Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning.

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules is crucial for rational development of immunotherapies and vaccines targeting CD4+ T cell activation. So far, most prediction methods for HLA class II antigen presentation have focused on HLA-DR because of limited availability of immunopeptidomics data for HLA-DQ and HLA-DP while not taking into account alternative peptide binding modes. We present an update to the NetMHCIIpan prediction method, which closes the performance gap between all three HLA class II loci. We accomplish this by first integrating large immunopeptidomics datasets describing the HLA class II specificity space across all loci using a refined machine learning framework that accommodates inverted peptide binders. Next, we apply targeted immunopeptidomics assays to generate data that covers additional HLA-DP specificities. The final method, NetMHCIIpan-4.3, achieves high accuracy and molecular coverage across all HLA class II allotypes.

HLA DQ protein changes the cell surface distribution pattern of HLA proteins as monitored by Förster resonance energy transfer and high-resolution electron microscopy.

Peptide presentation by MHC class I and MHC class II molecules plays important roles in the regulation of the immune response. One factor in these displays is the density of antigen, which must exceed a critical threshold for the effective activation of T cells. Nonrandom distribution of MHC class I and class II has already been detected at the nanometer level and at higher hierarchical levels. It is not clear how the absence and reappearance of some protein molecules can influence the nonrandom distribution. Therefore, we performed experiments on HLA II-deficient bare lymphocyte syndrome (BLS1) cells: we created a stable transfected cell line, tDQ6-BLS-1, and were able to detect the effect of the appearance of HLA-DQ6 molecules on the homo and heteroassociation of different cell surface molecules by comparing Förster resonance energy transfer (FRET) efficiency on transfected cells to that on nontransfected BLS-1 and JY human B-cell lines. Our FRET results show a decrease in homoassociation FRET between HLA I chains in HLA-DQ6-transfected tDQ6-BLS-1 cells compared with the parent BLS-1 cell line and an increase in heteroassociation FRET between HLA I and HLA II (compared with JY cells), suggesting a similar pattern of antigen presentation by the HLA-DQ6 allele. Transmission electron microscopy (TEM) revealed that both HLA class I and class II molecules formed clusters at higher hierarchical levels on the tDQ6-BLS-1 cells, and the de novo synthesized HLA DQ molecules did not intersperse with HLA class I islands. These observations could be important in understanding the fine tuning of the immune response.

Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome.

Human leukocyte antigen (HLA) class II antigen presentation is key for controlling and triggering T cell immune responses. HLA-DQ molecules, which are believed to play a major role in autoimmune diseases, are heterodimers that can be formed as both cis and trans variants depending on whether the α- and ß-chains are encoded on the same (cis) or opposite (trans) chromosomes. So far, limited progress has been made for predicting HLA-DQ antigen presentation. In addition, the contribution of trans-only variants (i.e. variants not observed in the population as cis) in shaping the HLA-DQ immunopeptidome remains largely unresolved. Here, we seek to address these issues by integrating state-of-the-art immunoinformatics data mining models with large volumes of high-quality HLA-DQ specific mass spectrometry immunopeptidomics data. The analysis demonstrates highly improved predictive power and molecular coverage for models trained including these novel HLA-DQ data. More importantly, investigating the role of trans-only HLA-DQ variants reveals a limited to no contribution to the overall HLA-DQ immunopeptidome. In conclusion, this study furthers our understanding of HLA-DQ specificities and casts light on the relative role of cis versus trans-only HLA-DQ variants in the HLA class II antigen presentation space. The developed method, NetMHCIIpan-4.2, is available at https://services.healthtech.dtu.dk/services/NetMHCIIpan-4.2 .

Specific Genetic Polymorphisms Contributing in Differential Binding of Gliadin Peptides to HLA-DQ and TCR to Elicit Immunogenicity in Celiac Disease.

