Defining the structural basis for human alloantibody binding to human leukocyte antigen allele HLA-A*11:01

Occlusion of TCR binding to HLA-A*11:01 by a non-pathogenic human alloantibody

Over the last decades, organ transplantation has made rapid progress as a curative therapy for organ failure. However, the adaptive immune system-alloreactive T cells and antibodies targeting human leukocyte antigens (HLA)-is the leading cause of graft rejection. The presence of anti-donor HLA antibodies is considered a risk factor that disqualifies a particular donor-recipient pair. However, alloantibodies are found in some long-term graft survivors, suggesting a protective blocking function of some alloantibodies. Therefore, whether alloantibodies can have a positive as well as a negative effect in transplantation remains unclear. Here, HLA-A*11:01-specific monoclonal antibodies were generated from a human non-immune antibody library, and the effect of these antibodies was investigated on activation of A*11:01- specific T cells. We identified an A*11:01-specific monoclonal antibody with the capacity to block TCR recognition, TCR recruitment to the immune synapse, and T cell activation. The antibody reduced translocation of the transcription factor NFAT1 and phosphorylation of the MAP kinase ERK, which are both required for T cell effector function and TCR signal transduction. Cross-linking mass spectrometry was used to identify the epitope, demonstrating that this alloantibody can inhibit TCR from binding to the HLA molecule. These findings indicate that some HLA-specific alloantibodies can reduce T cell responses to the allograft. This has significant implications for interpretation of the existence of donor-specific antibodies, since some of them can protect the graft. Moreover, such antibodies may have therapeutic potential as specific treatments targeting mismatched donor HLA molecules.

HLA-EpiCheck: novel approach for HLA B-cell epitope prediction using 3D-surface patch descriptors derived from molecular dynamic simulations

Motivation

The human leukocyte antigen (HLA) system is the main cause of organ transplant loss through the recognition of HLAs present on the graft by donor-specific antibodies raised by the recipient. It is therefore of key importance to identify all potentially immunogenic B-cell epitopes on HLAs in order to refine organ allocation. Such HLAs epitopes are currently characterized by the presence of polymorphic residues called "eplets". However, many polymorphic positions in HLAs sequences are not yet experimentally confirmed as eplets associated with a HLA epitope. Moreover, structural studies of these epitopes only consider 3D static structures.

Results

We present here a machine-learning approach for predicting HLA epitopes, based on 3D-surface patches and molecular dynamics simulations. A collection of 3D-surface patches labeled as Epitope (2117) or Nonepitope (4769) according to Human Leukocyte Antigen Eplet Registry information was derived from 207 HLAs (61 solved and 146 predicted structures). Descriptors derived from static and dynamic patch properties were computed and three tree-based models were trained on a reduced non-redundant dataset. HLA-Epicheck is the prediction system formed by the three models. It leverages dynamic descriptors of 3D-surface patches for more than half of its prediction performance. Epitope predictions on unconfirmed eplets (absent from the initial dataset) are compared with experimental results and notable consistency is found.

Availability and implementation

Structural data and MD trajectories are deposited as open data under doi: 10.57745/GXZHH8. In-house scripts and machine-learning models for HLA-EpiCheck are available from https://gitlab.inria.fr/capsid.public_codes/hla-epicheck.

A new strategy for systematically classifying HLA alleles into serological specificities: Update and refinement

HLA antigens were historically defined according to the unique reactivity pattern of cells expressing HLA molecules with distinctive clusters of allo-antisera and/or monoclonal antibodies. Subsequently, amino acid residues determining epitopes (DEP) in the HLA molecule were correlated with reactivity patterns. In current clinical practice, the presence of allo-antibodies is assessed using Luminex-based solid phase single antigen bead (SAB) assays for transplantation. Recently, novel antigens were proposed for HLA molecules with DEP patterns that do not match any serologically defined antigens recognised by the WHO Nomenclature Committee. To validate the antigens, mean fluorescence intensity values of SABs tested on >13,000 patients' sera were extracted from clinical databases and analysed by scatter plots using a linear regression model. We found that when two proteins were considered as the same antigen in the original study, for example, HLA-A*02:01 and -A*02:06, their correlation ranked among the highest values at each locus. In contrast, discrete asymmetric outliers were observed when there were different antigens, for example, HLA-A*30:01 and -A*30:02, allowing validation and confirmation of 20 novel antigens for HLA-A, -B, -C and -DR. The outliers were confirmed to be true or false by flow cytometric crossmatches. In addition to the previously defined residues for antigen assignments, findings suggest that further distinction should be made for common antigens by including the substitutions at residue 67 of HLA-B, 67 and 74 of -DR. These serologic analyses can be applied systematically to identify and confirm novel antigens. These developments will lead to designing optimal SAB panels and further improving virtual donor-specific antibodies assessment.

