Next Article in Journal
Donor-Derived Cell-Free DNA to Diagnose Graft Rejection Post-Transplant: Past, Present and Future
Next Article in Special Issue
A Retrospective Review of Calcineurin Inhibitors’ Impact on Cytomegalovirus Infections in Lung Transplant Recipients
Previous Article in Journal / Special Issue
Kidney Failure after Liver Transplantation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

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

by
André Renaldo
,
Adriel Roa-Bautista
,
Elena González-López
,
Marcos López-Hoyos
and
David San Segundo
*
Immunology Department, Marqués de Valdecilla Hospital-IDIVAL, 39008 Santander, Spain
*
Author to whom correspondence should be addressed.
Contributed equally in the work.
Transplantology 2021, 2(3), 336-347; https://doi.org/10.3390/transplantology2030033
Submission received: 1 July 2021 / Revised: 26 August 2021 / Accepted: 2 September 2021 / Published: 6 September 2021
(This article belongs to the Collection Progress and Recent Advances in Solid Organ Transplantation)

Abstract

:
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.

1. Introduction

Although there have been many breakthroughs in solid organ transplantation, histocompatibility remains a challenge. Poor HLA matching results in the formation of de novo donor-specific antibodies (dnDSA), which in turn lead to worse clinical outcomes and diminished graft survival [1]. Understanding how these antibodies (Abs) are developed can offer strategies to prevent their formation and could significantly improve long-term solid organ transplant results.
Advances in molecular analysis and computational software have given rise to a new concept of eplets, which are defined as clusters of polymorphic amino acids located on the surface of HLA molecules. Eplets have been described as functional epitopes as they include amino acids that can be recognized by anti-HLA antibodies from among the whole amino acid structure that comprises an HLA epitope. This provides a higher resolution view of the antigen–antibody binding and a mechanistic explanation for the old idea of cross-reactive serological groups [2].
Despite the fact that there is still much to elucidate, this new paradigm has started to be the subject of intense research, with great potential for incorporation into clinical practice in the form of thresholds for the number of donor–recipient eplet mismatches (MMs) and as part of the scoring in the organ allocation system.
In this review, we provide an up-to-date summary that is focused on the evaluation of some of the novel research that pioneered this concept, encompassing its application, organ-specific challenges as well as its limitations.

2. The Effects of Poor HLA Matching

Allograft allocation is a complex process. Currently, there are numerous factors such as the urgency of transplant, the lack of donor information, and the type of organ being allocated; because of this, it is often difficult to take HLA matching into account [3].
It is crucial to consider donor–recipient HLA matching because multiple MMs at first transplant results in the reduced lifetime of a functional graft. In the case of renal transplants, DR matching becomes a balance between waiting for dialysis, which increases morbidity and mortality, and accepting a somewhat mismatched donor [4,5]. An illustrative example of the former argument is the initiative called Share35, which grants children top priority in obtaining kidneys from deceased donors (DD) less than 35 years old in order to reduce long waiting times regardless of HLA matching, with the exception of 0 MMs [6].
Taking advantage of the Share35 paradigm, in 2007, Crafter et al. analyzed a Canadian retrospective cohort of 98 patients divided into two eras: before and after Share35 [7]. The requirements were ABO compatibility, negative cross-match, donor age between 5 and 45, but irrespective of HLA matching. This study assessed the impact on the length of time that patients were waitlisted and the quality of organs transplanted, and found that with the new policy, the waiting was ten times shorter than before. In addition, all of the patients were transplanted within six months. These results were then compared to a 25% transplant rate within six months of listing in the pre-Share35 era. Moreover, organs transplanted were also better by all clinical variables assessed [7].
Perhaps given more and more effective immunosuppression protocols, the importance of HLA MMs has diminished over time and does not play that big of a role as it once did in short-term graft survival. With regards to the compromise of time on the waiting list vs. proper HLA matching, we could also add the non-immunological indices of organ quality (i.e., creatinine, level of steatosis). The ideal organ allocation policy would take all three variables into account, and rather than disposing of HLA matching completely, it would be worthwhile to at least match in one locus such as the DR, which has been associated with better outcomes [8].
It has been shown that the risk of kidney graft failure increases with HLA MM in unsensitized recipients [9], with antibody-mediated injury being the main finding in biopsies of chronically rejected kidney allografts [10]. Stressing measures that reduce the humoral alloresponse would improve long-term graft survival. HLA matching is not considered at all in the case of lung transplant (LTx), in contrast to that of kidney, due to the urgency and the fact that there is no replacement therapy. However, it is known that an HLA MM is associated with dnDSA, which is related to chronic humoral rejection or chronic lung allograft dysfunction (CLAD) [11,12].