Immunogenicity of gliadin peptides in celiac disease (CD) is majorly determined by the pattern of molecular interactions with HLA-DQ and T-cell receptors (TCR). Investigation of the interactions between immune-dominant gliadin peptides, DQ protein, and TCR are warranted to unravel the basis of immunogenicity and variability contributed by the genetic polymorphisms. Homology modeling of HLA and TCR done using Swiss Model and iTASSER, respectively. Molecular interactions of eight common deamidated immune-dominant gliadin with HLA-DQ allotypes and specific TCR gene pairs were evaluated. Docking of the three structures was performed with ClusPro2.0 and ProDiGY was used to predict binding energies. Effects of known allelic polymorphisms and reported susceptibility SNPs were predicted on protein-protein interactions. CD susceptible allele, HLA-DQ2.5 was shown to have considerable binding affinity to 33-mer gliadin (ΔG = - 13.9; Kd = 1.5E - 10) in the presence of TRAV26/TRBV7. Higher binding affinity was predicted (ΔG = - 14.3, Kd = 8.9E - 11) when TRBV28 was replaced with TRBV20 paired with TRAV4 suggesting its role in CD predisposition. SNP rs12722069 at HLA-DQ8 that codes Arg76α forms three H-bonds with Glu12 and two H-bonds with Asn13 of DQ2 restricted gliadin in the presence of TRAV8-3/TRBV6. None of the HLA-DQ polymorphisms was found to be in linkage disequilibrium with reported CD susceptibility markers. Haplotypic presentations of rs12722069-G, rs1130392-C, rs3188043-C and rs4193-A with CD reported SNPs were observed in sub-ethnic groups. Highly polymorphic sites of HLA alleles and TCR variable regions could be utilized for better risk prediction models in CD. Therapeutic strategies by identifying inhibitors or blockers targeting specific gliadin:HLA-DQ:TCR binding sites could be investigated.

MHC2AffyPred: A machine-learning approach to estimate affinity of MHC class II peptides based on structural interaction fingerprints.

Understanding how MHC class II (MHC-II) binding peptides with differing lengths exhibit specific interaction at the core and extended sites within the large MHC-II pocket is a very important aspect of immunological research for designing peptides. Certain efforts were made to generate peptide conformations amenable for MHC-II binding and calculate the binding energy of such complex formation but not directed toward developing a relationship between the peptide conformation in MHC-II structures and the binding affinity (BA) (IC50 ). We present here a machine-learning approach to calculate the BA of the peptides within the MHC-II pocket for HLA-DRA1, HLA-DRB1, HLA-DP, and HLA-DQ allotypes. Instead of generating ensembles of peptide conformations conventionally, the biased mode of conformations was created by considering the peptides in the crystal structures of pMHC-II complexes as the templates, followed by site-directed peptide docking. The structural interaction fingerprints generated from such docked pMHC-II structures along with the Moran autocorrelation descriptors were trained using a random forest regressor specific to each MHC-II peptide lengths (9-19). The entire workflow is automated using Linux shell and Perl scripts to promote the utilization of MHC2AffyPred program to any characterized MHC-II allotypes and is made for free access at https://github.com/SiddhiJani/MHC2AffyPred. The MHC2AffyPred attained better performance (correlation coefficient [CC] of .612-.898) than MHCII3D (.03-.594) and NetMHCIIpan-3.2 (.289-.692) programs in the HLA-DRA1, HLA-DRB1 types. Similarly, the MHC2AffyPred program achieved CC between .91 and .98 for HLA-DP and HLA-DQ peptides (13-mer to 17-mer). Further, a case study on MHC-II binding 15-mer peptides of severe acute respiratory syndrome coronavirus-2 showed very close competency in computing the IC50 values compared to the sequence-based NetMHCIIpan v3.2 and v4.0 programs with a correlation of .998 and .570, respectively.

Structural basis of T cell receptor specificity and cross-reactivity of two HLA-DQ2.5-restricted gluten epitopes in celiac disease.

