Dual kidney transplantation (DKT) from small pediatric donors, either en-bloc or split dual kidney transplantation, contributes to mitigating organ scarcity. This study investigates the prognosis of DKT from pediatric deceased donors, and influencing factors.

A retrospective study included recipients who underwent DKT from pediatric donors between 2012 and 2022. Recipients were categorized into low mismatch (BWLM, n = 30) and high mismatch (BWHM, n = 10) groups based on donor-recipient weight ratio of 1:10. Outcome encompassed recipient and graft survival, renal function, and adverse events.

Forty recipients were included. The average follow-up period was 54.6 months. The 1, 3, and 5-year patient survival were 97.4%, with no significant differences between en-bloc and split dual kidney transplantation or between BWLM and BWHM groups. The graft survival at 1, 3, and 5 years were 89.9%, the graft survival of BWHM group was lower than BWLM group (70% vs 96.7%, p = 0.039). The average eGFR at 1, 3, and 5 years postoperatively were (78.93 ± 25.23), (83.82 ± 32.4), and (85.92 ± 37.08) mL/min/1.73 m2, respectively. The BWHM group also experienced higher rates of graft-related surgical complications (p = 0.006) and urinary tract surgical complications (p = 0.042).

DKT from pediatric donors yields favorable outcomes, with similar graft survival and complication rates across surgical subgroups. However, significant donor-recipient weight mismatch, particularly when the ratio is less than 1:10, may contribute to increased surgical complications and poorer graft survival. Efforts to minimize extreme weight mismatch are recommended to optimize outcomes.

Cox proportional hazard models have long been the model of choice for survival prediction after kidney transplantation. In recent years, a variety of novel model types have been proposed. We investigate the prediction performance across different model types, including machine learning models and traditional model types.

A systematic review was conducted following PROBAST and CHARMS, also considering extensions to TRIPOD+AI and PROBAST+AI, for data collection and risk of bias assessment. The review only included publications that reported on prediction performance for models of different types. A comparative analysis tested performance differences between the model types.

The review included 37 publications which presented 134 comparative studies. The designs of many studies left room for improvement and most studies had high risk of bias. The collected data admitted testing of performance differences for 22 pairs of model types, ten of which yielded significant differences. Support Vector Machines and Logistic Regression were never found to outperform other model types. Other comparisons, however, provide inconclusive comparative performance results and none of the model types performed consistently and significantly better than alternatives.

Rigorous review of current evidence and comparative performance evidence finds no significant kidney transplant survival prediction performance differences that Cox Proportional Hazard models are being outperformed. The design of many of the studies implies high risk of bias and more and better designed studies which reutilize best performing models are needed. This enables to resolve model biases, reporting issues, and to increase the power of comparative performance analysis.

Given the cardiovascular, renal, and survival benefits of GLP-1 receptor agonists for diabetes, these agents could be effective among kidney transplant recipients. However, kidney transplant recipients are distinct from GLP-1 receptor agonist trial participants, with longer diabetes duration and severity, greater end-organ damage, increased cardiovascular risk, and multimorbidity. We examined GLP-1 receptor agonist real-world effectiveness and safety in kidney transplant recipients with diabetes.

This USA-based retrospective cohort study included kidney transplant recipients with type 2 diabetes at transplantation and Medicare as their primary insurance from a national registry linked with Medicare claims. Post-transplantation GLP-1 receptor agonist use was identified through Medicare claims. Death-censored graft loss was estimated using the Fine-Gray sub-distribution hazard model and extended Cox models were used for mortality and safety endpoints. Models incorporated inverse probability of treatment weights. To further test whether bias could affect the main results, a cohort was created in which each GLP-1 receptor agonist user was matched with a kidney transplant recipient who had not started a GLP-1 receptor agonist, was alive with a functioning graft, and had accrued the same amount of post-transplant survival time.

Between Jan 1, 2013 and Dec 31, 2020, we identified 44 536 first time kidney transplant recipients with Medicare as primary payer in the 6 months before and at transplantation. 24 192 patients were excluded as they did not have type 2 diabetes. 2328 patients were ineligible (1916 had missing values and 412 used GLP-1 receptor agonists before transplantation). The primary cohort thus consisted of 18 016 kidney transplant recipients with diabetes. Of these patients, 1969 (10·9%) had at least one GLP-1 receptor agonist prescription filled post-transplant. Compared with patients who had not received a GLP-1 receptor agonist, GLP-1 receptor agonist users were younger (median age at transplant 57 years [IQR 49-64] vs 60 years [51-66], p<0·0001) and more likely to be female (786 [39·9%] vs 5645 [35·2%], p<0·0001). Among GLP-1 receptor agonist users, 552 [28·0%] were non-Hispanic White, 703 [35·7%] were non-Hispanic Black, and 568 [28·8%] were Hispanic. The 5-year unadjusted cumulative incidence of death-censored graft loss from a cohort matched on survival time before GLP-1 receptor agonist initiation was 6·0% for GLP-1 receptor agonist users and 10·7% for non-users (Gray's test p=0·004). The 5-year unadjusted cumulative incidence for mortality from a cohort matched on survival time before GLP-1 receptor agonist initiation was 17·0% for GLP-1 receptor agonist users and 25·8% for non-users (log-rank p=0·0006). The 5-year unadjusted cumulative incidence for mortality was 13·5% for GLP-1 receptor agonist users and 19·9% for non-users (log-rank p<0·0001). GLP-1 receptor agonist use was associated with a 49% lower incidence of death-censored graft loss (adjusted subhazard ratio [aSHR] 0·51, 95% CI 0·36-0·71; p=0·0001) and 31% lower mortality (adjusted hazard ratio [aHR] 0·69, 95% CI 0·55-0·86; p=0·001). Inferences were robust when matched on survival time (death-censored graft loss aSHR 0·53, 95% CI 0·37-0·75; p=0·0005; mortality aHR 0·70, 95% CI 0·55-0·88; p=0·003). Safety endpoints were rare and not associated with GLP-1 receptor agonists, with the exception of diabetic retinopathy (aHR 1·49, 1·11-2·00; p=0·008).

GLP-1 receptor agonists were associated with better graft and patient survival. Clinical trials are needed to confirm these findings.

National Institutes of Health.

Allograft biopsy remains the gold standard to diagnose rejection. New noninvasive biomarkers are needed to avoid unnecessary biopsies and to diagnose early rejection. We studied the performance of donor derived cell-free DNA (dd-cfDNA) to detect rejection in an unselected cohort of pediatric kidney transplant recipients (pKTRs) and determined whether dd-cfDNA could improve standard-of-care monitoring and detection of kidney allograft rejection in children.

