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

Association of HLA B- and T-cell molecular mismatches with HLA antibodies, rejection, and graft survival in pediatric kidney transplantation

BACKGROUND

Optimizing graft survival and diminishing human leukocyte antigen (HLA) sensitization are essential for pediatric kidney transplant recipients. More precise HLA matching predicting epitope mismatches could reduce alloreactivity. We investigated the association of predicted HLA B- and T-cell molecular mismatches with the formation of de novo donor-specific antibodies, HLA antibodies, rejection, and graft survival.

METHODS

Forty-nine pediatric kidney transplant recipients transplanted from 2009 to 2020 were retrospectively studied. Donors and recipients were high-resolution HLA typed, and recipients were screened for HLA antibodies posttransplant. HLA-EMMA (HLA Epitope MisMatch Algorithm) and PIRCHE-II (Predicted Indirectly ReCognizable HLA Epitopes) predicted the molecular mismatches. The association of molecular mismatches and the end-points was explored with logistic regression.

RESULTS

Five recipients (11%) developed de novo donor-specific antibodies. All five had de novo donor-specific antibodies against HLA class II, with four having HLA-DQ antibodies. We found no associations between PIRCHE-II or HLA-EMMA with de novo donor-specific antibodies, HLA sensitization, graft loss, or rejection. However, we did see a tendency towards an increased odds ratio in PIRCHE-II predicting de novo donor-specific antibodies formation, with an odds ratio of 1.12 (95% CI: 0.99; 1.28) on HLA class II.

CONCLUSION

While the study revealed no significant associations between the number of molecular mismatches and outcomes, a notable trend was observed - indicating a reduced risk of dnDSA formation with improved molecular match. It is important to acknowledge, however, that the modest population size and limited observed outcomes preclude us from making definitive conclusions.

Implications of MHC-restricted immunopeptidome in transplantation

The peptide presentation by donor and recipient major histocompatibility complex (MHC) molecules is the major driver of T-cell responses in transplantation. In this review, we address an emerging area of interest, the application of immunopeptidome in transplantation, and describe the potential opportunities that exist to use peptides for targeting alloreactive T cells. The immunopeptidome, the set of peptides presented on an individual's MHC, plays a key role in immune surveillance. In transplantation, the immunopeptidome is heavily influenced by MHC-derived peptides, delineating a key subset of the diverse peptide repertoire implicated in alloreactivity. A better understanding of the immunopeptidome in transplantation has the potential to open up new approaches to identify, characterize, longitudinally quantify, and therapeutically target donor-specific T cells and ultimately support more personalized immunotherapies to prevent rejection and promote allograft tolerance.

Advancing precision in histocompatibility and immunogenetics: a comprehensive review of the UCLA exchange program

Precise typing of human leukocyte antigens (HLA) is crucial for clinical hematopoietic stem cell and solid organ transplantations, transfusion medicine, HLA-related disease association, and drug hypersensitivity analysis. The UCLA Cell Exchange program has played a vital role in providing educational and proficiency testing surveys to HLA laboratories worldwide for the past 5 decades. This article highlights the significant contribution of the UCLA Cell and DNA Exchange Programs in advancing HLA antibody testing, genotyping, crossmatches, and, more recently, virtual crossmatches. Additionally, we discuss future directions of the UCLA Cell Exchange program to support histocompatibility testing to adapt to the fast-evolving field of immunotherapy, tolerance and xenotransplantation.

Belatacept with time-limited tacrolimus coimmunosuppression modifies the 3-year risk of eplet mismatch in kidney transplantation

Solid organ transplant donor-recipient eplet mismatch has been correlated with donor-specific antibody (DSA) formation, antibody-mediated rejection, and overall rejection rates. However, studies have been predominantly in patients on tacrolimus-based immunosuppression regimens and have not fully explored differences in ethnically and racially diverse populations. Evidence indicates that patients on belatacept have lower rates of DSA formation, suggesting mediation of the immunogenicity of mismatched human leukocyte antigen polymorphisms. We performed a retrospective, single-center analysis of class II eplet disparity in a cohort of kidney transplant recipients treated using belatacept with tacrolimus induction (Bela/TacTL) or tacrolimus regimens between 2016 and 2019. Bela/TacTL (n = 294) and tacrolimus (n = 294) cohorts were propensity score-matched with standardized difference <0.15. Single-molecule eplet risk level was associated with immune event rates for both groups. In Cox regression analysis stratified by eplet risk level, Bela/TacTL immunosuppression was associated with a decreased rate of DSA (hazard ratio [HR] = 0.4), antibody-mediated rejection (HR = 0.2), and rejection (HR = 0.45). In the low-risk group, cumulative graft failure was lower for patients on Bela/TacTL (P < .02). Analysis of eplet mismatch burden may be a useful adjunct in identifying high-risk populations with increased immunosuppression requirements and should encourage the design of allocation rules to incentivize lower-risk pairings without negatively impacting equity in access.