Celiac disease is a T cell-mediated chronic inflammatory condition often characterized by human leukocyte antigen (HLA)-DQ2.5 molecules presenting gluten epitopes derived from wheat, barley, and rye. Although some T cells exhibit cross-reactivity toward distinct gluten epitopes, the structural basis underpinning such cross-reactivity is unclear. Here, we investigated the T-cell receptor specificity and cross-reactivity of two immunodominant wheat gluten epitopes, DQ2.5-glia-α1a (PFPQPELPY) and DQ2.5-glia-ω1 (PFPQPEQPF). We show by surface plasmon resonance that a T-cell receptor alpha variable (TRAV) 4+-T-cell receptor beta variable (TRBV) 29-1+ TCR bound to HLA-DQ2.5-glia-α1a and HLA-DQ2.5-glia-ω1 with similar affinity, whereas a TRAV4- (TRAV9-2+) TCR recognized HLA-DQ2.5-glia-ω1 only. We further determined the crystal structures of the TRAV4+-TRBV29-1+ TCR bound to HLA-DQ2.5-glia-α1a and HLA-DQ2.5-glia-ω1, as well as the structure of an epitope-specific TRAV9-2+-TRBV7-3+ TCR-HLA-DQ2.5-glia-ω1 complex. We found that position 7 (p7) of the DQ2.5-glia-α1a and DQ2.5-glia-ω1 epitopes made very limited contacts with the TRAV4+ TCR, thereby explaining the TCR cross-reactivity across these two epitopes. In contrast, within the TRAV9-2+ TCR-HLA-DQ2.5-glia-ω1 ternary complex, the p7-Gln was situated in an electrostatic pocket formed by the hypervariable CDR3ß loop of the TCR and Arg70ß from HLA-DQ2.5, a polar network which would not be supported by the p7-Leu residue of DQ2.5-glia-α1a. In conclusion, we provide additional insights into the molecular determinants of TCR specificity and cross-reactivity to two closely-related epitopes in celiac disease.

Pathogenic T Cells in Celiac Disease Change Phenotype on Gluten Challenge: Implications for T-Cell-Directed Therapies.

Gluten-specific CD4+ T cells being drivers of celiac disease (CeD) are obvious targets for immunotherapy. Little is known about how cell markers harnessed for T-cell-directed therapy can change with time and upon activation in CeD and other autoimmune conditions. In-depth characterization of gluten-specific CD4+ T cells and CeD-associated (CD38+ and CD103+ ) CD8+ and γδ+ T cells in blood of treated CeD patients undergoing a 3 day gluten challenge is reported. The phenotypic profile of gluten-specific cells changes profoundly with gluten exposure and the cells adopt the profile of gluten-specific cells in untreated disease (CD147+ , CD70+ , programmed cell death protein 1 (PD-1)+ , inducible T-cell costimulator (ICOS)+ , CD28+ , CD95+ , CD38+ , and CD161+ ), yet with some markers being unique for day 6 cells (C-X-C chemokine receptor type 6 (CXCR6), CD132, and CD147) and with integrin α4ß7, C-C motif chemokine receptor 9 (CCR9), and CXCR3 being expressed stably at baseline and day 6. Among gluten-specific CD4+ T cells, 52% are CXCR5+ at baseline, perhaps indicative of germinal-center reactions, while on day 6 all are CXCR5- . Strikingly, the phenotypic profile of gluten-specific CD4+ T cells on day 6 largely overlaps with that of CeD-associated (CD38+ and CD103+ ) CD8+ and γδ+ T cells. The antigen-induced shift in phenotype of CD4+ T cells being shared with other disease-associated T cells is relevant for development of T-cell-directed therapies.

T cell receptor recognition of hybrid insulin peptides bound to HLA-DQ8.