We included 196 pKTRs, who underwent 367 biopsies with concomitant dd-cfDNA assessment. We assessed the association of dd-cfDNA with histological lesions and with rejection using a Cox regression model and compared the discrimination of 3 models: standard of care, dd-cfDNA alone, and combined.

We found a significant increase in dd-cfDNA levels with higher degree of inflammation on the biopsies. dd-cfDNA was strongly and independently associated with the presence of allograft rejection (odds ratio 1.89, 95% confidence interval [CI], 1.40-2.60). dd-cfDNA alone had a fair discrimination of 0.76 (95% CI, 0.69-0.81) to detect rejection and its addition to standard of care resulted in a significant increase in discrimination from 0.80 (95% CI, 0.71-0.85) to 0.84 (95% CI, 0.79-0.90), P = 0.01.

dd-cfDNA combined with standard of care improves the prediction of rejection in pKTRs. Further specific studies are needed to better define how to use this promising biomarker in various contexts of use in children.

ObjectivesThe aim of the present study was to compare the differences in clinical outcomes within 6 months postoperatively between a complement-dependent cytotoxicity <10% group of low-risk kidney transplant patients and a complement-dependent cytotoxicity ≥10% group of relatively high-risk patients.MethodsThe clinical data of 330 patients who underwent kidney transplantation were retrospectively analyzed. The patients were divided into three groups according to the results of complement-dependent cytotoxicity crossmatch: (a) group 1 (complement-dependent cytotoxicity ≥10%); (b) group 2a (5% ≤ complement-dependent cytotoxicity < 10%); and (c) group 2b (complement-dependent cytotoxicity <5%). The clinical outcomes were compared between the three groups.ResultsSignificant differences were noted in serum creatinine levels and estimated glomerular filtration rate between groups 2a and 2b on days (D) 1, 2, 3, and 7 (P < 0.005). From postoperative D1 to month (M) 6, a significant difference (P < 0.05) was noted in urea levels between the three groups. On D3, blood glucose levels were significantly lower in group 2b than in group 2a (P < 0.001); at M6, group 2b exhibited lower blood glucose levels than group 1 (P = 0.043). On D2, group 2b had a lower neutrophil percentage than group 1 (P < 0.05), which was significantly different from those of groups 1 and 2a on D3 (P < 0.05). The percentage and absolute number of lymphocytes in group 2b were significantly higher than those in group 1 (P < 0.01) on D1 and D2. The percentage and absolute number of lymphocytes were significantly higher in group 2b than in groups 1 and 2a on D3 and D7 (P < 0.05).ConclusionsComplement-dependent cytotoxicity <10%, particularly complement-dependent cytotoxicity <5%, was associated with superior attributes compared with complement-dependent cytotoxicity ≥10% in terms of most aspects of postoperative recovery and low incidence of adverse events. However, delayed graft function rate was highest in the complement-dependent cytotoxicity of 5%-10% group. The source of donor kidneys was the most important factor influencing delayed graft function, and a larger cohort with a longer follow-up period may be needed to verify the tendency.

Organ Procurement and Transplantation Network (OPTN) policy requires 2 years of follow-up for living kidney donors (LKDs); however, many transplant hospitals struggle to meet this requirement. We developed and tested a mobile health (mHealth) system for LKD follow-up in a pilot randomized-controlled trial (RCT).

LKDs were randomly assigned to either the intervention (mHealth + standard of care) or control arm (standard of care). We assessed OPTN policy-defined completeness and timeliness of 6-month, 1-year, and 2-year follow-ups. Four hundred LKDs were enrolled in the study (June 2018 to February 2021).

At 6-month follow-up, a higher proportion of the intervention arm participants completed composite visits (97.5% vs. 91.5%, p = 0.01). Both arms had similar compliance rates at 1- and 2-year follow-up (92.0% vs. 89.5%, p = 0.49, and 66.5% vs. 65.0%, p = 0.83). Intervention arm participants completed 6-month follow-up 11 days earlier than their counterparts (p = 0.009).

mHealth technologies improved 6-month follow-up, but did not impact 1- and 2-year LKD follow-up in this single-center RCT. Other strategies, such as providing services beyond data collection, may be necessary to improve donor engagement and support LDK's long-term follow-up.

We recently discovered 2 urinary exosomal mRNA signatures to identify and differentiate T-cell-mediated rejection (TCMR) from antibody-mediated rejection (ABMR) in kidney transplant recipients. Here, we developed Exosome Transplant Rejection Urine (ExoTRU), a urinetest based on a 4-gene signature from the previous discovery cohort, showed its clinical utility in a new cohort of kidney transplant recipients undergoing clinically indicated biopsies, and validated it through a separate laboratory in an independent-cohort of patients.

A workflow suited for clinical laboratories was developed, allowing for smaller urine volumes and widely standardized qPCR instrumentation. A total of 226 urine samples from 214 patients were paired with clinically indicated biopsies. Urinary exosomal mRNAs levels were evaluated for previously defined targets.

Four mRNAs (IL32, B2M, CXCL11, and PGK1) performed well in distinguishing biopsies with rejection or significant inflammation from those without inflammation, achieving 94% sensitivity, 62% positive predictive value, and 52% specificity. Patients who tested positive by the signature but negative by biopsy were nearly twice as likely to experience adverse outcomes in the 5-year follow-up period, including subsequent rejection, thereby showing the limitations of kidney biopsies and the prognostic potential of molecular signatures. The evaluation of an independent validation cohort showed similar performance, achieving an area under the curve (AUC) of 0.838. Another 6-gene signature distinguished TCMR from ABMR, with an AUC of 0.756.

Exosomal mRNA gene signatures identified patients with different stages and classes of rejection, including early stage and significant inflammation, enabling improved decision-making and patient management and reducing unnecessary biopsies by 45%. This represents a potential tool for risk stratification based on poor outcomes in patients with positive signatures.

Belatacept shows promise as an alternative immunosuppressant without the nephrotoxicity of calcineurin inhibitors. Avoiding nephrotoxicity is important with the expanding use of organs at risk of marginal graft function. To date, no large studies have compared belatacept directly with tacrolimus after T-cell depleting induction in renal transplantation.

The Standard Transplant Analysis and Research file was used to compare adult kidney transplant recipients induced with T-cell depleting agents treated with belatacept to propensity score-matched recipients treated with tacrolimus between August 10, 2011 and June 29, 2023. Kaplan-Meier survival analysis was used to compare death censored graft survival, patient survival, and time to acute rejection.

During the study period, 4391 adult kidney transplant recipients were treated with belatacept. Estimated GFR improved for belatacept-treated patients through year 9, whereas it decreased for the control group through year 10. Belatacept-treated patients had a higher rejection rate at 5 years (21% vs. 15%, p < 0.001). Death-censored graft survival did not differ between groups (p = 0.383). Among patients who had rejection, death-censored graft survival was superior in belatacept-treated patients at 5 years (70% vs. 60%, p = 0.026). Overall, patient survival did not differ between groups (p = 0.120).

