Genetics of the HLA region in the prediction of type 1 diabetes

The Current Landscape for Screening and Monitoring of Early-Stage Type 1 Diabetes

Type 1 diabetes (T1D) has two pre-symptomatic phases (stages 1 and 2) with progressive destruction of beta cells which have been identified through longitudinal cohort studies in recent decades. The definition of T1D, with hyperglycaemia that may or may not be symptomatic, is now defined as stage 3. There is growing evidence that screening for stages 1 and 2 reduces rates of diabetic ketoacidosis and prevents long-term complications. These stages can be defined by the presence of islet autoantibodies which are markers of autoimmune beta cell damage. Furthermore, genetic risk scores, which combine a variety of single nucleotide polymorphisms, identify people at high genetic risk of future T1D. Thus, they provide an opportunity to select high-risk individuals for islet autoantibody testing. Individuals identified as having stage 1 or 2 T1D require ongoing monitoring to detect hyperglycaemia and the need for insulin replacement. These individuals may also be eligible for emerging immunotherapies in future to delay progression to stage 3. This review article explores the current evidence for screening and summarises the recommended clinical care for early-stage T1D.

Advances in the Pathogenesis and Treatment Strategies for Type 1 Diabetes Mellitus

Type 1 diabetes (T1D) is a complex autoimmune disorder distinguished by the infiltration of immune cells into pancreatic islets, primarily resulting in damage to pancreatic β-cells. Despite extensive research, the precise pathogenesis of T1D remains elusive, with its etiology linked to a complex interplay of genetic, immune, and environmental factors. While genetic predispositions, such as HLA and other susceptibility genes, are necessary, they do not fully account for disease development. Environmental influences such as viral infections and dietary factors may contribute to the disease by affecting the immune system and epigenetic modifications. Additionally, endogenous retroviruses (ERVs) might play a role in T1D pathogenesis. Current therapeutic approaches, including insulin replacement therapy, immune omodulatory therapy, autoantigen immunotherapy, organ transplantation, and genetic modification, offer potential to alter disease progression but are still constrained by limitations. This review presents updated knowledge on T1D, with a focus on risk factors, predisposing hypotheses, and recent advancements in therapeutic strategies.

From Microbes to Metabolites: Advances in Gut Microbiome Research in Type 1 Diabetes

Background: Type 1 diabetes (T1D) is a severe chronic T-cell mediated autoimmune disease that attacks the insulin-producing beta cells of the pancreas. The multifactorial nature of T1D involves both genetic and environmental components, with recent research focusing on the gut microbiome as a crucial environmental factor in T1D pathogenesis. The gut microbiome and its metabolites play an important role in modulating immunity and autoimmunity. In recent years, studies have revealed significant alterations in the taxonomic and functional composition of the gut microbiome associated with the development of islet autoimmunity and T1D. These changes include reduced production of short-chain fatty acids, altered bile acid and tryptophan metabolism, and increased intestinal permeability with consequent perturbations of host (auto)immune responses. Methods/Results: In this review, we summarize and discuss recent observational, mechanistic and etiological studies investigating the gut microbiome in T1D and elucidating the intricate role of gut microbes in T1D pathogenesis. Moreover, we highlight the recent advances in intervention studies targeting the microbiota for the prevention or treatment of human T1D. Conclusions: A deeper understanding of the evolution of the gut microbiome before and after T1D onset and of the microbial signals conditioning host immunity may provide us with essential insights for exploiting the microbiome as a prognostic and therapeutic tool.

Type 1 Diabetes Genetic Risk Scores: History, Application and Future Directions

PURPOSE OF REVIEW

To review the genetics of type 1 diabetes (T1D) and T1D genetic risk scores, focusing on their development, research and clinical applications, and future directions.

RECENT FINDINGS

More than 90 genetic loci have been linked to T1D risk, with approximately half of the genetic risk attributable to the human leukocyte antigen (HLA) locus, along with non-HLA loci that have smaller effects to disease risk. The practical use of T1D genetic risk scores simplifies the complex genetic information, within the HLA and non-HLA regions, by combining the additive effect and interactions of single nucleotide polymorphisms (SNPs) associated with risk. Genetic risk scores have proven to be useful in various aspects, including classifying diabetes (e.g., distinguishing between T1D vs. neonatal, type 2 or other diabetes types), predicting the risk of developing T1D, assessing the prognosis of the clinical course (e.g., determining the risk of developing insulin dependence and glycemic control), and research into the heterogeneity of diabetes (e.g., atypical diabetes). However, there are gaps in our current knowledge including the specific sets of genes that regulate transition between preclinical stages of T1D, response to disease modifying therapies, and other outcomes of interest such as persistence of beta cell function. Several T1D genetic risk scores have been developed and shown to be valuable in various contexts, from classification of diabetes to providing insights into its etiology and predicting T1D risk across different stages of T1D. Further research is needed to develop and validate T1D genetic risk scores that are effective across all populations and ancestries. Finally, barriers such as cost, and training of medical professionals have to be addressed before the use of genetic risk scores can be incorporated into routine clinical practice.

The epidemiology of type 1 diabetes mellitus in older adults

Although type 1 diabetes mellitus (T1DM) is traditionally viewed as a youth-onset disorder, the number of older adults being diagnosed with this disease is growing. Improvements in the average life expectancy of people with T1DM have also contributed to the growing number of older people living with this disease. We summarize the evidence regarding the epidemiology (incidence, prevalence and excess mortality) of T1DM in older adults (ages ≥60 years) as well as the genetics, immunology and diagnostic challenges. Several studies report an incidence peak of T1DM in older adults of a similar size to or exceeding that in children, and population prevalence generally increases with increasing age. Glutamic acid decarboxylase antibody positivity is frequently observed in adult-onset T1DM. Guidelines for differentiating T1DM from type 2 diabetes mellitus in older adults recommend measuring levels of C-peptide and autoantibodies, including glutamic acid decarboxylase antibodies. However, there is no gold standard for differentiating T1DM from type 2 diabetes mellitus in people aged 60 years and over. As such, the global variation observed in T1DM epidemiology might be in part explained by misclassification, which increases with increasing age of diabetes mellitus onset. With a growing global population of older adults with T1DM, improved genetic and immunological evidence is needed to differentiate diabetes mellitus type at older ages so that a clear epidemiological picture can emerge.

Genetic Discovery and Risk Prediction for Type 1 Diabetes in Individuals Without High-Risk HLA-DR3/DR4 Haplotypes

OBJECTIVE

More than 10% of patients with type 1 diabetes (T1D) do not have high-risk HLA-DR3 or -DR4 haplotypes with distinct clinical features, such as later onset and reduced insulin dependence. We aimed to identify genetic drivers of T1D in the absence of DR3/DR4 and improve prediction of T1D risk in these individuals.

RESEARCH DESIGN AND METHODS

We performed T1D association and fine-mapping analyses in 12,316 non-DR3/DR4 samples. Next, we performed heterogeneity tests to examine differences in T1D risk variants in individuals without versus those with DR3/DR4 haplotypes. We further assessed genome-wide differences in gene regulatory element and biological pathway enrichments between the non-DR3/DR4 and DR3/DR4 cohorts. Finally, we developed a genetic risk score (GRS) to predict T1D in individuals without DR3/DR4 and compared with an existing T1D GRS.

RESULTS

A total of 18 T1D risk variants in non-DR3/DR4 samples were identified. Risk variants at the MHC and multiple other loci genome wide had heterogeneity in effects on T1D dependent on DR3/DR4 status, and non-DR3/DR4 T1D had evidence for a greater polygenic burden. T1D-associated variants in non-DR3/DR4 were more enriched for regulatory elements and pathways involved in antigen presentation, innate immunity, and β-cells and depleted in T cells compared with DR3/DR4. A non-DR3/DR4 GRS outperformed an existing risk score GRS2 in discriminating non-DR3/DR4 T1D from no diabetes (area under the curve 0.867; P = 7.48 × 10-32) and type 2 diabetes (0.907; P = 4.94 × 10-44).

CONCLUSIONS

In total, we identified heterogeneity in T1D genetic risk dependent on high-risk HLA-DR3/DR4 haplotype, which uncovers disease mechanisms and enables more accurate prediction of T1D across the HLA background.

