HLA-B*39:06 Efficiently Mediates Type 1 Diabetes in a Mouse Model Incorporating Reduced Thymic Insulin Expression

Advancing Animal Models of Human Type 1 Diabetes

Multiple rodent models have been developed to study the basis of type 1 diabetes (T1D). However, nonobese diabetic (NOD) mice and derivative strains still provide the gold standard for dissecting the basis of the autoimmune responses underlying T1D. Here, we review the developmental origins of NOD mice, and how they and derivative strains have been used over the past several decades to dissect the genetic and immunopathogenic basis of T1D. Also discussed are ways in which the immunopathogenic basis of T1D in NOD mice and humans are similar or differ. Additionally reviewed are efforts to "humanize" NOD mice and derivative strains to provide improved models to study autoimmune responses contributing to T1D in human patients.

HLA A*24:02-restricted T cell receptors cross-recognize bacterial and preproinsulin peptides in type 1 diabetes

CD8+ T cells destroy insulin-producing pancreatic β cells in type 1 diabetes through HLA class I-restricted presentation of self-antigens. Combinatorial peptide library screening was used to produce a preferred peptide recognition landscape for a patient-derived T cell receptor (TCR) that recognized the preproinsulin-derived (PPI-derived) peptide sequence LWMRLLPLL in the context of disease risk allele HLA A*24:02. Data were used to generate a strong superagonist peptide, enabling production of an autoimmune HLA A*24:02-peptide-TCR structure by crystal seeding. TCR binding to the PPI epitope was strongly focused on peptide residues Arg4 and Leu5, with more flexibility at other positions, allowing the TCR to strongly engage many peptides derived from pathogenic bacteria. We confirmed an epitope from Klebsiella that was recognized by PPI-reactive T cells from 3 of 3 HLA A*24:02+ patients. Remarkably, the same epitope selected T cells from 7 of 8 HLA A*24+ healthy donors that cross-reacted with PPI, leading to recognition and killing of HLA A*24:02+ cells expressing PPI. These data provide a mechanism by which molecular mimicry between pathogen and self-antigens could have resulted in the breaking of self-tolerance to initiate disease.

Fifty years of HLA-associated type 1 diabetes risk: history, current knowledge, and future directions

More than 50 years have elapsed since the association of human leukocyte antigens (HLA) with type 1 diabetes (T1D) was first reported. Since then, methods for identification of HLA have progressed from cell based to DNA based, and the number of recognized HLA variants has grown from a few to tens of thousands. Current genotyping methodology allows for exact identification of all HLA-encoding genes in an individual's genome, with statistical analysis methods evolving to digest the enormous amount of data that can be produced at an astonishing rate. The HLA region of the genome has been repeatedly shown to be the most important genetic risk factor for T1D, and the original reported associations have been replicated, refined, and expanded. Even with the remarkable progress through 50 years and over 5,000 reports, a comprehensive understanding of all effects of HLA on T1D remains elusive. This report represents a summary of the field as it evolved and as it stands now, enumerating many past and present challenges, and suggests possible paradigm shifts for moving forward with future studies in hopes of finally understanding all the ways in which HLA influences the pathophysiology of T1D.

