Dataset Information

No Major Effect of Innate Immune Genetics on Acute Kidney Rejection in the First 2 Weeks Post-Transplantation.

ABSTRACT: Background:Innate immunity contributes to acute rejection after kidney transplantation. Genetic polymorphisms affecting innate immunity may therefore influence patients' risk of rejection. IL2 -330T > G, IL10 -1082G > A, -819C > T, and -592C > A, and TNF -308G > A are not associated with acute rejection incidence in Caucasian kidney transplant recipients receiving a calcineurin inhibitor, ciclosporin or tacrolimus (TAC). However, other important innate immune genetic polymorphisms have not yet been extensively studied in recipients and donors. In addition, innate immunogenetics have not been investigated in kidney transplant cohorts receiving only TAC as the calcineurin inhibitor. Objective:To investigate the effect of recipient and donor CASP1, CRP, IL1B, IL2, IL6, IL6R, IL10, MYD88, TGFB, TLR2, TLR4, and TNF genetics on acute kidney rejection in the first 2 weeks post-transplant in TAC-treated kidney transplant recipients. Methods:This study included 154 kidney transplant recipients and 81 donors successfully genotyped for 17 polymorphisms in these genes. All recipients were under triple immunosuppressant therapy of TAC, mycophenolate mofetil, and prednisolone. Recipient and donor genotype differences in acute rejection incidence within the first 2 weeks post-transplantation were assessed by logistic regression, adjusting for induction therapy, human leukocyte antigen mismatches, kidney transplant number, living donor, and peak panel-reactive antibody scores. Results:A trend (Cochran-Armitage P = 0.031) of increasing acute rejection incidence was observed from recipient IL6 -6331 T/T (18%) to T/C (25%) to C/C (46%) genotype [C/C versus T/T odds ratio (95% confidence interval) = 6.6 (1.7 to 25.8) (point-wise P = 0.017)]. However, no genotype differences were significant after Bonferroni correction for multiple comparisons. Conclusions:This study did not detect any statistically significant effects of recipient or donor innate immune genetics on acute rejection incidence in the first 2 weeks post-transplantation. However, the sample size was small, and future larger studies or meta-analyses are required to demonstrate conclusively if innate immune genetics such as IL6 influence the risk of acute rejection after kidney transplantation.

SUBMITTER: Hu R

PROVIDER: S-EPMC7045476 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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No Major Effect of Innate Immune Genetics on Acute Kidney Rejection in the First 2 Weeks Post-Transplantation.

Hu Rong R Barratt Daniel T DT Coller Janet K JK Sallustio Benedetta C BC Somogyi Andrew A AA

Frontiers in pharmacology 20200220

<h4>Background</h4>Innate immunity contributes to acute rejection after kidney transplantation. Genetic polymorphisms affecting innate immunity may therefore influence patients' risk of rejection. <i>IL2</i> -330T > G, <i>IL10</i> -1082G > A, -819C > T, and -592C > A, and <i>TNF</i> -308G > A are not associated with acute rejection incidence in Caucasian kidney transplant recipients receiving a calcineurin inhibitor, ciclosporin or tacrolimus (TAC). However, other important innate immune genetic ...[more]

PMID: 32153387

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Project description:Background and objectivesIn preclinical studies, ischemia-reperfusion injury and older donor age are associated with graft inflammation in the early phase after transplantation. In human kidney transplantation, impaired allograft function in the first days after transplantation is often adjudicated to donor- and procedure-related characteristics, such as donor age, donor type, and ischemia times.Design, setting, participants, & measurementsIn a cohort of 984 kidney recipients, 329 indication biopsies were performed within the first 14 days after transplantation. The histologic picture of these biopsies and its relationship with alloimmune risk factors and donor- and procedure-related characteristics were studied, as well as the association with graft failure. Multivariable Cox models were applied to quantify the cause-specific hazard ratios for early rejection and early inflammatory scores, adjusted for potential confounders. For quantification of hazard ratios of early events for death-censored graft failure, landmark analyses starting from day 15 were used.ResultsEarly indication biopsy specimens displayed microvascular inflammation score ≥2 in 30% and tubulointerstitial inflammation score ≥2 in 49%. Rejection was diagnosed in 186 of 329 (57%) biopsies and associated with the presence of pretransplant donor-specific HLA antibodies and the number of HLA mismatches, but not nonimmune risk factors in multivariable Cox proportional hazards analysis. In multivariable Cox proportional hazards analysis, delayed graft function, the graft dysfunction that prompted an early indication biopsy, HLA mismatches, and pretransplant donor-specific HLA antibodies were significantly associated with a higher risk for death-censored graft failure, whereas early acute rejection was not.ConclusionsIndication biopsies performed early after kidney transplantation display inflammatory changes related to alloimmune risk factors. Nonimmune risk factors for ischemia-reperfusion injury, such as cold and warm ischemia time, older donor age, and donor type, were not identified as strong risk factors for early inflammation after human kidney transplantation.

Project description:Background and objectivesDefinition of individual risk profile is the first step to implement strategies to keep the delicate balance between under- and overimmunosuppression after kidney transplantation.Design, setting, participants, & measurementsWe used data from the Efficacy Limiting Toxicity Elimination Symphony Study (1190 patients between 2002 and 2004) to model risk of rejection and infection in the first year after kidney transplantation. External validation was performed in a study population from the Fixed-Dose Concentration-Controlled Trial (630 patients between 2003 and 2006).ResultsDespite different temporal dynamics, rejections and severe infections had similar overall incidences in the first year after transplantation (23.4% and 25.5%, respectively), and infections were the principal cause of death (43.2% of all deaths). Recipient older age, deceased donor, higher number of HLA mismatches, and high risk for cytomegalovirus disease were associated with infection; deceased donor, higher number of HLA mismatches, and immunosuppressive therapy including cyclosporin A (compared with tacrolimus), with rejection. These factors were integrated into a two-dimensional risk stratification model, which defined four risk groups: low risk for infection and rejection (30.8%), isolated risk for rejection (36.1%), isolated risk for infection (7.0%), and high risk for infection and rejection (26.1%). In internal validation, this model significantly discriminated the subgroups in terms of composite end point (low risk for infection/rejection, 24.4%; isolated risk for rejection and isolated risk for infection, 31.3%; high risk for infection/rejection, 54.4%; P<0.001), rejection episodes (isolated risk for infection and low risk for infection/rejection, 13.0%; isolated risk for rejection and high risk for infection/rejection, 24.2%; P=0.001), and infection episodes (low risk for infection/rejection and isolated risk for rejection, 12.0%; isolated risk for infection and high risk for infection/rejection, 37.6%; P<0.001). External validation confirmed the applicability of the model to an independent cohort.ConclusionsWe propose a two-dimensional risk stratification model able to disentangle the individual risk for rejection and infection in the first year after kidney transplantation. This concept can be applied to implement a personalized immunosuppressive and antimicrobial treatment approach.

Dataset Information

No Major Effect of Innate Immune Genetics on Acute Kidney Rejection in the First 2 Weeks Post-Transplantation.

Publications

No Major Effect of Innate Immune Genetics on Acute Kidney Rejection in the First 2 Weeks Post-Transplantation.

Similar Datasets

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