Disease-modifying pharmacological treatments of type 1 diabetes: Molecular mechanisms, target checkpoints, and possible combinatorial treatments

After a century of extensive scientific investigations, there is still no curative or disease-modifying treatment available that can provide long-lasting remission for patients diagnosed with type 1 diabetes (T1D). Although T1D has historically been regarded as a classic autoimmune disorder targeting and destroying pancreatic islet β-cells, significant research has recently demonstrated that β-cells themselves also play a substantial role in the disease's progression, which could explain some of the unfavorable clinical outcomes. We offer a thorough review of scientific and clinical insights pertaining to molecular mechanisms behind pathogenesis and the different therapeutic interventions in T1D covering over 20 possible pharmaceutical intervention treatments. The interventions are categorized as immune therapies, treatments targeting islet endocrine dysfunctions, medications with dual modes of action in immune and islet endocrine cells, and combination treatments with a broader spectrum of activity. We suggest that these collective findings can provide a valuable platform to discover new combinatorial synergies in search of the curative disease-modifying intervention for T1D. SIGNIFICANCE STATEMENT: This research delves into the underlying causes of T1D and identifies critical mechanisms governing β-cell function in both healthy and diseased states. Thus, we identify specific pathways that could be manipulated by existing or new pharmacological interventions. These interventions fall into several categories: (1) immunomodifying therapies individually targeting immune cell processes, (2) interventions targeting β-cells, (3) compounds that act simultaneously on both immune cell and β-cell pathways, and (4) combinations of compounds simultaneously targeting immune and β-cell pathways.

Immunopeptidomics for autoimmunity: unlocking the chamber of immune secrets

T cells mediate pathogenesis of several autoimmune disorders by recognizing self-epitopes presented on Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) complex. The majority of autoantigens presented to T cells in various autoimmune disorders are not known, which has impeded autoantigen identification. Recent advances in immunopeptidomics have started to unravel the repertoire of antigenic epitopes presented on MHC. In several autoimmune diseases, immunopeptidomics has led to the identification of novel autoantigens and has enhanced our understanding of the mechanisms behind autoimmunity. Especially, immunopeptidomics has provided key evidence to explain the genetic risk posed by HLA alleles. In this review, we shed light on how immunopeptidomics can be leveraged to discover potential autoantigens. We highlight the application of immunopeptidomics in Type 1 Diabetes (T1D), Systemic Lupus Erythematosus (SLE), and Rheumatoid Arthritis (RA). Finally, we highlight the practical considerations of implementing immunopeptidomics successfully and the technical challenges that need to be addressed. Overall, this review will provide an important context for using immunopeptidomics for understanding autoimmunity.

Pre-Type 1 Diabetes in Adolescents and Teens: Screening, Nutritional Interventions, Beta-Cell Preservation, and Psychosocial Impacts

Type 1 Diabetes (T1D) is a progressive autoimmune disease often identified in childhood or adolescence, with early stages detectable through pre-diabetic markers such as autoantibodies and subclinical beta-cell dysfunction. The identification of the pre-T1D stage is critical for preventing complications, such as diabetic ketoacidosis, and for enabling timely interventions that may alter disease progression. This review examines the multifaceted approach to managing T1D risk in adolescents and teens, emphasizing early detection, nutritional interventions, beta-cell preservation strategies, and psychosocial support. Screening for T1D-associated autoantibodies offers predictive insight into disease risk, particularly when combined with education and family resources that promote lifestyle adjustments. Although nutritional interventions alone are not capable of preventing T1D, certain lifestyle interventions, such as weight management and specific nutritional choices, have shown the potential to preserve insulin sensitivity, reduce inflammation, and mitigate metabolic strain. Pharmacological strategies, including immune-modulating drugs like teplizumab, alongside emerging regenerative and cell-based therapies, offer the potential to delay disease onset by protecting beta-cell function. The social and psychological impacts of a T1D risk diagnosis are also significant, affecting adolescents' quality of life, family dynamics, and mental health. Supportive interventions, including counseling, cognitive-behavioral therapy (CBT), and group support, are recommended for managing the emotional burden of pre-diabetes. Future directions call for integrating universal or targeted screening programs within schools or primary care, advancing research into nutrition and psychosocial support, and promoting policies that enhance access to preventive resources. Advocacy for the insurance coverage of screening, nutritional counseling, and mental health services is also crucial to support families in managing T1D risk. By addressing these areas, healthcare systems can promote early intervention, improve beta-cell preservation, and support the overall well-being of adolescents at risk of T1D.

Association of the Immunity Genes with Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (T1D) is a complicated illness marked by the death of insulin- producing pancreatic beta cells, which ultimately leads to insulin insufficiency and hyperglycemia. T lymphocytes are considered to destroy pancreatic beta cells in the etiology of T1D as a result of hereditary and environmental factors. Although the latter factors are very important causes of T1D development, this disease is very genetically predisposed, so there is a significant genetic component to T1D susceptibility. Among the T1D-associated gene mutations, those that affect genes that encode the traditional Human Leukocyte Antigens (HLA) entail the highest risk of T1D development. Accordingly, the results of decades of genetic linkage and association studies clearly demonstrate that mutations in the HLA genes are the most associated mutations with T1D. They can, therefore, be used as biomarkers for prediction strategies and may even prove to be of value for personalized treatments. Other immunity-associated genetic loci are also associated with higher T1D risk. Indeed, T1D is considered an autoimmune disease. Its prevalence is rising globally, especially among children and young people. Given the global rise of, and thus interest in, autoimmune diseases, here we present a short overview of the link between immunity, especially HLA, genes and T1D.

Type 1 diabetes genetic risk score variation across ancestries using whole genome sequencing and array-based approaches

A Type 1 Diabetes Genetic Risk Score (T1DGRS) aids diagnosis and prediction of Type 1 Diabetes (T1D). While traditionally derived from imputed array genotypes, Whole Genome Sequencing (WGS) provides a more direct approach and is now increasingly used in clinical and research studies. We investigated the concordance between WGS-based and array-based T1DGRS across genetic ancestries in 149,265 UK Biobank participants using WGS, TOPMed-imputed, and 1000 Genomes-imputed array genotypes. In the overall cohort, WGS-based T1DGRS demonstrated strong correlation with TOPMed-imputed array-based score (r = 0.996, average WGS-based score 0.0028 standard deviations (SD) lower, p < 10- 31), while showing lower correlation with 1000 Genomes-imputed array-based scores (r = 0.981, 0.043 SD lower in WGS, p < 10- 300). Ancestry-stratified analyses between WGS-based and TOPMed-imputed array-based score showed the highest correlation with European ancestry (r = 0.996, 0.044 SD lower in WGS, p < 10- 300) followed by African ancestry (r = 0.989, 0.0193 SD lower in WGS, p < 10- 14) and South Asian ancestry (r = 0.986, 0.0129 SD lower in WGS, p < 10 - 6). These differences were more pronounced when comparing WGS based score with 1000 Genomes-imputed array-based scores (r = 0.982, 0.975, 0.957 for European, South Asian, African respectively). Population-level analysis using WGS-based T1DGRS revealed significant ancestry-based stratification, with European ancestry individuals showing the highest scores, followed by South Asian (average 0.28 SD lower than Europeans, p < 10- 58) and African ancestry individuals (average 0.89 SD lower than Europeans, p < 10- 300). Notably, when applying the European ancestry-derived 90th centile risk threshold, only 0.71% (95% CI 0.41-1.13) of African ancestry individuals and 6.4% (95% CI 5.6-7.2) of South Asian individuals were identified as high-risk, substantially below the expected 10%. In conclusion, while WGS is viable for generating T1DGRS, with TOPMed-imputed genotypes offering a cost-effective alternative, the persistence of ancestry-based variations in T1DGRS distribution even using whole genome sequencing emphasises the need for ancestry-specific or pan-ancestry standards in clinical practice.

Gut microbiota as a modulator of type 1 diabetes: A molecular perspective

Type 1 diabetes (T1D) is defined as an autoimmune metabolic disorder, characterized by destruction of pancreatic β-cells and high blood sugar levels. If left untreated, T1D results in severe health complications, including cardiovascular and kidney disease, as well as nerve damage, with ultimately grave consequences. Besides the role of genetic and certain environmental factors in T1D development, in the last decade, one new player emerged to affect T1D pathology as well, and that is a gut microbiota. Dysbiosis of gut bacteria can contribute to T1D by gut barrier disruption and the activation of autoimmune response, leading to the destruction of insulin producing cells, causing the development and aggravation of T1D symptoms. The relationship between gut microbiota and diabetes is complex and varies between individuals and additional research is needed to fully understand the effects of gut microbiome alternations in T1D pathogenesis. Therefore, the goal of this review is to understand the current knowledge in underlying molecular mechanism of gut microbiota effects, which leads to the new approaches for further studies in the prevention and treatment of T1D.

