Citations

Background. Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole genome transcriptomic profiling offers a systems-based, unbiased approach to elucidate the molecular mechanisms underlying ACR. However, noninvasive, longitudinal biomarker assessments capable of capturing the temporal dynamics of rejection biology remain scarce. Methods. RNA sequencing of peripheral blood from heart transplant recipients before, during, and after ACR was compared with nonrejection controls. Pathway analysis was conducted using differentially expressed genes (DEGs), and a machine learning approach was applied to assess gene-based prediction of ACR. Results. A total of 235 rejection-specific significant DEGs and 863 postrejection DEGs (false discovery rate < 0.05) were identified. During ACR, DEGs were enriched for T-cell activation/differentiation, apoptosis, and B-cell receptor signaling pathways. By combining the 2 sets of DEGs, a panel of 71 common genes was identified that reflected the significant, longitudinal transcriptomic dynamics of ACR. In an elastic net machine learning–based classifier, DYNLL1 and SERF2 were identified as ACR predictive genes, and achieved a cross-validated area under the receiver operating characteristic curve of 0.63. Conclusions. Peripheral blood transcriptomics identify dynamic temporal responses in ACR including T- and B-cell pathways with potential ACR predictive genes that warrant further investigation.

ABSTRACT This study investigated the association between induction type and long‐term outcomes in kidney retransplant recipients who experienced graft loss due to BK virus–associated nephropathy (BKVAN). Using Scientific Registry of Transplant Recipients data (2003–2021), we identified 277 adult kidney‐alone retransplant recipients with BKVAN‐related graft loss and categorized them by induction regimen: depletional ( n = 217) and nondepletional ( n = 60). The groups were similar overall, except the nondepletional cohort had lower panel‐reactive antibodies, a shorter time between transplants, and more live donor kidneys. Kaplan–Meier curves assessed 10‐year recipient and graft survival, and Cox proportional hazards models, adjusted for key donor and recipient factors, evaluated associations between induction type and outcomes. Rates of delayed graft function, one‐year rejection, and estimated glomerular filtration rate were comparable between groups. Ten‐year recipient and death‐censored graft survival did not differ by induction type (recipient survival: HR 1.09; 95% CI 0.43–2.77; p = 0.85; graft survival: HR 0.85; 95% CI 0.24–2.97; p = 0.79). Recurrent BKVAN‐related graft failure occurred only in the depletional group (5 of 217; 2.3%), while rejection‐related graft failure was more common in the nondepletional group (5 of 60; 8.3% vs. 6 of 217; 2.8%). Although these differences did not translate into long‐term graft survival disparities, they highlight the competing risks of viral recurrence and rejection. Thus, clinicians should interpret these results with caution and weigh the risks and benefits of induction choice in retransplant recipients with prior BKVAN, recognizing that this observational study cannot establish causality.

Background. Delayed graft function (DGF) in deceased-donor kidney transplantation increases morbidity, prolongs hospitalization, and increases healthcare costs. Hypothermic machine perfusion (HMP) has emerged as a promising strategy to reduce DGF; however, large-scale real-world data remain limited. Methods. We performed a retrospective cohort analysis using the Scientific Registry of Transplant Recipients (2014–2024), including adult dialysis-dependent recipients of deceased-donor kidneys preserved using either static cold storage (SCS) or HMP. The primary outcome was DGF, defined as dialysis requirement within 7 d posttransplant. A matched-pairs analysis was conducted using kidneys from the same donor. Results. The overall cohort included 59 859 recipients (46.8% SCS, 53.2% HMP), with 2208 matched pairs identified. In the overall cohort, HMP grafts had longer cold ischemia times and a higher kidney donor risk index. They were more frequently obtained from older and donation after circulatory death donors. Although the overall DGF incidence was higher with HMP (34.4% versus 30.9%, P < 0.001), matched-pairs analysis revealed significantly lower DGF rates with HMP (29.8% versus 36.1%, P < 0.001). Adjusted analyses identified HMP as protective against DGF (overall cohort odds ratio, 0.71; 95% confidence interval, 0.66-0.78; paired cohort OR, 0.68; 95% CI, 0.50-0.93). Additional modifiable risk factors include prolonged cold ischemia time, higher recipient body mass index, and longer dialysis duration. Conclusions. This real-world study demonstrates that HMP is associated with a significant reduction in DGF risk in kidney transplantation compared with SCS, supporting its broader implementation and targeted management of modifiable risk factors.