Donor-Derived Cell-Free DNA at 1 Month after Kidney Transplantation Relates to HLA Class II Eplet Mismatch Load

Kidney transplantation is the preferred therapeutic option for end-stage renal disease; however, the alloimmune response is still the leading cause of renal allograft failure. To better identify immunologic disparities in order to evaluate HLA compatibility between the donor and the recipient, the concept of eplet load has arisen. Regular kidney function monitoring is essential for the accurate and timely diagnosis of allograft rejection and the appropriate treatment. Donor-derived cell-free DNA (dd-cfDNA) has been proposed as a potential biomarker of acute rejection and graft failure in kidney transplantation. The proportion of plasma dd-cfDNA was determined in forty-two kidney patients at 1 month after transplantation. A total of eleven (26.2%) patients had a dd-cfDNA proportion of ≥1.0%. The only pretransplant variable related to dd-cfDNA > 1.0% was the HLA class II eplet mismatch load, mainly the HLA-DQB1 eplet mismatch load. Furthermore, dd-cfDNA was able to discriminate the patients with antibody-mediated rejection (AbMR) (AUC 87.3%), acute rejection (AUC 78.2%), and troubled graft (AUC 81.4%). Increased dd-cfDNA levels were associated with kidney allograft deterioration, particularly rejection, as well as a greater HLA class II eplet mismatch load. Consequently, combining dd-cfDNA determination and HLA eplet mismatch load calculation should improve the assessment of the risk of short- and long-term allograft damage.

Adding epitope compatibility to deceased donor kidney allocation criteria: recommendations from a pan-Canadian online public deliberation

BACKGROUND

The widening supply-demand imbalance for kidneys necessitates finding ways to reduce rejection and improve transplant outcomes. Human leukocyte antigen (HLA) epitope compatibility between donor and recipient may minimize premature graft loss and prolong survival, but incorporating this strategy to deceased donor allocation criteria prioritizes transplant outcomes over wait times. An online public deliberation was held to identify acceptable trade-offs when implementing epitope compatibility to guide Canadian policymakers and health professionals in deciding how best to allocate kidneys fairly.

METHODS

Invitations were mailed to 35,000 randomly-selected Canadian households, with over-sampling of rural/remote locations. Participants were selected for socio-demographic diversity and geographic representation. Five two-hour online sessions were held from November-December 2021. Participants received an information booklet and heard from expert speakers prior to deliberating on how to fairly implement epitope compatibility for transplant candidates and governance issues. Participants collectively generated and voted on recommendations. In the final session, kidney donation and allocation policymakers engaged with participants. Sessions were recorded and transcribed.

RESULTS

Thirty-two individuals participated and generated nine recommendations. There was consensus on adding epitope compatibility to the existing deceased donor kidney allocation criteria. However, participants recommended including safeguards/flexibility around this (e.g., mitigating declining health). They called for a transition period to epitope compatibility, including an ongoing comprehensive public education program. Participants unanimously recommended regular monitoring and public sharing of epitope-based transplant outcomes.

CONCLUSIONS

Participants supported adding epitope compatibility to kidney allocation criteria, but advised safeguards and flexibility around implementation. These recommendations provide guidance to policymakers about incorporating epitope-based deceased donor allocation criteria.

Molecular HLA mismatching for prediction of primary humoral alloimmunity and graft function deterioration in paediatric kidney transplantation

Introduction

Rejection remains the main cause of allograft failure in paediatric kidney transplantation and is driven by donor-recipient HLA mismatching. Modern computational algorithms enable assessment of HLA mismatch immunogenicity at the molecular level (molecular-mismatch, molMM). Whilst molMM has been shown to correlate with alloimmune outcomes, evidence demonstrating improved prediction performance against traditional antigen mismatching (antMM) is lacking.

