Epitope-Based HLA Matching: A Useful Strategy With Many Shortcomings to Overcome

Role of HLA in cardiothoracic transplantation

In current clinical practice, transplant clinicians create collaborative working relationships with histocompatibility laboratory scientists to identify the risk of long-term graft failure, which may assist in establishing strategies for treatment and surveillance. Transplant immunology research also focuses on optimizing human leukocyte antibody tissue typing and defines the most effective test for detecting the presence of donor-specific antibodies. Although several studies have been conducted, data on pediatric heart transplant recipients are limited. Epitope load information may be utilized to identify donors with permissible human leukocyte antibody mismatches to increase transplant success. Although current guidelines do not consider human leukocyte antibody epitope-based matching tools, these guidelines could be useful for identifying recipients at a high risk of donor-specific antibody production, which would be appropriate for routine donor-specific antibody screening to initiate early interventions to prevent antibody-mediated rejection. Human leukocyte antibody matching at the epitope level offers an effective approach for identifying acceptable mismatches in sensitized patients and provides information about epitope loads. In the future, eplet matching may be used to define the best immunosuppressive therapy protocol for cardiothoracic organ transplantation. This report provides an overview of the role of human leukocyte antibodies in heart and lung transplantation.

Human leukocyte antigen epitope mismatch loads and the development of de novo donor-specific antibodies in cardiothoracic organ transplantation

De novo donor-specific human leucocyte antigen (HLA) antibodies (dnDSA) are associated with increased risk of rejection and mortality in solid organ transplantation. Such dnDSA is produced in some recipients upon allorecognition of mismatched HLA post-transplant. HLA matching is not currently considered in the allocation of deceased donor hearts and lungs and pre-transplant immunological risk stratification is based entirely on the mean fluorescence intensity (MFI) of circulating donor-directed HLA antibodies. HLA epitope-based matching tools predict B-cell or T-cell HLA epitopes that are present in the donor's HLA but absent in the recipient's HLA. We hypothesized that patients with higher epitope mismatch loads would be at increased risk of dnDSA development. We retrospectively analysed 73 heart and/or lung transplant recipients who were tested for DSA between 2015 and 2020. HLAMatchmaker, PIRCHE-II and HLA epitope mismatch algorithm (HLA-EMMA) were used to calculate eplet mismatch (EpMM) loads, T-cell epitope mismatch (TEpMM) loads and solvent accessible amino acid mismatch (SAMM) loads, respectively. Multivariate analyses showed that HLA-EMMA was the only tool with a significant association between the total score for all HLA loci and dnDSA production [odds ratio (OR) 1.021, 95% confidence interval (CI) 1.003-1.042, p = .0225] though this increased risk was marginal. The majority of dnDSA were directed against HLA-DQ and patients with higher HLA-DQ TEpMM loads (OR = 1.008, CI = 1.002-1.014, p = .007), and HLA-DR+DQ SAMM loads (OR = 1.035, CI = 1.010-1.064, p = .0077) were most at risk of producing dnDSA. We also showed that patients with a risk epitope within the HLA molecule encoded for by HLA-DQA1*05 + HLA-DQB1*02/03:01 were significantly more likely to produce dnDSA. The use of HLA epitope-based matching tools could be used for cardiothoracic transplant risk stratification to enable early intervention and monitoring of patients at increased risk of producing dnDSA.

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.

On Path to Informing Hierarchy of Eplet Mismatches as Determinants of Kidney Transplant Loss

Introduction

To mitigate risks related to human leukocyte antigen (HLA) incompatibility, we assessed whether certain structurally defined HLA targets present in donors but absent from recipients, known as eplet mismatches (EMM), are associated with death-censored graft failure (DCGF).

Methods

We studied a cohort of 118,313 American 0% panel reactive antibodies (PRA) first kidney transplant recipients (2000 to 2015) from the Scientific Registry of Transplant Recipients. Imputed allele-level donor and recipient HLA-A, -B, -C, -DRB1, and -DQB1 genotypes were converted to the repertoire of EMM. We fit survival models for each EMM with significance thresholds corrected for false discovery rate and validated those in an independent PRA > 0% cohort. We conducted network-based analyses to model relationships among EMM and developed models to select the subset of EMM most predictive of DCGF.