3. New Concept of Eplets

Our knowledge of the humoral immune response has dramatically increased in the past few years. It has long been recognized that recipient anti-HLA Abs bind to the polymorphic mismatched non-self HLA molecule expressed in the allograft, possibly triggering a graft loss or an unfavorable prognosis. What is novel and important is knowing that this binding is not against the whole antigen structure but rather against specific regions known as epitopes. Duquesnoy and colleagues have developed an algorithm known as HLA Matchmaker, which considers HLA alleles as strings of distinct molecular configurations that can eventually be recognized by antibodies [13].
The HLA Matchmaker software describes antibody-verified epitopes that have the ability to elicit an immune response, i.e., produce specific antibodies [14,15]. It is the polymorphic amino acid tridimensional configuration within the epitope that is referred to as an eplet. In short, for a recipient to develop dnDSA, there has to be an HLA mismatch. However, it has to be accessible at the protein level in its quaternary structure, and this accessibility can be predicted with a stereochemical modeling software [16,17].
In a 2015 pediatric cardiac transplant study, Sullivan et al. evaluated 4851 transplants and focused on the eplet MM loads in donor–recipient pairs. The HLA Matchmaker software was used to quantify structural differences between donors and recipients in order to evaluate graft loss risk [18]. It has been described that specific allele MMs are more antigenic than others, and some are even inconsequential. The authors stated that more mismatches at the allele level were also correlated with more eplet MMs. They observed that recipients with 10–20 or more class I eplet MMs experienced increased long-term graft loss versus recipients with less than ten eplet MMs in class I, establishing a possible cut-off point of <10 MMs [18]. They explained that even if recipients had 2–4 class I antigen MMs, which are generally considered high-risk, but had less than ten eplet MMs in class I, graft survival was comparable with that of low-risk patients. This suggests that not all HLA MMs are equal; in other words, an allele mismatch is not the same as an eplet mismatch. Thus, the Ab-accessible polymorphic regions (eplets) could be key to a more objective approach in defining the risk of anti-HLA Ab development and chronic allograft rejection [18].
We can see how donor–recipient pairs with a similar number of antigen MMs can vary considerably with eplet MMs, further highlighting the fact that eplet matching presents an exceedingly significant advantage compared with HLA matching. The eplet model offers far greater discrimination power and matching capacity. Thus, even though the two potential recipients have an equal number of HLA MMs, by analyzing it at the eplet level, one can see how one recipient is clearly a better match (See Figure 1). Using eplet matching, we can benefit from data at the molecular level [18]. This may aid in identifying recipients at risk of long-term graft loss and who could also benefit from post-transplant surveillance and management. Other studies have found that eplet MMs are associated with acute rejection in kidney transplant recipients, with 20 or more mismatches being the threshold [19].
Another similar study, also evaluating the differences between antigen and eplet MM, is the 2016 research by Bryan et al. that evaluated a retrospective cohort of 78 offers for 16 pediatric renal transplant patients to determine the prevalence of DR and DQ mismatching from donor offers during a one-year follow-up [20]. Based on their early age and time of transplant, this is important because a considerable number of children will need to be retransplanted later in life, and performing eplet matching could potentially reduce the development of dnDSA. The authors compared the HLA-matching method with the eplet-matching method, using thresholds established by Wiebe et al. [11]. Using eplet analysis, it was shown that two MMs in the DR antigen corresponded with a 64% risk of developing dnDSA [20]. Thus, this study validates HLA Matchmaker as a tool that has more granularity and as a crucial development that allows for the molecular comparison between donor antigen and self.
The assessment of eplet MM has several drawbacks; firstly, there is a lack of consensus in the cut-off value of eplet MM used in different studies (Table 1). Secondly, a high resolution of HLA type is required to perform proper eplet MM analysis (Table 2 summarizes the differences between antigen and epitope level analysis). The imputational approach for high-resolution HLA typing may render inaccurate results [21].

4. Organs and Eplet

4.1. Mechanism for How dnDSA Are Developed

The development of dnDSA represents the immunologic reaction the donor elicits in the transplant recipient. The Abs that do not preexist but develop after transplantation and are directed against foreign graft HLA are considered dnDSA. The distinction of being donor-specific is crucial as they are directed against the graft, eventually resulting in the loss of the organ.
In 2016, Kosmoliaptsis et al. devised a numerical approach to determine the immunogenicity of donor HLA [35]. They measured this as the differences in the number of amino acid mismatches and their physicochemical properties, which translate to an amino acid MM score (AMS), an eplet MM score (EpMS), and an electrostatic MM score (EMS), all of which are predictors of DSA in patients listed for retransplant. They found that the assessment of donor HLA immunogenicity based on these methods (AMS, EpMS, or EMS) offered additional information and value to conventional HLA MM grades. Another exciting fact described by the authors was that donor HLA-DR and DQ alloantigens with high AMS, EpMS, or EMS were more prone to developing DSA [35].
Regarding the natural history of dnDSA development, Wiebe et al. proposed a mechanism based on a 2012 prospective six-year follow-up cohort study of 315 patients. They analyzed anti-HLA antibodies pre/post-transplantation and looked for de novo DSA development. They saw that 15% of patients developed post-transplant dnDSA. Their formation began with early inflammatory events, and followed by subclinical injury consisting of peritubular capillaritis, C4d deposition, and glomerulitis. The predictors of dnDSA were the incidence of one or more DRB1 mismatches and nonadherence, with a strong trend toward clinical rejection episodes preceding dnDSA [1].