Is HLA-DQ typing useful in screening for celiac disease among Arabs with type 1 diabetes? A case-control study

OBJECTIVES

The data on the usefulness of DQ-typing in screening for celiac disease (CD) among type 1 diabetic (T1D) patients came from the West. We conducted this study among T1D patients to: (1) determine the frequency of DQ-genotypes, (2) assess the risk associated with human leukocyte antigen (HLA)-DQ genotypes, and (3) identify the cost-effective screening strategy.

METHODS

HLA-DQ genotyping was performed on 67 T1D patients with CD (cases) (mean age 15 years) and 224 T1D patients without CD (controls) (mean age 18.29 years) (2021-2023). The entry criterion for the control group was duration of T1D ≥5 years and negative annual celiac serology assay.

RESULTS

On comparison of the cases versus controls, T1D patients carrying homozygous DQ2.5 genotype (30% vs. 13.8%) or DR3-DQ2.5 haplotype (81.3% vs. 65.7%) showed significantly "higher risk" (odds ratio [OR] = 2.64, p = 0.002; OR = 2.3, p = 0.008, respectively) to develop CD. Only 4% do not harbor any of the CD-at risk genotypes (DQ2.5, DQ8, or DQ2.2) and none developed CD. Heterozygous DQ8 was associated with a significantly lower risk of developing CD with OR of 0.123 (1.5% in cases vs. 10.3% in controls, p = 0.022).

CONCLUSION

Only 4% of Saudi patients with T1D carry DQ-genotypes at no risk to develop CD, which supports the European guidelines that recommend celiac serology test as the most cost-effective screening method. We identified the risk gradient associated with DQ-genotypes to develop CD in our population which could help in counseling patients for the risk to develop CD and planning follow-up serology tests.

Inhibitory KIRs decrease HLA class II-mediated protection in Type 1 Diabetes

Inhibitory killer cell immunoglobulin-like receptors (iKIRs) are a family of inhibitory receptors that are expressed by natural killer (NK) cells and late-stage differentiated T cells. There is accumulating evidence that iKIRs regulate T cell-mediated immunity. Recently, we reported that T cell-mediated control was enhanced by iKIRs in chronic viral infections. We hypothesized that in the context of autoimmunity, where an enhanced T cell response might be considered detrimental, iKIRs would have an opposite effect. We studied Type 1 diabetes (T1D) as a paradigmatic example of autoimmunity. In T1D, variation in the Human Leucocyte Antigen (HLA) genes explains up to 50% of the genetic risk, indicating that T cells have a major role in T1D etiopathogenesis. To investigate if iKIRs affect this T cell response, we asked whether HLA associations were modified by iKIR genes. We conducted an immunogenetic analysis of a case-control T1D dataset (N = 11,961) and found that iKIR genes, in the presence of genes encoding their ligands, have a consistent and significant effect on protective HLA class II genetic associations. Our results were validated in an independent data set. We conclude that iKIRs significantly decrease HLA class II protective associations and suggest that iKIRs regulate CD4+ T cell responses in T1D.

Charting Peptide Shared Sequences Between 'Diabetes-Viruses' and Human Pancreatic Proteins, Their Structural and Autoimmune Implications

Diabetes mellitus (DM) is a metabolic syndrome characterized by hyperglycaemia, polydipsia, polyuria, and weight loss, among others. The pathophysiology for the disorders is complex and results in pancreatic abnormal function. Viruses have also been implicated in the metabolic syndrome. This study charted peptides to investigate and predict the autoimmune potential of shared sequences between 8 viral species proteins (which we termed 'diabetes-viruses') and the human pancreatic proteins. The structure and immunological relevance of shared sequences between viruses reported in DM onset and human pancreatic proteins were analysed. At nonapeptide mapping between human pancreatic protein and 'diabetic-viruses', reveal 1064 shared sequences distributed among 454 humans and 4288 viral protein sequences. The viral results showed herpesviruses, enterovirus (EV), human endogenous retrovirus, influenza A viruses, rotavirus, and rubivirus sequences are hosted by the human pancreatic protein. The most common shared nonapeptide was AAAAAAAAA, present in 30 human nonredundant sequences. Among the viral species, the shared sequence NSLEVLFQG occurred in 18 nonredundant EVs protein, while occurring merely in 1 human protein, whereas LGLDIEIAT occurred in 8 influenza A viruses overlapping to 1 human protein and KDELSEARE occurred in 2 rotaviruses. The prediction of the location of the shared sequences in the protein structures, showed most of the shared sequences are exposed and located either on the surface or cleft relative to the entire protein structure. Besides, the peptides in the viral protein shareome were predicted computationally for binding to MHC molecules. Here analyses showed that the entire 1064 shared sequences predicted 203 to be either HLA-A or B supertype-restricted epitopes. Fifty-one of the putative epitopes matched reported HLA ligands/T-cell epitopes majorly coming from EV B supertype representative allele restrictions. These data, shared sequences, and epitope charts provide important insight into the role of viruses on the onset of DM and its implications.

Proinsulin C-peptide is a major source of HLA-DQ8 restricted hybrid insulin peptides recognized by human islet-infiltrating CD4+ T cells

Type 1 diabetes (T1D) is an autoimmune disease that develops when T cells destroy the insulin-producing beta cells that reside in the pancreatic islets. Immune cells, including T cells, infiltrate the islets and gradually destroy the beta cells. Human islet-infiltrating CD4+ T cells recognize peptide epitopes derived from proinsulin, particularly C-peptide. Hybrid insulin peptides (HIPs) are neoepitopes formed by the fusion of two peptides derived from beta cell granule proteins and are known to be the targets of pathogenic CD4+ T cells in the non-obese diabetic (NOD) mouse and human islet-infiltrating CD4+ T cells. Proinsulin is widely recognized as a central antigen in T1D, but its role in forming HIPs is unclear. We developed a method to functionally screen TCRs derived from human islet-infiltrating CD4+ T cells and applied this to the identification of new proinsulin-derived HIPs. We generated a library of 4,488 candidate HIPs formed by fusion of proinsulin fragments and predicted to bind to HLA-DQ8. This library was screened against 109 islet-infiltrating CD4+ T cell receptors (TCRs) isolated from four organ donors who had T1D. We identified 13 unique HIPs recognized by nine different TCRs from two organ donors. HIP-specific T cell avatars responded specifically to a peptide extract from human islets. These new HIPs predominantly stimulated CD4+ T cell proliferation in peripheral blood mononuclear cells from individuals with T1D in contrast to HLA-matched controls. This is the first unbiased functional, islet-infiltrating T cell based, screen to identify proinsulin-derived HIPs. It has revealed many new HIPs and a central role of proinsulin C-peptide in their formation.

Status of islet transplantation and innovations to sustainable outcomes: novel sites, cell sources, and drug delivery strategies

Islet transplantation (ITx) is an effective means to restore physiologic glycemic regulation in those living with type 1 diabetes; however, there are a handful of barriers that prevent the broad application of this functionally curative procedure. The restricted cell supply, requisite for life-long toxic immunosuppression, and significant immediate and gradual graft attrition limits the procedure to only those living with brittle diabetes. While intraportal ITx is the primary clinical site, portal vein-specific factors including low oxygen tension and the instant blood-mediated inflammatory reaction are detrimental to initial engraftment and long-term function. These factors among others prevent the procedure from granting recipients long-term insulin independence. Herein, we provide an overview of the status and limitations of ITx, and novel innovations that address the shortcomings presented. Despite the marked progress highlighted in the review from as early as the initial islet tissue transplantation in 1893, ongoing efforts to improve the procedure efficacy and success are also explored. Progress in identifying unlimited cell sources, more favourable transplant sites, and novel drug delivery strategies all work to broaden ITx application and reduce adverse outcomes. Exploring combination of these approaches may uncover synergies that can further advance the field of ITx in providing sustainable functional cures. Finally, the potential of biomaterial strategies to facilitate immune evasion and local immune modulation are featured and may underpin successful application in alternative transplant sites.

HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data

Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits.