This is the largest longitudinal study to compare outcomes of belatacept versus tacrolimus-based therapy following T-cell depleting induction. Belatacept was associated with improved graft function despite an increased acute rejection rate. There was no difference in overall graft or patient survival compared to tacrolimus. This study suggests that belatacept-based therapy is not inferior to tacrolimus-based therapy following T-cell depletion.

Kidney allograft fibrosis accelerates the progression of chronic kidney disease (CKD), leads to allograft failure, and increases patient mortality. Emerging evidence suggests that metabolic syndrome in transplant recipients is associated with fibrosis development. However, it remains unclear whether targeting metabolic pathways can mitigate allograft fibrosis. This study aimed to explore the potential of targeting metabolic pathways using the GLP-1R/GCGR dual agonist TB001 for the treatment of kidney allograft fibrosis.

Kidney allograft fibrosis was induced in rat kidney transplant models. Histological analysis, transcriptome sequencing, and in vitro experiments were performed to investigate the efficacy of TB001 and its underlying mechanisms.

Compared with the control group, TB001-treated recipients had significantly improved kidney allograft function, as evidenced by lower creatinine and 24-hour urine protein levels. Moreover, TB001 treatment decreased the body weight and serum total cholesterol, LDL-cholesterol, and TNF-α levels in transplant recipients, indicating metabolic improvements. Pathological analysis demonstrated that TB001 treatment reduced inflammatory cell infiltration and downregulated the expression of fibrosis markers, including TGF-β1, α-SMA, COL1A1, and Vimentin. Further transcriptome sequencing of kidney grafts revealed that TB001-treated group had a gene expression pattern similar to that of the syngeneic control group and showed significant enhancement of lipid metabolism-related pathways, particularly the PPAR pathway. In vivo and in vitro experiments further demonstrated that TB001 upregulated the expression of CPT1A, a key molecule involved in lipid metabolism, and inhibited TGF-β1/Smad2/3/Twist and PKC-α/PKC-β pathways.

Targeting metabolic pathways using the GLP-1R/GCGR dual agonist TB001 shows potential for managing kidney allograft fibrosis.

Breastfeeding after kidney transplantation remains a complex and underexplored topic, primarily due to concerns regarding the safety of immunosuppressive therapies during lactation. Individuals who have received kidney transplants face a higher likelihood of delivering preterm infants and giving birth to babies with a low birth weight when compared with the general population. In this context, breastfeeding is increasingly important because of its advantages for preterm infants. Despite the well-established benefits of breastfeeding for both the mother and infant, the traditional recommendation has been to avoid nursing due to potential drug transmission through breast milk. However, emerging evidence suggests that certain immunosuppressants may be compatible with breastfeeding, challenging long-standing clinical guidelines. In this review, we examine the current literature on the pharmacokinetics, safety profiles, and clinical outcomes associated with key immunosuppressive agents, including cyclosporine, tacrolimus, everolimus, azathioprine, corticosteroids, and belatacept. Our work highlights that all published reports to date on the studied treatments indicate that the amount of the drug reaching breast milk is considered safe for the child's health. These conclusions, however, are derived from very short-term measurements and small numbers of patients. Therefore, we emphasize the need to design structured prospective studies to assess safety in the medium and long term. Our review aims to equip clinicians with the most up-to-date evidence on this topic, enabling them to make informed decisions regarding the compatibility of post-kidney transplant treatments with breastfeeding.

Kidney transplantation remains the best treatment for chronic kidney failure, offering better outcomes and quality of life compared with dialysis. Cardiovascular disease (CVD) is a major cause of morbidity and mortality in kidney transplant recipients and is associated with decreased patient survival and worse graft outcomes. Post-transplant CVD results from a complex interaction between traditional cardiovascular risk factors, such as hypertension and diabetes, and risk factors specific to kidney transplant recipients including chronic kidney disease, immunosuppressive drugs, or vascular access. An accurate assessment of cardiovascular risk is now needed to optimize the management of cardiovascular comorbidities through the detection of risk factors and the screening of hidden pretransplant coronary artery disease. Promising new strategies are emerging, such as GLP-1 receptor agonists and SGLT2 inhibitors, with a high potential to mitigate cardiovascular complications, although further research is needed to determine their role in kidney transplant recipients. Despite this progress, a significant gap remains in understanding the optimal management of post-transplant CVD, especially coronary artery disease, stroke, and peripheral artery disease. Addressing these challenges is essential to improve the short- and long-term outcomes in kidney transplant recipients. This narrative review aims to provide a comprehensive overview of cardiovascular risk assessment and post-transplant CVD management.

Kidney transplant offers better outcomes and reduced costs compared with chronic dialysis. However, racial and ethnic disparities in access to kidney transplant persist despite efforts to expand access to transplant and improve the equity of deceased donor allocation. Our objective was to evaluate after listing the association of race and ethnicity with access to deceased donor kidney transplant (DDKT) after changes to the allocation system in 2014.

This retrospective study evaluated access to DDKT after listing since the implementation of the 2014 kidney allocation system. Waitlist status and transplant outcomes were ascertained from data from the Scientific Registry of Transplant Recipients. Our analysis included every adult kidney transplant candidate on the waiting list in the US from January 1, 2015, through June 30, 2023.

A total of 290 763 candidates were on the waiting list for DDKT during the study period. Of these, 36.4% of candidates were African American and 22.2% were Latino. Compared with White non-Latino patients, access to DDKT after listing was reduced for African American (unadjusted hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.92-0.94) and Latino individuals (unadjusted HR, 0.88; 95% CI, 0.87-0.90). After controlling for demographic and clinical factors, these differences in access to transplant widened substantially for African American (HR, 0.78; 95% CI, 0.77-0.80) and Latino patients (HR, 0.73; 95% CI, 0.72-0.74).

African American and Latino patients had reduced access to DDKT after listing. More effective approaches to improving access for African American and Latino individuals after listing are needed.