4.2. Renal

Immune-mediated injury is still the leading cause of renal graft loss despite immunosuppression and modern cross-matching techniques. Moreover, two-thirds of chronically rejected kidney allografts are due to antibody-mediated rejection (AMR) [10,36,37].
Doxiaidis et al. analyzed a retrospective cohort of 456 renal transplant patients in 2007 to evaluate the different effects of HLA-DR matching versus HLA-A and B. They demonstrated that full HLA-DR compatibility was associated with a lower incidence of biopsy-confirmed acute rejection within the first 180 days post-transplant. An additional positive fact described by these researchers was that matching HLA-A and HLA-B was only beneficial if the entire HLA-DR group was compatible, noting that a single HLA-DR incompatibility obliterates the effect of HLA-A and B matching [8].
In the 2016 prospective cohort study by Kaussman et al. [22], a one-year follow-up in pediatric renal transplants utilized the HLA Matchmaker software to develop a kidney allocation strategy using eplet loads. They set eplet thresholds for class I at less than ten and less than 30 for class II. They then compared the development of dnDSA between the exclusion and no-exclusion groups based on the eplet threshold and found that it was a suitable allocation method, with less time spent on the waiting list. It also served as an acceptable MM [38] and dnDSA developed less; however, early clinical outcomes such as AMR were similar between groups [22]. In other words, low levels of dnDSA are associated with better graft survival in the long term despite having similar short-term outcomes concerning AMR.
In 2013, Wiebe et al. performed a retrospective cohort study of 286 renal transplant recipients. They assessed epitope matching and traditional HLA matching as predictors of dnDSA in DR and DQ antigens, as well as the relative immunogenicity of specific epitopes. Once again, HLA Matchmaker was used to characterize epitope MMs, finding that locus-specific MMs were superior in patients who developed HLA-DR and HLA-DQ dnDSA alone [11].
Eplet analysis might serve as a way to identify high-risk patients that will benefit from frequent monitoring post-transplant. The combination of eplet MMs and nonadherence to immunosuppressive medication seems to have a synergistic effect, as Wiebe et al. described in a 2015 retrospective cohort study of 195 participants. They found that a DR load greater than ten eplet MMs and nonadherence had a 35% increased chance of graft loss as compared to 8% if they adhered to their immunosuppression. The threshold was more than 17 eplet MMs for the DQ locus, while for nonadherence, the graft loss was 33% as compared to 10% [23]. Taken together, these findings suggest that prior to attempting minimization of immunosuppression, providers should consider eplet MM load. Recently, a multicenter study suggested both the assessment of eplet MM and performing a cell-specific assay before kidney transplantation in order to personalize the minimization of immunosuppression with tacrolimus monotherapy [39].
In 2017, Lobashevsky et al. conducted a retrospective study of a cohort of 458 renal transplant recipients, all of whom had low levels of preexisting class I DSA and a mean fluorescence intensity (MFI) of less than 2000; they analyzed the deleterious effects defined by several criteria such as biopsy-proven AMR, transplant glomerulopathy (TG), dnDSA, and increasing MFI of existing DSA. Recipients were divided into two study groups, one with harmful outcomes and the other with expected results. They correlated the patient data and entered them into the HLA Matchmaker software, and saw that the number of MM eplets between DR pairs was a strong predictor of deleterious effects. In this study, the 127K epitope was found to be immunogenic, and when unmatched at this epitope, they observed an odds ratio of 9 for a deleterious effect. They detected a threshold of 12 eplets for MM, with anything higher than this being a strong predictor of a poor outcome [24]. However, to better define the role of eplet MM load in alloresponse, a profound definition of eplet immunogenicity should be provided [40]. Recently, in a sensitization approach after pregnancy, different immunogenic eplet MMs for both class I [14] and class II [15] were identified. The HLA-class II eplet MM in living kidney donors improved the prediction of dnDSA development [25] and AMR [26].

4.3. Lung

Due to the nature, complexity, and urgency of lung transplantation, HLA incompatibility is overlooked. However, the HLA MM in lung transplantation has been associated with chronic allograft lung dysfunction (CLAD) [41]. Matching in lung transplantation is focused on helping to prevent CLAD and its associated morbidity and mortality.
The concept of eplet load is helpful since it allows for the definition of HLA compatibility with greater precision. Although this strategy cannot be used in urgent cases, as has been noted before, knowing the eplet load can guide clinicians in post-transplant monitoring [42]. Tikkanen et al. studied 340 recipients and found that almost half developed dnDSA, and most of them were against DQ, with a hazard ratio of 2.03 for chronic lung allograft vasculopathy. Male sex and ex vivo lung perfusion were independent risk factors in the development of dnDSA [43].
In a 2014 study, Safavi et al. performed a retrospective study of a cohort of 148 patients where they compared the relationship between dnDSA and the development of bronchiolitis obliterans syndrome (BOS), a clinical picture of progressive small-airway obstruction that leads to chronic allograft dysfunction, which is the primary cause of death beyond the first year of a lung transplant. In a multivariate analysis, dnDSA was associated with a significantly higher hazard ratio for BOS at all stages. Other variables related to BOS were female sex and comorbid emphysema [44,45].
Another research that elucidated the possible association of dnDSA development and BOS was conducted by Morrell et al. in a single-center prospective study of 445 participants screening for dnDSA at the two-year follow-up. They detected 13% of dnDSA in the cohort, which presented a significantly reduced disease-free time compared to the group without dnDSA. Using a Cox proportional hazards model, they observed that the development of dnDSA was associated with BOS and high-grade BOS [46].
Not only does eplet matching offer more granularity than antigen/allele mismatches, but it also has a predictive capacity for developing chronic lung allograft dysfunction (CLAD) in the case of lung transplantation [27].
Walton et al. performed a retrospective study of 175 recipients using eplet mismatches to predict CLAD and restrictive obliterative syndrome (ROS). In their sample population, the average eplet load for all classes was 60, thus serving as a threshold for high or low loads. They demonstrated that antigen mismatches correlated with eplet mismatches. The ability of eplet matching to detect CLAD and ROS was measured, obtaining an area under the ROC curve (AUC) of 0.71 and 0.77, respectively. These findings were significant in utilizing eplet MMs, but not so for HLA MMs [27].

4.4. Cardiac

The donor HLA typing in heart transplantation and the HLA match are limited to potential HLA-sensitized patients on the waiting list, but an HLA-DR mismatch has been associated with early allograft rejection and worse graft survival. Thus, most cardiac transplants are mismatched and result in DSA development, which contributes to the development of cardiac allograft vasculopathy, a multifactorial entity requiring both immune and non-immune factors [12].
In 2011, a retrospective study by Smith et al. analyzed a cohort of 243 patients, measured their HLA antibody status pre- and post-transplant. Most persistent dnDSA were against HLA class II, irrespective of complement fixation and acute rejection stimulus for developing dnDSA [12,47]. Cardiac transplant recipients were HLA-screened before and after transplant. Their goal was to identify persistent dnDSA associated with more immunogenic epitopes and to develop an allocation algorithm that would predict and reduce this occurrence. They identified a risk epitope mismatch (REM) when the donor was DQA1*05/DQB1*02 or DQA1*05/DQB1*03, which generated dnDSA against its mismatched risk epitope of 45EV 45GE3 [48].
In 2020, Osorio-Jaramillo et al. evaluated the association of eplet MMs with post-transplant graft survival, rejection, and cardiac allograft vasculopathy (CAV) in a retrospective study of 1167 cardiac transplanted patients. They determined the number of amino acid differences in Ab-verified HLA eplets between donor and recipient, and showed that high HLA-DR eplet MMs were associated with less graft survival at one year, whereas an eplet mismatch in HLA-A and B had no impact. In addition, high loads of HLA-A, -B, and -DR, the MMs increased the risk of rejection. Finally, they did not find any impact on CAV development. The molecular-level HLA MMs are associated with rejection and worsened graft survival in heart transplant recipients [29].
On the contrary, Nilsson et al. carried out a novel study using the HLA Matchmaker algorithm to stratify risk in a large cohort of heart transplant recipients; their results showed an increased graft loss with the HLA-DR/DQ eplet MM level, but were not superior to HLA-DR/DQ antigen-level MMs [30].