RLpMIEC: High-Affinity Peptide Generation Targeting Major Histocompatibility Complex-I Guided and Interpreted by Interaction Spectrum-Navigated Reinforcement Learning

Major histocompatibility complex (MHC) plays a vital role in presenting epitopes (short peptides from pathogenic proteins) to T-cell receptors (TCRs) to trigger the subsequent immune responses. Vaccine design targeting MHC generally aims to find epitopes with a high binding affinity for MHC presentation. Nevertheless, to find novel epitopes usually requires high-throughput screening of bulk peptide database, which is time-consuming, labor-intensive, more unaffordable, and very expensive. Excitingly, the past several years have witnessed the great success of artificial intelligence (AI) in various fields, such as natural language processing (NLP, e.g., GPT-4), protein structure prediction and engineering (e.g., AlphaFold2), and so on. Therefore, herein, we propose a deep reinforcement-learning (RL)-based generative algorithm, RLpMIEC, to quantitatively design peptide targeting MHC-I systems. Specifically, RLpMIEC combines the energetic spectrum (namely, the molecular interaction energy component, MIEC) based on the peptide-MHC interaction and the sequence information to generate peptides with strong binding affinity and precise MIEC spectra to accelerate the discovery of candidate peptide vaccines. RLpMIEC performs well in all the generative capability evaluations and can generate peptides with strong binding affinities and precise MIECs and, moreover, with high interpretability, demonstrating its powerful capability in participation for accelerating peptide-based vaccine development.

HLA topography enforces shared and convergent immunodominant B cell and antibody alloresponses in transplant recipients

Donor-specific antibody (DSA) responses against human leukocyte antigen (HLA) proteins mismatched between kidney transplant donors and recipients cause allograft loss. The rules governing the immunogenicity of non-self donor HLA are poorly understood. Using single-cell, molecular, structural, and proteomic techniques, we profiled the HLA-specific B cell response in the kidney and blood of a transplant recipient with antibody-mediated rejection (AMR). We observed an immunodominant B cell antibody response focused on topographically exposed, solvent-accessible mismatched HLA residues along the peptide-binding groove - a subregion comprising only 20% of the HLA molecule. We further demonstrated that, even within a diverse cohort of transplant recipients, the B cell alloresponse consistently converges on this same immunodominant subregion on the crown of the HLA molecule. Based on these findings, we propose that B cell immunodominance in transplant rejection relies on antigenic topography, and we suggest that this link could be exploited for organ matching and therapeutics.

Enhancing cholangiocarcinoma immunotherapy with adoptive T cells targeting HLA-restricted neoantigen peptides derived from driver gene mutations

Precision immunotherapy, driven by genomic and bioinformatic advancements, has emerged as a promising and viable approach to combat cancer. Targeting neoantigens offers the advantage of specific immune responses with minimal off-tumor toxicity. In this study, we investigated the potential of adoptive T cells activated by HLA-restricted neoantigen peptides from driver gene mutations for treating cholangiocarcinoma (CCA), a highly aggressive cancer with poor prognosis and high mortality rates. Through whole exome sequencing of CCA cell lines, KKU-213A and KKU-100, we identified mutations in common driver genes and predicted corresponding HLA-restricted peptides. Peptides from KRAS, RNF43, and TP53 mutations exhibited strong binding affinity to HLA-A11, as validated through molecular docking and T2-cell binding assays. Dendritic cells (DCs) from healthy donors expressing HLA-A* 11:01, pulsed with individual or pooled peptides, showed comparable levels of costimulatory molecules (CD11c, CD40, CD86, and HLA-DR) to conventional DCs but higher expression of maturation markers, CD80 and CD86. Autologous HLA-A* 11:01-restricted T cells, activated by peptide-pulsed DCs, effectively lysed KKU-213A (HLA-A*11:01) cells, outperforming conventional tumor lysate-pulsed DCs. This effect was specific to HLA-A* 11:01-restricted T cells and not observed in KKU-100 (HLA-A*33:03) cells. Moreover, HLA-A* 11:01-restricted T cells exhibited elevated levels of IFN-gamma, granulysin, and granzyme B, indicating their potent anti-tumor capabilities. These findings underscore the specificity and efficiency of HLA-A* 11:01-restricted T cells targeting KRAS, RNF43, TP53 mutated CCA cells, and offer valuable insights for developing immunotherapeutic strategies and therapeutic peptide-vaccines for CCA treatment.

