HLA class II eplet mismatch load improves prediction of dnDSA development after living donor kidney transplantation

HLA Genotype Imputation Results in Largely Accurate Epitope Mismatch Risk Categorization Across Racial Groups

Background

Biomarkers that predict posttransplant alloimmunity could lead to improved long-term graft survival. Evaluation of the number of mismatched epitopes between donor and recipient HLA proteins, termed molecular mismatch analysis, has emerged as an approach to classify transplant recipients as having high, intermediate, or low risk of graft rejection. When high-resolution genotypes are unavailable, molecular mismatch analysis requires algorithmic assignment, or imputation, of a high-resolution genotyping. Although imputation introduces inaccuracies in molecular mismatch analyses, it is unclear whether these inaccuracies would impact the clinical risk assessment for graft rejection.

Methods

Using renal transplant patients and donors from our center, we constructed cohorts of surrogate donor-recipient pairs with high-resolution and low-resolution HLA genotyping that were racially concordant or discordant. We systemically assessed the impact of imputation on molecular mismatch analysis for cohorts of 180-200 donor-recipient pairs for each of 4 major racial groups. We also evaluated the effect of imputation for a racially diverse validation cohort of 35 real-world renal transplant pairs.

Results

In the surrogate donor-recipient cohorts, imputation preserved the molecular mismatch risk category for 90.5%-99.6% of racially concordant donor-recipient pairs and 92.5%-100% of racially discordant pairs. In the validation cohort, which comprised 72% racially discordant pairs, we found that imputation preserved the molecular mismatch risk category for 97.1% of pairs.

Conclusions

Overall, these data demonstrate that imputation preserves the molecular mismatch risk assessment in the vast majority of cases and provides evidence supporting imputation in the performance of molecular mismatch analysis for clinical assessment.

Strategies for choosing the best living donor: A review of the literature and a proposal of a decision-making paradigm

Transplantation remains the gold-standard treatment for pediatric end-stage kidney disease. While living donor transplant is the preferred option for most pediatric patients, it is not the right choice for all. For those who have the option to choose between deceased donor and living donor transplantation, or from among multiple potential living donors, the transplant clinician must weigh multiple dynamic factors to identify the most optimal donor. This review will cover the key considerations when choosing between potential living donors and will propose a decision-making algorithm.

Antibody verification of HLA class I and class II eplets by human monoclonal HLA antibodies

In solid organ transplantation, formation of de novo donor-specific HLA antibodies is induced by mismatched eplets on donor HLA molecules. While several studies have shown a strong correlation between the number of eplet mismatches and inferior outcomes, not every eplet mismatch is immunogenic. Eplets are theoretically defined entities, necessitating formal proof that they can be recognised and bound by antibodies. This antibody verification is pivotal to ensure that clinically relevant eplets are considered in studies on molecular matching. Recombinant human HLA-specific monoclonal antibodies (mAbs) were generated from HLA-reactive B cell clones isolated from HLA immunised individuals using recombinant HLA molecules. Subsequently, the reactivity patterns of the mAbs obtained from single antigen bead assay were analysed using HLA-EMMA software to identify single or configurations of solvent accessible amino acids uniquely present on the reactive HLA alleles and were mapped to eplets. Two HLA class I and seven HLA class II-specific human mAbs were generated from four individuals. Extensive mAb reactivity analysis, led to antibody verification of three HLA-DR-specific eplets, and conversion of five eplets (one HLA-A, one HLA-B, two HLA-DR, and one HLA-DP), from provisionally verified to truly antibody-verified. Finally, one HLA-DQ-specific eplet was upgraded from level A2 to level A1 verification evidence. The generation of recombinant human HLA-specific mAbs with different specificities contributes significantly to the antibody verification of eplets and therefore is instrumental for implementation of eplet matching in the clinical setting.

The Effect of Genetic HLA Matching on Liver Transplantation Outcome: A Systematic Review and Meta-Analysis

Objective

We aim to investigate the effects of genetically based HLA matching on patient and graft survival, and acute and chronic rejection after liver transplantation.

Background

Liver transplantation is a common treatment for patients with end-stage liver disease. In contrast to most other solid organ transplantations, there is no conclusive evidence supporting human leukocyte antigen (HLA) matching for liver transplantations. With emerging alternatives such as transplantation of bankable (stem) cells, HLA matching becomes feasible, which may decrease the need for immunosuppressive therapy and improve transplantation outcomes.