Circulating hsa-miR-320a and its regulatory network in type 1 diabetes mellitus

Introduction

Increasing evidence from human and animal model studies indicates the significant role of microRNAs (miRNAs) in pancreatic beta cell function, insulin signaling, immune responses, and pathogenesis of type 1 diabetes (T1D).

Methods

We aimed, using next-generation sequencing, to screen miRNAs from peripheral blood mononuclear cells of eight independent Kuwaiti-Arab families with T1D affected siblings, consisting of 18 T1D patients and 18 unaffected members, characterized by no parent-to-child inheritance pattern.

Results

Our analysis revealed 20 miRNAs that are differentially expressed in T1D patients compared with healthy controls. Module-based weighted gene co-expression network analysis prioritized key consensus miRNAs in T1D pathogenesis. These included hsa-miR-320a-3p, hsa-miR-139-3p, hsa-miR-200-3p, hsa-miR-99b-5p and hsa-miR-6808-3p. Functional enrichment analysis of differentially expressed miRNAs indicated that PI3K-AKT is one of the key pathways perturbed in T1D. Gene ontology analysis of hub miRNAs also implicated PI3K-AKT, along with mTOR, MAPK, and interleukin signaling pathways, in T1D. Using quantitative RT-PCR, we validated one of the key predicted miRNA-target gene-transcription factor networks in an extended cohort of children with new-onset T1D positive for islet autoantibodies. Our analysis revealed that hsa-miR-320a-3p and its key targets, including PTEN, AKT1, BCL2, FOXO1 and MYC, are dysregulated in T1D, along with their interacting partners namely BLIMP3, GSK3B, CAV1, CXCL3, TGFB, and IL10. Receiver Operating Characteristic analysis highlighted the diagnostic potential of hsa-miR-320a-3p, CAV1, GSK3B and MYC for T1D.

Discussion

Our study presents a novel link between hsa-miR-320a-3p and T1D, and highlights its key regulatory role in the network of mRNA markers and transcription factors involved in T1D pathogenesis.

Associations of classical HLA alleles with sleep behaviours

Immune dysregulation has been observed in individuals with sleep disturbance, with HLA molecules play a crucial role in the immune response. This study aimed to investigate the associations between HLA alleles and sleep behaviours, considering several environmental factors. Data were sourced from the UK Biobank. Logistic regression analyses were performed to explore the associations between 359 HLA alleles and 4 sleep behaviours, including chronotype (n = 204,636), insomnia (n = 227,553), snoring (n = 214,350) and daytime dozing (n = 227,197). Furthermore, gene-environmental interaction studies (GEIS) were conducted to evaluate the interactions of HLA alleles with environmental factors on sleep behaviours. This study analysed a total sample and subgroups stratified by sex to elucidate the impact of HLA alleles on sleep behaviours. Our findings revealed several associations between specific HLA alleles and sleep behaviours. Notably, HLA-A*23:01 was associated with evening chronotype in the total sample (OR = 0.918, 95%CI: 0.872-0.965), while HLA-A*32:01 was associated with evening chronotype in males (OR = 1.089, 95%CI: 1.037-1.144). Furthermore, GEIS identified multiple sets of interactions associated with sleep behaviours. For example, the interaction of HLA-DPA1*01:04 with alcohol consumption was associated with daytime dozing in the total sample (OR = 1.993, 95%CI: 1.351-2.941), while the interaction of HLA-DQB1*05:04 with ever suffered mental distress preventing usual activities was associated with insomnia in males (OR = 0.409, 95%CI: 0.254-0.658). Our findings highlight the involvement of HLA in sleep regulation and underscore the potential interactions between HLA alleles and environmental factors in modulating susceptibility to sleep behaviours.

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.

Immune perturbations in human pancreas lymphatic tissues prior to and after type 1 diabetes onset

Autoimmune destruction of pancreatic β cells results in type 1 diabetes (T1D), with pancreatic immune infiltrate representing a key feature in this process. Studies of human T1D immunobiology have predominantly focused on circulating immune cells in the blood, while mouse models suggest diabetogenic lymphocytes primarily reside in pancreas-draining lymph nodes (pLN). A comprehensive study of immune cells in human T1D was conducted using pancreas draining lymphatic tissues, including pLN and mesenteric lymph nodes, and the spleen from non-diabetic control, β cell autoantibody positive non-diabetic (AAb+), and T1D organ donors using complementary approaches of high parameter flow cytometry and CITEseq. Immune perturbations suggestive of a proinflammatory environment were specific for T1D pLN and AAb+ pLN. In addition, certain immune populations correlated with high T1D genetic risk independent of disease state. These datasets form an extensive resource for profiling human lymphatic tissue immune cells in the context of autoimmunity and T1D.

A structural basis of T cell cross-reactivity to native and spliced self-antigens presented by HLA-DQ8

Type 1 diabetes (T1D) is a T cell-mediated autoimmune disease that has a strong HLA association, where a number of self-epitopes have been implicated in disease pathogenesis. Human pancreatic islet-infiltrating CD4+ T cell clones not only respond to proinsulin C-peptide (PI40-54; GQVELGGGPGAGSLQ) but also cross-react with a hybrid insulin peptide (HIP; PI40-47-IAPP74-80; GQVELGGG-NAVEVLK) presented by HLA-DQ8. How T cell receptors recognize self-peptide and cross-react to HIPs is unclear. We investigated the cross-reactivity of the CD4+ T cell clones reactive to native PI40-54 epitope and multiple HIPs fused at the same N-terminus (PI40-54) to the degradation products of two highly expressed pancreatic islet proteins, neuropeptide Y (NPY68-74) and amyloid polypeptide (IAPP23-29 and IAPP74-80). We observed that five out of the seven selected SKW3 T cell lines expressing TCRs isolated from CD4+ T cells of people with T1D responded to multiple HIPs. Despite shared TRAV26-1-TRBV5-1 gene usage in some T cells, these clones cross-reacted to varying degrees with the PI40-54 and HIP epitopes. Crystal structures of two TRAV26-1+-TRBV5-1+ T cell receptors (TCRs) in complex with PI40-54 and HIPs bound to HLA-DQ8 revealed that the two TCRs had distinct mechanisms responsible for their differential recognition of the PI40-54 and HIP epitopes. Alanine scanning mutagenesis of the PI40-54 and HIPs determined that the P2, P7, and P8 residues in these epitopes were key determinants of TCR specificity. Accordingly, we provide a molecular basis for cross-reactivity towards native insulin and HIP epitopes presented by HLA-DQ8.

Predicting autoimmune diseases: A comprehensive review of classic biomarkers and advances in artificial intelligence

Autoimmune diseases comprise a spectrum of disorders characterized by the dysregulation of immune tolerance, resulting in tissue or organ damage and inflammation. Their prevalence has been on the rise, significantly impacting patients' quality of life and escalating healthcare costs. Consequently, the prediction of autoimmune diseases has recently garnered substantial interest among researchers. Despite their wide heterogeneity, many autoimmune diseases exhibit a consistent pattern of paraclinical findings that hold predictive value. From serum biomarkers to various machine learning approaches, the array of available methods has been continuously expanding. The emergence of artificial intelligence (AI) presents an exciting new range of possibilities, with notable advancements already underway. The ultimate objective should revolve around disease prevention across all levels. This review provides a comprehensive summary of the most recent data pertaining to the prediction of diverse autoimmune diseases and encompasses both traditional biomarkers and the latest innovations in AI.

A Review of Stage 0 Biomarkers in Type 1 Diabetes: The Holy Grail of Early Detection and Prevention?

Type 1 diabetes mellitus (T1D) is an incurable autoimmune disease characterized by the destruction of pancreatic islet cells, resulting in lifelong dependency on insulin treatment. There is an abundance of review articles addressing the prediction of T1D; however, most focus on the presymptomatic phases, specifically stages 1 and 2. These stages occur after seroconversion, where therapeutic interventions primarily aim to delay the onset of T1D rather than prevent it. This raises a critical question: what happens before stage 1 in individuals who will eventually develop T1D? Is there a "stage 0" of the disease, and if so, how can we detect it to increase our chances of truly preventing T1D? In pursuit of answers to these questions, this narrative review aimed to highlight recent research in the field of early detection and prediction of T1D, specifically focusing on biomarkers that can predict T1D before the onset of islet autoimmunity. Here, we have compiled influential research from the fields of epigenetics, omics, and microbiota. These studies have identified candidate biomarkers capable of predicting seroconversion from very early stages to several months prior, suggesting that the prophylactic window begins at birth. As the therapeutic landscape evolves from treatment to delay, and ideally from delay to prevention, it is crucial to both identify and validate such "stage 0" biomarkers predictive of islet autoimmunity. In the era of precision medicine, this knowledge will enable early intervention with the potential for delaying, modifying, or completely preventing autoimmunity and T1D in at-risk children.

