Cognitive improvement after kidney transplantation is associated with structural and functional changes on MRI

Several studies have reported improved cognitive outcomes after kidney transplantation, but most studies either did not include controls or lacked extensive neuroimaging. In addition, there is uncertainty whether kidney donation is a safe procedure in terms of cognitive outcomes.Education and Child Studie

CD8 and CD4 T cell populations in human kidneys

Background: At border sites, and in internal organs, tissue resident memory T cells (T-RM) contribute to the immune barrier against pathogens like viruses, bacteria, fungi, and cancer. However, information on the presence and function of these cells in the human kidney is scant. In order to better understand the T cell-mediated immunological defense in this organ, we aimed to determine phenotypic and functional aspects of CD8 and CD4 T cells present in healthy and allograft kidney tissue. Methods: Using multichannel flow cytometry, we assessed the phenotype and function of T cells in healthy renal tissue samples (n = 5) and kidney allograft tissue (n = 7) and compared these aspects to T cells in peripheral blood from healthy controls (n = 13). Results: Kidney tissue samples contained substantial amounts of CD8 and CD4 T cells. In contrast to the circulating cells, kidney T cells frequently expressed CD69 and CD103, and were more often actively cycling. Furthermore, nearly all kidney T cells expressed CXCR3, and often expressed CXCR6 compared to T cells in the circulation. Markedly, kidney T cells produced greater quantities of IFN gamma than circulating cells and were frequently polyfunctional. Conclusion: Functional T cells with the characteristic traits of T-RM reside in human kidney tissues. These cells are more often actively cycling and frequently express CXCR3 and CXCR6.Immunopathology of vascular and renal diseases and of organ and celltransplantationIP1

Rationale and design of the OPTIMIZE trial: OPen label multicenter randomized trial comparing standard IMmunosuppression with tacrolimus and mycophenolate mofetil with a low exposure tacrolimus regimen In combination with everolimus in de novo renal transplantation in Elderly patients

BackgroundIn 2019, more than 30% of all newly transplanted kidney transplant recipients in The Netherlands were above 65 years of age. Elderly patients are less prone to rejection, and death censored graft loss is less frequent compared to younger recipients. Elderly recipients do have increased rates of malignancy and infection-related mortality. Poor kidney transplant function in elderly recipients may be related to both pre-existing (i.e. donor-derived) kidney damage and increased susceptibility to nephrotoxicity of calcineurin inhibitors (CNIs) in kidneys from older donors. Hence, it is pivotal to shift the focus from prevention of rejection to preservation of graft function and prevention of over-immunosuppression in the elderly. The OPTIMIZE study will test the hypothesis that reduced CNI exposure in combination with everolimus will lead to better kidney transplant function, a reduced incidence of complications and improved health-related quality of life for kidney transplant recipients aged 65 years and older, compared to standard immunosuppression.MethodsThis open label, randomized, multicenter clinical trial will include 374 elderly kidney transplant recipients (>= 65 years) and consists of two strata. Stratum A includes elderly recipients of a kidney from an elderly deceased donor and stratum B includes elderly recipients of a kidney from a living donor or from a deceased donor= 45 ml/min per 1.73 m(2) in stratum B, after 2 years, respectively.ConclusionsThe OPTIMIZE study will help to determine the optimal immunosuppressive regimen after kidney transplantation for elderly patients and the cost-effectiveness of this regimen. It will also provide deeper insight into immunosenescence and both subjective and objective outcomes after kidney transplantation in elderly recipients.Trial registrationClinicalTrials.gov: NCT03797196, registered January 9th, 2019. EudraCT: 2018-003194-10, registered March 19th, 2019.Nephrolog

Time interval between self-expandable metal stent placement or creation of a decompressing stoma and elective resection of left-sided obstructive colon cancer