HLA-DQ8, a genetic risk factor in type I diabetes (T1D), presents hybrid insulin peptides (HIPs) to autoreactive CD4+ T cells. The abundance of spliced peptides binding to HLA-DQ8 and how they are subsequently recognised by the autoreactive T cell repertoire is unknown. Here we report, the HIP (GQVELGGGNAVEVLK), derived from splicing of insulin and islet amyloid polypeptides, generates a preferred peptide-binding motif for HLA-DQ8. HLA-DQ8-HIP tetramer+ T cells from the peripheral blood of a T1D patient are characterised by repeated TRBV5 usage, which matches the TCR bias of CD4+ T cells reactive to the HIP peptide isolated from the pancreatic islets of a patient with T1D. The crystal structure of three TRBV5+ TCR-HLA-DQ8-HIP complexes shows that the TRBV5-encoded TCR ß-chain forms a common landing pad on the HLA-DQ8 molecule. The N- and C-termini of the HIP is recognised predominantly by the TCR α-chain and TCR ß-chain, respectively, in all three TCR ternary complexes. Accordingly, TRBV5 + TCR recognition of HIP peptides might occur via a 'polarised' mechanism, whereby each chain within the αßTCR heterodimer recognises distinct origins of the spliced peptide presented by HLA-DQ8.

A high-affinity human TCR-like antibody detects celiac disease gluten peptide-MHC complexes and inhibits T cell activation.

Antibodies specific for peptides bound to human leukocyte antigen (HLA) molecules are valuable tools for studies of antigen presentation and may have therapeutic potential. Here, we generated human T cell receptor (TCR)-like antibodies toward the immunodominant signature gluten epitope DQ2.5-glia-α2 in celiac disease (CeD). Phage display selection combined with secondary targeted engineering was used to obtain highly specific antibodies with picomolar affinity. The crystal structure of a Fab fragment of the lead antibody 3.C11 in complex with HLA-DQ2.5:DQ2.5-glia-α2 revealed a binding geometry and interaction mode highly similar to prototypic TCRs specific for the same complex. Assessment of CeD biopsy material confirmed disease specificity and reinforced the notion that abundant plasma cells present antigen in the inflamed CeD gut. Furthermore, 3.C11 specifically inhibited activation and proliferation of gluten-specific CD4+ T cells in vitro and in HLA-DQ2.5 humanized mice, suggesting a potential for targeted intervention without compromising systemic immunity.

Etiology of Autoimmune Islet Disease: Timing Is Everything.

Life is about timing. -Carl LewisThe understanding of autoimmune type 1 diabetes is increasing, and examining etiology separate from pathogenesis has become crucial. The components to explain type 1 diabetes development have been known for some time. The strong association with HLA has been researched for nearly 50 years. Genome-wide association studies added another 60+ non-HLA genetic factors with minor contribution to risk. Insulitis has long been known to be present close to clinical diagnosis. T and B cells recognizing ß-cell autoantigens are detectable prior to diagnosis and in newly diagnosed patients. Islet autoantibody tests against four major autoantigens have been standardized and used as biomarkers of islet autoimmunity. However, to clarify the etiology would require attention to time. Etiology may be defined as the cause of a disease (i.e., type 1 diabetes) or abnormal condition (i.e., islet autoimmunity). Timing is everything, as neither the prodrome of islet autoimmunity nor the clinical onset of type 1 diabetes tells us much about the etiology. Rather, the islet autoantibody that appears first and persists would mark the diagnosis of an autoimmune islet disease (AID). Events after the diagnosis of AID would represent the pathogenesis. Several islet autoantibodies without (stage 1) or with impaired glucose tolerance (stage 2) or with symptoms (stage 3) would define the pathogenesis culminating in clinical type 1 diabetes. Etiology would be about the timing of events that take place before the first-appearing islet autoantibody.

Nine residues in HLA-DQ molecules determine with susceptibility and resistance to type 1 diabetes among young children in Sweden.