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.

Genetic association and machine learning improves discovery and prediction of type 1 diabetes

Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can lead to novel biological and therapeutic discovery and improved risk prediction. In this study, we performed genetic association and fine-mapping analyses in 817,718 European ancestry samples genome-wide and 29,746 samples at the MHC locus, which identified 165 independent risk signals for T1D of which 19 were novel. We used risk variants to train a machine learning model (named T1GRS) to predict T1D, which highly differentiated T1D from non-disease and type 2 diabetes (T2D) in Europeans as well as African Americans at or beyond the level of current standards. We identified extensive non-linear interactions between risk loci in T1GRS, for example between HLA-DQB1*57 and INS, coding and non-coding HLA alleles, and DEXI, INS and other beta cell loci, that provided mechanistic insight and improved risk prediction. T1D individuals formed distinct clusters based on genetic features from T1GRS which had significant differences in age of onset, HbA1c, and renal disease severity. Finally, we provided T1GRS in formats to enhance accessibility of risk prediction to any user and computing environment. Overall, the improved genetic discovery and prediction of T1D will have wide clinical, therapeutic, and research applications.

Cracking the type 1 diabetes code: Genes, microbes, immunity, and the early life environment

Type 1 diabetes (T1D) results from a complex interplay of genetic predisposition, immunological dysregulation, and environmental triggers, that culminate in the destruction of insulin-secreting pancreatic β cells. This review provides a comprehensive examination of the multiple factors underpinning T1D pathogenesis, to elucidate key mechanisms and potential therapeutic targets. Beginning with an exploration of genetic risk factors, we dissect the roles of human leukocyte antigen (HLA) haplotypes and non-HLA gene variants associated with T1D susceptibility. Mechanistic insights gleaned from the NOD mouse model provide valuable parallels to the human disease, particularly immunological intricacies underlying β cell-directed autoimmunity. Immunological drivers of T1D pathogenesis are examined, highlighting the pivotal contributions of both effector and regulatory T cells and the multiple functions of B cells and autoantibodies in β-cell destruction. Furthermore, the impact of environmental risk factors, notably modulation of host immune development by the intestinal microbiome, is examined. Lastly, the review probes human longitudinal studies, unveiling the dynamic interplay between mucosal immunity, systemic antimicrobial antibody responses, and the trajectories of T1D development. Insights garnered from these interconnected factors pave the way for targeted interventions and the identification of biomarkers to enhance T1D management and prevention strategies.

Haplotype Analysis Reveals Pleiotropic Disease Associations in the HLA Region

The human leukocyte antigen (HLA) region plays an important role in human health through involvement in immune cell recognition and maturation. While genetic variation in the HLA region is associated with many diseases, the pleiotropic patterns of these associations have not been systematically investigated. Here, we developed a haplotype approach to investigate disease associations phenome-wide for 412,181 Finnish individuals and 2,459 traits. Across the 1,035 diseases with a GWAS association, we found a 17-fold average per-SNP enrichment of hits in the HLA region. Altogether, we identified 7,649 HLA associations across 647 traits, including 1,750 associations uncovered by haplotype analysis. We find some haplotypes show trade-offs between diseases, while others consistently increase risk across traits, indicating a complex pleiotropic landscape involving a range of diseases. This study highlights the extensive impact of HLA variation on disease risk, and underscores the importance of classical and non-classical genes, as well as non-coding variation.

Coxsackievirus B infection invokes unique cell-type specific responses in primary human pancreatic islets

Coxsackievirus B (CVB) infection has long been considered an environmental factor precipitating Type 1 diabetes (T1D), an autoimmune disease marked by loss of insulin-producing β cells within pancreatic islets. Previous studies have shown CVB infection negatively impacts islet function and viability but do not report on how virus infection individually affects the multiple cell types present in human primary islets. Therefore, we hypothesized that the various islet cell populations have unique transcriptional responses to CVB infection. Here, we performed single-cell RNA sequencing on human cadaveric islets treated with either CVB or poly(I:C), a viral mimic, for 24 and 48 hours. Our global analysis reveals CVB differentially induces dynamic transcriptional changes associated with multiple cell processes and functions over time whereas poly(I:C) promotes an immune response that progressively increases with treatment duration. At the single-cell resolution, we find CVB infects all islet cell types at similar rates yet induces unique cell-type specific transcriptional responses with β, α, and ductal cells having the strongest response. Sequencing and functional data suggest that CVB negatively impacts mitochondrial respiration and morphology in distinct ways in β and α cells, while also promoting the generation of reactive oxygen species. We also observe an increase in the expression of the long-noncoding RNA MIR7-3HG in β cells with high viral titers and reveal its knockdown reduces gene expression of viral proteins as well as apoptosis in stem cell-derived islets. Together, these findings demonstrate a cell-specific transcriptional, temporal, and functional response to CVB infection and provide new insights into the relationship between CVB infection and T1D.

COVID-19 and Diabetes: An Epidemiologic Overview

Past literature on the development of type 1 diabetes (T1D) and type 2 diabetes (T2D) has emphasized the influence of exogenous factors, including viral infections, in the development of these conditions. The coronavirus disease 2019 (COVID-19) pandemic again highlighted the complicated connection between viral infection and the development of diabetes. The complex interplay of proinflammatory, genetic, and socioeconomic factors can help explain the increased incidence of T1D and T2D during the pandemic. Proposed pathophysiological mechanisms connecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to T1D include the expression of angiotensin enzyme 2 receptors on pancreatic islet cells, resultant proinflammatory states, and potential transient damage caused by viral entry. The intricate web of genetic factors, social determinants of health (including the rise of obesity), and the impact of proinflammatory states during SARS-CoV-2 infection on insulin resistance suggests mechanisms linking SARS-CoV-2 infection to the development of diabetes. [Pediatr Ann. 2024;53(7):e258-e263.].

First-in-human, double-blind, randomized phase 1b study of peptide immunotherapy IMCY-0098 in new-onset type 1 diabetes: an exploratory analysis of immune biomarkers

BACKGROUND

IMCY-0098, a synthetic peptide developed to halt disease progression via elimination of key immune cells in the autoimmune cascade, has shown a promising safety profile for the treatment of type 1 diabetes (T1D) in a recent phase 1b trial. This exploratory analysis of data from that trial aimed to identify the patient biomarkers at baseline associated with a positive response to treatment and examined the associations between immune response parameters and clinical efficacy endpoints (as surrogates for mechanism of action endpoints) using an artificial intelligence-based approach of unsupervised explainable machine learning.

METHODS

We conducted an exploratory analysis of data from a phase 1b, dose-escalation, randomized, placebo-controlled study of IMCY-0098 in patients with recent-onset T1D. Here, a panel of markers of T cell activation, memory T cells, and effector T cell response were analyzed via descriptive statistics. Artificial intelligence-based analyses of associations between all variables, including immune responses and clinical responses, were performed using the Knowledge Extraction and Management (KEM®) v 3.6.2 analytical platform.

RESULTS

The relationship between all available patient data was investigated using unsupervised machine learning implemented in the KEM® environment. Of 15 associations found for the dose C group (450 μg subcutaneously followed by 3 × 225 μg subcutaneously), seven involved human leukocyte antigen (HLA) type, all of which identified improvement/absence of worsening of disease parameters in DR4+ patients and worsening/absence of improvement in DR4- patients. This association with DR4+ and non-DR3 was confirmed using the endpoints normalized area under the curve C-peptide from mixed meal tolerance tests where presence of DR4 HLA haplotype was associated with an improvement in both endpoints. Exploratory immune analysis showed that IMCY-0098 dose B (150 μg subcutaneously followed by 3 × 75 μg subcutaneously) and dose C led to an increase in presumed/potentially protective antigen-specific cytolytic CD4+ T cells and a decrease in pathogenic CD8+ T cells, consistent with the expected mechanism of action of IMCY-0098. The analysis identified significant associations between immune and clinical responses to IMCY-0098.

