Hierarchical Order of Distinct Autoantibody Spreading and Progression to Type 1 Diabetes in the TEDDY Study

Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk of (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb+; (2) when people who are IAb+ are initially identified there is a need for confirmation using a second sample; (3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care.

A set of circulating microRNAs belonging to the 14q32 chromosome locus identifies two subgroups of individuals with recent-onset type 1 diabetes

Circulating microRNAs (miRNAs) are linked to the onset and progression of type 1 diabetes mellitus (T1DM), thus representing potential disease biomarkers. In this study, we employed a multiplatform sequencing approach to analyze circulating miRNAs in an extended cohort of prospectively evaluated recent-onset T1DM individuals from the INNODIA consortium. Our findings reveal that a set of miRNAs located within T1DM susceptibility chromosomal locus 14q32 distinguishes two subgroups of individuals. To validate our results, we conducted additional analyses on a second cohort of T1DM individuals, confirming the identification of these subgroups, which we have named cluster A and cluster B. Remarkably, cluster B T1DM individuals, who exhibit increased expression of a set of 14q32 miRNAs, show better glycemic control and display a different blood immunomics profile. Our findings suggest that this set of circulating miRNAs can identify two different T1DM subgroups with distinct blood immunomics at baseline and clinical outcomes during follow-up.

HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07)

OBJECTIVE

To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed. Together with available clinical covariables, we applied the Cox regression model to assess HLAII immunogenic associations with the disease progression.

RESULTS

First, the current investigation updated the previously reported genetic associations of DQA1*03:01-DQB1*03:02 (hazard ratio [HR] = 1.25, P = 3.50*10-3) and DQA1*03:03-DQB1*03:01 (HR = 0.56, P = 1.16*10-3), and also uncovered a risk association with DQA1*05:01-DQB1*02:01 (HR = 1.19, P = 0.041). Second, after adjusting for DQ, DPA1*02:01-DPB1*11:01 and DPA1*01:03-DPB1*03:01 were found to have opposite associations with progression (HR = 1.98 and 0.70, P = 0.021 and 6.16*10-3, respectively). Third, DRB1*03:01-DRB3*01:01 and DRB1*03:01-DRB3*02:02, sharing the DRB1*03:01, had opposite associations (HR = 0.73 and 1.44, P = 0.04 and 0.019, respectively), indicating a role of DRB3. Meanwhile, DRB1*12:01-DRB3*02:02 and DRB1*01:03 alone were found to associate with progression (HR = 2.6 and 2.32, P = 0.018 and 0.039, respectively). Fourth, through enumerating all heterodimers, it was found that both DQ and DP could exhibit associations with disease progression.

CONCLUSIONS

These results suggest that HLAII polymorphisms influence progression from islet autoimmunity to T1D among at-risk subjects with islet autoantibodies.

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review

BACKGROUND

Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies.

METHODS

We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment.

RESULTS

Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation.

CONCLUSIONS

Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.

Type 1 Diabetes Screening and Diagnosis

Those with concerning signs or symptoms should be evaluated for type 1 diabetes (T1D). Those with first-degree relatives with T1D or based on the presence of high-risk genes are at increased risk and benefit from screening. Universal screening should be considered in light of new potential therapies to delay disease progression. Although oral glucose tolerance test is the gold standard for T1D staging, there are multiple tools available when oral glucose tolerance test is not feasible. Risk score calculations increase the ability to predict disease progression. Testing should be repeated when symptoms of overt diabetes mellitus are not present.

A novel, high-performance, low-volume, rapid luciferase immunoprecipitation system (LIPS) assay to detect autoantibodies to zinc transporter 8

BACKGROUND

Zinc transporter 8 autoantibodies (ZnT8A) are thought to appear close to type 1 diabetes (T1D) onset and can identify high-risk multiple (≥2) autoantibody positive individuals. Radiobinding assays (RBA) are widely used for ZnT8A measurement but have limited sustainability. We sought to develop a novel, high-performance, non-radioactive luciferase immunoprecipitation system (LIPS) assay to replace RBA.

METHODS

A custom dual C-terminal ZnT8 (aa268-369; R325/W325) heterodimeric antigen, tagged with a NanoluciferaseTM (Nluc-ZnT8) reporter, and LIPS assay was developed. Assay performance was evaluated by testing sera from new onset T1D (n = 573), healthy schoolchildren (n = 521), and selected first-degree relatives (FDRs) from the Bart's Oxford family study (n = 617; 164 progressed to diabetes).