Organ transplantation is a critical medical procedure that saves and improves lives, yet the system faces significant challenges that result in many missed opportunities. This comprehensive review examines the factors contributing to these missed opportunities and the concerns of potential donors. The shortage of donors remains a major issue, exacerbated by low registration rates, family consent refusals, and strict medical and health criteria. Inefficiencies within the organ procurement and transplantation process, including logistical delays and suboptimal matching systems, further hinder the availability of organs. Public misconceptions and cultural and religious beliefs also negatively impact donor willingness. Moreover, potential donors and their families face ethical, psychological, and procedural concerns. Ethical dilemmas revolve around issues of autonomy and informed consent, while psychological concerns include fear and anxiety about the donation process and its impact on families. Procedural issues, such as transparency, legal hurdles, and post-donation follow-up, add to the complexities of organ donation. This review explores potential solutions to address these challenges, such as enhancing public education campaigns to dispel myths, and providing incentives for proactive registration. It also recommends improving the performance of organ procurement organizations, optimizing logistics for organ transport, and developing advanced matching algorithms to ensure equitable organ allocation. Addressing donor concerns through robust ethical standards, comprehensive psychological support, and clear communication strategies is essential. By adopting these multifaceted strategies, the organ transplantation system can be made more efficient and supportive, increasing the availability of organs and ultimately saving more lives. This review underscores the need for integrated and targeted approaches to overcome the existing barriers in organ transplantation.

Solid organ transplant recipients (SOTRs) have a heightened risk of adverse coronavirus disease 2019 (COVID-19) outcomes because of immunosuppression and medical comorbidity. We quantified the burden of COVID-19 mortality in United States (US) SOTRs. A sample of deaths documented in the US solid organ transplant registry from June 2020 through December 2022 was linked to the National Death Index to identify COVID-19 deaths and weighted to represent all SOTR deaths during the study period. Among 505 757 SOTRs, 57 575 deaths occurred, and based on the linkage, 12 396 (21.5%) were due to COVID-19. COVID-19 mortality was higher in males (mortality rate ratio [MRR]: 1.13), SOTRs aged 65 years and older (MRR: 1.50 in ages 65-74 vs ages 55-64 years), and non-Hispanic Black and Hispanic SOTRs (MRRs: 1.55 and 1.79 vs non-Hispanic White SOTRs). Kidney and lung recipients had the highest COVID-19 mortality, followed by heart, and then liver recipients. COVID-19 mortality also varied over time and across US states. Overall, SOTRs had a 7-fold increased risk of COVID-19 death compared to the US general population. SOTRs comprised 0.13% of the US population but accounted for 1.46% of all US COVID-19 deaths. SOTRs experience greatly elevated COVID-19 mortality. Clinicians should continue to prioritize COVID-19 prevention and treatment in this high-risk population.

Introduction: Donor-derived cell-free DNA (dd-cfDNA) in the peripheral blood of allograft recipients has shown to early identify allograft injury. In this study, we assessed the factors that influence the amount of circulating dd-cfDNA during the first month postkidney transplant as well as its longitudinal trend. Materials and Methods: A consecutive series of 98 adult kidney transplant recipients at a single center between July 2018 and January 2020 were included in this study. All demographic and operative details were collected for donors and recipients of the organ transplant. Median eGFR, dd-cfDNA, and serum creatinine were calculated at 1, 2, 3, 6, and 12 month posttransplant. Descriptive statistics were used for patient demographics. Nonparametric comparisons of dd-cfDNA cumulative distributions between dichotomized groupings were evaluated using Kruskal-Wallis or Mann-Whitney U tests. Results: The median age of recipients was 54.5 years (IQR: 42.7-62.2). The cause of ESRD among recipients was hypertension (43%) and Type II diabetes mellitus (29%). Eighty-two percentage of patients received a deceased donor allograft, 14% received a living unrelated allograft, and 4% received a living related allograft. Sixteen percentage of recipients experienced delayed graft function (DGF). Median creatinine level at 1 month posttransplant was 1.75 mg/dL (IQR: 1.34-2.26) and median eGFR at 1 month posttransplant was 49.6 mL/min/1.73 m2 (IQR: 35-65). The median dd-cfDNA score at 1 month posttransplant for all recipients was 0.4% (IQR: 0.15-5.3). Donor sex was a statistically significant differential for dd-cfDNA score. Recipients from male donors had a significantly higher median dd-cf DNA score at 1 month posttransplant versus those who received a female kidney (0.57% vs. 0.28%, p < 0.01). Highest median score was recorded at the first month posttransplant (0.4%, IQR: 0.26-0.74), and a sustained downward trend was observed through Month 2 (0.19%, IQR: 0.17-0.31) and Month 3 (0.19%, IQR: 0.15-0.26). Correlation between 1-, 2-, 3-, 6-, and 12-month posttransplant median dd-cfDNA scores between deceased donor and living donor (LRD and LURD) cohorts was not statistically significant. Conclusion: This study provides further insight into donor and recipient variables' effects on dd-cfDNA in the early posttransplant phase by analyzing a more diverse cohort of patients and adds to the knowledge around interpreting dd-cfDNA scores with clinical correlation for posttransplant management.

Acute T cell mediated rejection of allografts remains a significant risk factor for early graft loss. Our prior work defined a population of graft-specific CD8 + T cells positive for the activated receptor CD43 (expressing the 1B11 epitope) that form during acute rejection, leading us to further understand the in vivo fate and clinical relevance of this population. We found that during acute rejection, the CD43 + ICOS + phenotype was sensitive for proliferative graft-specific CD8 + T cells. We evaluated whether CD43 1B11 signaling could impact graft survival, and found that CD43 1B11 mAb treatment could overcome costimulation-blockade induced tolerance in the majority of mice. Using an adoptive transfer approach, we investigated the fate of CD43 1B11 + and CD43 1B11 - CD8 + T cell populations, and found that CD43 1B11 + CD8 + T cells were more persistent three weeks after transplantation. A portion of CD43 1B11 - CD8 + T cells converted to CD43 1B11 + , while CD43 1B11 + CD8 + T cells retained CD43 1B11 + status. In healthy human donors, we found that the CD43 1D4 clone, which identifies the large CD43 isoform, defines a population of antigen-experienced CD8 + T cells independent of the canonical CD8 + T cell populations. CD43 1D4 + CD8 + T cells were efficient cytokine-producers after stimulation. In scRNA-seq analysis of graft-infiltrating cells from renal transplant patients experiencing acute rejection, a population of SPN + GCNT1 + CD8 + T cells had an effector phenotype that includes high expression of IFNG, ICOS, and perforins/granzymes. Together, these data provide evidence that the CD43 1B11 expression defines a proliferative and persistent population of CD8 + T cells in mice, and that an analogous population of antigen-experienced CD8 + T cells that participate in allograft rejection.