CONCLUSIONS

Promising preliminary efficacy results support the design of a phase 2 study of IMCY-0098 in patients with recent-onset T1D.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03272269; EudraCT: 2016-003514-27.

Association of HLA Haplotypes with Autoimmune Pathogenesis in Newly Diagnosed Type 1 Romanian Diabetic Children: A Pilot, Single-Center Cross-Sectional Study

BACKGROUND

The increasing incidence of autoimmune diseases in type 1 diabetes mellitus (T1DM) patients highlights the influence of human leukocyte antigen (HLA) haplotypes on their development. This study aims to determine genetic predisposition to autoimmune diseases in T1DM patients, including thyroid disease and celiac diseases, and explore its correlation with vitamin D deficiency.

METHODS

A cross-sectional study involving thirty-six T1DM children was conducted. Typing was performed for the HLA A, B, C, DP, DR, and DQ loci. Regression analysis linked DR-DQ haplotypes to T1DM and the associated conditions.

RESULTS

The most frequent predisposing alleles and haplotypes were HLA-DR3 (70.27%), DQ2 (70.27%), DR3-DQ2 (70.27%), DQB1*02:01 (70.27%), A02 (54.05%), whereas the most prevalent protecting allele was DPB1*04:01 (52.63%). Positive correlations were observed between positive anti-thyroid peroxidase antibodies and the absence of protective alleles (DPB1*04:02, p = 0.036; DPB1*04:01, p = 0.002). Associations were found between the absence of DPB1*04:01 and anti-thyroglobulin antibodies (p = 0.03). HLA allele DPB1*03:01 was linked with vitamin D deficiency (p = 0.021). Positive anti-transglutaminase antibodies correlated with C03:03 (p = 0.026) and DRB1*04:01-DQA1*03-DQB1*03:01 (p < 0.0001) and the lack of DQA1*01:03-DQB1*06:03-DRB1*13:01 (p < 0.0001).

CONCLUSIONS

The predisposing T1DM haplotypes were associated with the presence of anti-transglutaminase and anti-thyroid antibodies, indicating a genetic predisposition to autoimmune diseases.

Unveiling the Significance of HLA and KIR Diversity in Underrepresented Populations

Human leukocyte antigen (HLA) molecules and their relationships with natural killer (NK) cells, specifically through their interaction with killer-cell immunoglobulin-like receptors (KIRs), exhibit robust associations with the outcomes of diverse diseases. Moreover, genetic variations in HLA and KIR immune system genes offer limitless depths of complexity. In recent years, a surge of high-powered genome-wide association studies (GWASs) utilizing single nucleotide polymorphism (SNP) arrays has occurred, significantly advancing our understanding of disease pathogenesis. Additionally, advances in HLA reference panels have enabled higher resolution and more reliable imputation, allowing for finer-grained evaluation of the association between sequence variations and disease risk. However, it is essential to note that the majority of these GWASs have focused primarily on populations of Caucasian and Asian origins, neglecting underrepresented populations in Latin America and Africa. This omission not only leads to disparities in health care access but also restricts our knowledge of novel genetic variants involved in disease pathogenesis within these overlooked populations. Since the KIR and HLA haplotypes prevalent in each population are clearly modelled by the specific environment, the aim of this review is to encourage studies investigating HLA/KIR involvement in infection and autoimmune diseases, reproduction, and transplantation in underrepresented populations.

Human inherited PD-L1 deficiency is clinically and immunologically less severe than PD-1 deficiency

We previously reported two siblings with inherited PD-1 deficiency who died from autoimmune pneumonitis at 3 and 11 years of age after developing other autoimmune manifestations, including type 1 diabetes (T1D). We report here two siblings, aged 10 and 11 years, with neonatal-onset T1D (diagnosed at the ages of 1 day and 7 wk), who are homozygous for a splice-site variant of CD274 (encoding PD-L1). This variant results in the exclusive expression of an alternative, loss-of-function PD-L1 protein isoform in overexpression experiments and in the patients' primary leukocytes. Surprisingly, cytometric immunophenotyping and single-cell RNA sequencing analysis on blood leukocytes showed largely normal development and transcriptional profiles across lymphoid and myeloid subsets in the PD-L1-deficient siblings, contrasting with the extensive dysregulation of both lymphoid and myeloid leukocyte compartments in PD-1 deficiency. Our findings suggest that PD-1 and PD-L1 are essential for preventing early-onset T1D but that, unlike PD-1 deficiency, PD-L1 deficiency does not lead to fatal autoimmunity with extensive leukocytic dysregulation.

The immunology of type 1 diabetes

Following the seminal discovery of insulin a century ago, treatment of individuals with type 1 diabetes (T1D) has been largely restricted to efforts to monitor and treat metabolic glucose dysregulation. The recent regulatory approval of the first immunotherapy that targets T cells as a means to delay the autoimmune destruction of pancreatic β-cells highlights the critical role of the immune system in disease pathogenesis and tends to pave the way for other immune-targeted interventions for T1D. Improving the efficacy of such interventions across the natural history of the disease will probably require a more detailed understanding of the immunobiology of T1D, as well as technologies to monitor residual β-cell mass and function. Here we provide an overview of the immune mechanisms that underpin the pathogenesis of T1D, with a particular emphasis on T cells.

Polymorphism in F pocket affects peptide selection and stability of type 1 diabetes-associated HLA-B39 allotypes

HLA-B*39:06, HLA-B*39:01, and HLA-B*38:01 are closely related HLA allotypes differentially associated with type 1 diabetes (T1D) risk and progression. B*39:06 is highly predisposing, while B*39:01 and B*38:01 are weakly predisposing and protective allotypes, respectively. Here, we aimed to decipher molecular mechanisms underlying the differential association of these allotypes with T1D pathogenesis. We addressed peptide binding and conformational stability of HLA-B allotypes using computational and experimental approaches. Computationally, we found that B*39:06 and B*39:01 allotypes had more rigid peptide-binding grooves and were more promiscuous in binding peptides than B*38:01. Peptidomes of B*39:06 and B*39:01 contained fewer strong binders and were of lower affinity than that of B*38:01. Experimentally, we demonstrated that B*39:06 and B*39:01 had a higher capacity to bind peptides and exit to the cell surface but lower surface levels and were degraded faster than B*38:01. In summary, we propose that promiscuous B*39:06 and B*39:01 may bind suboptimal peptides and transport them the cell surface, where such unstable complexes may contribute to the pathogenesis of T1D.

Shared and distinct genetics of pure type 1 diabetes and type 1 diabetes with celiac disease, homology in their auto-antigens and immune dysregulation states: a study from North India

AIM

This study was undertaken to explicate the shared and distinctive genetic susceptibility and immune dysfunction in patients with T1D alone and T1D with CD (T1D + CD).

METHODS

A total of 100 T1D, 50 T1D + CD and 150 healthy controls were recruited. HLA-DRB1/DQB1 alleles were determined by PCR-sequence-specific primer method, SNP genotyping for CTLA-4 and PTPN22 was done by simple probe-based SNP-array and genotyping for INS-23 Hph1 A/T was done by RFLP. Autoantibodies and cytokine estimation was done by ELISA. Immune-regulation was analysed by flow-cytometry. Clustering of autoantigen epitopes was done by epitope cluster analytical tool.

RESULTS

Both T1D alone and T1D + CD had a shared association of DRB1*03:01, DRB1*04, DRB3*01:07/15 and DQB1*02. DRB3*01:07/15 confers the highest risk for T1D with relative risk of 11.32 (5.74-22.31). Non-HLA gene polymorphisms PTPN22 and INS could discriminate between T1D and T1D + CD. T1D + CD have significantly higher titers of autoantibodies, expression of costimulatory molecules on CD4 and CD8 cells, and cytokine IL-17A and TGF-β1 levels compared to T1D patients. Epitopes from immunodominant regions of autoantigens of T1D and CD clustered together with 40% homology.

CONCLUSION

Same HLA genes provide susceptibility for both T1D and CD. Non-HLA genes CTLA4, PTPN22 and INS provide further susceptibility while different polymorphisms in PTPN22 and INS can discriminate between T1D and T1D + CD. Epitope homology between autoantigens of two diseases further encourages the two diseases to occur together. The T1D + CD being more common in females along with co-existence of thyroid autoimmunity, and have more immune dysregulated state than T1D alone.

