Verified offer sets, time-stamped candidate data, explicit compatibility constraints, and prospective evaluation are required before clinical use.

BACKGROUND: Increased left ventricular mass (LVM) at a single time point after heart transplantation (HT) predicts future adverse outcomes. However, dynamic changes in LVM could have better biological relevance and reflect adverse graft remodeling (AGR). The prognostic significance of such serial changes has not been studied. METHODS: Using an automated, electronic health record-based institutional data infrastructure, we studied 439 HT recipients with 5,563 LVM measurements. Separate Bayesian joint models estimated the simultaneous associations of current LVM and its instantaneous rate of change with graft dysfunction (GD) and mortality. A joint-model-derived remodeling score combining patient-specific deviations in LVM and slope was dichotomized to define AGR and non-AGR groups. A mixed-effects analysis of all clinical variables was performed to assess associations with LVM both between and within patients. An independent cohort of 35 patients with 79 surveillance-biopsy RNA-sequencing samples was used to examine early stress-responsive pathways associated with the remodeling score. RESULTS: LVM declined by approximately 7 g/year after transplantation, with regression attenuating over time. Sixty patients (13.7%) had GD, and 75 (17.1%) died. Higher LVM was associated with subsequent GD (hazard ratio [HR] per 10 g, 1.14; 95% credible interval [CrI], 1.02-1.28) and mortality (HR, 1.10; 95% CrI, 1.02-1.19). A more positive LVM slope was associated with GD (HR per 1 g/year, 1.21; 95% CrI, 1.06-1.42) and with cardiac allograft vasculopathy (CAV) grade 2 or 3 (HR, 1.39; 95% Crl, 1.02-1.96). LVM regressed more slowly in the AGR group (-5.8 vs -8.4 g/year), with higher GD (21.0% vs 6.4%) and mortality (24.2% vs 10.0%). Time-updated GD was associated with subsequent death (HR, 8.12; 95% Confidence Interval [CI], 4.67-14.14). Transcriptomic analysis showed enrichment of interferon-mediated signaling and vascular endothelial activation with higher remodeling scores, whereas lower scores were associated with mitochondrial and metabolic processes, ribosome biogenesis, and pathways related to tissue repair and stress responses. CONCLUSIONS: AGR is an easily accessible imaging biomarker that reflects the changes in the allograft in response to various stressors and predicts future adverse outcomes. Discovery of molecular mechanisms of AGR could lead to novel therapies to protect the allograft from chronic rejection.

Background: Acute kidney injury (AKI) is a common complication after liver transplantation (LT). Alactic base excess (ABE) reflects the metabolic component of acid base disturbances not attributable to lactate and has been associated with kidney dysfunction in other clinical settings. We evaluated the association between intraoperative ABE and postoperative AKI after LT. Methods: We conducted a retrospective cohort study of adult patients undergoing LT. ABE was calculated from standard base excess and lactate obtained from the last intraoperative arterial blood gas analysis. The primary outcome was creatinine based AKI occurring within the first 7 postoperative days according to Kidney Disease: Improving Global Outcomes criteria. The association between ABE and AKI was estimated using modified Poisson regression with robust variance, adjusted for age, sex, body mass index, MELD score, cold ischemia time, and anhepatic phase duration. A post hoc exploratory analysis evaluated severe AKI, defined as KDIGO stages 2,3. Results: Seventy patients were included, of whom 32 (45.7%) developed AKI. ABE values were lower among patients who developed AKI than among those who did not (median, -1.15 vs 0.75 mmol/L; Hodges Lehmann location shift, -1.60 mmol/L; 95%CI, -2.80 to -0.20). After multivariable adjustment, ABE was not independently associated with AKI (aRR, 0.91; 95%CI, 0.82-1.01; p=0.07). Severe AKI occurred in 14 patients (20.0%), and ABE was not independently associated with severe AKI (aRR, 0.98; 95%CI, 0.78-1.23; p=0.87). Sensitivity analyses yielded consistent findings. Conclusions: A single intraoperative ABE measurement was not independently associated with postoperative AKI or severe AKI after LT. Serial measurements across different phases of transplantation may better characterize the potential relationship between ABE dynamics and postoperative kidney injury.