RESULTS

In new-onset T1D, ZnT8A levels by LIPS strongly correlated with RBA (Spearman's r = 0.89; P < 0.0001), and positivity was highly concordant (94.3%). At a high specificity (95%), LIPS and RBA had comparable assay performance [LIPS pROC-AUC(95) 0.032 (95% CI: 0.029-0.036); RBA pROC-AUC(95) 0.031 (95% CI: 0.028-0.034); P = 0.376]. Overall, FDRs found positive by LIPS or RBA had a comparable 20-year diabetes risk (52.6% and 59.7%, respectively), but LIPS positivity further stratified T1D risk in FDRs positive for at least one other islet autoantibody detected by RBA (P = 0.0346).

CONCLUSION

This novel, high-performance, cheaper, quicker, higher throughput, low blood volume Nluc-ZnT8 LIPS assay is a safe, non-radioactive alternative to RBA with enhanced sensitivity and ability to discriminate T1D progressors. This method offers an advanced approach to current strategies to screen the general population for T1D risk for immunotherapy trials and to reduce rates of diabetic ketoacidosis at diagnosis.

Cellular zinc metabolism and zinc signaling: from biological functions to diseases and therapeutic targets

Zinc metabolism at the cellular level is critical for many biological processes in the body. A key observation is the disruption of cellular homeostasis, often coinciding with disease progression. As an essential factor in maintaining cellular equilibrium, cellular zinc has been increasingly spotlighted in the context of disease development. Extensive research suggests zinc's involvement in promoting malignancy and invasion in cancer cells, despite its low tissue concentration. This has led to a growing body of literature investigating zinc's cellular metabolism, particularly the functions of zinc transporters and storage mechanisms during cancer progression. Zinc transportation is under the control of two major transporter families: SLC30 (ZnT) for the excretion of zinc and SLC39 (ZIP) for the zinc intake. Additionally, the storage of this essential element is predominantly mediated by metallothioneins (MTs). This review consolidates knowledge on the critical functions of cellular zinc signaling and underscores potential molecular pathways linking zinc metabolism to disease progression, with a special focus on cancer. We also compile a summary of clinical trials involving zinc ions. Given the main localization of zinc transporters at the cell membrane, the potential for targeted therapies, including small molecules and monoclonal antibodies, offers promising avenues for future exploration.

Epitope-based precision immunotherapy of Type 1 diabetes

Antigen-specific immunotherapies (ASITs) address important clinical needs in treating autoimmune diseases. However, Type 1 diabetes is a heterogeneous disease wherein patient characteristics influence responsiveness to ASITs. Targeting not only disease-relevant T cell populations, but also specific groups of patients using precision medicine is a new goal toward achieving effective treatment. HLA-restricted peptides provide advantages over protein as antigens, however, methods for profiling antigen-specific T cells need to improve in sensitivity, depth, and throughput to facilitate epitope selection. Delivery approaches are highly diverse, illustrating the many ways relevant antigen-presenting cell populations and anatomical locations can be targeted for tolerance induction. The role of persistence of antigen presentation in promoting durable antigen-specific tolerance requires further investigation. Based on the outcome of ASIT trials, the field is moving toward using patient-specific variations to improve efficacy, but challenges still lie on the path to delivering more effective and safer treatment to the T1D patient population.

Teplizumab in Type 1 Diabetes Mellitus: An Updated Review

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune condition characterized by the irreversible destruction of the β cells of the pancreas, which leads to a lifelong dependency on exogenous insulin. Despite the advancements in insulin delivery methods, the suboptimal outcomes of these methods have triggered the search for therapies that may prevent or reverse the disease. Given the autoimmune aetiology of T1DM, therapies counteracting the immune-mediated destruction of the β-cells are the obvious target. Although several treatment strategies have been attempted to target cellular, humoral and innate immunity, very few have had a clinically meaningful impact. Of all the available immunomodulatory agents, cluster of differentiation (CD) 3 antibodies have exhibited the most promising preclinical and clinical results. Muromonab-CD3, which also happened to be a murine CD3 antibody, was the first monoclonal antibody approved for clinical use and was primarily indicated for graft rejection. The adverse effects associated with muromonab-CD3 led to its withdrawal. Teplizumab, a newer CD3 antibody, has a better side-effect profile because of its humanized nature and non-Fc-receptor-binding domain. In November 2022, teplizumab became the first immunomodulatory agent to be licensed by the US Food and Drug Administration for delaying the onset of T1DM in high-risk adults and children over 8 years old. The mechanism seems to be enhancing regulatory T-cell activity and promoting immune tolerance. This article reviews the mechanism of action and the clinical trials of teplizumab in individuals with T1DM or at risk of developing the disease.