4.5. Liver

The effect of eplet mismatch in liver transplantation has not been studied in detail, and the impact of HLA matching on outcomes remains controversial [49]. For this reason, in 2019, Guiral et al. analyzed eplet MMs in a retrospective study of 43 liver transplant recipients. Patients with a high eplet load in the C locus had higher T-cell mediated rejection [31].
A similar study on liver eplet mismatch conducted by Forner et al. retrospectively analyzed a cohort of 67 recipients for eplet mismatch and found that high eplet loads at the A locus were associated with decreased graft survival, but did not reach statistical significance, and no other loci were found to be predictive [32].
In 2019, Ekong et al. performed a retrospective study of 42 liver recipients. They used HLA Matchmaker to predict the risk of developing Abs and found that 48% developed dnDSA, using >5 MMs as the DQ thresholds. In this cohort, DQB1*02 was associated with acute rejection and a higher portal fibrosis score; additionally, they highlighted the immunodominant epitopes, which were 4Q, 45GE, 52PQ, 52PL [33].
Moreover, in 2018, Kubal et al. analyzed a prospective cohort of 80 liver transplant recipients. They hypothesized that HLA eplet mismatches are a possible marker of immunogenicity and a risk factor for de novo DSA, resulting in 34% of the patients developing only dnDSA class II. They did not find any association between dnDSA formation and acute cellular rejection (ACR) or antibody-mediated rejection (AMR) [34].
Taken together, it remains unclear which HLA locus mismatch is more immunogenic in liver transplants. The data seems to point to class II, as is the case with other solid organs. Though an epitope-matching-based allocation system is not practical for the liver, it can be used to stratify patients according to risk. As is the case for recipients of other organs, higher-risk patients warrant closer surveillance, and lower-risk patients can be placed on tolerance protocols for immunosuppression. This is especially apt in the case of the liver due to its particularities, being one of the most tolerogenic organs transplanted [50].

5. Conclusions

This review summarizes the current evidence regarding the clinical utility of eplet load and epitope-level matching. We have described how donor-recipient pairs with the same number of mismatched alleles can vary considerably depending on the specific protein structure. The nature of the eplets allows for a high-resolution view of the molecular structure and the string of epitopes that comprise the HLA antigen protein.
Consideration of the HLA status at this level can serve clinicians in the transplant field in many ways. Even if it is not part of organ allocation, it can serve as a way for physicians to identify patients at high risk of rejection phenomena and thus adapt their immunosuppression, which is associated with multiple collateral effects such as an increased risk of malignancy and a lower quality of life. If taken into account prior to transplant, a shift towards eplet-level matching—considering risk-epitope mismatches instead of broad antigen—can lead to better outcomes and decrease the likelihood of dnDSA formation, and thus graft survival. It can also help alleviate organ shortage as more donor offers are considered because despite antigen incompatibility, there are no immunogenic eplets in that given locus. It can also grant recipients with exotic HLA types, or those with high-panel reactive antibodies, access to transplant by being selective and not restricting donors with a whole locus.
Many aspects of this new concept remain to be elucidated, such as the thresholds for high and low eplet loads and their respective diagnostic accuracies. Most notable is the immunogenicity of mismatched eplets. Identifying immunogenic eplets would help to identify those patients at risk of de novo antibody development and graft loss. Furthermore, a high-resolution HLA typing for both donor and patients in order to assign eplet MMs should be performed to avoid the potential bias of the imputation HLA antigens [21].
Nevertheless, the move towards a higher resolution and more complex, granular analysis are inevitable. As laboratory techniques and molecular tools have improved, eplets have emerged as another layer of complexity built upon previous concepts. The question is whether this approach should be incorporated into clinical practice, and the fact is that this procedure has progressed from being a purely theoretical exercise to being applied in transplant centers worldwide with promising results.
More data will continue to accumulate on the immunogenicity of each eplet and on the appropriate thresholds that determine high risk. This method must be analyzed in a new way that will ensure graft survival and improved outcomes in transplantation.

Author Contributions

A.R., A.R.-B. and E.G.-L. wrote the manuscript. D.S.S. and M.L.-H. conceptualization, supervision and review of the draft manuscripts. All authors have read and agreed to the published version of the manuscript.