Structural and biochemical analysis of highly similar HLA-B allotypes differentially associated with type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease involving T cell-mediated destruction of the insulin-producing beta cells in the pancreatic islets of Langerhans. CD8+ T cells, responding to beta cell peptides presented by class I major histocompatibility complex (MHC) molecules, are important effectors leading to beta cell elimination. Human leukocyte antigen (HLA) B∗39:06, B∗39:01, and B∗38:01 are closely related class I MHC allotypes that nonetheless show differential association with T1D. HLA-B∗39:06 is the most predisposing of all HLA class I molecules and is associated with early age at disease onset. B∗39:01 is also associated with susceptibility to T1D, but to a lesser extent, though differing from B∗39:06 by only two amino acids. HLA-B∗38:01, in contrast, is associated with protection from the disease. Upon identifying a peptide that binds to both HLA-B∗39:06 and B∗39:01, we determined the respective X-ray structures of the two allotypes presenting this peptide to 1.7 Å resolution. The peptide residues available for T cell receptor contact and those serving as anchors were identified. Analysis of the F pocket of HLA-B∗39:06 and B∗39:01 provided an explanation for the distinct peptide C terminus preferences of the two allotypes. Structure-based modeling of the protective HLA-B∗38:01 suggested a potential reason for its peptide preferences and its reduced propensity to present 8-mer peptides compared to B∗39:06. Notably, the three allotypes showed differential binding to peptides derived from beta cell autoantigens. Taken together, our findings should facilitate identification of disease-relevant candidate T cell epitopes and structure-guided therapeutics to interfere with peptide binding.

Human insulin as both antigen and protector in type 1 diabetes

Type 1 diabetes (T1D) is characterized by T-cell responses to islet antigens. Investigations in humans and the nonobese diabetic (NOD) mouse model of T1D have revealed that T-cell reactivity to insulin plays a central role in the autoimmune response. As there is no convenient NOD-based model to study human insulin (hIns) or its T-cell epitopes in the context of spontaneous T1D, we developed a NOD mouse strain transgenically expressing hIns in islets under the control of the human regulatory region. Female NOD.hIns mice developed T1D at approximately the same rate and overall incidence as NOD mice. Islet-infiltrating T cells from NOD.hIns mice recognized hIns peptides; both CD8 and CD4 T-cell epitopes were identified. We also demonstrate that islet-infiltrating T cells from HLA-transgenic NOD.hIns mice can be used to identify potentially patient-relevant hIns T-cell epitopes. Besides serving as an antigen, hIns was expressed in the thymus of NOD.hIns mice and could serve as a protector against T1D under certain circumstances, as previously suggested by genetic studies in humans. NOD.hIns mice and related strains facilitate human-relevant epitope discovery efforts and the investigation of fundamental questions that cannot be readily addressed in humans.

Next-generation sequencing reveals additional HLA class I and class II alleles associated with type 1 diabetes and age at onset

Introduction

Type 1 diabetes is an autoimmune disease with an significant genetic component, played mainly by the HLA class II genes. Although evidence on the role of HLA class I genes in developing type 1 diabetes and its onset have emerged, current HLA screening is limited to determining DR3 and DR4 haplotypes. This study aimed to investigate the role of HLA genes on type 1 diabetes risk and age of onset by extensive typing.

Methods

This study included 115 children and young adults with type 1 diabetes for whom typing of HLA-A, -B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, -DPA1 and -DPB1 genes was conducted using Next Generation Sequencing.

Results

We observed that 13% of type 1 diabetes subjects had non-classical HLA haplotypes that predispose to diabetes. We also found that compared to type 1 diabetes subjects with classical HLA haplotypes, non-classical HLA subjects had a significantly higher frequency of HLA-B*39:06:02 (p-value=0.01) and HLA-C*07:02:01 (p-value=0.03) alleles, known to be involved in activating the immune response. Non-classical HLA subjects also presented peculiar clinical features compared to classical HLA subjects, such as multiple diabetic antibodies and the absence of other autoimmune diseases (i.e., coeliac disease and thyroiditis). We also observed that subjects with early onset had a higher frequency of DQ2/DQ8 genotype than late-onset individuals. Moreover, subjects with late-onset had a higher frequency of alleles HLA-B*27 (p-value=0.003), HLA-C*01:02:01 (p-value=0.027) and C*02:02:02 (p-value=0.01), known to be associated with increased protection against viral infections.

Discussion

This study reveals a broader involvement of the HLA locus in the development and onset of type 1 diabetes, providing insights into new possible disease prevention and management strategies.