Hybrid structural modeling of alloantibody binding to human leukocyte antigen with rapid and reproducible cross-linking mass spectrometry

Alloantibody recognition of donor human leukocyte antigen (HLA) is associated with poor clinical transplantation outcomes. However, the molecular and structural basis for the alloantibody-HLA interaction is not well understood. Here, we used a hybrid structural modeling approach on a previously studied alloantibody-HLA interacting pair with inputs from ab initio, in silico, and in vitro data. Highly reproducible cross-linking mass spectrometry data were obtained with both discovery- and targeted mass spectrometry-based approaches approaches. The cross-link information was then used together with predicted antibody Fv structure, predicted antibody paratope, and in silico-predicted interacting surface to model the antibody-HLA interaction. This hybrid structural modeling approach closely recapitulates the key interacting residues from a previously solved crystal structure of an alloantibody-HLA-A∗11:01 pair. These results suggest that a predictive-based hybrid structural modeling approach supplemented with cross-linking mass spectrometry data can provide functionally relevant structural models to understand the structural basis of antibody-HLA mismatch in transplantation.

Epitopes, paratopes, and other topes 30 years on: Understanding what we are talking about

The question of which protein antigens, such as HLA class I or class II molecules, will bind, and how well, to a given antibody is often assumed to depend exclusively on the details of protein surface structure. These structures are usually based on static models resulting from X-ray crystallography. While these notions are useful, the ultimate causal factors determining how well a given antigen binds a given antibody are based in thermodynamics and can include atomic mobility and the time-varying conformations of proteins. In this article, fundamental biophysical principles of antibody-antigen interaction are discussed, concepts critical for a deeper understanding of the pertinent molecular phenomena are highlighted, and common misunderstandings are identified and debunked.

Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies

T-cell receptor-mimetic antibodies (TCRms) targeting disease-associated peptides presented by Major Histocompatibility Complexes (pMHCs) are set to become a major new drug modality. However, we lack a general understanding of how TCRms engage pMHC targets, which is crucial for predicting their specificity and safety. Several new structures of TCRm:pMHC complexes have become available in the past year, providing sufficient initial data for a holistic analysis of TCRms as a class of pMHC binding agents. Here, we profile the complete set of TCRm:pMHC complexes against representative TCR:pMHC complexes to quantify the TCR-likeness of their pMHC engagement. We find that intrinsic molecular differences between antibodies and TCRs lead to fundamentally different roles for their heavy/light chains and Complementarity-Determining Region loops during antigen recognition. The idiotypic properties of antibodies may increase the likelihood of TCRms engaging pMHCs with less peptide selectivity than TCRs. However, the pMHC recognition features of some TCRms, including the two TCRms currently in clinical trials, can be remarkably TCR-like. The insights gained from this study will aid in the rational design and optimisation of next-generation TCRms.

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.

HLA-DQ-Specific Recombinant Human Monoclonal Antibodies Allow for In-Depth Analysis of HLA-DQ Epitopes

HLA-DQ donor-specific antibodies (DSA) are the most prevalent type of DSA after renal transplantation and have been associated with eplet mismatches between donor and recipient HLA. Eplets are theoretically defined configurations of surface exposed amino acids on HLA molecules that require verification to confirm that they can be recognized by alloantibodies and are therefore clinically relevant. In this study, we isolated HLA-DQ specific memory B cells from immunized individuals by using biotinylated HLA-DQ monomers to generate 15 recombinant human HLA-DQ specific monoclonal antibodies (mAb) with six distinct specificities. Single antigen bead reactivity patterns were analyzed with HLA-EMMA to identify amino acids that were uniquely shared by the reactive HLA alleles to define functional epitopes which were mapped to known eplets. The HLA-DQB1*03:01-specific mAb LB_DQB0301_A and the HLA-DQB1*03-specific mAb LB_DQB0303_C supported the antibody-verification of eplets 45EV and 55PP respectively, while mAbs LB_DQB0402_A and LB_DQB0602_B verified eplet 55R on HLA-DQB1*04/05/06. For three mAbs, multiple uniquely shared amino acid configurations were identified, warranting further studies to define the inducing functional epitope and corresponding eplet. Our unique set of HLA-DQ specific mAbs will be further expanded and will facilitate the in-depth analysis of HLA-DQ epitopes, which is relevant for further studies of HLA-DQ alloantibody pathogenicity in transplantation.