Funding

This work was partially funded by a grant from Instituto de Salud Carlos III (PI19/01509).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wiebe, C.; Gibson, I.W.; Blydt-Hansen, T.D.; Karpinski, M.; Ho, J.; Storsley, L.J.; Goldberg, A.; Birk, P.E.; Rush, D.N.; Nickerson, P.W. Evolution and clinical pathologic correlations of de novo donor-specific HLA antibody post kidney transplant. Am. J. Transplant. 2012, 12, 1157–1167. [Google Scholar] [CrossRef] [PubMed]
  2. Larkins, N.G.; Wong, G.; Taverniti, A.; Lim, W.H. Epitope matching in kidney transplantation: Recent advances and current limitations. Curr. Opin. Organ. Transplant. 2019, 24, 370–377. [Google Scholar] [CrossRef]
  3. Taherkhani, N.; Sepehri, M.M.; Shafaghi, S.; Khatibi, T. Identification and weighting of kidney allocation criteria: A novel multi-expert fuzzy method. BMC Med. Inform. Decis. Mak. 2019, 19, 1–15. [Google Scholar] [CrossRef] [Green Version]
  4. Edwards, E.B.; Bennett, L.E.; Cecka, J.M. Effect of HLA matching on the relative risk of mortality for kidney recipients: A comparison of the mortality risk after transplant to the mortality risk of remaining on the waiting list. Transplantation 1997, 64, 1274–1277. [Google Scholar] [CrossRef]
  5. Nissel, R.; Brázda, I.; Feneberg, R.; Wigger, M.; Greiner, C.; Querfeld, U.; Haffner, D. Effect of renal transplantation in childhood on longitudinal growth and adult height. Kidney Int. 2004, 66, 792–800. [Google Scholar] [CrossRef] [Green Version]
  6. Foster, B.J.; Dahhou, M.; Zhang, X.; Platt, R.W.; Smith, J.M.; Hanley, J.A. Impact of HLA mismatch at first kidney transplant on lifetime with graft function in young recipients. Am. J. Transplant. 2014, 14, 876–885. [Google Scholar] [CrossRef] [Green Version]
  7. Crafter, S.R.; Bell, L.; Foster, B.J. Balancing organ quality, HLA-matching, and waiting times: Impact of a pediatric priority allocation policy for deceased donor kidneys in Quebec. Transplantation 2007, 83, 1411–1415. [Google Scholar] [CrossRef] [PubMed]
  8. Doxiadis, I.I.N.; De Fijter, J.W.; Mallat, M.J.K.; Haasnoot, G.W.; Ringers, J.; Persijn, G.G.; Claas, F.H.J. Simpler and equitable allocation of kidneys from postmortem donors primarily based on full HLA-DR compatibility. Transplantation 2007, 83, 1207–1213. [Google Scholar] [CrossRef]
  9. Williams, R.C.; Opelz, G.; McGarvey, C.J.; Weil, E.J.; Chakkera, H.A. The risk of transplant failure with hla mismatch in first adult kidney allografts from deceased donors. Transplantation 2016, 100, 1094–1102. [Google Scholar] [CrossRef] [PubMed]
  10. Sellarés, J.; De Freitas, D.G.; Mengel, M.; Reeve, J.; Einecke, G.; Sis, B.; Hidalgo, L.G.; Famulski, K.; Matas, A.; Halloran, P.F. Understanding the causes of kidney transplant failure: The dominant role of antibody-mediated rejection and nonadherence. Am. J. Transplant. 2012, 12, 388–399. [Google Scholar] [CrossRef] [PubMed]
  11. Wiebe, C.; Pochinco, D.; Blydt-Hansen, T.D.; Ho, J.; Birk, P.E.; Karpinski, M.; Goldberg, A.; Storsley, L.J.; Gibson, I.W.; Rush, D.N.; et al. Class II HLA epitope matching—A strategy to minimize de novo donor-specific antibody development and improve outcomes. Am. J. Transplant. 2013, 13, 3114–3122. [Google Scholar] [CrossRef] [PubMed]
  12. Smith, J.D.; Banner, N.R.; Hamour, I.M.; Ozawa, M.; Goh, A.; Robinson, D.; Terasaki, P.I.; Rose, M.L. De novo donor HLA-specific antibodies after heart transplantation are an independent predictor of poor patient survival. Am. J. Transplant. 2011, 11, 312–319. [Google Scholar] [CrossRef]
  13. Duquesnoy, R.J. Epitope-based human leukocyte antigen matching for transplantation: A personal perspective of its future. Curr. Opin. Organ. Transplant. 2018, 23, 486–492. [Google Scholar] [CrossRef] [PubMed]
  14. Hönger, G.; Niemann, M.; Schawalder, L.; Jones, J.; van Heck, M.R.; van de Pasch, L.A.L.; Vendelbosch, S.; Rozemuller, E.H.; Hösli, I.; Blümel, S.; et al. Toward defining the immunogenicity of HLA epitopes: Impact of HLA class I eplets on antibody formation during pregnancy. HLA 2020, 96, 589–600. [Google Scholar] [CrossRef] [PubMed]
  15. Schawalder, L.; Hönger, G.; Kleiser, M.; van Heck, M.R.; van de Pasch, L.A.L.; Vendelbosch, S.; Rozemuller, E.H.; Schaub, S. Development of an immunogenicity score for HLA-DQ eplets: A conceptual study. HLA 2021, 97, 30–43. [Google Scholar] [CrossRef]
  16. Sypek, M.; Kausman, J.; Holt, S.; Hughes, P. HLA Epitope Matching in Kidney Transplantation: An Overview for the General Nephrologist. Am. J. Kidney Dis. 2018, 71, 720–731. [Google Scholar] [CrossRef]
  17. Duquesnoy, R.J.; Askar, M. HLAMatchmaker: A Molecularly Based Algorithm for Histocompatibility Determination. V. Eplet Matching for HLA-DR, HLA-DQ and HLA-DP. Hum. Immunol. 2007, 68, 12–25. [Google Scholar] [CrossRef] [Green Version]
  18. Sullivan, P.M.; Warner, P.; Kemna, M.S.; Albers, E.L.; Law, S.P.; Weiss, N.S.; Law, Y.M. HLA molecular epitope mismatching and long-term graft loss in pediatric heart transplant recipients. J. Heart Lung Transplant. 2015, 34, 950–957. [Google Scholar] [CrossRef] [PubMed]