CD4+ T Cells From Individuals With Type 1 Diabetes Respond to a Novel Class of Deamidated Peptides Formed in Pancreatic Islets

The β-cell plays a crucial role in the pathogenesis of type 1 diabetes, in part through the posttranslational modification of self-proteins by biochemical processes such as deamidation. These neoantigens are potential triggers for breaking immune tolerance. We report the detection by LC-MS/MS of 16 novel Gln and 27 novel Asn deamidations in 14 disease-related proteins within inflammatory cytokine-stressed human islets of Langerhans. T-cell clones responsive against one Gln- and three Asn-deamidated peptides could be isolated from peripheral blood of individuals with type 1 diabetes. Ex vivo HLA class II tetramer staining detected higher T-cell frequencies in individuals with the disease compared with control individuals. Furthermore, there was a positive correlation between the frequencies of T cells specific for deamidated peptides, insulin antibody levels at diagnosis, and duration of disease. These results highlight that stressed human islets are prone to enzymatic and biochemical deamidation and suggest that both Gln- and Asn-deamidated peptides can promote the activation and expansion of autoreactive CD4+ T cells. These findings add to the growing evidence that posttranslational modifications undermine tolerance and may open the road for the development of new diagnostic and therapeutic applications for individuals living with type 1 diabetes.

ARTICLE HIGHLIGHTS

An Insulin-Chromogranin A Hybrid Peptide Activates DR11-Restricted T Cells in Human Type 1 Diabetes

Hybrid insulin peptides (HIPs) formed through covalent cross-linking of proinsulin fragments to secretory granule peptides are detectable within murine and human islets. The 2.5HIP (C-peptide-chromogranin A [CgA] HIP), recognized by the diabetogenic BDC-2.5 clone, is a major autoantigen in the nonobese diabetic mouse. However, the relevance of this epitope in human disease is currently unclear. A recent study probed T-cell reactivity toward HIPs in patients with type 1 diabetes, documenting responses in one-third of the patients and isolating several HIP-reactive T-cell clones. In this study, we isolated a novel T-cell clone and showed that it responds vigorously to the human equivalent of the 2.5HIP (designated HIP9). Although the responding patient carried the risk-associated DRB1*04:01/DQ8 haplotype, the response was restricted by DRB1*11:03 (DR11). HLA class II tetramer staining revealed higher frequencies of HIP9-reactive T cells in individuals with diabetes than in control participants. Furthermore, in DR11+ participants carrying the DRB4 allele, HIP9-reactive T-cell frequencies were higher than observed frequencies for the immunodominant proinsulin 9-28 epitope. Finally, there was a negative correlation between HIP9-reactive T-cell frequency and age at diagnosis. These results provide direct evidence that this C-peptide-CgA HIP is relevant in human type 1 diabetes and suggest a mechanism by which nonrisk HLA haplotypes may contribute to the development of β-cell autoimmunity.

ARTICLE HIGHLIGHTS

Checkpoint Inhibitor-Associated Autoimmune Diabetes Mellitus Is Characterized by C-peptide Loss and Pancreatic Atrophy

OBJECTIVE

To conduct a multicenter case series characterizing the clinical characteristics at presentation and pancreatic volume changes of patients with checkpoint inhibitor-associated autoimmune diabetes (CIADM).

RESEARCH DESIGN AND METHODS

Electronic medical records were reviewed with 36 consecutive patients identified with CIADM, as defined by (1) previous immune checkpoint inhibitor (ICI) therapy, (2) new-onset hyperglycemia (blood glucose level ≥ 11.1 mmol/L and/or glycosylated hemoglobin ≥ 6.5%), and (3) insulin deficiency [C-peptide <0.4 nmol/L or diabetic ketoacidosis (DKA)] within 1 month of presentation. Pancreatic volume was available and measured using computed tomography volumetry for 17 patients with CIADM and 3 sets of control patients: 7 with ICI-related pancreatitis, 13 with asymptomatic ICI-related lipase elevation, and 11 ICI-treated controls for comparison.

RESULTS

All patients had either anti-programmed cell death protein 1 or anti-programmed cell death ligand 1 therapy. Median time from ICI commencement to CIADM diagnosis was 15 weeks. At presentation, 25 (69%) had DKA, 27 (84%) had low C-peptide, and, by 1 month, 100% had low C-peptide. Traditional type 1 diabetes autoantibodies were positive in 15/35 (43%). Lipase was elevated in 13/27 (48%) at presentation. In 4 patients with longitudinal lipase testing, elevated levels peaked 1 month prior to CIADM diagnosis. Pancreatic volume was lower pre-ICI in CIADM patients compared with controls and demonstrated a mean decline of 41% from pretreatment to 6 months post-CIADM diagnosis.

CONCLUSION

Pronounced biochemical and radiologic changes occur during CIADM pathogenesis. Rapid loss of C-peptide is a distinct characteristic that can be used to aid diagnosis as autoantibodies are often negative.

Differences in F pocket impact on HLA I genetic associations with autoimmune diabetes

Introduction

Human leukocyte antigen (HLA) I molecules present antigenic peptides to activate CD8+ T cells. Type 1 Diabetes (T1D) is an auto-immune disease caused by aberrant activation of the CD8+ T cells that destroy insulin-producing pancreatic β cells. Some HLA I alleles were shown to increase the risk of T1D (T1D-predisposing alleles), while some reduce this risk (T1D-protective alleles).

Methods

Here, we compared the T1D-predisposing and T1D-protective allotypes concerning peptide binding, maturation, localization and surface expression and correlated it with their sequences and energetic profiles using experimental and computational methods.

Results

T1D-predisposing allotypes had more peptide-bound forms and higher plasma membrane levels than T1D-protective allotypes. This was related to the fact that position 116 within the F pocket was more conserved and made more optimal contacts with the neighboring residues in T1D-predisposing allotypes than in protective allotypes.

Conclusion

Our work uncovers that specific polymorphisms in HLA I molecules potentially influence their susceptibility to T1D.

High Frequency of Recessive WFS1 Mutations Among Indian Children With Islet Antibody-negative Type 1 Diabetes

BACKGROUND

While the frequency of islet antibody-negative (idiopathic) type 1 diabetes mellitus (T1DM) is reported to be increased in Indian children, its aetiology has not been studied. We investigated the role of monogenic diabetes in the causation of islet antibody-negative T1DM.

METHODS

We conducted a multicenter, prospective, observational study of 169 Indian children (age 1-18 years) with recent-onset T1DM. All were tested for antibodies against GAD65, islet antigen-2, and zinc transporter 8 using validated ELISA. Thirty-four islet antibody-negative children underwent targeted next-generation sequencing for 31 genes implicated in monogenic diabetes using the Illumina platform. All mutations were confirmed by Sanger sequencing.

RESULTS

Thirty-five (21%) children were negative for all islet antibodies. Twelve patients (7% of entire cohort, 34% of patients with islet antibody-negative T1DM) were detected to have pathogenic or likely pathogenic genetic variants. The most frequently affected locus was WFS1, with 9 patients (5% of entire cohort, 26% of islet antibody-negative). These included 7 children with homozygous and 1 patient each with a compound heterozygous and heterozygous mutation. Children with Wolfram syndrome 1 (WS) presented with severe insulin-requiring diabetes (including 3 patients with ketoacidosis), but other syndromic manifestations were not detected. In 3 patients, heterozygous mutations in HNF4A, ABCC8, and PTF1A loci were detected.

CONCLUSION

Nearly one-quarter of Indian children with islet antibody-negative T1DM had recessive mutations in the WFS1 gene. These patients did not exhibit other features of WS at the time of diagnosis. Testing for monogenic diabetes, especially WS, should be considered in Indian children with antibody-negative T1DM.