Viruses as a potential environmental trigger of type 1 diabetes mellitus (Review)

The etiopathogenesis of type 1 diabetes mellitus (T1DM) is a complex multifactorial process that involves an intricate network of genetic, epigenetic, immunological, and environmental factors. Despite the advances in recent years, some aspects of the mechanisms involved in triggering the disease are still unclear. Infections with certain viruses have been suggested as possible environmental triggers for the autoimmune process that leads to selective and progressive destruction of pancreatic β-cells and insufficiency of insulin production, which is its hallmark. In this review, advances in knowledge and evidence that suggest the participation of certain viruses in the mechanisms of disease initiation and progression are described. It has been accepted that environmental factors, including viruses, can initiate and possibly sustain, accelerate, or slow down the autoimmune process and consequently damage insulin-producing pancreatic β-cells. Although the role of these agents, especially human enteroviruses, has been exhaustively studied as the most likely triggers of the activation of autoimmunity that destroys pancreatic islets and leads to T1DM, certain doubts remain. Clinical epidemiological and experimental studies in humans and animals provide consistent and increasing evidence that persistent viral infections, especially with human enteroviruses and rotavirus infections, are associated with an increased risk of the disease in individuals genetically predisposed to autoimmunity.

Microbes as triggers and boosters of Type 1 Diabetes - Mediation by molecular mimicry

AIMS

Type 1 diabetes is characterized by steadily increasing incidence and largely obscured pathogenesis. Molecular mimicry is well-established as trigger for different autoimmune pathologies, but obscurely explored in the context of T1D. The presented study explores the underestimated role of molecular mimicry in T1D-etiology/progression in search for etiologic factors among human pathogens and commensals.

METHODS

A comprehensive immunoinformatics analysis of T1D-specific experimental T-cell epitopes across bacterial, fungal, and viral proteomes was performed, coupled with MHC-restricted mimotope validation and docking of most potent epitopes/mimotopes to T1D-high-risk MHCII molecules. In addition, re-analysis of the publicly available T1D-microbiota dataset was performed, including samples at the pre-T1D disease stage.

RESULTS

A number of bacterial pathogens/commensals were tagged as putative T1D triggers/boosters, including ubiquitous gut residents. The prediction of most likely mimicked epitopes revealed heat-shock proteins as most potent autoantigens for autoreactive T-cell priming via molecular mimicry. Docking revealed analogous interactions for predicted bacterial mimotopes and corresponding experimental epitopes. Finally, re-analysis of T1D gut microbiota datasets prompted pre-T1D as most significantly different/dysbiotic, compared to other explored categories (T1D stage/controls).

CONCLUSIONS

Obtained results support the unrecognized role of molecular mimicry in T1D, suggesting that autoreactive T-cell priming might be the triggering factor of disease development.

HLA-B*13, B*35 and B*39 Alleles Are Closely Associated With the Lack of Response to ART in HIV Infection: A Cohort Study in a Population of Northern Brazil

Introduction

Immune reconstitution failure after HIV treatment is a multifactorial phenomenon that may also be associated with a single polymorphism of human leukocyte antigen (HLA); however, few reports include patients from the Brazilian Amazon. Our objective was to evaluate the association of the immunogenic profile of the “classical” HLA-I and HLA-II loci with treatment nonresponse in a regional cohort monitored over 24 months since HIV diagnosis.

Materials and Methods

Treatment-free participants from reference centers in the state of Pará, Brazil, were enrolled. Infection screening was performed using enzyme immunoassays (Murex AG/AB Combination DiaSorin, UK) and confirmed by immunoblots (Bio-Manguinhos, FIOCRUZ). Plasma viral load was quantified by real-time PCR (ABBOTT, Chicago, Illinois, USA). CD4⁺/CD8⁺ T lymphocyte quantification was performed by immunophenotyping and flow cytometry (BD Biosciences, San Jose, CA, USA). Infection was monitored via test and logistics platforms (SISCEL and SICLOM). Therapeutic response failure was inferred based on CD4⁺ T lymphocyte quantification after 1 year of therapy. Loci A, B and DRB1 were genotyped using PCR-SSO (One Lambda Inc., Canoga Park, CA, USA). Statistical tests were applied using GENEPOP, GraphPad Prism 8.4.3 and BioEstat 5.3.