BackgroundLiving donor kidney transplantation improves outcomes for eligible patients with kidney failure, yet living donation remains limited. Public awareness about the possibility of living donation may not be sufficient to translate into willingness to donate. This study evaluated knowledge, attitudes, personal exposure, perceived barriers, motivators, and financial considerations associated with willingness to participate in living kidney donation among adults in San Antonio, Texas. MethodsA cross-sectional community-based survey was conducted among 346 adults. The survey assessed demographic characteristics, knowledge about kidney transplantation and living donation, personal exposure to dialysis, transplantation, and living kidney donation, misconceptions regarding donation, motivating and discouraging factors, financial considerations, and willingness to become a living donor. Associations with willingness were evaluated using multivariable logistic regression models. ResultsAlthough 83.8% of participants knew that a healthy person could donate one kidney while living, only 68 participants (19.8%) expressed general willingness to become a living donor. Only 40.0% identified kidney transplantation as the best treatment for eligible patients with kidney failure. Demographic and socioeconomic factors were not independently associated with willingness, and individual misconceptions were not independently associated with willingness. In the integrated model, knowing a living kidney donor was associated with greater willingness (OR 2.82, 95% CI 1.33-5.95), whereas knowing a transplant recipient was associated with lower willingness (OR 0.42, 95% CI 0.19- 0.96). Helping someone in need was associated with greater willingness (OR 2.48, 95% CI 1.39-4.44), while concern about long-term donor health complications was associated with lesser willingness to donate (OR 0.48, 95% CI 0.26-0.90). Nearly half of respondents who answered the compensation question selected a monetary amount that could motivate donation. ConclusionsIn this community-based sample, awareness that living donation is possible did not translate into broad willingness to donate. Willingness appeared to be shaped by personal exposure, altruistic motivation, donor safety concerns and financial considerations. Community education should move beyond basic awareness and address donor safety, financial protection, living donor experiences, and the benefits of kidney transplantation.

Viral infections remain a cause of substantial morbidity and mortality in allogeneic hematopoietic cell transplant (aHCT) recipients. While antiviral prophylaxis has dramatically reduced the risk of herpes simplex virus (HSV) disease, the relationship between HSV serostatus and major post-transplant complications in the context of HSV prophylaxis is unknown. We evaluated the association between HSV serostatus and survival among adults who received a first aHCT at the Fred Hutchinson Cancer Center between 2002 and 2022. Patients were screened for HSV-1 and HSV-2 by Western blot (WB) prior to transplant. We fit Cox proportional hazards models for mortality up to one year post-transplant, comparing HSV seropositive to seronegative patients. Models were adjusted for age, sex, cytomegalovirus (CMV) serostatus, conditioning regimen, disease risk, graft type and HLA matching, year of transplant and acute graft-versus host disease. A total of 4,016 aHCT recipients were included in this analysis. The cumulative all-cause 1-year mortality was 29.8%. For HSV-1, the adjusted hazard ratio (aHR) for all-cause mortality comparing seropositive to seronegative individuals was 1.20 (95% CI: 1.06-1.36). The aHRs for relapse, non-relapse mortality (NRM) and relapse-related mortality (RRM) were 1.46 (1.24-1.71), 1.04 (0.89-1.21), and 1.75 (1.40-2.19), respectively. For HSV-2, the aHRs for all-cause mortality, relapse, NRM, and RRM were 1.03 (0.93-1.14), 1.16 (1.03-1.31), 0.99 (0.87-1.13), and 1.13 (0.97-1.33), respectively. Despite universal antiviral prophylaxis, HSV-1 seropositivity was associated with higher mortality in the year after transplant, driven by RRM. Further studies are needed to confirm the association and understand the potential mechanisms underlying this relationship.