Association between HLA alleles and sub-phenotype of childhood steroid-sensitive nephrotic syndrome

BACKGROUND

Few studies have addressed the effects of human leukocyte antigen (HLA) alleles on different clinical sub-phenotypes in childhood steroid-sensitive nephrotic syndrome (SSNS), including SSNS without recurrence (SSNSWR) and steroid-dependent nephrotic syndrome/frequently relapse nephrotic syndrome (SDNS/FRNS). In this study, we investigated the relationship between HLA system and children with SSNSWR and SDNS/FRNS and clarified the value of HLA allele detection for precise typing of childhood SSNS.

METHODS

A total of 241 Chinese Han individuals with SSNS were genotyped using GenCap-WES Capture Kit, and four-digit resolution HLA alleles were imputed from available Genome Wide Association data. The distribution and carrying frequency of HLA alleles in SSNSWR and SDNS/FRNS were investigated. Additionally, logistic regression and mediating effects were used to examine the relationship between risk factors for disease process and HLA system.

RESULTS

Compared with SSNSWR, significantly decreased serum levels of complement 3 (C3) and complement 4 (C4) at onset were detected in SDNS/FRNS (C3, P < 0.001; C4, P = 0.018). The average time to remission after sufficient initial steroid treatment in SDNS/FRNS was significantly longer than that in SSNSWR (P = 0.0001). Low level of C4 was further identified as an independent risk factor for SDNS/FRNS (P = 0.008, odds ratio = 0.174, 95% confidence interval 0.048-0.630). The HLA-A*11:01 allele was independently associated with SSNSWR and SDNS/FRNS (P = 0.0012 and P = 0.0006, respectively). No significant HLA alleles were detected between SSNSWR and SDNS/FRNS. In addition, a mediating effect among HLA-I alleles (HLA-B*15:11, HLA-B*44:03 and HLA-C*07:06), C4 level and SDNS/FRNS was identified.

CONCLUSIONS

HLA-I alleles provide novel genetic markers for SSNSWR and SDNS/FRNS. HLA-I antigens may be involved in steroid dependent or frequent relapse in children with SSNS as mediators of immunoregulation.

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.

Immunogenetics of heteroclitic recognition of HLA-DQB1 55R eplet specificity by human alloantibody

Heteroclitic antibodies bind to a related antigen with higher affinity than to the immunizing antigen to which they were generated. This uncommon phenomenon is not well characterized for antibodies to HLA antigens. Here we analyzed allosera reactivity from two transplant recipients sensitized to mismatched donor alleles DQB1*06:01 and DQB1*06:02 respectively. Epitope analysis demonstrated the reactivity of both sera was restricted to DQB1*04, 05, and 06 alleles, with a specificity associated with the 55R eplet. Serum from one of these subjects (TE) was significantly more reactive with DQB1*04 alleles than the immunizing DQB1*06:01 or other alleles, a pattern not present in serum from the other patient. Antibody absorption/elution experiments using B cell lines expressing DQB1*06:01 or DQB1*04:02 alleles confirmed that the heteroclitic TE antibody eluted from cells carrying DQB1*06:01 was significantly more reactive with beads carrying the DQB1*04 alleles than with the DQB1*06 or other alleles. The significantly higher reactivity of the heteroclitic alloantibody with DQB1*04 specificity was explained structurally by variations of amino acid residues within 3.5 Å of 55R. These findings have important implications for the interpretation of DQ alloantibody cross-reactivity frequently observed in transplant recipients.

A rapid simple point-of-care assay for the detection of SARS-CoV-2 neutralizing antibodies

Background

Neutralizing antibodies (NAbs) prevent pathogens from infecting host cells. Detection of SARS-CoV-2 NAbs is critical to evaluate herd immunity and monitor vaccine efficacy against SARS-CoV-2, the virus that causes COVID-19. All currently available NAb tests are lab-based and time-intensive.