Results

Of the 270 patients monitored, 134 responded to treatment (CD4⁺ ≥ 500 cells/µL), and 136 did not respond to treatment (CD4⁺ < 500 cells/µL). The allele frequencies of the loci were similar to heterogeneous populations. The allelic profile of locus B was statistically associated with treatment nonresponse, and the B*13, B*35 and B*39 alleles had the greatest probabilistic influence. The B*13 allele had the highest risk of treatment nonresponse, and carriers of the allele had a detectable viral load and a CD4+ T lymphocyte count less than 400 cells/µL with up to 2 years of therapy. The B*13 allele was associated with a switch in treatment regimens, preferably to efavirenz (EFZ)-based regimens, and among those who switched regimens, half had a history of coinfection with tuberculosis.

Conclusions

The allelic variants of the B locus are more associated with non-response to therapy in people living with HIV (PLHIV) from a heterogeneous population in the Brazilian Amazon.

Genetic Modifiers of Thymic Selection and Central Tolerance in Type 1 Diabetes

Type 1 diabetes (T1D) is caused by the T cell-driven autoimmune destruction of insulin-producing cells in the pancreas. T1D served as the prototypical autoimmune disease for genome wide association studies (GWAS) after having already been the subject of many linkage and association studies prior to the development of GWAS technology. Of the many T1D-associated gene variants, a minority appear disease-specific, while most are shared with one or more other autoimmune condition. Shared disease variants suggest defects in fundamental aspects of immune tolerance. The first layer of protective tolerance induction is known as central tolerance and takes place during the thymic selection of T cells. In this article, we will review candidate genes for type 1 diabetes whose function implicates them in central tolerance. We will describe examples of gene variants that modify the function of T cells intrinsically and others that indirectly affect thymic selection. Overall, these insights will show that a significant component of the genetic risk for T1D - and autoimmunity in general - pertains to the earliest stages of tolerance induction, at a time when protective intervention may not be feasible.

Preclinical Models to Evaluate the Human Response to Autoantigen and Antigen-Specific Immunotherapy in Human Type 1 Diabetes

Type 1 Diabetes (T1D) is an autoimmune disease that results from the destruction of pancreatic islet β-cells by auto-reactive T cells. The clinical management of T1D faces the lack of fully predictive biomarkers in its preclinical stage and of antigen-specific therapies to induce or re-induce immune tolerance to β-cell autoantigens and prevent its development. From a therapeutic standpoint, preclinical models of T1D have fallen short of directly translating into humans. To circumvent this limitation, preclinical models are being optimized to allow defining autoantigen epitopes that are presented to T cells and directly apply to the human. In this review, we propose to make a point on the latest available models such as humanized immunodeficient NOD mice models and HLA and autoantigen transgenic mice and their application in the context of T1D.

A Humanized Mouse Strain That Develops Spontaneously Immune-Mediated Diabetes

To circumvent the limitations of available preclinical models for the study of type 1 diabetes (T1D), we developed a new humanized model, the YES-RIP-hB7.1 mouse. This mouse is deficient of murine major histocompatibility complex class I and class II, the murine insulin genes, and expresses as transgenes the HLA-A*02:01 allele, the diabetes high-susceptibility HLA-DQ8A and B alleles, the human insulin gene, and the human co-stimulatory molecule B7.1 in insulin-secreting cells. It develops spontaneous T1D along with CD4⁺ and CD8⁺ T-cell responses to human preproinsulin epitopes. Most of the responses identified in these mice were validated in T1D patients. This model is amenable to characterization of hPPI-specific epitopes involved in T1D and to the identification of factors that may trigger autoimmune response to insulin-secreting cells in human T1D. It will allow evaluating peptide-based immunotherapy that may directly apply to T1D in human and complete preclinical model availability to address the issue of clinical heterogeneity of human disease.