The Banff classification is useful for diagnosing renal transplant rejection. However, it has limitations due to subjectivity and varying concordance in physicians' assessments. Artificial intelligence (AI) can help standardize research, increase objectivity and accurately quantify morphological characteristics, improving reproducibility in clinical practice. This study aims to develop an AI-based solutions for diagnosing acute kidney transplant rejection by introducing automated evaluation of prognostic morphological patterns. The proposed approach aims to help accurately distinguish borderline changes from rejection. We trained a deep-learning model utilizing a fine-tuned Mask R-CNN architecture which achieved a mean Average Precision value of 0.74 for the segmentation of renal tissue structures. A strong positive nonlinear correlation was found between the measured infiltration areas and fibrosis, indicating the model's potential for assessing these parameters in kidney biopsies. The ROC analysis showed a high predictive ability for distinguishing between ci and i scores based on infiltration area and fibrosis area measurements. The AI model demonstrated high precision in predicting clinical scores which makes it a promising AI assisting tool for pathologists. The application of AI in nephropathology has a potential for advancements, including automated morphometric evaluation, 3D histological models and faster processing to enhance diagnostic accuracy and efficiency.

Rejection is one of the major factors affecting the long-term prognosis of kidney transplantation, and timely recognition and aggressive treatment of rejection is essential to prevent disease progression. RBPs are proteins that bind to RNA to form ribonucleoprotein complexes, thereby affecting RNA stability, processing, splicing, localization, transport, and translation, which play a key role in post-transcriptional gene regulation. However, their role in renal transplant rejection and long-term graft survival is unclear. The aim of this study was to comprehensively analyze the expression of RPBs in renal rejection and use it to construct a robust prediction strategy for long-term graft survival. The microarray expression profiles used in this study were obtained from GEO database. In this study, a total of eight hub RBPs were identified, all of which were upregulated in renal rejection samples. Based on these RBPs, the renal rejection samples could be categorized into two different clusters (cluster A and cluster B). Inflammatory activation in cluster B and functional enrichment analysis showed a strong association with rejection-related pathways. The diagnostic prediction model had a high diagnostic accuracy for T cell mediated rejection (TCMR) in renal grafts (area under the curve = 0.86). The prognostic prediction model effectively predicts the prognosis and survival of renal grafts (p < .001) and applies to both rejection and non-rejection situations. Finally, we validated the expression of hub genes, and patient prognosis in clinical samples, respectively, and the results were consistent with the above analysis.

The pathogenesis of allograft (dys)function has been increasingly studied using 'omics'-based technologies, but the focus on individual organs has created knowledge gaps that neither unify nor distinguish pathological mechanisms across allografts. Here we present a comprehensive study of human pan-organ allograft dysfunction, analyzing 150 datasets with more than 12,000 samples across four commonly transplanted solid organs (heart, lung, liver and kidney, n = 1,160, 1,241, 1,216 and 8,853 samples, respectively) that we leveraged to explore transcriptomic differences among allograft dysfunction (delayed graft function, acute rejection and fibrosis), tolerance and stable graft function. We identified genes that correlated robustly with allograft dysfunction across heart, lung, liver and kidney transplantation. Furthermore, we developed a transfer learning omics prediction framework that, by borrowing information across organs, demonstrated superior classifications compared to models trained on single organs. These findings were validated using a single-center prospective kidney transplant cohort study (a collective 329 samples across two timepoints), providing insights supporting the potential clinical utility of our approach. Our study establishes the capacity for machine learning models to learn across organs and presents a transcriptomic transplant resource that can be employed to develop pan-organ biomarkers of allograft dysfunction.

Lengthening waiting lists for organ transplant mandates the development of strategies to expand the deceased donor pool. Due to concerns regarding organ viability, most organ donation organizations internationally wait no longer than 1 to 2 hours for potential donation after circulatory death (DCD), possibly underutilizing an important organ source; UK policy mandates a minimum 3-hour wait time.

To assess whether time to death (TTD) from withdrawal of life-sustaining treatment (WLST) is associated with kidney transplant outcomes.

This population-based cohort study used data from the prospectively maintained UK Transplant Registry from all 23 UK kidney transplant centers from January 1, 2013, to December 31, 2021; follow-up was until the date of data extraction (October 2023). Participants comprised 7183 adult recipients of DCD kidney-alone transplants.

Duration of TTD, defined as time from WLST to donor mechanical asystole.

Primary outcome was 12-month estimated glomerular filtration rate (eGFR; for the main eGFR model, variables with significant right skew [histogram visual assessment] were analyzed on the log2 scale), with secondary outcomes of delayed graft function and graft survival (censored at death or 5 years).

This study included 7183 kidney transplant recipients (median age, 56 years [IQR, 47-64 years]; 4666 men [65.0%]). Median donor age was 55 years (IQR, 44-63 years). Median TTD was 15 minutes (range, 0-407 minutes), with 885 kidneys transplanted from donors with TTD over 1 hour and 303 kidneys transplanted from donors with TTD over 2 hours. Donor TTD was not associated with recipient 12-month eGFR on adjusted linear regression (change per doubling of TTD, -0.25; 95% CI, -0.68 to 0.19; P = .27), nor with delayed graft function (adjusted odds ratio, 1.01; 95% CI, 0.97-1.06; P = .65) or graft survival (adjusted hazard ratio, 1.00; 95% CI, 0.95-1.07; P = .92). These findings were confirmed with restricted cubic spline models (assessing nonlinear associations) and tests of interaction (including normothermic regional perfusion). In contrast, donor asystolic time, cold ischemic time, and reperfusion time were independently associated with outcomes. Compared with a theoretical 1-hour maximum wait time, the UK policy (minimum 3-hour wait time) has been associated with 885 extra DCD transplants compared with 6298 transplants (14.1% increase).

In this cohort study of DCD kidney recipients, donor TTD was not associated with posttransplant outcomes, in contrast to subsequent ischemic times. Altering international transplant practice to mandate minimum 3-hour donor wait times could substantially increase numbers of kidney transplants performed without prejudicing outcomes.

A major change to deceased-donor kidney allocation in the United States, Kidney Allocation System 250 (KAS250), was implemented on March 15, 2021. Evaluating the consequences of this policy on critical system performance metrics is critical to determining its success.

We performed a retrospective analysis of critical performance measures of the kidney transplant system by reviewing all organs procured during a 4-y period in the United States. To mitigate against possible effects of the COVID-19 pandemic, Scientific Registry of Transplant Recipients records were stratified into 2 pre- and 2 post-KAS250 eras: (1) 2019; (2) January 1, 2020-March14, 2021; (3) March 15, 2021-December 31, 2021; and (4) 2022. Between-era differences in rates of key metrics were analyzed using chi-square tests with pairwise z -tests. Multivariable logistic regression and analysis of variations methods were used to evaluate the effects of the policy on rural and urban centers.

Over the period examined, among kidneys recovered for transplant, nonuse increased from 19.7% to 26.4% (all between-era P < 0.05) and among all Kidney Donor Profile Index strata. Cold ischemia times increased ( P < 0.001); however, the distance between donor and recipient hospitals decreased ( P < 0.05). Kidneys from small-metropolitan or nonmetropolitan hospitals were more likely to not be used over all times ( P < 0.05).