Method

We develop a 10 min cellulose pull-down test to detect NAbs against SARS-CoV-2 from human plasma. The test evaluates the ability of antibodies to disrupt ACE2 receptor-RBD complex formation. The simple, portable, and rapid testing process relies on two key technologies: (i) the vertical-flow paper-based assay format and (ii) the rapid interaction of cellulose binding domain to cellulose paper.

Results

Here we show the construction of a cellulose-based vertical-flow test. The developed test gives above 80% sensitivity and specificity and up to 93% accuracy as compared to two current lab-based methods using COVID-19 convalescent plasma.

Conclusions

A rapid 10 min cellulose based test has been developed for detection of NAb against SARS-CoV-2. The test demonstrates comparable performance to the lab-based tests and can be used at Point-of-Care. Importantly, the approach used for this test can be easily extended to test RBD variants or to evaluate NAbs against other pathogens.

HLA-C and KIR permutations influence chronic obstructive pulmonary disease risk

A role for hereditary influences in the susceptibility for chronic obstructive pulmonary disease (COPD) is widely recognized. Cytotoxic lymphocytes are implicated in COPD pathogenesis, and functions of these leukocytes are modulated by interactions between their killer cell Ig-like receptors (KIR) and human leukocyte antigen–Class I (HLA–Class I) molecules on target cells. We hypothesized HLA–Class I and KIR inheritance affect risks for COPD. HLA–Class I alleles and KIR genotypes were defined by candidate gene analyses in multiple cohorts of patients with COPD (total n = 392) and control smokers with normal spirometry (total n = 342). Compared with controls, patients with COPD had overrepresentations of HLA-C*07 and activating KIR2DS1, with underrepresentations of HLA-C*12. Particular HLA-KIR permutations were synergistic; e.g., the presence of HLA-C*07 + KIR2DS1 + HLA-C12^null versus HLAC*07^null + KIR2DS1^null + HLA-C12 was associated with COPD, especially among HLA-C1 allotype homozygotes. Cytotoxicity of COPD lymphocytes was more enhanced by KIR stimulation than those of controls and was correlated with lung function. These data show HLA-C and KIR polymorphisms strongly influence COPD susceptibility and highlight the importance of lymphocyte-mediated cytotoxicity in COPD pathogenesis. Findings here also indicate that HLA-KIR typing could stratify at-risk patients and raise possibilities that HLA-KIR axis modulation may have therapeutic potential.

Matchmaker, matchmaker make me a match: Opportunities and challenges in optimizing compatibility of HLA eplets in transplantation

The development of donor-specific antibodies (DSAs) is a major complication in transplantation, which is associated with inferior graft survival, impaired quality of life, and increased healthcare costs. DSA develop upon recognition of nonself HLA by the recipient's immune system. HLA molecules contain epitopes, which are the surface regions of HLA molecules recognized by antibodies. HLAMatchmaker is an algorithm for assessing donor:recipient HLA compatibility at the level of structurally defined HLA targets called eplets. The consideration of eplets, rather than the whole HLA molecule, could offer some advantages when classifying the immune risk associated with particular donor:recipient pairs. Assessing compatibility at the level of HLA eplets could decrease misclassification of post-transplant immune risk by improving specificity, when antibodies are confirmed to be directed against donor eplets missing from the recipient's repertoire of eplets. Consideration of eplets may also increase the sensitivity of immune risk assessment, when identifying mismatched eplets that could give rise to new, not previously detected, donor-specific antibodies post-transplant. Eplet matching can serve as a rational strategy for immune risk mitigation. Herein, we review the evolution of HLA (in) compatibility assessment for organ allocation. We outline challenges in the implementation of eplet-based donor:recipient matching, including unavailability of allele-level donor genotypes for 11 HLA loci at the time of organ allocation and difficulty in assessing the hierarchy of immune risk associated with particular HLA eplet mismatches. Opportunities to address some of the current shortcomings of donor genotyping and HLAMatchmaker are also discussed. While there is a demonstrated benefit in the application of HLAMatchmaker for donor: recipient HLA (in)compatibility assessment, evolving long-read genotyping methods, compilation of large data sets with allele-level genotypes, and standardization of methods to verify eplets as determinants of immune-mediated injuries are required before HLA eplet matching is implemented in organ allocation to improve upon transplant outcomes.