Background The optimal timing of resection after decompression of left-sided obstructive colon cancer is unknown. Revised expert-based guideline recommendations have shifted from an interval of 5-10 days to approximately 2 weeks following self-expandable metal stent (SEMS) placement, and recommendations after decompressing stoma are lacking. We aimed to evaluate the recommended bridging intervals after SEMS and explore the timing of resection after decompressing stoma.Methods This nationwide study included patients registered between 2009 and 2016 in the prospective, mandatory Dutch ColoRectal Audit. Additional data were collected through patient records in 75 hospitals. Only patients who underwent either SEMS placement or decompressing stoma as a bridge to surgery were selected. Technical SEMS failure and unsuccessful decompression within 48 hours were exclusion criteria.Results 510 patients were included (182 SEMS, 328 decompressing stoma). Median bridging interval was 23 days (interquartile range [IQR] 13-31) for SEMS and 36 days (IQR 22-65) for decompressing stoma. Following SEMS placement, no significant differences in post-resection complications, hospital stay, or laparoscopic resections were observed with resection after 11-17 days compared with 5-10 days. Of SEMS-related complications, 48% occurred in patients operated on beyond 17 days. Compared with resection within 14 days, an interval of 14-28 days following decompressing stoma resulted in significantly more laparoscopic resections, more primary anastomoses, and shorter hospital stays. No impact of bridging interval on mortality, disease-free survival, or overall survival was demonstrated.Conclusions Based on an overview of the data with balancing of surgical outcomes and timing of adverse events, a bridging interval of approximately 2 weeks seems appropriate after SEMS placement, while waiting 2-4 weeks after decompressing stoma further optimizes surgical conditions for laparoscopic resection with restoration of bowel continuity.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Allocation to highly sensitized patients based on acceptable mismatches results in low rejection rates comparable to nonsensitized patients

Contains fulltext : 208426.pdf (publisher's version ) (Open Access)Whereas regular allocation avoids unacceptable mismatches on the donor organ, allocation to highly sensitized patients within the Eurotransplant Acceptable Mismatch (AM) program is based on the patient's HLA phenotype plus acceptable antigens. These are HLA antigens to which the patient never made antibodies, as determined by extensive laboratory testing. AM patients have superior long-term graft survival compared with highly sensitized patients in regular allocation. Here, we questioned whether the AM program also results in lower rejection rates. From the PROCARE cohort, consisting of all Dutch kidney transplants in 1995-2005, we selected deceased donor single transplants with a minimum of 1 HLA mismatch and determined the cumulative 6-month rejection incidence for patients in AM or regular allocation. Additionally, we determined the effect of minimal matching criteria of 1 HLA-B plus 1 HLA-DR, or 2 HLA-DR antigens on rejection incidence. AM patients showed significantly lower rejection rates than highly immunized patients in regular allocation, comparable to nonsensitized patients, independent of other risk factors for rejection. In contrast to highly sensitized patients in regular allocation, minimal matching criteria did not affect rejection rates in AM patients. Allocation based on acceptable antigens leads to relatively low-risk transplants for highly sensitized patients with rejection rates similar to those of nonimmunized individuals

Early Steroid Withdrawal Compared With Standard Immunosuppression in Kidney Transplantation - Interim Analysis of the Amsterdam-Leiden-Groningen Randomized Controlled Trial

Nephrolog

Evaluation of spelt germplasm for polyphenol oxidase activity and aluminium resistance

Kidney transplantation is the best treatment option for patients with end-stage renal failure. At present, approximately 800 Dutch patients are registered on the active waiting list of Eurotransplant. The waiting time in the Netherlands for a kidney from a deceased donor is on average between 3 and 4years. During this period, patients are fully dependent on dialysis, which replaces only partly the renal function, whereas the quality of life is limited. Mortality among patients on the waiting list is high. In order to increase the number of kidney donors, several initiatives have been undertaken by the Dutch Kidney Foundation including national calls for donor registration and providing information on organ donation and kidney transplantation. The aim of the national PROCARE consortium is to develop improved matching algorithms that will lead to a prolonged survival of transplanted donor kidneys and a reduced HLA immunization. The latter will positively affect the waiting time for a retransplantation. The present algorithm for allocation is among others based on matching for HLA antigens, which were originally defined by antibodies using serological typing techniques. However, several studies suggest that this algorithm needs adaptation and that other immune parameters which are currently not included may assist in improving graft survival rates. We will employ a multicenter-based evaluation on 5429 patients transplanted between 1995 and 2005 in the Netherlands. The association between key clinical endpoints and selected laboratory defined parameters will be examined, including Luminex-defined HLA antibody specificities, T and B cell epitopes recognized on the mismatched HLA antigens, non-HLA antibodies, and also polymorphisms in complement and Fc receptors functionally associated with effector functions of anti-graft antibodies. From these data, key parameters determining the success of kidney transplantation will be identified which will lead to the identification of additional parameters to be included in future matching algorithms aiming to extend survival of transplanted kidneys and to diminish HLA immunization. Computer simulation studies will reveal the number of patients having a direct benefit from improved matching, the effect on shortening of the waiting list, and the decrease in waiting time

Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study

Background Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas of pathology, requiring considerable expertise, time, and effort. We aimed to analyse the utility of deep learning to preclassify histology of kidney allograft biopsies into three main broad categories (ie, normal, rejection, and other diseases) as a potential biopsy triage system focusing on transplant rejection.Methods We performed a retrospective, multicentre, proof-of-concept study using 5844 digital whole slide images of kidney allograft biopsies from 1948 patients. Kidney allograft biopsy samples were identified by a database search in the Departments of Pathology of the Amsterdam UMC, Amsterdam, Netherlands (1130 patients) and the University Medical Center Utrecht, Utrecht, Netherlands (717 patients). 101 consecutive kidney transplant biopsies were identified in the archive of the Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany. Convolutional neural networks (CNNs) were trained to classify allograft biopsies as normal, rejection, or other diseases. Three times cross-validation (1847 patients) and deployment on an external real-world cohort (101 patients) were used for validation. Area under the receiver operating characteristic curve (AUROC) was used as the main performance metric (the primary endpoint to assess CNN performance).Findings Serial CNNs, first classifying kidney allograft biopsies as normal (AUROC 0.87 [ten times bootstrapped CI 0.85-0.88]) and disease (0.87 [0.86-0.88]), followed by a second CNN classifying biopsies classified as disease into rejection (0.75 [0.73-0.76]) and other diseases (0.75 [0.72-0.77]), showed similar AUROC in cross-validation and deployment on independent real-world data (first CNN normal AUROC 0.83 [0.80-0.85], disease 0.83 [0.73-0.91]; second CNN rejection 0.61 [0.51-0.70], other diseases 0.61 [0.50-4.74]). A single CNN classifying biopsies as normal, rejection, or other diseases showed similar performance in cross-validation (normal AUROC 0.80 [0.73-0.84], rejection 0.76 [0.66-0.80], other diseases 0.50 [0.36-0.57]) and generalised well for normal and rejection classes in the real-world data. Visualisation techniques highlighted rejection-relevant areas of biopsies in the tubulointerstitium.Interpretation This study showed that deep learning-based classification of transplant biopsies could support pathological diagnostics of kidney allograft rejection. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Immunopathology of vascular and renal diseases and of organ and celltransplantationIP

PIRCHE-II is related to graft failure after kidney transplantation

Individual HLA mismatches may differentially impact graft survival after kidney transplantation. Therefore, there is a need for a reliable tool to define permissible HLA mismatches in kidney transplantation. We previously demonstrated that donor-derived Predicted Indirectly ReCognizable HLA Epitopes presented by recipient HLA class II (PIRCHE-II) play a role in de novo donor-specific HLA antibodies formation after kidney transplantation. In the present Dutch multi-center study, we evaluated the possible association between PIRCHE-II and kidney graft failure in 2,918 donor-recipient couples that were transplanted between 1995 and 2005. For these donors-recipients couples, PIRCHE-II numbers were related to graft survival in univariate and multivariable analyses. Adjusted for confounders, the natural logarithm of PIRCHE-II was associated with a higher risk for graft failure [hazard ratio (HR): 1.13, 95% CI: 1.04-1.23, p = 0.003]. When analyzing a subgroup of patients who had their first transplantation, the HR of graft failure for ln(PIRCHE-II) was higher compared with the overall cohort (HR: 1.22, 95% CI: 1.10-1.34, p < 0.001). PIRCHE-II demonstrated both early and late effects on graft failure in this subgroup. These data suggest that the PIRCHE-II may impact graft survival after kidney transplantation. Inclusion of PIRCHE-II in donor-selection criteria may eventually lead to an improved kidney graft survival

T-cell epitopes shared between immunizing HLA and donor HLA associate with graft failure after kidney transplantation

CD4(+) T-helper cells play an important role in alloimmune reactions following transplantation by stimulating humoral as well as cellular responses, which might lead to failure of the allograft. CD4(+) memory T-helper cells from a previous immunizing event can potentially be reactivated by exposure to HLA mismatches that share T-cell epitopes with the initial immunizing HLA. Consequently, reactivity of CD4(+) memory T-helper cells toward T-cell epitopes that are shared between immunizing HLA and donor HLA could increase the risk of alloimmunity following transplantation, thus affecting transplant outcome. In this study, the amount of T-cell epitopes shared between immunizing and donor HLA was used as a surrogate marker to evaluate the effect of donor-reactive CD4(+) memory T-helper cells on the 10-year risk of death-censored kidney graft failure in 190 donor/recipient combinations using the PIRCHE-II algorithm. The T-cell epitopes of the initial theoretical immunizing HLA and the donor HLA were estimated and the number of shared PIRCHE-II epitopes was calculated. We show that the natural logarithm-transformed PIRCHE-II overlap score, or Shared T-cell EPitopes (STEP) score, significantly associates with the 10-year risk of death-censored kidney graft failure, suggesting that the presence of pre-transplant donor-reactive CD4(+) memory T-helper cells might be a strong indicator for the risk of graft failure following kidney transplantation.Nephrolog