Islet autoimmunity in human type 1 diabetes: initiation and progression from the perspective of the beta cell

Type 1 diabetes results from the poorly understood process of islet autoimmunity, which ultimately leads to the loss of functional pancreatic beta cells. Mounting evidence supports the notion that the activation and evolution of islet autoimmunity in genetically susceptible people is contingent upon early life exposures affecting the islets, especially beta cells. Here, we review some of the recent advances and studies that highlight the roles of these changes as well as antigen presentation and stress response pathways in beta cells in the onset and propagation of the autoimmune process in type 1 diabetes. Future progress in this area holds promise for advancing islet- and beta cell-directed therapies that could be implemented in the early stages of the disease and could be combined with immunotherapies.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Prevalence of markers of beta cell autoimmunity and thyroid disease in children with coeliac disease

BACKGROUND

Over the last decades, the prevalence of coeliac disease (CD), an autoimmune disorder, rose to 1-2%. Whether patients with CD have higher risk of developing other autoimmune disorders such as type 1 diabetes, Hashimoto thyroiditis, or Graves` disease remains unclear.

AIM

The aim of this study was to determine the prevalence of biomarkers of beta cell and thyroid autoimmunity in children with CD.

METHODS

Retrospective cross-sectional cohort study comparing pediatric patients suffering from CD with age and sex-matched healthy controls (HC). Participant`s serum was tested by immunoassay for following autoantibodies (aAb): TSH-receptor antibodies (TRAb), anti-thyroglobulin (anti-Tg), anti-thyroid peroxidase (anti-TPO), anti-glutamic acid decarboxylase (anti-GAD), anti-zinc transporter 8 (anti-ZnT8), anti-islet antigen 2 (anti-IA2) and anti-insulin.

RESULTS

A total of 95 patients with CD (mean age 8.9 years; 63% female) and 199 matched healthy controls (mean age 9.2 years; 59.8% female) were included in the study. For patients with CD, a seroprevalence of 2.1% (vs. 1.5% in HC) was calculated for anti-GAD, 1.1% for anti-IA2 (vs. 1.5% in HC), 3.2% for anti-ZnT8 (vs. 4.2% in HC), and 1.1% (vs. 1% in HC) for anti-insulin. For thyroid disease, a seroprevalence of 2.2% for TRAb (vs. 1% in HC), 0% for anti-TPO (vs. 2.5% in HC) and 4.3% for anti-Tg (vs. 3.5% in HC) was found for patients with CD.

CONCLUSION

This study suggests a higher prevalence of autoimmune antibodies againstthyroid in children with CD compared to HC, whilst it is similar for pancreatic antibodies. Prospective cohort studies are needed to first evaluate the occurrence of autoimmune antibodies against beta cells and thyroid over a longer follow-up time and second to explore their clinical relevance.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association of Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (Hb A1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of Hb A1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity

Type 1 diabetes (T1D) results from autoimmune destruction of β cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development.

The importance of biomarker development for monitoring type 1 diabetes progression rate and therapeutic responsiveness

Type 1 diabetes (T1D) is an autoimmune condition of children and adults in which immune cells target insulin-producing pancreatic β-cells for destruction. This results in a chronic inability to regulate blood glucose levels. The natural history of T1D is well-characterized in childhood. Evidence of two or more autoantibodies to the islet antigens insulin, GAD, IA-2 or ZnT8 in early childhood is associated with high risk of developing T1D in the future. Prediction of risk is less clear in adults and, overall, the factors controlling the progression rate from multiple islet autoantibody positivity to onset of symptoms are not fully understood. An anti-CD3 antibody, teplizumab, was recently shown to delay clinical progression to T1D in high-risk individuals including adults and older children. This represents an important proof of concept for those at risk of future T1D. Given their role in risk assessment, islet autoantibodies might appear to be the most obvious biomarkers to monitor efficacy. However, monitoring islet autoantibodies in clinical trials has shown only limited effects, although antibodies to the most recently identified autoantigen, tetraspanin-7, have not yet been studied in this context. Measurements of beta cell function remain fundamental to assessing efficacy and different models have been proposed, but improved biomarkers are required for both progression studies before onset of diabetes and in therapeutic monitoring. In this mini-review, we consider some established and emerging predictive and prognostic biomarkers, including markers of pancreatic function that could be integrated with metabolic markers to generate improved strategies to measure outcomes of therapeutic intervention.