Methods

We analysed 177 patients from the CERTAIN registry (median follow-up 4.5 years). molMM scores included Amino-Acid-Mismatch-Score (AAMS), Electrostatic-Mismatch-Score (EMS3D) and netMHCIIpan (netMHC1k: peptide binding affinity ≤1000 nM; netMHC: binding affinity ≤500 nM plus rank <2%). We stratified patients into high/low-risk groups based on risk models of DSA development.

Results

Donor-specific HLA antibodies (DSA) predominantly targeted the highest scoring molMM donor antigen within each HLA locus. MolMM scores offered superior discrimination versus antMM in predicting de novo DSA for all HLA loci; the EMS3D algorithm had particularly consistent performance (area under the receiver operating characteristic curve (AUC) >0.7 for all HLA loci vs. 0.52-0.70 for antMM). ABMR (but not TCMR) was associated with HLA-DQ molMM scores (AAMS, EMS3D and netMHC). Patients with high-risk HLA-DQ molMM had increased risk of graft function deterioration (50% reduction in baseline eGFR (eGFR50), adjusted HR: 3.5, 95% CI 1.6-8.2 high vs. low EMS3D). Multivariable modelling of the eGFR50 outcome using EMS3D HLA-DQ stratification showed better discrimination (AUC EMS3D vs. antMM at 2 years: 0.81 vs. 0.77, at 4.5 years: 0.72 vs. 0.64) and stratified more patients into the low-risk group, compared to traditional antMM.

Conclusion

Molecular mismatching was superior to antigen mismatching in predicting humoral alloimmunity. Molecular HLA-DQ mismatching appears to be a significant prognostic factor for graft function deterioration in paediatric kidney transplantation.

Epitope mismatch at HLA-DRB1 associates with reduced relapse risk in cord blood transplant for standard-risk hematological malignancy

BACKGROUND

Cord blood transplantation (CBT) is an attractive therapeutic option for patients with hematological malignancies. CBT tolerates HLA mismatches between donors and recipients, but which HLA mismatches generate graft-versus-tumor (GVT) effects is unknown.

OBJECTIVE

Given that HLA molecules contain epitopes comprising polymorphic amino acids that determine their immunogenicity, we investigated associations between epitope-level HLA mismatches and relapse following single-unit CBT.

STUDY DESIGN

A total of 492 patients with hematological malignancies who received single unit, T cell replete CBT were included in this multi-center retrospective study. HLA epitope mismatches (EM) were quantified using HLA matchmaker software from donor and patient HLA-A, B, C and DRB1 allele data. Patients were dichotomized by median EM value and divided into groups transplanted in complete/partial remission (standard stage: 62.4%) and others (advanced stage: 37.6%).

RESULTS

Median EM numbers in the graft-versus-host direction (GVH-EM) at HLA-class I and HLA-DRB1 were 3 (range, 0-16) and 1 (range, 0-7), respectively. Higher HLA-class I GVH-EM increased non-relapse mortality (NRM) in the advanced stage group (adjusted hazard ratio [HR], 2.12; p=0.021), with no significant advantage for relapse in either stage. On the other hand, higher HLA-DRB1 GVH-EM was associated with better disease-free survival in the standard stage group (adjusted HR, 0.63; p=0.020), which was attributed to lower relapse risk (adjusted HR, 0.46; p=0.014). These associations were also observed even within HLA-DRB1 allele-mismatched transplants in the standard stage group, indicating that EM might have impacts on relapse risk independently of allele mismatch. High HLA-DRB1 GVH-EM did not increase NRM in either stage.

CONCLUSIONS

High HLA-DRB1 GVH-EM may lead to potent GVT effects and favorable prognosis following CBT especially in the patients transplanted in the standard stage. This approach may facilitate appropriate unit selection and improve the overall prognosis of patients with hematological malignancies who receive CBT.

HLA-DPB1 molecular mismatches are risk factors for acute rejection and low 5-year graft function in first kidney transplants