HLA Risk Alleles in Aromatic Antiepileptic Drug-Induced Maculopapular Exanthema

To characterize human leukocyte antigen (HLA) loci as risk factors in aromatic antiepileptic drug-induced maculopapular exanthema (AED-MPE). A case-control study was performed to investigate HLA loci involved in AED-MPE in a southern Han Chinese population. Between January 2007 and June 2019, 267 patients with carbamazepine (CBZ), oxcarbazepine (OXC), or lamotrigine (LTG) associated MPE and 387 matched drug-tolerant controls from six centers were enrolled. HLA-A/B/C/DRB1 genotypes were determined using sequence-based typing. Potential risk alleles were validated by meta-analysis using data from different populations and in silico analysis of protein-drug interactions. HLA-DRB1*04:06 was significantly associated with OXC-MPE (p = 0.002, p _c = 0.04). HLA-B*38:02 was associated with CBZ-MPE (p = 0.03). When pooled, HLA-A*24:02, HLA-A*30:01, and HLA-B*35:01 additionally revealed significant association with AED-MPE. Logistic regression analysis showed a multiplicative interaction between HLA-A*24:02 and HLA-B*38:02 in CBZ-MPE. Meta-analysis of data from different populations revealed that HLA-24*:02 and HLA-A*30:01 were associated with AED-MPE (p = 0.02 and p = 0.04, respectively). In silico analysis of protein-drug interaction demonstrated that HLA-A*24:02 and HLA-A*30:01 had higher affinities with the three aromatic AEDs than the risk-free HLA-A allele. HLA-DRB1*04:06 showed relatively specific high affinity with S-monohydroxy derivative of OXC. HLA-DRB1*04:06 is a specific risk allele for OXC-induced MPE in the Southern Han Chinese. HLA-A*24:02, possibly HLA-A*30:01, are common risk factors for AED-MPE. The multiplicative risk potential between HLA-A*24:02 and HLA-B*38:02 suggests that patients with two risk alleles are at greater risk than those with one risk allele. Inclusion of these HLA alleles in pre-treatment screening would help estimating the risk of AED-MPE.

Generation and reactivity analysis of human recombinant monoclonal antibodies directed against epitopes on HLA-DR

In kidney transplantation, eplet mismatches between donor and recipient have been associated with de novo donor-specific antibody development. Eplets are theoretically defined configurations of polymorphic amino acids and require experimental verification to establish whether they can be bound by alloantibodies. Human HLA-specific monoclonal antibodies (mAbs) have been instrumental for this purpose but are largely lacking for HLA class II. In this study, we isolated single HLA-DR-specific memory B cells from peripheral blood of immunized individuals (n = 3) using HLA class II tetramers to generate recombinant human HLA-DR antigen-reactive mAbs (n = 5). Comparison of the amino acid composition of the reactive HLA alleles in relation to the antibody reactivity patterns led to identification of 3 configurations, 70Q 73A, 31F 32Y 37Y, and 14K 25Q recognized, respectively, by HLA-DRB1*01:01, HLA-DRB1*04:01, and HLA-DRB1*07:01 antigen-reactive mAbs. The first 2 correspond to eplets 70QA and 31FYY and can now be considered antibody verified. The latter indicates that eplet 25Q needs to be redefined before being considered as antibody verified. Generation and reactivity analysis of human HLA-DR mAbs allowed for identification of amino acid configurations corresponding to known eplets, whereas the other patterns may be used to redefine eplets with similar, but not identical predicted amino acid composition.

Defining the structural basis for human leukocyte antigen reactivity in clinical transplantation

The current state-of-the-art technology employed to assess anti-human leukocyte antigen antibodies (Anti-HLA Ab) for donor-recipient matching and patient risk stratification in renal transplantation is the single antigen bead (SAB) assay. However, there are limitations to the SAB assay as it is not quantitative and due to variations in techniques and reagents, there is no standardization across laboratories. In this study, a structurally-defined human monoclonal alloantibody was employed to provide a mechanistic explanation for how fundamental alloantibody biology influences the readout from the SAB assay. Performance of the clinical SAB assay was evaluated by altering Anti-HLA Ab concentration, subclass, and detection reagents. Tests were conducted in parallel by two internationally accredited laboratories using standardized protocols and reagents. We show that alloantibody concentration, subclass, laboratory-specific detection devices, subclass-specific detection reagents all contribute to a significant degree of variation in the readout. We report a significant prozone effect affecting HLA alleles that are bound strongly by the test alloantibody as opposed to those bound weakly and this phenomenon is independent of complement. These data highlight the importance for establishing international standards for SAB assay calibration and have significant implications for our understanding of discordance in previous studies that have analyzed its clinical relevance.