Investigating the genetic makeup of the major histocompatibility complex (MHC) in the United Arab Emirates population through next-generation sequencing

The Human leukocyte antigen (HLA) molecules are central to immune response and have associations with the phenotypes of various diseases and induced drug toxicity. Further, the role of HLA molecules in presenting antigens significantly affects the transplantation outcome. The objective of this study was to examine the extent of the diversity of HLA alleles in the population of the United Arab Emirates (UAE) using Next-Generation Sequencing methodologies and encompassing a larger cohort of individuals. A cohort of 570 unrelated healthy citizens of the UAE volunteered to provide samples for Whole Genome Sequencing and Whole Exome Sequencing. The definition of the HLA alleles was achieved through the application of the bioinformatics tools, HLA-LA and xHLA. Subsequently, the findings from this study were compared with other local and international datasets. A broad range of HLA alleles in the UAE population, of which some were previously unreported, was identified. A comparison with other populations confirmed the current population's unique intertwined genetic heritage while highlighting similarities with populations from the Middle East region. Some disease-associated HLA alleles were detected at a frequency of > 5%, such as HLA-B*51:01, HLA-DRB1*03:01, HLA-DRB1*15:01, and HLA-DQB1*02:01. The increase in allele homozygosity, especially for HLA class I genes, was identified in samples with a higher level of genome-wide homozygosity. This highlights a possible effect of consanguinity on the HLA homozygosity. The HLA allele distribution in the UAE population showcases a unique profile, underscoring the need for tailored databases for traditional activities such as unrelated transplant matching and for newer initiatives in precision medicine based on specific populations. This research is part of a concerted effort to improve the knowledge base, particularly in the fields of transplant medicine and investigating disease associations as well as in understanding human migration patterns within the Arabian Peninsula and surrounding regions.

Gene-environment interaction in the pathophysiology of type 1 diabetes

Type 1 diabetes (T1D) is a complex metabolic autoimmune disorder that affects millions of individuals worldwide and often leads to significant comorbidities. However, the precise trigger of autoimmunity and disease onset remain incompletely elucidated. This integrative perspective article synthesizes the cumulative role of gene-environment interaction in the pathophysiology of T1D. Genetics plays a significant role in T1D susceptibility, particularly at the major histocompatibility complex (MHC) locus and cathepsin H (CTSH) locus. In addition to genetics, environmental factors such as viral infections, pesticide exposure, and changes in the gut microbiome have been associated with the development of T1D. Alterations in the gut microbiome impact mucosal integrity and immune tolerance, increasing gut permeability through molecular mimicry and modulation of the gut immune system, thereby increasing the risk of T1D potentially through the induction of autoimmunity. HLA class II haplotypes with known effects on T1D incidence may directly correlate to changes in the gut microbiome, but precisely how the genes influence changes in the gut microbiome, and how these changes provoke T1D, requires further investigations. These gene-environment interactions are hypothesized to increase susceptibility to T1D through epigenetic changes such as DNA methylation and histone modification, which in turn modify gene expression. There is a need to determine the efficacy of new interventions that target these epigenetic modifications such as "epidrugs", which will provide novel avenues for the effective management of T1D leading to improved quality of life of affected individuals and their families/caregivers.

A new, all-encompassing aetiology of type 1 diabetes

The aetiology of type 1 diabetes (T1D) is considered multifactorial with the contribution of the MHC on chromosome 6 being most important. Multiple factors also contribute to the aetiology of colorectal neoplasia, but the final event causing the change from normal mucosa to polyp and from polyp to cancer is due to a single somatic mutation event. Repeated formation of colorectal neoplasia within an at-risk population results in a predictable, tapering, exponential neoplasia distribution. Critical mutations driving colorectal neoplasia formation occur in mutation-prone DNA. These observations led to three hypotheses related to T1D. First, a single somatic mutation within the MHC of antigen presenting cells results in a change in phenotype from normal to T1D. Second, the distribution of additional autoimmune diseases (AAIDs) among persons with T1D adheres to a predictable, tapering, exponential distribution. And third, critical mutations driving development of T1D occur in mutation-prone DNA. To address the hypotheses in an orderly fashion, a new analytical method called genome-wide aetiology analysis (GWEA) consisting of nine steps is presented. All data required for GWEA of T1D are obtained from peer-reviewed publications or publicly available genome and proteome databases. Critical GWEA steps include AAID distribution among persons with T1D, analysis of at-risk HLA loci for mutation-prone DNA, determination of the role of non-MHC genes on GWAS, and verification of human data by cell culture or animal experiments. GWEA results show that distribution of AAID among persons with T1D adheres to a predictable, tapering, exponential distribution. A single, critical, somatic mutation within the epitope-binding groove of at-risk HLA loci alters HLA-insulin-peptide-T-cell-receptor (TCR) complex binding affinity and creates a new pathway that leads to loss of self-tolerance. The at-risk HLA loci, in particular binding pockets P1, P4 and P9, are encoded by mutation-prone DNA: GC-rich DNA sequence and somatic hypermutation hotspots. All other genes on GWAS can but do not have to amplify the new autoimmune pathway by facilitating DNA mutations, changing peptide binding affinity, reducing signal inhibition or augmenting signal intensity. Animal experiments agree with human studies. In conclusion, T1D is caused by a somatic mutation within the epitope-binding groove of an at-risk HLA gene that affects HLA-insulin-peptide-TCR complex binding affinity and initiates an autoimmune pathway. The nature of the peptide that binds to a mutated epitope-binding groove of an at-risk HLA gene determines the type of autoimmune disease that develops, that is, one at-risk HLA locus, multiple autoimmune diseases. Thus, T1D and AAIDs, and therefore common autoimmune diseases, share a similar somatic mutation-based aetiology.

Dietary Factors Associated with Glycemic Control in Children and Adolescents with Type 1 Diabetes

Type 1 diabetes mellitus (T1DM) is a chronic metabolic disease that results from the autoimmune destruction of pancreatic β-cells, leading to insulin deficiency and hyperglycemia. It is a common chronic disease in childhood, with a prevalence of 1 in 300 children in the United States and an increasing incidence of 2-5% annually, worldwide. Managing T1DM requires regular insulin administration, adjustment of food intake and exercise, and a comprehensive understanding of nutrition. This review aims to explore the relationship between dietary factors, physical activity, obesity, genetics, and glycemic control in children and adolescents with T1DM. To conduct this review, we conducted a thorough search of publications from December 2004 through April 2022 using PubMed, ScienceDirect, and Embase databases. Key topics included obesity, children, adolescents, nutrients, carbohydrates, proteins, fat, water-soluble vitamins, fat-soluble vitamins, dietary patterns, fruits and vegetables, physical activity, genetics, food habits, carbohydrate count and environmental factors.

Genetic discovery and risk prediction for type 1 diabetes in individuals without high-risk HLA-DR3/DR4 haplotypes

Over 10% of type 1 diabetes (T1D) cases do not have high-risk HLA-DR3 or DR4 haplotypes with distinct clinical features such as later onset and reduced insulin dependence. To identify genetic drivers of T1D in the absence of DR3/DR4, we performed association and fine-mapping analyses in 12,316 non-DR3/DR4 samples. Risk variants at the MHC and other loci genome-wide had heterogeneity in effects on T1D dependent on DR3/DR4, and non-DR3/DR4 T1D had evidence for a greater polygenic burden. T1D-assocated variants in non-DR3/DR4 were more enriched for loci, regulatory elements, and pathways for antigen presentation, innate immunity, and beta cells, and depleted in T cells, compared to DR3/DR4. Non-DR3/DR4 T1D cases were poorly classified based on an existing genetic risk score GRS2, and we created a new GRS which highly discriminated non-DR3/DR4 T1D from both non-diabetes and T2D. In total we identified heterogeneity in T1D genetic risk and disease mechanisms dependent on high-risk HLA haplotype and which enabled accurate classification of T1D across HLA background.

Nanomedicines based on trace elements for intervention of diabetes mellitus

Epidemiology shows that the incidence of diabetes mellitus (DM) is increasing year by year globally. Proper interventions are highly aspired for diabetics to improve the quality of life and prevent development of chronic complications. Trace elements, also known as microelements, are chemical substances that are present in our body in minute amounts. They are necessitated by the body for growth, development and functional metabolism. For the past few years, trace element nanoparticles have aroused considerable interest as a burgeoning form of nanomedicines in antidiabetic applications. These microelement-based nanomedicines can regulate glucose metabolism in several ways, showing great potential for diabetes management. Starting from the pathophysiology of diabetes, the state-of-the-art of diabetes treatment, the physiological roles of trace elements, various emerging trace element nanoparticles specific for diabetes were comprehensively reviewed in this work. Our findings disclose that trace element nanoparticles can fight against diabetes by lowering blood glucose, promoting insulin secretion, alleviating glucose intolerance, improving insulin sensitivity, ameliorating lipid profile, anti-inflammation and anti-oxidant stress, and other mechanisms. In conclusion, trace element nanoparticles can be applied as nanomedicines or dietary modifiers for effective intervention for diabetes.