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De novo donor‐specific antibody (dnDSA) develops in 15–25% of renal transplant recipients within 5 years of transplantation and is associated with 40% lower graft survival at 10 years. HLA epitope matching is a novel strategy that may minimize dnDSA development. HLAMatchmaker software was used to characterize epitope mismatches at 395 potential HLA‐DR/DQ/DP conformational epitopes for 286 donor–recipient pairs. Epitope specificities were assigned using single antigen HLA bead analysis and correlated with known monoclonal alloantibody epitope targets. Locus‐specific epitope mismatches were more numerous in patients who developed HLA‐DR dnDSA alone (21.4 vs. 13.2, p < 0.02) or HLA‐DQ dnDSA alone (27.5 vs. 17.3, p < 0.001). An optimal threshold for epitope mismatches (10 for HLA‐DR, 17 for HLA‐DQ) was defined that was associated with minimal development of Class II dnDSA. Applying these thresholds, zero and 2.7% of patients developed dnDSA against HLA‐DR and HLA‐DQ, respectively, after a median of 6.9 years. Epitope specificity analysis revealed that 3 HLA‐DR and 3 HLA‐DQ epitopes were independent multivariate predictors of Class II dnDSA. HLA‐DR and DQ epitope matching outperforms traditional low‐resolution antigen‐based matching and has the potential to minimize the risk of de novo Class II DSA development, thereby improving long‐term graft outcome.

Despite more than two decades of use, the optimal maintenance dose of tacrolimus for kidney transplant recipients is unknown. We hypothesized that HLA class II donor-specific antibody (DSA) development correlates with tacrolimus trough levels and the recipient's individualized alloimmune risk determined by HLA-DR/DQ epitope mismatch. A cohort of 596 renal transplant recipients with 50,011 serial tacrolimus trough levels had HLA-DR/DQ eplet mismatch determined using HLAMatchmaker software. We analyzed the frequency of tacrolimus trough levels below a series of thresholds <6 ng/ml and the mean tacrolimus levels before DSA development in the context of HLA-DR/DQ eplet mismatch. HLA-DR/DQ eplet mismatch was a significant multivariate predictor ofDSA development. Recipients treated with a cyclosporin regimen had a 2.7-fold higher incidence of DSA development than recipients on a tacrolimus regimen. Recipients treated with tacrolimus who developed HLA-DR/DQDSA had a higher proportion of tacrolimus trough levels <5 ng/ml, which continued to be significant after adjustment for HLA-DR/DQ eplet mismatch. Mean tacrolimus trough levels in the 6 months before DSA development were significantly lower than the levels>6 months before DSA development in the same patients. Recipients with a high-risk HLA eplet mismatch score were less likely to tolerate low tacrolimus levels without developingDSA. We conclude that HLA-DR/DQ eplet mismatch and tacrolimus trough levels are independent predictors of DSA development. Recipients with high HLA alloimmune risk should not target tacrolimus levels<5 ng/ml unless essential, and monitoring for DSA may be advisable in this setting.

Abstract. At present, the diagnosis of renal allograft rejection requires a renal biopsy. Clinical management of renal transplant patients would be improved by the development of noninvasive markers of rejection that can be measured frequently. This study sought to determine whether such candidate proteins can be detected in urine using mass spectrometry. Four patient groups were rigidly defined on the basis of allograft function, clinical course, and allograft biopsy result: acute clinical rejection group (n ϭ 18), stable transplant group (n ϭ 22), acute tubular necrosis group (n ϭ 5), and recurrent (or de novo) glomerulopathy group (n ϭ 5). Urines collected the day of the allograft biopsy were analyzed by mass spectrometry. As a normal control group, 28 urines from healthy individuals were analyzed the identical manner, as well as 5 urines from non-transplanted patients with lower urinary tract infection. Furthermore, sequential urine analysis was performed in patients in the acute clinical rejection and the stable transplant group. Three prominent peak clusters were found in 17 of 18 patients (94%) with acute rejection episodes, but only in 4 of 22 patients (18%) without clinical and histologic evidence for rejection and in 0 of 28 normal controls (P Ͻ 0.001). In addition, the presence or absence of these peak clusters correlated with the clinicopathologic course in most patients. Acute tubular necrosis, glomerulopathies, lower urinary tract infection, and cytomegalovirus viremia were not confounding variables. In conclusion, proteomic technology together with stringent definition of patient groups can detect urine proteins associated with acute renal allograft rejection. Identification of these proteins may prove useful as non-invasive diagnostic markers for rejection and the development of novel therapeutic agents.