Background Long-term survival after solid organ transplantation remains limited by infection, graft dysfunction, and systemic complications. Recent evidence suggests that gut dysbiosis, marked by loss of beneficial commensals and expansion of opportunistic pathogens, is associated with increased mortality in solid organ transplant recipients (SOTRs). While specific species have been associated with higher mortality risk or improved survival, the functional mechanisms on the strain level underlying these associations remain unclear. Here, we integrated gene-centric functional profiling with strain-level resolved metagenome-assembled genomes (MAGs) across 1231 gut metagenomes from 1008 SOTRs (580 kidney, 245 liver, 133 lung and 50 heart transplant recipients) and 233 healthy controls from the TransplantLines Biobank and Cohort Study to link gut microbial functions and metabolic modules to their originating MAGs and assess their association with post-transplant overall survival. Results Functional profiling of the gut microbiome revealed pronounced functional dysbiosis in SOTRs compared with healthy controls, with higher dysbiosis scores significantly associated with increased post-transplant mortality. We identified 97 microbial functions (KEGG Orthologs, KOs) positively associated with impaired survival (hazard ratio >1; FDR < 0.10) and 661 KOs associated with improved survival (hazard ratio <1; FDR < 0.10) after transplantation. KOs associated with excess mortality predominantly encoded functions related to bacterial adhesion, virulence, and stress adaptation. In contrast, protective KOs mapped to 12 highly complete metabolic modules, including shikimate and pyridoxal phosphate biosynthesis. Genome-resolved analysis of 10,397 MAGs revealed that KOs associated with excess mortality were concentrated in members of the Proteobacteria phylum, particularly the Enterobacteriaceae family, whereas protective KOs were enriched in members of the Firmicutes A lineage. Conclusion The functional capacity of the post-transplant gut microbiome differed significantly from that of healthy controls, consistent with a state of post-transplant gut dysbiosis. Notably, functional dysbiosis of the gut microbiome was associated with post-transplant survival. These findings highlight microbial functional potential as a determinant of post-transplant survival and a promising target for microbiome-informed risk prediction and therapeutic intervention.

BackgroundLupus nephritis remains a major cause of chronic kidney disease and kidney failure in systemic lupus erythematosus. Glucocorticoids are central to treatment but are limited by systemic toxicity. We evaluated whether a previously characterized collagen IV 3-targeted liposomal nanoparticle formulation carrying low-dose prednisolone could attenuate established lupus nephritis in MRL/lpr mice. MethodsFemale MRL/lpr mice with disease present at treatment initiation and C57BL/6J control mice received saline or collagen IV 3-targeted prednisolone-loaded nanoparticles (Col4-3-Pred-NPs). Renal outcomes were assessed by longitudinal proteinuria, glomerular filtration rate (GFR), survival, kidney histopathology, renal IgG and C3d deposition, dUTP/TUNEL-associated injury staining, and renal cytokine/chemokine profiling. Body weight, food and water intake, and blood glucose were monitored as measures of general condition and preliminary tolerability. ResultsCol4-3-Pred-NPs improved survival in MRL/lpr mice, reduced cumulative proteinuria burden, and attenuated terminal GFR decline compared with saline-treated MRL/lpr controls. Treatment reduced glomerular and tubulointerstitial injury, lowered composite EGTI histopathology scores, decreased terminal kidney enlargement, reduced glomerular IgG deposition and renal dUTP-positive injury signals, and reduced renal signals for IL-28A/B, IL-7, PD-ECGF, IL-11, CCL6/C10, and IL-15. C3d deposition was not significantly altered. Nanoparticle treatment was not associated with sustained treatment-related increases in blood glucose or body-weight loss during the measured study period. ConclusionsCollagen IV 3-targeted liposomal delivery of low-dose prednisolone attenuated established lupus nephritis in MRL/lpr mice and improved renal structural, functional, inflammatory, and survival outcomes. These findings support further evaluation of glomerulus-targeted nanotherapy as a potential strategy to improve the precision and therapeutic index of glucocorticoid treatment in lupus nephritis.