The study aimed to investigate the impact of HLA-DPB1 allelic and molecular mismatches on the occurrence of acute rejection (AR) and low 5-year graft function (5Y-GF) in first kidney transplant (KT) recipients. This is a single center retrospective study of 130 deceased donor KT recipients transplanted between 2014 and 2016. HLA-DPB1 allelic MM and the following molecular MM (mMM) were analyzed: expression MM with the high expression G allele in the donor; T cell epitope MM (TCE MM); epitope MM (EMM), considering all six hypervariable regions (EMM-ABCDEF HVR), or only ABEF regions (EMM-ABEF HVR); eplet MM (EpMM); antibody-verified eplet MM (AbVer EpMM); and solvent accessible amino acid MM (SAMM). There was no association of allelic MM with AR or 5Y-GF. The variables independently associated (Cox regression analyses) with AR were high donor final creatinine, nonpermissive TCE MM, ABCDEF EMM load ≥6, EpMM load ≥6; SAMM load ≥5, and AbVer EpMM load ≥3. No association between any HLA-DPB1 mMM and 5Y-GF was observed when all 130 transplant recipients were considered. However, when transplants from expanded criteria donors were excluded, independent associations were detected (logistic regression analyses) with AbVerEpMM load ≥2, SAMM load ≥7, cerebro-vascular death, donor age, and AR. To our knowledge, this is the first study that shows that some HLA-DPB1 mMM are associated with AR and low 5Y-GF in a population of exclusively first kidney transplant recipients.

Can We Use Eplets (or Molecular) Mismatch Load Analysis to Improve Organ Allocation? The Hope and the Hype

In recent years, there have been calls for implementation of "epitope matching" in deceased-donor organ allocation policies (later changed to "eplet matching"). Emerging data indeed support the use of molecular mismatch load analysis in specific patient groups, with the objective of posttransplant stratification into different treatment arms. For this purpose, the expectation is to statistically categorize patients as low- or high-immune-risk. Importantly, these patients will continue to be monitored' and their risk category, as well as their management, can be adjusted according to on-going findings. However, when discussing deceased donor organ allocation and matching algorithms, where the decision is not modifiable and has lasting impact on outcomes, the situation is fundamentally different. The goal of changing allocation schemes is to achieve the best possible HLA compatibility between donor and recipient. Immunologically speaking, this is a very different objective. For this purpose, the specific interplay of immunogenicity between the donor and any potential recipient must be understood. In seeking compatibility, the aim is not to redefine matching but to identify those mismatches that are "permissible" or' in other words, less immunogenic. In our eagerness to improve transplant outcome, unfortunately, we have conflated the hype with the hope. Terminology is used improperly, and new terms are created in the process with no sufficient support. Here, we call for a cautious evaluation of baseline assumptions and a critical review of the evidence to minimize unintended consequences.

Sensitization in transplantation: Assessment of Risk 2022 Working Group Meeting Report

The Sensitization in Transplantation: Assessment of Risk workgroup is a collaborative effort of the American Society of Transplantation and the American Society of Histocompatibility and Immunogenetics that aims at providing recommendations for clinical testing, highlights gaps in current knowledge, and proposes areas for further research to enhance histocompatibility testing in support of solid organ transplantation. This report provides updates on topics discussed by the previous Sensitization in Transplantation: Assessment of Risk working groups and introduces 2 areas of exploration: non-human leukocyte antigen antibodies and utilization of human leukocyte antigen antibody testing measurement to evaluate the efficacy of antibody-removal therapies.

Progress in kidney transplantation: The role for systems immunology

The development of systems biology represents an immense breakthrough in our ability to perform translational research and deliver personalized and precision medicine. A multidisciplinary approach in combination with use of novel techniques allows for the extraction and analysis of vast quantities of data even from the volume and source limited samples that can be obtained from human subjects. Continued advances in microfluidics, scalability and affordability of sequencing technologies, and development of data analysis tools have made the application of a multi-omics, or systems, approach more accessible for use outside of specialized centers. The study of alloimmune and protective immune responses after solid organ transplant offers innumerable opportunities for a multi-omics approach, however, transplant immunology labs are only just beginning to adopt the systems methodology. In this review, we focus on advances in biological techniques and how they are improving our understanding of the immune system and its interactions, highlighting potential applications in transplant immunology. First, we describe the techniques that are available, with emphasis on major advances that allow for increased scalability. Then, we review initial applications in the field of transplantation with a focus on topics that are nearing clinical integration. Finally, we examine major barriers to adapting these methods and discuss potential future developments.