  19. Do Nguyen, H.T.; Wong, G.; Chapman, J.R.; McDonald, S.P.; Coates, P.T.; Watson, N.; Russ, G.R.; D’Orsogna, L.; Lim, W.H. The Association between Broad Antigen HLA Mismatches, Eplet HLA Mismatches and Acute Rejection after Kidney Transplantation. Transplant. Direct. 2016, 2, e120. [Google Scholar] [CrossRef]
  20. Bryan, C.F.; Chadha, V.; Warady, B.A. Donor selection in pediatric kidney transplantation using DR and DQ eplet mismatching: A new histocompatibility paradigm. Pediatr. Transplant. 2016, 20, 926–930. [Google Scholar] [CrossRef] [PubMed]
  21. Engen, R.M.; Jedraszko, A.M.; Conciatori, M.A.; Tambur, A.R. Substituting imputation of HLA antigens for high-resolution HLA typing: Evaluation of a multiethnic population and implications for clinical decision making in transplantation. Am. J. Transplant. 2021, 21, 344–352. [Google Scholar] [CrossRef]
  22. Kausman, J.Y.; Walker, A.M.; Cantwell, L.S.; Quinlan, C.; Sypek, M.P.; Ierino, F.L. Application of an epitope-based allocation system in pediatric kidney transplantation. Pediatr. Transplant. 2016, 20, 931–938. [Google Scholar] [CrossRef] [PubMed]
  23. Wiebe, C.; Nevins, T.E.; Robiner, W.N.; Thomas, W.; Matas, A.J.; Nickerson, P.W. The Synergistic Effect of Class II HLA Epitope-Mismatch and Nonadherence on Acute Rejection and Graft Survival. Am. J. Transplant. 2015, 15, 2197–2202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Lobashevsky, A.; Goggins, W.; Rosner, K.; Taber, T. Immunogenicity of Class I HLA but not preformed low MFI donor specific antibodies correlates with outcomes after first renal transplantation. Transpl. Immunol. 2017, 43, 42–48. [Google Scholar] [CrossRef] [PubMed]
  25. Tafulo, S.; Malheiro, J.; Santos, S.; Dias, L.; Almeida, M.; Martins, L.S.; Pedroso, S.; Mendes, C.; Lobato, L.; Castro-Henriques, A. HLA class II eplet mismatch load improves prediction of dnDSA development after living donor kidney transplantation. Int. J. Immunogenet. 2021, 48, 1–7. [Google Scholar] [CrossRef] [PubMed]
  26. Tafulo, S.; Malheiro, J.; Santos, S.; Dias, L.; Almeida, M.; Martins, L.S.; Pedroso, S.; Mendes, C.; Lobato, L.; Castro-Henriques, A. Degree of HLA class II eplet mismatch load improves prediction of antibody-mediated rejection in living donor kidney transplantation. Hum. Immunol. 2019, 80, 966–975. [Google Scholar] [CrossRef]
  27. Hayes, D.; Black, S.M.; Tobias, J.D.; Kopp, B.T.; Kirkby, S.E.; Mansour, H.M.; Whitson, B.A. Influence of human leukocyte antigen mismatching on bronchiolitis obliterans syndrome in lung transplantation. J. Heart Lung Transplant. 2016, 35, 186–194. [Google Scholar] [CrossRef] [Green Version]
  28. McCaughan, J.A.; Battle, R.K.; Singh, S.K.S.; Tikkanen, J.M.; Moayedi, Y.; Ross, H.J.; Singer, L.G.; Keshavjee, S.; Tinckam, K.J. Identification of risk epitope mismatches associated with de novo donor-specific HLA antibody development in cardiothoracic transplantation. Am. J. Transplant. 2018, 18, 2924–2933. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Osorio-Jaramillo, E.; Haasnoot, G.W.; Kaider, A.; Schaefer, A.K.; Haberl, T.; Goekler, J.; Angleitner, P.; Moayedifar, R.; Zuckermann, A.; Fischer, G.F.; et al. Molecular-level HLA mismatch is associated with rejection and worsened graft survival in heart transplant recipients—A retrospective study. Transpl. Int. 2020, 33, 1078–1088. [Google Scholar] [CrossRef]
  30. Nilsson, J.; Ansari, D.; Ohlsson, M.; Höglund, P.; Liedberg, A.S.; Smith, J.G.; Nugues, P.; Andersson, B. Human Leukocyte Antigen-Based Risk Stratification in Heart Transplant Recipients—Implications for Targeted Surveillance. J. Am. Heart Assoc. 2019, 8, e11124. [Google Scholar] [CrossRef] [Green Version]
  31. Guiral, S.; Segundo, D.S.; Irure, J.; Casafont, F.; Fortea, J.I.; Puente, Á.; López-Hoyos, M.; Crespo, J.; Fabrega, E. Number of antibody-verified eplet in HLA-C locus as an independent factor of t-cell-mediated rejection after liver transplantation. Transplantation 2020, 104, 562–567. [Google Scholar] [CrossRef]
  32. Forner, D.; Liwski, R.; Alwayn, I. Human leukocyte antigen, allele, and eplet mismatches in liver transplantation; observations from a small, single center cohort. Hum. Immunol. 2018, 79, 154–159. [Google Scholar] [CrossRef] [PubMed]
  33. Ekong, U.D.; Antala, S.; Bow, L.; Sese, D.; Morotti, R.; Rodriguez-Davalos, M.; Gan, G.; Deng, Y.; Emre, S.H. HLA, Non-HLA Antibodies, and eplet mismatches in pediatric liver transplantation: Observations from a small, single-center cohort. Exp. Clin. Transplant. 2019, 17, 6–17. [Google Scholar] [CrossRef] [PubMed]
  34. Kubal, C.A.; Mangus, R.; Ekser, B.; Mihaylov, P.; Ceballos, B.; Higgins, N.; Chalasani, N.; Ghabril, M.; Nephew, L.; Lobashevsky, A. Class II Human Leukocyte Antigen Epitope Mismatch Predicts De Novo Donor-Specific Antibody Formation After Liver Transplantation. Liver Transplant. 2018, 24, 1101–1108. [Google Scholar] [CrossRef] [Green Version]