T cell receptor revision and immune repertoire changes in autoimmune diseases

Autoimmune disease (AID) is a condition in which the immune system breaks down and starts to attack the body. Some common AIDs include systemic lupus erythematosus, rheumatoid arthritis, type 1 diabetes mellitus and so forth. The changes in T-cell receptor (TCR) repertoire have been found in several autoimmune diseases, and may be responsible for the breakdown of peripheral immune tolerance. In this review, we discussed the processes of TCR revision in peripheral immune environment, the changes in TCR repertoire that occurred in various AIDs, and the specifically expanded T cell clones. We hope our discussion can provide insights for the future studies, helping with the discovery of disease biomarkers and expanding the strategies of immune-targeted therapy. HighlightsRestricted TCR repertoire and biased TCR-usage are found in a variety of AIDs.TCR repertoire shows tissue specificity in a variety of AID diseases.The relationship between TCR repertoire diversity and disease activity is still controversial in AIDs.Dominant TCR clonotypes may help to discover new disease biomarkers and expand the strategies of immune-targeted therapy.

HLA transgenic mice: application in reproducing idiosyncratic drug toxicity

Various types of transgenic mice carrying either class I or II human leukocyte antigen (HLA) molecules are readily available, and reports describing their use in a variety of studies have been published for more than 30 years. Examples of their use include the discovery of HLA-specific antigens against viral infection as well as the reproduction of HLA-mediated autoimmune diseases for the development of therapeutic strategies. Recently, HLA transgenic mice have been used to reproduce HLA-mediated idiosyncratic drug toxicity (IDT), a rare and unpredictable adverse drug reaction that can result in death. For example, abacavir-induced IDT has successfully been reproduced in HLA-B*57:01 transgenic mice. Several reports using HLA transgenic mice for IDT have proven the utility of this concept for the evaluation of IDT using various HLA allele combinations and drugs. It has become apparent that such models may be a valuable tool to investigate the mechanisms underlying HLA-mediated IDT. This review summarizes the latest findings in the area of HLA transgenic mouse models and discusses the current challenges that must be overcome to maximize the potential of this unique animal model.

New Insights into the Genetics of Latent Autoimmune Diabetes in Adults

PURPOSE OF REVIEW

Diabetes is a spectrum of clinical manifestations, including latent autoimmune diabetes in adults (LADA). However, it has been questioned whether LADA exists or simply is a group of misclassified type 1 diabetes (T1D) and type 2 diabetes (T2D) patients. This review will provide an updated overview of the genetics of LADA, highlight what genetics tell us about LADA as a diabetes subtype, and point to future directions in the study of LADA.

RECENT FINDINGS

Recent studies have verified the genetic overlap between LADA and both T1D and T2D and have contributed identification of a novel LADA-specific locus, namely, PFKFB3, and subtype-specific signatures in the HLA region. Genetic risk scores comprising T1D-risk variants have been shown to be a promising tool for discriminating diabetes subtypes and identifying patients rapidly progressing to insulin dependence. Genetic data support the existence of LADA, but further studies are needed to fully determine the place of LADA in the diabetes spectrum.

Genetic Discrimination Between LADA and Childhood-Onset Type 1 Diabetes Within the MHC

OBJECTIVE

The MHC region harbors the strongest loci for latent autoimmune diabetes in adults (LADA); however, the strength of association is likely attenuated compared with that for childhood-onset type 1 diabetes. In this study, we recapitulate independent effects in the MHC class I region in a population with type 1 diabetes and then determine whether such conditioning in LADA yields potential genetic discriminators between the two subtypes within this region.