Implementation of KAS250 was associated with increased nonuse rates across all Kidney Donor Profile Index strata, increased cold ischemic times, and shorter distance traveled.

Chronic allograft dysfunction (CAD) poses a significant challenge in kidney transplantation, with renal vascular endothelial-to-mesenchymal transition (EndMT) playing a vital role. While renal vascular EndMT has been verified as an important contributing factor to renal allograft interstitial fibrosis/tubular atrophy in CAD patients, its underlying mechanisms remain obscure. Currently, Src activation is closely linked to organ fibrosis development. Single-cell transcriptomic analysis in clinical patients revealed that Src is a potential pivotal mediator in CAD progression. Our findings revealed a significant upregulation of Src which closely associated with EndMT in CAD patients, allogeneic kidney transplanted rats and endothelial cells lines. In vivo, Src inhibition remarkably alleviate EndMT and renal allograft interstitial fibrosis in allogeneic kidney transplanted rats. It also had a similar antifibrotic effect in two endothelial cell lines. Mechanistically, the knockout of Src resulted in an augmented AMBRA1-mediated mitophagy in endothelial cells. We demonstrate that Src knockdown upregulates AMBRA1 level and activates mitophagy by stabilizing Parkin's ubiquitination levels and mitochondrial translocation. Subsequent experiments demonstrated that the knockdown of the Parkin gene inhibited mitophagy in endothelial cells, leading to increased production of Interleukin-6, thereby inducing EndMT. Consequently, our study underscores Src as a critical mediator of renal vascular EndMT and allograft interstitial fibrosis, exerting its impact through the regulation of AMBRA1/Parkin-mediated mitophagy.

Current kidney perfusion protocols are not optimized for addressing the ex vivo physiological and metabolic needs of the kidney. Ex vivo normothermic perfusion may be utilized to distinguish high-risk kidneys to determine suitability for transplantation. Here, we assessed the association of tissue metabolic changes with changes in a kidney injury biomarker and functional parameters in eight deceased donor kidneys deemed unsuitable for transplantation during a 12-hour ex vivo normothermic perfusion. The kidneys were grouped into good and poor performers based on blood flow and urine output. The mean age of the deceased kidney donors was 43 years with an average cold ischemia time of 37 hours. Urine output and creatinine clearance progressively increased and peaked at six hours post-perfusion among good performers. Poor performers had 71 ng/ml greater (95% confidence interval 1.5, 140) urinary neutrophil gelatinase-associated lipocalin at six hours compared to good performers corresponding to peak functional differences. Organ performance was distinguished by tissue metabolic differences in branched chain amino acid metabolism and that their tissue levels negatively correlated with urine output among all kidneys at six hours. Tissue lipid profiling showed poor performers were highlighted by the accumulation of membrane structure components including glycerolipids and sphingolipids at early perfusion time points. Thus, we showed that six hours is needed for kidney function recovery during ex vivo normothermic perfusion and that branched chain amino acid metabolism may be a major determinant of organ function and resilience.

The mismatch between the number of patients awaiting kidney transplantation and the supply of donor organs has contributed to the increase in kidney transplantation from donors after circulatory death (DCD). Persistently long waiting times have led the transplant community to continue to explore the use of expanded- criteria DCD kidneys. In parallel, advances in organ preservation strategies have contributed to an overall increase in DCD organ transplantation and are altering the transplant landscape. Some of these techniques may improve kidney allograft outcomes and affect how DCD kidneys are used. We aimed to better understand practices in accepting DCD kidney offers in the modern era.

Directors of 196 US kidney transplant centers were emailed a link to an online survey over a 5-week period.

Forty-eight out of the 364 directors (13%) responded, with all United Network for Organ Sharing regions represented. Definitions of warm ischemia time (WIT) used in DCD kidney evaluation varied widely among the respondents. The maximum total WIT limit varied, with 19 (39.6%) <60-minute responses, followed by 16 (33%) <90-minute responses, and 10 (20.8%) <120-minute responses.

Despite increasing DCD kidney transplantation volumes in the United States, there are no standardized procurement biopsy practices, organ procurement organization preoperative protocols, or consensus definition or limits of WIT. Agreement on terminology may facilitate rapid clinical communication, efficiency of organ allocation and utilization, recording of data, research, and improvements in policy.

Lung transplantation is the only definitive therapy for end-stage pulmonary disease. Less than 20 % of offered lungs are successfully transplanted due to a limited ischemic time window and poor donor lung quality manifested by pulmonary edema, hypoxia, or trauma. Therefore, poor donor organ recovery and utilization are significant barriers to wider implementation of the life-saving therapy of transplantation. While ischemia reperfusion injury (IRI) is often identified as the underlying molecular insult leading to immediate poor lung function in the post-operative period, this injury encompasses several pathways of cellular injury in addition to the recruitment of the innate immune system to the site of injury to propagate this inflammatory cascade. Pyroptosis is a central molecular inflammatory pathway that is the most significant contributor to injury in this early post-operative phase. Pyroptosis is another form of programmed cell death and is often associated with IRI. The mitigation of pyroptosis in the early post-operative period following lung transplantation is a potential novel way to prevent poor allograft function and improve outcomes for all recipients. Here we detail the pyroptotic pathway, its importance in lung transplantation, and several therapeutic modalities that can mitigate this harmful inflammatory pathway.

Clinicians often face uncertainty when interpreting whether a decline in estimated glomerular filtration rate is within the patient's expected range of fluctuation or if the decline signals a substantial deviation. Thus, accurate predictions of glomerular filtration rate can be an early warning system, prompting timely interventions, such as biopsies to preclude early graft rejection and adjustments in immunosuppression. Traditional models, encompassing linear and conventional methods, typically struggle with variabilities and complexities in posttransplant data.

We evaluated the efficacy of a gradient boosting model in predicting posttransplant glomerular filtration rate, to potentially enhance accuracy over traditional prediction approaches. Our patient dataset included 68 pediatric patients aged 1 to 18 years who underwent kidney transplant between 2017 and 2023 at Baskent University Hospital (Ankara, Turkey). The dataset comprised 2285 glomerular filtration rate measurements, along with patient demographics and transplant-related data. For our model, we included "days to transplant" (glomerular filtration rate values pretransplant), "days from transplant" (glomerular filtration rate values up to 7 days posttransplant), patient age, sex, and donor types. We divided the dataset into a training set (70%) and a test set (30%). To evaluate model performance, we used mean absolute error and root mean squared error, with a focus on the accuracy of glomerular filtration rate predictions at various posttransplant stages.

In the training set, the gradient boosting model demonstrated a significant improvement in prediction accuracy, achieving an mean absolute error of ~5.64 mL/min/1.73 m².