HLA-DQ molecules account over 50% genetic risk of type 1 diabetes (T1D), but little is known about associated residues. Through next generation targeted sequencing technology and deep learning of DQ residue sequences, the aim was to uncover critical residues and their motifs associated with T1D. Our analysis uncovered (αa1, α44, α157, α196) and (ß9, ß30, ß57, ß70, ß135) on the HLA-DQ molecule. Their motifs captured all known susceptibility and resistant T1D associations. Three motifs, "DCAA-YSARD" (OR = 2.10, p = 1.96*10-20), "DQAA-YYARD" (OR = 3.34, 2.69*10-72) and "DQDA-YYARD" (OR = 3.71, 1.53*10-6) corresponding to DQ2.5 and DQ8.1 (the latter two motifs) associated with susceptibility. Ten motifs were significantly associated with resistance to T1D. Collectively, homozygous DQ risk motifs accounted for 43% of DQ-T1D risk, while homozygous DQ resistant motifs accounted for 25% protection to DQ-T1D risk. Of the identified nine residues five were within or near anchoring pockets of the antigenic peptide (α44, ß9, ß30, ß57 and ß70), one was the N-terminal of the alpha chain (αa1), one in the CD4-binding region (ß135), one in the putative cognate TCR-induced αß homodimerization process (α157), and one in the intra-membrane domain of the alpha chain (α196). Finding these critical residues should allow investigations of fundamental properties of host immunity that underlie tolerance to self and organ-specific autoimmunity.

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.

Structural Perspective of Gliadin Peptides Active in Celiac Disease.

Gluten fragments released in gut of celiac individuals activate the innate or adaptive immune systems. The molecular mechanisms associated with the adaptive response involve a series of immunodominant gluten peptides which are mainly recognized by human leucocyte antigen (HLA)-DQ2.5 and HLA-DQ8. Other peptides, such as A-gliadin P31-43, are not recognized by HLA and trigger innate responses by several routes not yet well detailed. Among the gluten fragments known to be active in Celiac disease, here we focus on the properties of all gluten peptides with known tri-dimensional structure either those locked into HLA-DQ complexes whose crystals were X-ray analyzed or characterized in solution as free forms. The aim of this work was to find the structural reasons why some gluten peptides prompt the adaptive immune systems while others do not, by apparently involving just the innate immune routes. We propose that P31-43 is a non-adaptive prompter because it is not a good ligand for HLA-DQ. Even sharing a similar ability to adopt polyproline II structure with the adaptive ones, the way in which the proline residues are located along the sequence disfavors a productive P31-43-HLA-DQ binding.

Motifs of Three HLA-DQ Amino Acid Residues (α44, ß57, ß135) Capture Full Association With the Risk of Type 1 Diabetes in DQ2 and DQ8 Children.

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next-generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1- to 18 year-old patients (n = 962) and control subjects (n = 636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically organized haplotype (HOH) association analysis allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (odds ratio [OR] 3.29, P = 2.38 * 10-85) and ß57A (OR 3.44, P = 3.80 * 10-84) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, ß57) due to complete linkage disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and ß135D to share the risk for T1D (OR 2.10, P = 1.96 * 10-20). The motif "QAD" of α44, ß57, and ß135 captured the T1D risk association of DQ8.1 (OR 3.44, P = 3.80 * 10-84), and the corresponding motif "CAD" captured the risk association of DQ2.5 (OR 2.10, P = 1.96 * 10-20). Two risk associations were related to GAD65 autoantibody (GADA) and IA-2 autoantibody (IA-2A) but in opposite directions. CAD was positively associated with GADA (OR 1.56, P = 6.35 * 10-8) but negatively with IA-2A (OR 0.59, P = 6.55 * 10-11). QAD was negatively associated with GADA (OR 0.88; P = 3.70 * 10-3) but positively with IA-2A (OR 1.64; P = 2.40 * 10-14), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential T-cell receptor contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AAs (α44, ß57, ß135) conferring T1D risk should sharpen functional and translational studies.