Toward defining the immunogenicity of HLA epitopes: Impact of HLA class I eplets on antibody formation during pregnancy

Eplets are functional units of structural epitopes on donor HLA, potentially recognized by complementarity-determining regions of the paratope of the recipients' B-cell receptors or antibodies (Ab). Their individual immunogenicity is poorly described, yet this feature would be of clinical importance for pretransplant risk assessment. The aim of this study was to determine the relative immunogenicity of HLA class I eplets in the pregnancy setting, where mismatched eplets are present on paternal HLA antigens of the unborn child. One hundred fifty-nine predominantly Caucasian mothers giving birth at the University Hospital Basel and their first newborns were HLA-typed at high-resolution by next-generation sequencing (NGS) (NGSgo Workflow and NGSengine from GenDx; sequencing with a Miseq from Illumina) and eplets were determined using HLAMatchmaker. HLA class I specific IgG Ab was assessed in maternal sera drawn immediately after full-term delivery, by OneLambda LABScreen single antigen ibeads. The Ab profile was subsequently evaluated for eplet-associated patterns. All 72 currently Ab-verified HLA class I eplets were examined for their immunogenicity according to the frequency of child-specific HLA Ab (CSA) directed against their structures. Four hundred twelve of 477 (86.4%) paternal HLA-A, -B or -C alleles were mismatched. CSA were present in 46 mothers (28.9%), directed against 80 (19.4%) of these mismatches. The 10 most immunogenic eplets were 62GK, 145KHA, 144TKH, 62GE, 107W, 80I, 82LR, 41T, 127K, 45KE with immunogenicity rates between 45.8% and 27.3%. This pregnancy study also identified five non-reactive eplets: 62RR, 76ESN, 80TLR, 156DA, 163RW. Based on our results, immunogenic hot and cold spots on the surface of HLA class I molecules were localized and visualized on 3D models. This study strengthens the presumption that different eplets represent different immunogenic potentials. Validation of these results in the clinical transplant setting is an essential next step in identifying those eplets representing a particularly high-risk potential.

Activating killer cell immunoglobulin-like receptors: Detection, function and therapeutic use

Killer cell immunoglobulin-like receptors (KIRs) have a central role in the control of natural killer (NK) cell function. The functions of the activating KIRs, as compared to those of the inhibitory KIR, have been more difficult to define due to difficulties in antibody-mediated identification and their apparent low affinities for HLA class I. Immunogenetic studies have shown associations of activating KIRs with the outcome of autoimmune diseases, pregnancy-associated disorders, infectious diseases and cancers. Activating KIR are thus thought to have important roles in the control of natural killer cell functions and their role in disease. In this review, we discuss current knowledge on activating KIR, their ligands and, their roles in the pathogenesis and potential therapy of human diseases.

Recombinant human monoclonal HLA antibodies of different IgG subclasses recognising the same epitope: Excellent tools to study differential effects of donor-specific antibodies

In the field of transplantation, the humoural immune response against mismatched HLA antigens of the donor is associated with inferior graft survival, but not in every patient. Donor‐specific HLA antibodies (DSA) of different immunoglobulin G (IgG) subclasses may have differential effects on the transplanted organ. Recombinant technology allows for the generation of IgG subclasses of a human monoclonal antibody (mAb), while retaining its epitope specificity. In order to enable studies on the biological function of IgG subclass HLA antibodies, we used recombinant technology to generate recombinant human HLA mAbs from established heterohybridomas. We generated all four IgG subclasses of a human HLA class I and class II mAb and showed that the different subclasses had a comparable affinity, normal human Fc glycosylation, and retained HLA epitope specificity. For both mAbs, the IgG1 and IgG3 isotypes were capable of binding complement component 3d (C3d) and efficient in complement‐dependent cell lysis against their specific targets, while the IgG2 and IgG4 subclasses were not able to induce cytotoxicity. Considering the fact that the antibody‐binding site and properties remained unaffected, these IgG subclass HLA mAbs are excellent tools to study the function of individual IgG subclass HLA class I and class II‐specific antibodies in a controlled fashion.