ABSTRACT Background Ureteral stents are commonly placed during kidney transplantation (KT) to mitigate urologic complications. The objective of this study was to compare clinical outcomes in KT recipients with either early stent removal when attached to the Foley catheter or late removal via cystoscopy when unattached. Methods We conducted a multi‐center retrospective analysis of consecutive living donor KT patients (8/18/21‐4/21/23) stratified into Foley‐attached and unattached stent groups. Outcomes assessed were ureteral stricture, urine leaks, UTIs at 90 days and allograft failure and BKV DNAemia (BK virus DNAemia) at 1 year. Data are reported as mean and standard deviation. Results Among 247 patients with attached and 260 with unattached stents, baseline demographics (age, sex, diabetes) were similar between groups. There was a difference in race (87.9% vs. 77.8% Caucasian; p = 0.004). Foley catheters remained longer in the attached group (3.7 ± 1.8 vs. 3.0 ± 2.0 days; p < 0.001), but stents were removed earlier (3.7 ± 1.8 vs. 21.9 ± 4.7 days; p < 0.001). Comparing attached versus unattached, there were no differences in ureteral stricture (0.4% vs. 1.5%; p = 0.197), urine leak (0.8% vs. 0.4%; p = 0.533), BKV DNAemia (17.7% vs. 16.9%; p = 0.616), or allograft failure (0% vs. 0.8%; p = 0.167). However, UTI incidence by 90 days was lower in the attached group (5.7% vs. 11.9% p = 0.013). Induction therapy differed significantly between groups, with Alemtuzumab more common in the unattached group (58.1% vs. 19.4%, p < 0.001), Basiliximab more common in the attached group (43.3% vs. 35.0%, p < 0.001), and Thymoglobulin more common in the attached group (36.0% vs. 6.9%, p < 0.001). Baseline steroid use was higher in the unattached group (81.9% vs. 57.9%, p < 0.001). Conclusion Early stent removal via connection to the Foley catheter had similarly low rates of ureteral complications while reducing urinary tract infections and avoiding cystoscopic removal.

Artificial neural networks are now used across many fields, from medicine to chatbots. However, they are often complicated and give “black-box” predictions. To better understand these models, we outline some of the terminology, provide example applications in solid organ transplantation, and offer recommendations for those interested in starting to use such models. Examples and definitions are sourced from PubMed searches as well as a review of several applied texts in machine and deep learning. Neural networks have been applied in transplantation since the 1990s, but more recent applications involve their use to process nontabular data, such as images and text. Although interpretations of model results should take context into account, the power of these models holds great potential for the future in transplantation.

Objective: To develop and validate a risk score for predicting post-transplant recurrence in perihilar cholangiocarcinoma (pCCA) patients. Background: pCCA is an aggressive malignancy with a poor prognosis. Although neoadjuvant chemoradiation (CRT) followed by liver transplantation (LT) offers a potential cure for patients with unresectable, early-stage de novo or primary sclerosing cholangitis (PSC)-associated pCCA, post-transplant recurrence negatively impacts survival. Currently, no risk stratification tools exist. Methods: This retrospective study included consecutive patients with unresectable de novo or PSC-associated pCCA who underwent neoadjuvant CRT followed by LT at Mayo Clinic (1993–2024). Predictors of post-transplant recurrence were identified using multivariable Cox regression with LASSO variable selection. The Perihilar Cholangiocarcinoma Risk Estimation of Tumor Recurrence after Transplant (PRETREAT) risk score was created by assigning points from model coefficients. Score performance was evaluated by discrimination (c-statistic), internally validated with 10-fold cross-validation, and externally validated in a separate cohort. Survival outcomes were compared across 3 PRETREAT risk groups and between 2 time periods. Results: This study included 399 patients (development: 301; validation: 98). The 5-year cumulative incidence of post-transplant recurrence was 29.7% in the development cohort and 27.6% in the validation cohort. Multivariable analysis identified 4 independent predictors: macroscopic residual tumor on explant [hazard ratio (HR): 12.4], vascular encasement (HR: 2.18), lymphovascular invasion (HR: 2.04), and radial tumor diameter (HR: 1.02/mm). The PRETREAT score (0–22), based on these factors, demonstrated excellent performance in both internal and external validation (C-index 0.83 and 0.85, respectively). Patients were stratified into low-risk (0–7), moderate-risk (8–15), and high-risk (16–22) groups. The 5-year recurrence-free survival rates significantly differed across low-risk, moderate-risk, and high-risk groups (89.0%, 38.3%, and 15.4%, respectively; P<0.001). Over the last decade, overall survival improved significantly only in moderate-risk patients (70.4% vs 46.9%, P=0.024), without significant improvement in recurrence-free survival. Conclusions: The PRETREAT score provides a valuable tool for guiding post-transplant management of pCCA, enabling risk-stratified surveillance, and laying the foundation for future clinical trials.