A molecular basis for the T cell response in HLA-DQ2.2 mediated celiac disease.

The highly homologous human leukocyte antigen (HLA)-DQ2 molecules, HLA-DQ2.5 and HLA-DQ2.2, are implicated in the pathogenesis of celiac disease (CeD) by presenting gluten peptides to CD4+ T cells. However, while HLA-DQ2.5 is strongly associated with disease, HLA-DQ2.2 is not, and the molecular basis underpinning this differential disease association is unresolved. We here provide structural evidence for how the single polymorphic residue (HLA-DQ2.5-Tyr22α and HLA-DQ2.2-Phe22α) accounts for HLA-DQ2.2 additionally requiring gluten epitopes possessing a serine at the P3 position of the peptide. In marked contrast to the biased T cell receptor (TCR) usage associated with HLA-DQ2.5-mediated CeD, we demonstrate with extensive single-cell sequencing that a diverse TCR repertoire enables recognition of the immunodominant HLA-DQ2.2-glut-L1 epitope. The crystal structure of two CeD patient-derived TCR in complex with HLA-DQ2.2 and DQ2.2-glut-L1 (PFSEQEQPV) revealed a docking strategy, and associated interatomic contacts, which was notably distinct from the structures of the TCR:HLA-DQ2.5:gliadin epitope complexes. Accordingly, while the molecular surfaces of the antigen-binding clefts of HLA-DQ2.5 and HLA-DQ2.2 are very similar, differences in the nature of the peptides presented translates to differences in responding T cell repertoires and the nature of engagement of the respective antigen-presenting molecules, which ultimately is associated with differing disease penetrance.

T cell receptor cross-reactivity between gliadin and bacterial peptides in celiac disease.

The human leukocyte antigen (HLA) locus is strongly associated with T cell-mediated autoimmune disorders. HLA-DQ2.5-mediated celiac disease (CeD) is triggered by the ingestion of gluten, although the relative roles of genetic and environmental risk factors in CeD is unclear. Here we identify microbially derived mimics of gliadin epitopes and a parental bacterial protein that is naturally processed by antigen-presenting cells and activated gliadin reactive HLA-DQ2.5-restricted T cells derived from CeD patients. Crystal structures of T cell receptors in complex with HLA-DQ2.5 bound to two distinct bacterial peptides demonstrate that molecular mimicry underpins cross-reactivity toward the gliadin epitopes. Accordingly, gliadin reactive T cells involved in CeD pathogenesis cross-react with ubiquitous bacterial peptides, thereby suggesting microbial exposure as a potential environmental factor in CeD.

Discriminative T cell recognition of cross-reactive islet-antigens is associated with HLA-DQ8 transdimer-mediated autoimmune diabetes.

Human leukocyte antigen (HLA)-DQ8 transdimer (HLA-DQA1*0501/DQB1*0302) confers exceptionally high risk in autoimmune diabetes. However, little is known about HLA-DQ8 transdimer-restricted CD4 T cell recognition, an event crucial for triggering HLA-DQ8 transdimer-specific anti-islet immunity. Here, we report a high degree of epitope overlap and T cell promiscuity between susceptible HLA-DQ8 and HLA-DQ8 transdimer. Despite preservation of putative residues for T cell receptor (TCR) contact, stronger disease-associated responses to cross-reactive, immunodominant islet epitopes are elicited by HLA-DQ8 transdimer. Mutagenesis at the α chain of HLA-DQ8 transdimer in complex with the disease-relevant GAD65250-266 peptide and in silico analysis reveal the DQ α52 residue located within the N-terminal edge of the peptide-binding cleft for the enhanced T cell reactivity, altering avidity and biophysical affinity between TCR and HLA-peptide complexes. Accordingly, a structurally promiscuous but nondegenerate TCR-HLA-peptide interface is pivotal for HLA-DQ8 transdimer-mediated autoimmune diabetes.