Eplet-Predicted Antigens: An Attempt to Introduce Eplets into Unacceptable Antigen Determination and Calculated Panel-Reactive Antibody Calculation Facilitating Kidney Allocation

(1) Calculated panel-reactive antibody (CPRA) is a measure of sensitization based on unacceptable antigens (UAs). Determination of UAs based on single-antigen bead assays at allele or antigen levels may be inappropriate. We aimed to introduce eplets for better assessment of sensitization; (2) 900 recipients and 1427 donors were enrolled for candidate or donor pools, respectively. Eplets were from the HLA Epitope Registry. UAs were determined by anti-HLA antibodies identified using LIFECODES Single Antigen (LSA) kits. CPRA values were calculated using a simplified method of donor filtering; (3) HLA antigens containing all eplets of an HLA antigen in LSA kits (LSA antigen) were defined as eplet-predicted (EP) antigens, the reactivity of which could be predicted by that LSA antigen. High reactivity concordance was found between LSA and EP antigens. More HLA antigens were covered by EP antigens in the population than LSA antigens. CPRA values at the EP level were higher than at the allele level and lower than at the antigen level. The EP antigens facilitated UA determination for non-LSA antigens and avoided acute rejection; (4) UA determination using EP antigens can lead to more accurate assessment of sensitization, enabling a high probability of compatible organs and a low risk of adverse outcomes.

Dissecting the impact of molecular T-cell HLA mismatches in kidney transplant failure: A retrospective cohort study

Introduction

Kidney transplantation is the optimal treatment in end-stage kidney disease, but de-novo donor specific antibody development continues to negatively impact patients undergoing kidney transplantation. One of the recent advances in solid organ transplantation has been the definition of molecular mismatching between donors and recipients' Human Leukocyte Antigens (HLA). While not fully integrated in standard clinical care, cumulative molecular mismatch at the level of eplets (EMM) as well as the PIRCHE-II score have shown promise in predicting transplant outcomes. In this manuscript, we sought to study whether certain T-cell molecular mismatches (TcEMM) were highly predictive of death-censored graft failure (DCGF).

Methods

We studied a retrospective cohort of kidney donor:recipient pairs from the Scientific Registry of Transplant Recipients (2000-2015). Allele level HLA-A, B, C, DRB1 and DQB1 types were imputed from serologic types using the NMDP algorithm. TcEMMs were then estimated using the PIRCHE-II algorithm. Multivariable Accelerated Failure Time (AFT) models assessed the association between each TcEMM and DCGF. To discriminate between TcEMMs most predictive of DCGF, we fit multivariable Lasso penalized regression models. We identified co-expressed TcEMMs using weighted correlation network analysis (WGCNA). Finally, we conducted sensitivity analyses to address PIRCHE and IMGT/HLA version updates.

Results

A total of 118,309 donor:recipient pairs meeting the eligibility criteria were studied. When applying the PIRCHE-II algorithm, we identified 1,935 distinct TcEMMs at the population level. A total of 218 of the observed TcEMM were independently associated with DCGF by AFT models. The Lasso penalized regression model with post selection inference identified a smaller subset of 86 TcEMMs (56 and 30 TcEMM derived from HLA Class I and II, respectively) to be highly predictive of DCGF. Of the observed TcEMM, 38.14% appeared as profiles of highly co-expressed TcEMMs. In addition, sensitivity analyses identified that the selected TcEMM were congruent across IMGT/HLA versions.

Conclusion

In this study, we identified subsets of TcEMMs highly predictive of DCGF and profiles of co-expressed mismatches. Experimental verification of these TcEMMs determining immune responses and how they may interact with EMM as predictors of transplant outcomes would justify their consideration in organ allocation schemes and for modifying immunosuppression regimens.

Snowflake epitope matching correlates with child-specific antibodies during pregnancy and donor-specific antibodies after kidney transplantation

Development of donor-specific human leukocyte antigen (HLA) antibodies (DSA) remains a major risk factor for graft loss following organ transplantation, where DSA are directed towards patches on the three-dimensional structure of the respective organ donor's HLA proteins. Matching donors and recipients based on HLA epitopes appears beneficial for the avoidance of DSA. Defining surface epitopes however remains challenging and the concepts underlying their characterization are not fully understood. Based on our recently implemented computational deep learning pipeline to define HLA Class I protein-specific surface residues, we hypothesized a correlation between the number of HLA protein-specific solvent-accessible interlocus amino acid mismatches (arbitrarily called Snowflake) and the incidence of DSA. To validate our hypothesis, we considered two cohorts simultaneously. The kidney transplant cohort (KTC) considers 305 kidney-transplanted patients without DSA prior to transplantation. During the follow-up, HLA antibody screening was performed regularly to identify DSA. The pregnancy cohort (PC) considers 231 women without major sensitization events prior to pregnancy who gave live birth. Post-delivery serum was screened for HLA antibodies directed against the child's inherited paternal haplotype (CSA). Based on the involved individuals' HLA typings, the numbers of interlocus-mismatched antibody-verified eplets (AbvEPS), the T cell epitope PIRCHE-II model and Snowflake were calculated locus-specific (HLA-A, -B and -C), normalized and pooled. In both cohorts, Snowflake numbers were significantly elevated in recipients/mothers that developed DSA/CSA. Univariable regression revealed significant positive correlation between DSA/CSA and AbvEPS, PIRCHE-II and Snowflake. Snowflake numbers showed stronger correlation with numbers of AbvEPS compared to Snowflake numbers with PIRCHE-II. Our data shows correlation between Snowflake scores and the incidence of DSA after allo-immunization. Given both AbvEPS and Snowflake are B cell epitope models, their stronger correlation compared to PIRCHE-II and Snowflake appears plausible. Our data confirms that exploring solvent accessibility is a valuable approach for refining B cell epitope definitions.