  35. Kosmoliaptsis, V.; Mallon, D.H.; Chen, Y.; Bolton, E.M.; Bradley, J.A.; Taylor, C.J. Alloantibody Responses After Renal Transplant Failure Can Be Better Predicted by Donor–Recipient HLA Amino Acid Sequence and Physicochemical Disparities Than Conventional HLA Matching. Am. J. Transplant. 2016, 16, 2139–2147. [Google Scholar] [CrossRef] [Green Version]
  36. Süsal, C.; Opelz, G. Good kidney transplant outcome in recipients with presensitization against HLA class II but not HLA class I. Hum. Immunol. 2004, 65, 810–816. [Google Scholar] [CrossRef]
  37. Lim, W.H.; Chadban, S.J.; Clayton, P.; Budgeon, C.A.; Murray, K.; Campbell, S.B.; Cohney, S.; Russ, G.R.; Mcdonald, S.P. Human leukocyte antigen mismatches associated with increased risk of rejection, graft failure, and death independent of initial immunosuppression in renal transplant recipients. Clin. Transplant. 2012, 26, E428–E437. [Google Scholar] [CrossRef]
  38. Heidt, S.; Haasnoot, G.W.; van Rood, J.J.; Witvliet, M.D.; Claas, F.H.J. Kidney allocation based on proven acceptable antigens results in superior graft survival in highly sensitized patients. Kidney Int. 2018, 93, 491–500. [Google Scholar] [CrossRef]
  39. Bestard, O.; Meneghini, M.; Crespo, E.; Bemelman, F.; Koch, M.; Volk, H.D.; Viklicky, O.; Giral, M.; Banas, B.; Ruiz, J.C.; et al. Preformed T cell alloimmunity and HLA eplet mismatch to guide immunosuppression minimization with tacrolimus monotherapy in kidney transplantation: Results of the CELLIMIN trial. Am. J. Transplant. 2021, 21, 2833–2845. [Google Scholar] [CrossRef]
  40. Heidt, S.; Claas, F.H.J. Not all HLA epitope mismatches are equal. Kidney Int. 2020, 97, 653–655. [Google Scholar] [CrossRef] [PubMed]
  41. Walton, D.C.; Hiho, S.J.; Cantwell, L.S.; Diviney, M.B.; Wright, S.T.; Snell, G.I.; Paraskeva, M.A.; Westall, G.P. HLA Matching at the Eplet Level Protects Against Chronic Lung Allograft Dysfunction. Am. J. Transplant. 2016, 16, 2695–2703. [Google Scholar] [CrossRef] [Green Version]
  42. Woodle, E.S.; Shields, A.R.; Ejaz, N.S.; Sadaka, B.; Girnita, A.; Walsh, R.C.; Alloway, R.R.; Brailey, P.; Cardi, M.A.; Abu Jawdeh, B.G.; et al. Prospective iterative trial of proteasome inhibitor-based desensitization. Am. J. Transplant. 2015, 15, 101–118. [Google Scholar] [CrossRef] [PubMed]
  43. Tikkanen, J.M.; Singer, L.G.; Kim, S.J.; Li, Y.; Binnie, M.; Chaparro, C.; Chow, C.W.; Martinu, T.; Azad, S.; Keshavjee, S.; et al. De novo DQ donor-specific antibodies are associated with chronic lung allograft dysfunction after lung transplantation. Am. J. Respir. Crit. Care Med. 2016, 194, 596–606. [Google Scholar] [CrossRef]
  44. Sato, M. Chronic lung allograft dysfunction after lung transplantation: The moving target. Gen. Thorac. Cardiovasc. Surg. 2013, 61, 67–78. [Google Scholar] [CrossRef] [PubMed]
  45. Safavi, S.; Robinson, D.R.; Soresi, S.; Carby, M.; Smith, J.D. De novo donor HLA-specific antibodies predict development of bronchiolitis obliterans syndrome after lung transplantation. J. Heart Lung Transplant. 2014, 33, 1273–1281. [Google Scholar] [CrossRef] [PubMed]
  46. Morrell, M.R.; Pilewski, J.M.; Gries, C.J.; Pipeling, M.R.; Crespo, M.M.; Ensor, C.R.; Yousem, S.A.; D’Cunha, J.; Shigemura, N.; Bermudez, C.A.; et al. De novo donor-specific HLA antibodies are associated with early and high-grade bronchiolitis obliterans syndrome and death after lung transplantation. J. Heart Lung Transplant. 2014, 33, 1288–1294. [Google Scholar] [CrossRef] [PubMed]
  47. Everly, M.J.; Terasaki, P.I. Monitoring and treating posttransplant human leukocyte antigen antibodies. Hum. Immunol. 2009, 70, 655–659. [Google Scholar] [CrossRef]
  48. Claas, F.H.J.; Dankers, M.K.; Oudshoorn, M.; van Rood, J.J.; Mulder, A.; Roelen, D.L.; Duquesnoy, R.J.; Doxiadis, I.I.N. Differential immunogenicity of HLA mismatches in clinical transplantation. Transpl. Immunol. 2005, 14, 187–191. [Google Scholar] [CrossRef]
  49. O’Leary, J.G.; Demetris, A.J.; Friedman, L.S.; Gebel, H.M.; Halloran, P.F.; Kirk, A.D.; Knechtle, S.J.; McDiarmid, S.V.; Shaked, A.; Terasaki, P.I.; et al. The role of donor-specific HLA alloantibodies in liver transplantation. Am. J. Transplant. 2014, 14, 779–787. [Google Scholar] [CrossRef] [Green Version]
  50. Starzl, T.E. The “privileged” liver and hepatic tolerogenicity. Liver Transplant. 2001, 7, 918–920. [Google Scholar] [CrossRef]
Figure 1. Schematic comparison between antigen and eplet matching approaches. The HLA typing for donors and two potential recipients reveals an equal number of mismatches (mm) at A and B loci. However, eplet matching views antigens (A, B) as a sequence of polymorphic amino acids which adopt a tridimensional conformation in the HLA protein. By considering the quaternary structure, the eplet approach offers far greater discrimination power and matching capacity. Thus, even though the two potential recipients have an equal number of antigen-level mm, recipient 2 is a better match at the eplet level. This could translate into less donor-specific antibody development and better long-term graft survival.