Results

Of 412 EMM observed, 119 class I and 118 class II EMM were associated with DCGF. Network analysis showed that although 210 eplets formed profiles of 2 to 12 simultaneously occurring EMMs, 202 were singleton EMMs that were not involved in any profile. A variable selection procedure identified 55 single HLA class I and II EMMs in 70% of the dataset; of those, 15 EMMs (9 singleton and 6 involved in profiles) were predictive of DCGF in the remaining dataset.

Conclusion

Our analysis distinguished increasingly smaller subsets of EMMs associated with increased risk of DCGF. Validation of these EMMs as important predictors of transplant outcomes (in contrast to acceptable EMMs) in datasets with measured allele-level genotypes will support their role as immunodominant EMMs worthy of consideration in organ allocation schemes.

Molecular-level HLA mismatch is associated with rejection and worsened graft survival in heart transplant recipients - a retrospective study

The aim was to evaluate the association of molecular‐level human leukocyte antigen (HLA) mismatching with post‐transplant graft survival, rejection, and cardiac allograft vasculopathy (CAV). We retrospectively analyzed all primary cardiac transplant recipients between 01/1984‐06/2016. 1167 patients fulfilled inclusion criteria and had HLA typing information available. In 312 donor‐recipient pairs, typing at serological split antigen level was available. We used the Epitope MisMatch Algorithm to calculate the number of amino acid differences in antibody‐verified HLA eplets (amino acid mismatch load (AAMM)) between donor and recipient. Patients with a higher HLA‐DR AAMM load had inferior 1‐year graft survival (hazard ratio [HR], 1.14; 95% confidence interval [CI], 1.01–1.28). The HLA‐AB AAMM load showed no impact on graft survival. In the subgroup with available split‐level information, we observed an inferior graft survival for a higher HLA‐DR AAMM load 3 months after transplantation (HR, 1.22; 95% CI, 1.04–1.44) and a higher risk for rejection for an increasing HLA‐AB (HR, 1.70; 95% CI, 1.29–2.24) and HLA‐DR (HR, 1.32; 95% CI, 1.09–1.61) AAMM load. No impact on the development of CAV was found. Molecular‐level HLA mismatch analysis could serve as a tool for risk stratification after heart transplantation and might take us one step further into precision medicine.

Different eplet software programs give discordant and incorrect results: An analysis of HLAMatchmaker vs Fusion Matchmaker Eplet calling software

HLA eplet matching is a novel approach to define acceptable HLA mismatches for transplant recipients. We performed an eplet analysis of three different transplant case-series to determine if the available software programs gave accurate results. Eplet analysis was performed for three different transplant case-series typed by NGS for all HLA class I and II loci. The three different HLA datasets were entered into both the HLAMatchmaker program (v2.1) and OLI Fusion MatchMaker (v4.2) software tools. Eplet results which were discordant were cross referenced against eplet registry and published HLA allele sequence data to determine the correct assignments. The comparison reveals that there was poor concordance between the two eplet programs. Analysis of the same donor/recipient pair often gave rise to different total eplet scores, incorrect eplet mismatches and antibody verification status, and both programs have eplets assigned to incorrect HLA alleles. Overall, the OLI Fusion MatchMaker eplet tool gave more accurate and useful eplet results. Eplet matching is still primarily a research tool. Before eplet matching can enter routine clinical practice further work is required to validate the accuracy of available eplet software programs. Incorrect eplet assignment could have serious adverse consequences in the clinical transplant setting.

PIRCHE-II: an algorithm to predict indirectly recognizable HLA epitopes in solid organ transplantation

Human leukocyte antigen (HLA) mismatches between donors and recipients may lead to alloreactivity after solid organ transplantation. Over the last few decades, our knowledge of the complexity of the HLA system has dramatically increased, as numerous new HLA alleles have been identified. As a result, the likelihood of alloreactive responses towards HLA mismatches after solid organ transplantation cannot easily be assessed. Algorithms are promising solutions to estimate the risk for alloreactivity after solid organ transplantation. In this review, we show that the recently developed PIRCHE-II (Predicted Indirectly ReCognizable HLA Epitopes) algorithm can be used to minimize alloreactivity towards HLA mismatches. Together with the use of other algorithms and simulation approaches, the PIRCHE-II algorithm aims for a better estimated alloreactive risk for individual patients and eventually an improved graft survival after solid organ transplantation.