RESEARCH DESIGN AND METHODS

Chromosome 6 was imputed using SNP2HLA, with conditional analysis performed in type 1 diabetes case subjects (n = 1,985) and control subjects (n = 2,219). The same approach was applied to a LADA cohort (n = 1,428) using population-based control subjects (n = 2,850) and in a separate replication cohort (656 type 1 diabetes case, 823 LADA case, and 3,218 control subjects).

RESULTS

The strongest associations in the MHC class II region (rs3957146, β [SE] = 1.44 [0.05]), as well as the independent effect of MHC class I genes, on type 1 diabetes risk, particularly HLA-B*39 (β [SE] = 1.36 [0.17]), were confirmed. The conditional analysis in LADA versus control subjects showed significant association in the MHC class II region (rs3957146, β [SE] = 1.14 [0.06]); however, we did not observe significant independent effects of MHC class I alleles in LADA.

CONCLUSIONS

In LADA, the independent effects of MHC class I observed in type 1 diabetes were not observed after conditioning on the leading MHC class II associations, suggesting that the MHC class I association may be a genetic discriminator between LADA and childhood-onset type 1 diabetes.

The Evolving Landscape of Autoantigen Discovery and Characterization in Type 1 Diabetes

Type 1 diabetes (T1D) is an autoimmune disease that is caused, in part, by T cell-mediated destruction of insulin-producing β-cells. High risk for disease, in those with genetic susceptibility, is predicted by the presence of two or more autoantibodies against insulin, the 65-kDa form of glutamic acid decarboxylase (GAD65), insulinoma-associated protein 2 (IA-2), and zinc transporter 8 (ZnT8). Despite this knowledge, we still do not know what leads to the breakdown of tolerance to these autoantigens, and we have an incomplete understanding of T1D etiology and pathophysiology. Several new autoantibodies have recently been discovered using innovative technologies, but neither their potential utility in monitoring disease development and treatment nor their role in the pathophysiology and etiology of T1D has been explored. Moreover, neoantigen generation (through posttranslational modification, the formation of hybrid peptides containing two distinct regions of an antigen or antigens, alternative open reading frame usage, and translation of RNA splicing variants) has been reported, and autoreactive T cells that target these neoantigens have been identified. Collectively, these new studies provide a conceptual framework to understand the breakdown of self-tolerance, if such modifications occur in a tissue- or disease-specific context. A recent workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases brought together investigators who are using new methods and technologies to identify autoantigens and characterize immune responses toward these proteins. Researchers with diverse expertise shared ideas and identified resources to accelerate antigen discovery and the detection of autoimmune responses in T1D. The application of this knowledge will direct strategies for the identification of improved biomarkers for disease progression and treatment response monitoring and, ultimately, will form the foundation for novel antigen-specific therapeutics. This Perspective highlights the key issues that were addressed at the workshop and identifies areas for future investigation.

Model validity for preclinical studies in precision medicine: precisely how precise do we need to be?

The promise of personalized medicine is that each patient’s treatment can be optimally tailored to their disease. In turn, their disease, as well as their response to the treatment, is determined by their genetic makeup and the “environment,” which relates to their general health, medical history, personal habits, and surroundings. Developing such optimized treatment strategies is an admirable goal and success stories include examples such as switching chemotherapy agents based on a patient’s tumor genotype. However, it remains a challenge to apply precision medicine to diseases for which there is no known effective treatment. Such diseases require additional research, often using experimentally tractable models. Presumably, models that recapitulate as much of the human pathophysiology as possible will be the most predictive. Here we will discuss the considerations behind such “precision models.” What sort of precision is required and under what circumstances? How can the predictive validity of such models be improved? Ultimately, there is no perfect model, but our continually improving ability to genetically engineer a variety of systems allows the generation of more and more precise models. Furthermore, our steadily increasing awareness of risk alleles, genetic background effects, multifactorial disease processes, and gene by environment interactions also allows increasingly sophisticated models that better reproduce patients’ conditions. In those cases where the research has progressed sufficiently far, results from these models appear to often be translating to effective treatments for patients.