Our model underscored the promise of advanced machine learning techniques in refining prediction of glomerular filtration rate after kidney transplant. With its augmented precision, the model can support clinicians in making informed decisions regarding early biopsies and interventions, thus highlighting the vital role of sophisticated analytical methods in medical prognosis and the monitoring of pediatric patient care.

Cancer development in the remnant kidney in living kidney donors represents a challenging process in terms of patient management. Total nephrectomy is the preferred method for tumors exceeding 7 cm in size. In the case presented here, partial nephrectomy was preferred because the patient was a prior living kidney donor. On the other hand, being an organ donor always creates concerns for long-term safety and survival. The guidelines on the evaluation and care of living kidney donors have generally focused on assessment of the risk for chronic kidney disease in donors and donor-to-recipient infection or cancer transmission. In this case report, we also evaluated whether being a donor is a facilitating factor for cancer development in the remnant kidney.

Indoleamine-2,3-dioxygenase (IDO)1 degrades tryptophan, obtained through dietary intake, into immunoregulatory metabolites of the kynurenine pathway. Deficiency or blockade of IDO1 results in the enhancement of autoimmune severity in rodent models and increased susceptibility to developing autoimmunity in humans. Despite this, therapeutic modalities that leverage IDO1 for the treatment of autoimmunity remain limited. Here, we use messenger (m)RNA formulated in lipid nanoparticles (LNPs) to deliver a human IDO1 variant containing the myristoylation site of Src to anchor the protein to the inner face of the plasma membrane. This membrane-anchored IDO1 has increased protein production, leading to increased metabolite changes, and ultimately ameliorates disease in three models of T cell-mediated autoimmunity: experimental autoimmune encephalomyelitis (EAE), rat collagen-induced arthritis (CIA), and acute graft-versus-host disease (aGVHD). The efficacy of IDO1 is correlated with hepatic expression and systemic tryptophan depletion. Thus, the delivery of membrane-anchored IDO1 by mRNA suppresses the immune response in several well-characterized models of autoimmunity.

We previously reported that normothermic ex vivo kidney  perfusion (NEVKP) is superior in terms of organ protection compared to static cold storage (SCS), which is still the standard method of organ preservation, but the mechanisms are incompletely understood. We used a large animal kidney autotransplant model to evaluate mitochondrial function during organ preservation and after kidney transplantation, utilizing live cells extracted from fresh kidney tissue. Male porcine kidneys stored under normothermic perfusion showed preserved mitochondrial function and higher ATP levels compared to kidneys stored at 4 °C (SCS). Mitochondrial respiration and ATP levels were further enhanced when AP39, a mitochondria-targeted hydrogen sulfide donor, was administered during warm perfusion. Correspondingly, the combination of NEVKP and AP39 was associated with decreased oxidative stress and inflammation, and with improved graft function after transplantation. In conclusion, our findings suggest that the organ-protective effects of normothermic perfusion are mediated by maintenance of mitochondrial function and enhanced by AP39 administration. Activation of mitochondrial function through the combination of AP39 and normothermic perfusion could represent a new therapeutic strategy for long-term renal preservation.

The purpose of this study was to investigate gender differences in cardiovascular outcomes of kidney transplant recipients (KTRs). Here, a retrospective cohort study was conducted, and data from the National Health Insurance Research Database in Taiwan were used. In total, 2904 patients who had end-stage renal disease (ERSD) and received kidney transplantation (KT) were identified by propensity score matching (PSM) and were enrolled from 1997 to 2012, with follow-up ending in 2013. Besides, major adverse cardiovascular events (MACEs) were defined as a composite of all-cause mortality, nonfatal myocardial infarction, and nonfatal strokes. Apart from that, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by Cox regression, while the Bayesian network model was constructed to assess the importance of risk factors for MACEs. Furthermore, the original cohort was a sensitivity analysis. Women had a lower risk of MACEs compared with men (hazard ratio [HR]: 0.84; 95% CI: 0.72-0.98; P = .024). Beyond that, stratified analysis of age and waiting time for KT showed that the risk of MACEs was significantly lower in women than in men among KTRs aged > 50 years (HR: 0.79; 95% CI: 0.62-1.0; P = .05) or waiting time for KT ≤ 6 years (HR: 0.85; 95% CI: 0.72-0.99; P = .04). Bayesian network indicated that age is an important determinant of cardiovascular outcomes in KTRs, regardless of gender. In Taiwan, women had a lower risk of adverse cardiovascular outcomes than men in KTRs aged > 50 years or with a waiting time for KT ≤ 6 years. Furthermore, age is an important independent determinant for the prognosis of KTRs.

Efforts to address the shortage of donor organs include increasing the use of renal allografts from donors after circulatory death (DCD). While warm ischemia time (WIT) is thought to be an important factor in DCD kidney evaluation, few studies have compared the relationship between WIT and DCD kidney outcomes, and WIT acceptance practices remain variable.

We conducted a single-center retrospective review of all adult patients who underwent deceased donor kidney transplantation from 2000 to 2021. We evaluated the impact of varied functional warm ischemia time (fWIT) in controlled DCD donors by comparing donor and recipient characteristics and posttransplant outcomes between high fWIT (>60 min), low fWIT (≤60 min), and kidneys transplanted from donors after brain death (DBD).

Two thousand eight hundred eleven patients were identified, 638 received low fWIT DCD, 93 received high fWIT DCD, and 2080 received DBD kidneys. There was no significant difference in 5-year graft survival between the DCD low fWIT, high fWIT, and DBD groups, with 84%, 83%, and 83% of grafts functioning, respectively. Five-year patient survival was 91% in the low fWIT group, 92% in the high fWIT group, and 90% in the DBD group. An increase in kidney donor risk index (KDRI) (HR 3.37, 95% CI = 2.1-5.7) and high CIT compared to low CIT (HR 2.12, 95% CI = 1.4-3.1) have higher hazard ratios for 1-year graft failure.

Increased acceptance of kidneys from selected DCD donors with prolonged fWIT may present an opportunity to increase kidney utilization while preserving outcomes. Our group specifically prioritizes the use of kidneys from younger donors, with lower KDPI, and without acute kidney injury, or risk factors for underlying chronic kidney disease.