Snowflake: A deep learning-based human leukocyte antigen matching algorithm considering allele-specific surface accessibility

Histocompatibility in solid-organ transplantation has a strong impact on long-term graft survival. Although recent advances in matching of both B-cell epitopes and T-cell epitopes have improved understanding of allorecognition, the immunogenic determinants are still not fully understood. We hypothesized that HLA solvent accessibility is allele-specific, thus supporting refinement of HLA B-cell epitope prediction. We developed a computational pipeline named Snowflake to calculate solvent accessibility of HLA Class I proteins for deposited HLA crystal structures, supplemented by constructed HLA structures through the AlphaFold protein folding predictor and peptide binding predictions of the APE-Gen docking framework. This dataset trained a four-layer long short-term memory bidirectional recurrent neural network, which in turn inferred solvent accessibility of all known HLA Class I proteins. We extracted 676 HLA Class-I experimental structures from the Protein Data Bank and supplemented it by 37 Class-I alleles for which structures were predicted. For each of the predicted structures, 10 known binding peptides as reported by the Immune Epitope DataBase were rendered into the binding groove. Although HLA Class I proteins predominantly are folded similarly, we found higher variation in root mean square difference of solvent accessibility between experimental structures of different HLAs compared to structures with identical amino acid sequence, suggesting HLA’s solvent accessible surface is protein specific. Hence, residues may be surface-accessible on e.g. HLA-A*02:01, but not on HLA-A*01:01. Mapping these data to antibody-verified epitopes as defined by the HLA Epitope Registry reveals patterns of (1) consistently accessible residues, (2) only subsets of an epitope’s residues being consistently accessible and (3) varying surface accessibility of residues of epitopes. Our data suggest B-cell epitope definitions can be refined by considering allele-specific solvent-accessibility, rather than aggregating HLA protein surface maps by HLA class or locus. To support studies on epitope analyses in organ transplantation, the calculation of donor-allele-specific solvent-accessible amino acid mismatches was implemented as a cloud-based web service.

Pediatric Kidney Transplantation-Can We Do Better? The Promise and Limitations of Epitope/Eplet Matching

Kidney transplant is the optimal treatment for end-stage kidney disease as it offers significant survival and quality of life advantages over dialysis. While recent advances have significantly improved early graft outcomes, long-term overall graft survival has remained largely unchanged for the last 20 years. Due to the young age at which children receive their first transplant, most children will require multiple transplants during their lifetime. Each subsequent transplant becomes more difficult because of the development of de novo donor specific HLA antibodies (dnDSA), thereby limiting the donor pool and increasing mortality and morbidity due to longer time on dialysis awaiting re-transplantation. Secondary prevention of dnDSA through increased post-transplant immunosuppression in children is constrained by a significant risk for viral and oncologic complications. There are currently no FDA-approved therapies that can meaningfully reduce dnDSA burden or improve long-term allograft outcomes. Therefore, primary prevention strategies aimed at reducing the risk of dnDSA formation would allow for the best possible long-term allograft outcomes without the adverse complications associated with over-immunosuppression. Epitope matching, which provides a more nuanced assessment of immunological compatibility between donor and recipient, offers the potential for improved donor selection. Although epitope matching is promising, it has not yet been readily applied in the clinical setting. Our review will describe current strengths and limitations of epitope matching software, the evidence for and against improved outcomes with epitope matching, discussion of eplet load vs. variable immunogenicity, and conclude with a discussion of the delicate balance of improving matching without disadvantaging certain populations.