Background: Adult congenital heart disease (ACHD) patients are prone to HLA-antibody formation from multiple surgeries, transfusions, and prosthetic surgical material. Females with ACHD may accrue additional, non-surgical alloantigen exposure. Whether sex modifies the impact of allosensitization on heart transplant (HT) access and outcomes in ACHD remains unknown. Methods: We retrospectively analyzed the OPTN/UNOS registry of adults with ACHD listed for first-time HT (2018-2025). Sensitization was defined by calculated panel reactive antibodies (cPRA) at listing. We tested the sex x sensitization (highly sensitized, cPRA >50%) interaction on transplant access using Fine-Gray competing-risks regression, treating transplantation as the event of interest and death or removal from the waitlist as competing events, and on post-transplant survival using multivariable Cox proportional-hazards regression, both adjusted for age at listing, mechanical support at listing, and the number of distinct prior cardiac surgery categories. Results: Among 856 candidates (38% female), females were more often highly sensitized than males (23% vs 14%; age-adjusted OR 1.81, 95% CI 1.26-2.61), even after adjusting for surgical burden. Sensitization reduced transplant access in females (84% to 71%; median wait 60 to 110 days, p < 0.001) but not males (79% vs 79%, median wait 88 vs 98 days). In adjusted Fine-Gray models, the subdistribution hazard for transplant was reduced in sensitized females (sHR 0.54, 95% CI 0.41-0.72) with no effect in males (sHR 0.96, 95% CI 0.73-1.26), and the sex x sensitization interaction was significant (interaction sHR 0.64, 95% CI 0.44-0.94, p = 0.02). Post-transplant mortality was numerically higher in sensitized than non-sensitized candidates in both sexes and the sex x sensitization interaction on 1-year mortality was not significant. The sex-asymmetric effect persisted and was more pronounced in the multiorgan candidates. Conclusions: Allosensitization is not a sex-neutral barrier to transplant in HT candidates with ACHD. Females are more sensitized and have reduced transplant access without differences in 1-year mortality. The female excess in sensitization is not accounted for by surgical burden, and the exposures responsible remain to be defined. These findings warrant a sex-aware listing strategy and further studies.

Background: The Lung Transplant Frailty Scale (LT-FS) is a validated binary measure of frailty in lung transplant candidates. We aimed to refine the LT-FS Base and Body Composition measures by developing a three-category classification to improve clinical risk stratification with serum albumin as a more clinically practical frailty biomarker. Methods: To develop the refined LT-FS, we applied a 4-step measure development method to a multicenter prospective cohort study of lung transplant candidates. Low albumin (<3.5 g/dL) replaced high serum C-reactive protein ([&ge;]10 mg/L) as the LT-FS biomarker. Cutpoints that balanced discrimination, risk prediction, and calibration were identified to define ''frail'', ''pre-frail'', and ''not frail'' categories. Next, we evaluated associations between the refined LT-FS and exercise capacity, patient-reported outcomes, and mortality using multivariate linear and Cox regression. Results: Among 419 participants, the refined LT-FS identified a graded increase in mortality risk across frailty categories. For example, compared with candidates who were not frail, pre-frailty and frailty by the LT-FS Body Composition were associated with a 2.9-fold (HR 2.9, 95% CI 1.2-6.9) and 7-fold (HR 6.9, 95% CI 2.6-18.2) higher risk of waitlist delisting or death, respectively. Pre-frailty and frailty by LT-FS Body Composition were associated with 2-fold (HR 2.1, 95% CI 1.2-3.8) and 3.6-fold (HR 3.6, 95% CI 1.8-7.3) higher risk of mortality after transplant. Relationships with exercise capacity and patient-reported disability were less consistent. Conclusions: A refined Lung Transplant Frailty Scale incorporating serum albumin demonstrates strong associations with waitlist and post-transplant mortality. The addition of a pre-frail category better captures the continuum of frailty and improves clinical risk stratification of lung transplant candidates.

Background: Transplant arterial injury is an underlying feature of acute organ transplant rejection and is a main cause of late heart transplant failure. The role of the gut microbiota, and especially specific microbial components of this community, in controlling immune responses that cause this aspect of rejection is poorly understood. Methods: We utilized a murine aortic interposition model of transplant arterial injury to investigate the role of the gut commensal bacteria, Akkermansia muciniphila, in controlling immune responses in transplant arteries. Results: Early life treatment of female mice with broad spectrum antibiotics, which delayed colonization of the intestinal tract with bacteria until after weaning, led to the development of dysbiosis in adults that was characterized by the absence of A. muciniphila. This was related to an elevation in systemic levels of CCL2 and a reduction in the immunomodulatory short-chain fatty acid, propionate. When transplant arterial injury was examined, there was more arterial injury indicative of acute rejection and increased intimal thickening reflective of transplant arteriosclerosis in grafts from dysbiotic mice compared to controls. Dysbiosis also increased macrophage accumulation early after transplantation in dysbiotic mice. Notably, restoring A. muciniphila in the gut microbiota of dysbiotic mice through voluntary oral administration in infants ameliorated macrophage-mediated transplant arterial injury. Conclusions: A. muciniphila is an immunomodulatory component of the gut microbiota that protects against vascular injury and pathology in organ transplantation.