H1N1 hemagglutinin-specific HLA-DQ6-restricted CD4+ T cells can be readily detected in narcolepsy type 1 patients and healthy controls.

Following the 2009 H1N1 influenza pandemic, an increased risk of narcolepsy type 1 was observed. Homology between an H1N1 hemagglutinin and two hypocretin sequences has been reported. T cell reactivity to these peptides was assessed in 81 narcolepsy type 1 patients and 19 HLA-DQ6-matched healthy controls. HLA-DQ6-restricted H1N1 hemagglutinin-specific T cell responses were detected in 28.4% of patients and 15.8% of controls. Despite structural homology between HLA-DQ6-hypocretin and -H1N1 peptide complexes, T cell cross-reactivity was not detected. These results indicate that it is unlikely that cross-reactivity between H1N1 hemagglutinin and hypocretin peptides presented by HLA-DQ6 is involved in the development of narcolepsy.

Peptides identified on monocyte-derived dendritic cells: a marker for clinical immunogenicity to FVIII products.

The immunogenicity of protein therapeutics is an important safety and efficacy concern during drug development and regulation. Strategies to identify individuals and subpopulations at risk for an undesirable immune response represent an important unmet need. The major histocompatibility complex (MHC)-associated peptide proteomics (MAPPs) assay directly identifies the presence of peptides derived from a specific protein therapeutic on a donor's MHC class II (MHC-II) proteins. We applied this technique to address several questions related to the use of factor VIII (FVIII) replacement therapy in the treatment of hemophilia A (HA). Although >12 FVIII therapeutics are marketed, most fall into 3 categories: (i) human plasma-derived FVIII (pdFVIII), (ii) full-length (FL)-recombinant FVIII (rFVIII; FL-rFVIII), and (iii) B-domain-deleted rFVIII. Here, we investigated whether there are differences between the FVIII peptides found on the MHC-II proteins of the same individual when incubated with these 3 classes. Based on several observational studies and a prospective, randomized, clinical trial showing that the originally approved rFVIII products may be more immunogenic than the pdFVIII products containing von Willebrand factor (VWF) in molar excess, it has been hypothesized that the pdFVIII molecules yield/present fewer peptides (ie, potential T-cell epitopes). We have experimentally tested this hypothesis and found that dendritic cells from HA patients and healthy donors present fewer FVIII peptides when administered pdFVIII vs FL-rFVIII, despite both containing the same molar VWF excess. Our results support the hypothesis that synthesis of pdFVIII under physiological conditions could result in reduced heterogeneity and/or subtle differences in structure/conformation which, in turn, may result in reduced FVIII proteolytic processing relative to FL-rFVIII.

HLA-DR/DQ molecular mismatch: A prognostic biomarker for primary alloimmunity.

Alloimmune risk stratification in renal transplantation has lacked the necessary prognostic biomarkers to personalize recipient care or optimize clinical trials. HLA molecular mismatch improves precision compared to traditional antigen mismatch but has not been studied in detail at the individual molecule level. This study evaluated 664 renal transplant recipients and correlated HLA-DR/DQ single molecule eplet mismatch with serologic, histologic, and clinical outcomes. Compared to traditional HLA-DR/DQ whole antigen mismatch, HLA-DR/DQ single molecule eplet mismatch improved the correlation with de novo donor-specific antibody development (area under the curve 0.54 vs 0.84) and allowed recipients to be stratified into low, intermediate, and high alloimmune risk categories. These risk categories were significantly correlated with primary alloimmune events including Banff ≥1A T cell-mediated rejection (P = .0006), HLA-DR/DQ de novo donor-specific antibody development (P < .0001), antibody-mediated rejection (P < .0001), as well as all-cause graft loss (P = .0012) and each of these correlations persisted in multivariate models. Thus, HLA-DR/DQ single molecule eplet mismatch may represent a precise, reproducible, and widely available prognostic biomarker that can be applied to tailor immunosuppression or design clinical trials based on individual patient risk.