Improving Access to HLA-Matched Kidney Transplants for African American Patients

Introduction

Kidney transplants fail more often in Black than in non-Black (White, non-Black Hispanic, and Asian) recipients. We used the estimated physicochemical immunogenicity for polymorphic amino acids of donor/recipient HLAs to select weakly immunogenic kidney transplants for Black vs. White or non-Black patients.

Methods

OPTN data for 65,040 donor/recipient pairs over a 20-year period were used to calculate the individual physicochemical immunogenicity by hydrophobic, electrostatic and amino acid mismatch scores (HMS, EMS, AMS) and graft-survival outcomes for Black vs. White or vs. non-Black recipients, using Kaplan-Meier survival and Cox regression analyses. Simulations for re-matching recipients with donors were based on race-adjusted HMS thresholds with clinically achievable allocations.

Results

The retrospective median kidney graft survival was 12.0 years in Black vs. 18.6 years in White (6.6-year difference; p>0.001) and 18.4 years in non-Black (6.4-year difference; p>0.01) recipients. Only 0.7% of Blacks received transplants matched at HLA-A/B/DR/DQ (HMS=0) vs. 8.1% in Whites (p<0.001). Among fully matched Blacks (HMS=0), graft survival was 16.1-years and in well-matched Blacks (HMS ≤ 3.0) it was 14.0-years. Whites had 21.6-years survival at HMS ≤ 3.0 and 18.7-years at HMS ≤ 7.0 whereas non-Blacks had 22.0-year at HMS ≤ 3.0 and 18.7-year at HMS ≤ 7.0, confirming that higher HMS thresholds produced excellent survival. Simulation of ABO-compatible donor-recipient pairs using race-adjusted HMS thresholds identified weakly immunogenic matches at HMS=0 for 6.1% Blacks and 18.0% at HMS ≤ 3.0. Despite prioritizing Black patients, non-Black patients could be matched at the same level as in current allocation (47.0% vs 56.5%, at HMS ≤ 7.0).

Conclusions

Race-adjusted HMS (EMS, AMS)-based allocation increased the number of weakly immunogenic donors for Black patients, while still providing excellent options for non-Black recipients.

hlaR: A rapid and reproducible tool to identify eplet mismatches between transplant donors and recipients

Eplet mismatch load, both overall and at the single molecule level, correlates with transplant recipient outcomes. However, precise eplet assessment requires high-resolution HLA typing of both the donor and recipient. Anything less than high-resolution typing requires imputation of HLA types. The currently available methods to identify eplet mismatch are both tedious and demanding. Therefore, we developed a software package and user-friendly web application (hlaR), that simplifies the workflow of eplet analysis, provides functions to impute high-resolution from low-resolution data and calculates both overall and single molecule eplet mismatch for single or multiple donor recipient pairs. Compared to manual assessments using currently available tools (namely, HLAMatchMaker), hlaR resulted in only minimal discrepancy in eplet mismatches (mean absolute difference of 0.56 for class I and 0.86 for class II for unique sum across loci). Additionally, output of the single molecule eplet function compared well to manual calculation, with an average single antigen count increase of 0.19. Importantly, the hlaR tool permits rapid and reproducible imputation and eplet mismatch including comparison between eplet reference tables (e.g. HLAMatchMaker version 2 or 3). Users can import data from a spreadsheet rather than relying on keystroke entry of individual donor and recipient data, thus reducing the risk of data entry errors. The resulting improved scalability of the hlaR tool is highlighted by plotting analysis time against the size of the input dataset. The new hlaR tool can provide eplet mismatch data with a streamlined workflow. With decreased effort from the end user, eplet matching and mismatch load data can be further incorporated into both research and clinical use.

A Comprehensive Evaluation of the Antibody-Verified Status of Eplets Listed in the HLA Epitope Registry