Background and Aims: Among those with primary sclerosing cholangitis (PSC), perihilar cholangiocarcinoma (pCCA) is often diagnosed at a late stage and is a leading source of mortality. Detection of pCCA in PSC when curative action can be taken is challenging. Our aim was to create a deep learning model that analyzed MRI to detect early-stage pCCA and compare its diagnostic performance with expert radiologists. Approach and Results: We conducted a multicenter, international, retrospective cohort study involving adults with large duct PSC who underwent contrast-enhanced MRI. Senior abdominal radiologists reviewed the images. All patients with pCCA had early-stage cancer and were registered for liver transplantation. We trained a 3D DenseNet-121 model, a form of deep learning, using MRI images and assessed its performance in a separate test cohort. The study included 398 patients (training cohort n=150; test cohort n=248). pCCA was present in 230 individuals (training cohort n=64; test cohort n=166). In the test cohort, the respective performances of the model compared to the radiologists were: sensitivity 87.9% versus 50.0%, p <0.001; specificity 84.1% versus 100.0%, p <0.001; area under receiving operating curve 86.0% versus 75.0%, p <0.001. Even when a mass was absent, the model had a higher sensitivity for pCCA than radiologists (91.6% vs. 50.6%, p <0.001) and maintained good specificity (84.1%). Conclusions: The 3D DenseNet-121 MRI model effectively detects early-stage pCCA in PSC patients. Compared to expert radiologists, the model missed fewer cases of cancer.

ABSTRACTIntroductionThe incidence of mortality late in the pandemic, particularly after widespread vaccine availability, is not well understood. Herein, we elucidate the effect of this impact of the COVID pandemic as well as risk factors for mortality during it.MethodsThe primary end point was death with a functioning graft with secondary endpoints of mortality rates in subgroups and at different time intervals during the pandemic.ResultsDespite widespread vaccination, mortality rates for kidney transplant (KTx) recipients almost doubled during the COVID‐19 era (6.40 deaths per 100 person years vs. 3.54 pre‐COVID). Mortality increased in all racial/ethnic groups but increased more in Native Americans, Hispanics, and African Americans compared to non‐Hispanic Caucasians. The highest mortality rate occurred during the Delta and Omicron time frames. In contrast to the general population, mortality was more evenly spread across age groups in KTx recipients.ConclusionsMortality rates during the COVID‐19 era were extremely high, more than doubling in some racial/ethnic groups. We conclude that the KTx population was a particularly vulnerable group during the COVID‐19 era and suggests the need for further research into the management of variants in the future.

ABSTRACTCellular senescence is a biological mechanism of aging and age‐related diseases. The aim of this study was to examine whether senescence biomarkers are associated with frailty and physical function trajectories in patients undergoing kidney transplantation (KT). We also discussed the relationship between senescence biomarkers and KT function. In this multicenter study, we prospectively assessed plasma levels of senescence biomarkers, frailty as measured by the Physical Frailty Phenotype, and physical function as measured by the Short Physical Performance Battery prior to KT. Frailty, physical function, and KT function were also measured 1 year after KT. Variable associations were assessed using Cox and relaxed least absolute shrinkage and selection operation regression. The cohort consisted of 197 participants (mean age 53 ± 13 years, 61.4% male, and 80.2% White race). Higher pre‐KT levels of macrophage‐derived chemokine (MDC/CCL22) and growth differentiation factor‐15 (GDF‐15) were independently associated with less improvement in frailty and/or physical function during the first year after KT. Higher pre‐KT levels tumor necrosis factor receptor superfamily member 6 (FAS) and MMP‐9 levels were independently associated with lower KT function one year after KT. Pre‐KT cellular senescence may contribute to frailty, physical function, and kidney function trajectories during the first year after KT.