Methods

We systematically searched the PubMed, Embase, and Cochrane databases and performed a meta-analysis investigating the effect of genetic HLA matching on liver transplantation outcomes (acute/chronic rejection, graft failure, and mortality).

Results

We included 14 studies with 2682 patients. HLA-C mismatching significantly increased the risk of acute rejection (full mismatching: risk ratio = 1.90, 95% confidence interval = 1.08 to 3.33, P = 0.03; partial mismatching: risk ratio = 1.33, 95% confidence interval = 1.07 to 1.66, P = 0.01). We did not discern any significant effect of HLA mismatching per locus on acute rejection for HLA-A, -B, -DR, and -DQ, nor on chronic rejection, graft failure, or mortality for HLA-DR, and -DQ.

Conclusions

We found evidence that genetic HLA-C matching reduces the risk of acute rejection after liver transplantation while matching for other loci does not reduce the risk of acute rejection, chronic rejection, graft failure, or mortality.

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.

Combined Analysis of HLA Class II Eplet Mismatch and Tacrolimus Levels for the Prediction of De Novo Donor Specific Antibody Development in Kidney Transplant Recipients

We investigated whether HLA class II eplet mismatch was related to dnDSA development and analyzed its combined impact with tacrolimus levels for kidney transplantation outcomes. A total of 347 kidney transplants were included. HLA Matchmaker was used for the single molecular eplet, total eplet, antibody (Ab)-verified eplet mismatch analyses, and Ab-verified single molecular analysis to identify HLA-DR/DQ molecular thresholds for the risk of dnDSA development. A time-weighted tacrolimus trough level (TAC-C0) of 5 ng/mL and a TAC-C0 time-weighted coefficient variability (TWCV) of 20% were applied to find the combined effects on dnDSA development. A high level of mismatch for single molecular eplet (DQ ≥ 10), total eplet (DQ ≥ 12), Ab-verified eplet (DQ ≥ 4), and Ab-verified single molecular eplet (DQ ≥ 4) significantly correlated with HLA class II dnDSA development. Class II dnDSA developed mostly in patients with low TAC-C0 and high eplet mismatch. In the multivariable analyses, low TAC-C0 and high eplet mismatch showed the highest hazard ratio for the development of dnDSA. No significant combined effect was observed in dnDSA development according to TWCV. In conclusion, the determination of HLA class II eplet mismatch may improve the risk stratification for dnDSA development, especially in conjunction with tacrolimus trough levels.

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.

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.

The utility of imputation for molecular mismatch analysis in solid organ transplantation

HLA genotyping has undergone a rapid progression in resolution since the development of DNA-based typing methods. Despite the advent of high-resolution next-generation sequencing, the bulk of solid organ genotyping is performed at intermediate resolution, which provides multiple possible two-field results for each classical HLA loci. As a result, several methodologies have been developed to impute the most likely allele-level (two-field) HLA genotype for the purposes of donor-recipient compatibility analysis. The advent of molecular mismatch analysis, however, has placed a new emphasis on the accuracy of imputation. While seminal molecular mismatch studies have relied on the imputation of intermediate resolution genotyping, several recent studies have performed analysis showing that imputation generates inaccuracies in epitope identification. While the clinical impact of these errors is not clear, it is important that these concerns do not preclude future progress in understanding the utility of molecular mismatch analysis in transplantation. In the future, advances in genotyping methods will result in routine two-field resolution that will abrogate these concerns. In the meantime, however, studies are needed in order to address the role of molecular mismatch in diverse patient populations and to carefully address the potential of molecular mismatch analysis in the context of imputation.

Epitope-Level Matching—A Review of the Novel Concept of Eplets in Transplant Histocompatibility

The development of de novo donor-specific antibodies is related to the poor matching of the human leukocyte antigen (HLA) between donor and recipient, which leads to dismal clinical outcomes and graft loss. However, new approaches that stratify the risks of long-term graft failure in solid organ transplantation have emerged, changing the paradigm of HLA compatibility. In addition, advances in software development have given rise to a new structurally based algorithm known as HLA Matchmaker, which determines compatibility at the epitope rather than the antigen level. Although this technique still has limitations, plenty of research maintains that this assessment represents a more complete and detailed definition of HLA compatibility. This review summarizes recent aspects of eplet mismatches, highlighting the most recent advances and future research directions.