Quality indicators in kidney transplants are needed to identify care gaps and improve access to transplants. We used linked administrative health care databases to examine multiple ways of defining pre-emptive living donor kidney transplants, including different patient cohorts and censoring definitions. We included adults from Ontario, Canada with advanced chronic kidney disease between January 1, 2013, to December 31, 2018. We created 4 unique incident patient cohorts, varying the eligibility by the risk of progression to kidney failure and whether individuals had a recorded contraindication to kidney transplant (eg, home oxygen use). We explored the effect of 4 censoring event definitions. Across the 4 cohorts, size varied substantially from 20 663 to 9598 patients, with the largest reduction (a 43% reduction) occurring when we excluded patients with ≥1 recorded contraindication to kidney transplantation. The incidence rate (per 100 person-years) of pre-emptive living donor kidney transplant varied across cohorts from 1.02 (95% CI: 0.91-1.14) for our most inclusive cohort to 2.21 (95% CI: 1.96-2.49) for the most restrictive cohort. Our methods can serve as a framework for developing other quality indicators in kidney transplantation and monitoring and improving access to pre-emptive living donor kidney transplants in health care systems.

Over one thousand pediatric kidney transplant candidates are added to the waitlist annually, yet the prospective time spent waiting is unknown for many. Our study fills this gap by identifying variables that impact waitlist time and by creating an index to predict the likelihood of a pediatric candidate receiving a transplant within 1 year of listing. This index could be used to guide patient management by giving clinicians a potential timeline for each candidate's listing based on a unique combination of risk factors.

A retrospective analysis of 3757 pediatric kidney transplant candidates from the 2014 to 2020 OPTN/UNOS database was performed. The data was randomly divided into a training set, comprising two-thirds of the data, and a testing set, comprising one-third of the data. From the training set, univariable and multivariable logistic regressions were used to identify significant predictive factors affecting wait times. A predictive index was created using variables significant in the multivariable analysis. The index's ability to predict likelihood of transplantation within 1 year of listing was validated using ROC analysis on the training set. Validation of the index using ROC analysis was repeated on the testing set.

A total of 10 variables were found to be significant. The five most significant variables include the following: blood group, B (OR 0.65); dialysis status (OR 3.67); kidney disease etiology, SLE (OR 0.38); and OPTN region, 5 (OR 0.54) and 6 (OR 0.46). ROC analysis of the index on the training set yielded a c-statistic of 0.71. ROC analysis of the index on the testing set yielded a c-statistic of 0.68.

This index is a modest prognostic model to assess time to pediatric kidney transplantation. It is intended as a supplementary tool to guide patient management by providing clinicians with an individualized prospective timeline for each candidate. Early identification of candidates with potential for prolonged waiting times may help encourage more living donation including paired donation chains.

The risk factors of cardiovascular disease (CVD) in end-stage renal disease (ESRD) with hemodialysis remain not fully understood. In this study, we developed and validated a clinical-longitudinal model for predicting CVD in patients with hemodialysis, and employed Mendelian randomization to evaluate the causal 6study included 468 hemodialysis patients, and biochemical parameters were evaluated every three months. A generalized linear mixed (GLM) predictive model was applied to longitudinal clinical data. Calibration curves and area under the receiver operating characteristic curves (AUCs) were used to evaluate the performance of the model. Kaplan-Meier curves were applied to verify the effect of selected risk factors on the probability of CVD. Genome-wide association study (GWAS) data for CVD (n = 218,792,101,866 cases), end-stage renal disease (ESRD, n = 16,405, 326 cases), diabetes (n = 202,046, 9,889 cases), creatinine (n = 7,810), and uric acid (UA, n = 109,029) were obtained from the large-open GWAS project. The inverse-variance weighted MR was used as the main analysis to estimate the causal associations, and several sensitivity analyses were performed to assess pleiotropy and exclude variants with potential pleiotropic effects.

The AUCs of the GLM model was 0.93 (with accuracy rates of 93.9% and 93.1% for the training set and validation set, sensitivity of 0.95 and 0.94, specificity of 0.87 and 0.86). The final clinical-longitudinal model consisted of 5 risk factors, including age, diabetes, ipth, creatinine, and UA. Furthermore, the predicted CVD response also allowed for significant (p < 0.05) discrimination between the Kaplan-Meier curves of each age, diabetes, ipth, and creatinine subclassification. MR analysis indicated that diabetes had a causal role in risk of CVD (β = 0.088, p < 0.0001) and ESRD (β = 0.26, p = 0.007). In turn, ESRD was found to have a causal role in risk of diabetes (β = 0.027, p = 0.013). Additionally, creatinine exhibited a causal role in the risk of ESRD (β = 4.42, p = 0.01).

The results showed that old age, diabetes, and low level of ipth, creatinine, and UA were important risk factors for CVD in hemodialysis patients, and diabetes played an important bridging role in the link between ESRD and CVD.

Kidney transplantation (KT) is the best treatment for end-stage renal disease. Although long and short-term survival rates for the graft have improved significantly with the development of immunosuppressants, acute rejection (AR) remains a major risk factor attacking the graft and patients. The innate immune response plays an important role in rejection. Therefore, our objective is to determine the biomarkers of congenital immunity associated with AR after KT and provide support for future research.

A differential expression genes (DEGs) analysis was performed based on the dataset GSE174020 from the NCBI gene Expression Synthesis Database (GEO) and then combined with the GSE5099 M1 macrophage-related gene identified in the Molecular Signatures Database. We then identified genes in DEGs associated with M1 macrophages defined as DEM1Gs and performed gene ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) enrichment analysis. Cibersort was used to analyze the immune cell infiltration during AR. At the same time, we used the protein-protein interaction (PPI) network and Cytoscape software to determine the key genes. Dataset, GSE14328 derived from pediatric patients, GSE138043 and GSE9493 derived from adult patients, were used to verify Hub genes. Additional verification was the rat KT model, which was used to perform HE staining, immunohistochemical staining, and Western Blot. Hub genes were searched in the HPA database to confirm their expression. Finally, we construct the interaction network of transcription factor (TF)-Hub genes and miRNA-Hub genes.

Compared to the normal group, 366 genes were upregulated, and 423 genes were downregulated in the AR group. Then, 106 genes related to M1 macrophages were found among these genes. GO and KEGG enrichment analysis showed that these genes are mainly involved in cytokine binding, antigen binding, NK cell-mediated cytotoxicity, activation of immune receptors and immune response, and activation of the inflammatory NF-κB signaling pathway. Two Hub genes, namely CCR7 and CD48, were identified by PPI and Cytoscape analysis. They have been verified in external validation sets, originated from both pediatric patients and adult patients, and animal experiments. In the HPA database, CCR7 and CD48 are mainly expressed in T cells, B cells, macrophages, and tissues where these immune cells are distributed. In addition to immunoinfiltration, CD4+T, CD8+T, NK cells, NKT cells, and monocytes increased significantly in the AR group, which was highly consistent with the results of Hub gene screening. Finally, we predicted that 19 TFs and 32 miRNAs might interact with the Hub gene.

Through a comprehensive bioinformatic analysis, our findings may provide predictive and therapeutic targets for AR after KT.