Figure 1. Schematic comparison between antigen and eplet matching approaches. The HLA typing for donors and two potential recipients reveals an equal number of mismatches (mm) at A and B loci. However, eplet matching views antigens (A, B) as a sequence of polymorphic amino acids which adopt a tridimensional conformation in the HLA protein. By considering the quaternary structure, the eplet approach offers far greater discrimination power and matching capacity. Thus, even though the two potential recipients have an equal number of antigen-level mm, recipient 2 is a better match at the eplet level. This could translate into less donor-specific antibody development and better long-term graft survival.
Transplantology 02 00033 g001
Table 1. Selected studies and corresponding results of eplet mismatch in solid organ transplantation.
Table 1. Selected studies and corresponding results of eplet mismatch in solid organ transplantation.
ReferencesYear, AuthorStudyOrganHLA LociObservationsClinical CorrelateEplet
[11]2013, Wiebep-cohort,
n = 286
RenalDR,
DQ
HLA-DR epitope MM load OR = 1.06 * (1.03–1.10) a
HLA-DQ epitope MM load OR = 1.04 * (1.0–1.02) a
dnDSA-
[19]2016, Do NguyenR-cohort,
n = 3499
RenalAll0–2 HLA MMs + >20 eplet MMs, HR = 1.85 (1.11–3.08) aRisk of rejection-
[20]2016, BryanR-cochort,
n = 16
Renal (peds)DR,
DQ
HLA-DR > 10 MMs, HLA-DQ > 17 MMsdnDSA-
[22]2016, Kaussmanp-cohort, n = 19Renal (peds)AllClass I < 10 MMs, class II < 30 MMsAMR-
[23]2015, WiebeR-cohort,
n = 195
RenalDR, DQHLA-DR > 10 MMs, HLA-DQ > 17 MMsSynergistic with Tx nonadherence-
[24]2017, LobashevskyR-cohort,
n = 141
RenalClass IThreshold > 12 MMs, OR = 9 (1.0–81.2) aAMR, TG, dnDSA, existing DSA127K
[25]2021, TafuloR-cohort,
n = 96
RenalClass IIClass II eplet MMs, HR = 1.105 (1.011–1.208) adnDSA-
[26]2019, TafuloR-cohort,
n = 151
RenalClass IIClass II eplet MMs, HR = 14.839 (1.846–119.282) aAMR-
[27]2016, WaltonR-cohort,
n = 175
LungAllThreshold > 60 eplets MMsCLAD, ROS-
[28]2019, McCaughanR-cohort,
n = 433
LungDQOR = 4.9dnDSA45EV, 45GE3
[28]2019, McCaughanR-cohort,
n = 265
CardiacDQOR = 4.2dnDSA45EV, 45GE3
[29]2020, Osorio-JaramilloR-cohort,
n = 1167
CardiacDR, ABHLA-DR eplet MMs had inferior 1 year graft survival, HR = 1.14 (1.01–1.28) a
Risk of rejection: HLA-AB MM load HR = 1.70 (1.29–2.24) a and HLA-DR HR = 1.32 (1.09–1.61) a
Graft survival and rejection-
[30]2019, NilssonR-cohort,
n = 34,681
CardiacDR, DQHLA-DR/DQ > 40 eplets MMS HR = 1.11 (1.03–1.21) aGraft loss-
[18]2015, SullivanR-cohort
n = 4851
Cardiac(peds)AllClass I > 10 MMsGraft loss-
[31]2019, GuiralR-cohort,
n = 43
LiverCOR = 3.8 (1.59–8.93) aTCMR-
[32]2018, FornerR-cohort,
n = 67
LiverADecreased graft survival, not significant--
[33]2019, EkongR-cohort,
n = 42
LiverDQHLA-DQ > 5 MMsACR, portal fibrosis score4Q, 45GE, 52PQ, 52PL
[34]2018, Kubalp-cohort,
n = 80
LiverDRB1,DQA1/B1Class II MM eplets was associated with dnDSA OR = 1.2dnDSA-
Abbreviations—ACR: acute cellular rejection; AMR: antibody-mediated rejection; CAV: cardiac allograft vasculopathy; CLAD: chronic lung allograft dysfunction rejection; dnDSA: de novo donor-specific antibodies; HR: hazard ratio; MMs: mismatches; OR: odds ratio; p-cohort: prospective cohort; Peds: pediatric patients; R-cohort: retrospective cohort; ROS: restrictive obliterans syndrome; TCMR: T cell mediated rejection; Tx: treatment; TG: transplant glomerulopathy. * OR per unit change; a 95% confidence intervals.
Table 2. Comparison of antigen-level and epitope-level analyses.
Table 2. Comparison of antigen-level and epitope-level analyses.
HLA Antigen Mismatch Eplet Mismatch
Advantages
  • Ease of measurement
  • Widespread use
  • HLA typing information already available for analysis
  • High-resolution view at molecular level
  • Can guide clinicians to tailor immunosuppression-lowering trials
  • Can help predict patients at risk of long-term graft loss
Disadvantages
  • Lack of granularity
  • Restricts a donor locus without taking into account recipient’s whole repertoire of epitopes
  • Needs continued, experimental verification of Ab binding
  • Unclear thresholds and cutoffs
Abbreviations—Ab: antibody.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Renaldo, A.; Roa-Bautista, A.; González-López, E.; López-Hoyos, M.; San Segundo, D. Epitope-Level Matching—A Review of the Novel Concept of Eplets in Transplant Histocompatibility. Transplantology 2021, 2, 336-347. https://doi.org/10.3390/transplantology2030033

AMA Style

Renaldo A, Roa-Bautista A, González-López E, López-Hoyos M, San Segundo D. Epitope-Level Matching—A Review of the Novel Concept of Eplets in Transplant Histocompatibility. Transplantology. 2021; 2(3):336-347. https://doi.org/10.3390/transplantology2030033

Chicago/Turabian Style

Renaldo, André, Adriel Roa-Bautista, Elena González-López, Marcos López-Hoyos, and David San Segundo. 2021. "Epitope-Level Matching—A Review of the Novel Concept of Eplets in Transplant Histocompatibility" Transplantology 2, no. 3: 336-347. https://doi.org/10.3390/transplantology2030033

Article Metrics

Back to TopTop