Matching strategies based on HLA eplets instead of HLA antigens in solid organ transplantation may not only increase the donor pool for highly sensitized patients, but also decrease the incidence of de novo donor-specific antibody formation. However, since not all eplets are equally capable of inducing an immune response, antibody verification is needed to confirm their ability to be bound by antibodies, such that only clinically relevant eplets are considered. The HLA Epitope Registry has documented all theoretically defined HLA eplets along with their antibody verification status and has been the foundation for many clinical studies investigating eplet mismatch in transplantation. The verification methods for eplets in the Registry range from polyclonal sera from multi- and uni-parous women to murine and human monoclonal antibodies (mAbs), and antibodies purified by adsorption and elution from sera of HLA immunized individuals. The classification of antibody verification based on different methods for validation is problematic, since not all approaches represent the same level of evidence. In this study, we introduce a classification system to evaluate the level of evidence for the antibody-verified status of all eplets in the HLA Epitope Registry. We demonstrate that for a considerable number of eplets, the antibody-verified status is solely based on polyclonal serum reactivity of multiparous women or on reactivity of murine mAbs. Furthermore, we noted that a substantial proportion of patient sera analyses and human mAb data presented in the HLA Epitope Registry Database has never been published in a peer-reviewed journal. Therefore, we tested several unpublished human HLA-specific mAbs by luminex single antigen beads assay to analyze their HLA reactivity for eplet antibody verification. Although the majority of analyzed mAbs indeed verified their assigned eplets, this was not the case for a number of eplets. This comprehensive overview of evidence for antibody verification of eplets in the HLA Epitope Registry is instrumental for future investigations towards eplet immunogenicity and clinical studies considering antibody-verified eplet mismatch in transplantation and warrants further standardization of antibody verification using high quality data.

Implementation of molecular matching in transplantation requires further characterization of both immunogenicity and antigenicity of individual HLA epitopes

Over the past decade, high HLA epitope mismatch scores have been associated with inferior transplant outcomes using several tools, of which HLAMatchmaker is most well-known. This software uses theoretically defined polymorphic amino acid configurations, called eplets, for HLA compatibility analysis. Although consideration of eplet mismatch loads has potential for immunological risk stratification of transplant patients, the use of eplet matching in organ allocation algorithms is hindered by lacking knowledge of the immunogenicity of individual eplets, and the possibility that single mismatched amino acids, rather than complete eplets, are responsible for HLA antibody induction. There are several approaches to define eplet immunogenicity, such as antibody verification of individual eplets, and data-driven approaches using large datasets that correlate specific eplet mismatches to donor specific antibody formation or inferior transplant outcomes. Data-driven approaches can also be used to define whether single amino acid mismatches may be more informative than eplet mismatches for predicting HLA antibody induction. When using epitope knowledge for the assignment of unacceptable antigens, it important to realize that alleles sharing an eplet to which antibodies have formed are not automatically all unacceptable since multiple contact sites determine the binding strength and thus biological function and pathogenicity of an antibody, which may differ between reactive alleles. While the future looks bright for using HLA epitopes in clinical decision making, major steps need to be taken to make this a clinical reality.

Role of HLA molecular mismatch in clinical practice

To date, traditional pre-transplant risk factors have failed to provide accurate risk stratification in transplantation. As a result, the practice of precision medicine remains elusive, resulting in a one-size-fits-all therapeutic approach for most patients. However, recent advancements in the understanding of HLA molecules at the molecular level have revitalized interest in HLA mismatch assessment. This review discusses HLA molecular mismatch as a potential prognostic and predictive biomarker available at the time of transplantation and answers some of the common questions and critiques of this approach. We highlight the retrospective data that supports single molecule risk categorization and explore the next steps required to evaluate its potential in clinical practice.

Not all eplet mismatches are created equal - A cohort study illustrating implications to long-term graft outcomes

We assessed implications of various eplet-compatibility strategies to death-censored graft failure (DCGF), defined as return to dialysis or re-transplantation, in a base-case scenario from the Scientific Registry of Transplant Recipients. To inform personalized care, we evaluated how recipient, donor, and transplant characteristics affect DCGF by ascending categories of eplet mismatches (EMM), and derived adjusted hazard ratios (HR). The base-case analysis demonstrated 15-year estimated survival probabilities of 77.1%, 75.4%, 73.6%, 72.2%, 74.9%, and 73.5% for the lowest EMM categories (complete epitype: 0-19, antibody-verified (AbVer) epitype and class II eplets: 0-9, class II AbVer eplets: 0-4, 55 high-risk eplets associated with DCGF: 0-3, and subset of 15 high-risk eplets validated in an independent subcohort: 0 EMM, respectively). Beyond the lowest EMM categories, the Epi15 strategy allowed better differentiation of change in DCGF risk per EMM, with additional 5.2%, 3.9% and 4.1% decrease in estimated graft survival for each additional EMM (1, 2, and ≥ 3, respectively). Recipients < 25 years, donors > 55 years, and immunosuppression regimens excluding calcineurin inhibitors and steroids, demonstrated higher HR for DCGF. High-risk EMM allowed better differentiation between DCGF probabilities per EMM, suggesting that recipients at higher risk for graft failure could benefit most from allocation schemes ensuring compatibility on these eplets.