Islet Autoantibody Standardization Program: interlaboratory comparison of insulin autoantibody assay performance in 2018 and 2020 workshops

AIMS/HYPOTHESIS

The Islet Autoantibody Standardization Program (IASP) aims to improve the performance of immunoassays measuring autoantibodies in type 1 diabetes and the concordance of results across laboratories. IASP organises international workshops distributing anonymised serum samples to participating laboratories and centralises the collection and analysis of results. In this report, we describe the results of assays measuring IAA submitted to the IASP 2018 and 2020 workshops.

METHODS

The IASP distributed uniquely coded sera from individuals with new-onset type 1 diabetes, multiple islet autoantibody-positive individuals, and diabetes-free blood donors in both 2018 and 2020. Serial dilutions of the anti-insulin mouse monoclonal antibody HUI-018 were also included. Sensitivity, specificity, area under the receiver operating characteristic curve (ROC-AUC), partial ROC-AUC at 95% specificity (pAUC95) and concordance of qualitative/quantitative results were compared across assays.

RESULTS

Results from 45 IAA assays of seven different formats and from 37 IAA assays of six different formats were submitted to the IASP in 2018 and 2020, respectively. The median ROC-AUC was 0.736 (IQR 0.617-0.803) and 0.790 (IQR 0.730-0.836), while the median pAUC95 was 0.016 (IQR 0.004-0.021) and 0.023 (IQR 0.014-0.026) in the 2018 and 2020 workshops, respectively. Assays largely differed in AUC (IASP 2018 range 0.232-0.874; IASP 2020 range 0.379-0.924) and pAUC95 (IASP 2018 and IASP 2020 range 0-0.032).

CONCLUSIONS/INTERPRETATION

Assay formats submitted to this study showed heterogeneous performance. Despite the high variability across laboratories, the in-house radiobinding assay (RBA) remains the gold standard for IAA measurement. However, novel non-radioactive IAA immunoassays showed a good performance and, if further improved, might be considered valid alternatives to RBAs.

Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children

AIMS/HYPOTHESIS

The aim of this study was to explore the utility of islet autoantibody (IAb) levels for the prediction of type 1 diabetes in autoantibody-positive children.

METHODS

Prospective cohort studies in Finland, Germany, Sweden and the USA followed 24,662 children at increased genetic or familial risk of developing islet autoimmunity and diabetes. For the 1403 who developed IAbs (523 of whom developed diabetes), levels of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA) and insulinoma-associated antigen-2 (IA-2A) were harmonised for analysis. Diabetes prediction models using multivariate logistic regression with inverse probability censored weighting (IPCW) were trained using 10-fold cross-validation. Discriminative power for disease was estimated using the IPCW concordance index (C index) with 95% CI estimated via bootstrap.

RESULTS

A baseline model with covariates for data source, sex, diabetes family history, HLA risk group and age at seroconversion with a 10-year follow-up period yielded a C index of 0.61 (95% CI 0.58, 0.63). The performance improved after adding the IAb positivity status for IAA, GADA and IA-2A at seroconversion: C index 0.72 (95% CI 0.71, 0.74). Using the IAb levels instead of positivity indicators resulted in even better performance: C index 0.76 (95% CI 0.74, 0.77). The predictive power was maintained when using the IAb levels alone: C index 0.76 (95% CI 0.75, 0.76). The prediction was better for shorter follow-up periods, with a C index of 0.82 (95% CI 0.81, 0.83) at 2 years, and remained reasonable for longer follow-up periods, with a C index of 0.76 (95% CI 0.75, 0.76) at 11 years. Inclusion of the results of a third IAb test added to the predictive power, and a suitable interval between seroconversion and the third test was approximately 1.5 years, with a C index of 0.78 (95% CI 0.77, 0.78) at 10 years follow-up.

CONCLUSIONS/INTERPRETATION

Consideration of quantitative patterns of IAb levels improved the predictive power for type 1 diabetes in IAb-positive children beyond qualitative IAb positivity status.

Recognition of mRNA Splice Variant and Secretory Granule Epitopes by CD4+ T Cells in Type 1 Diabetes

A recent discovery effort resulted in identification of novel splice variant and secretory granule antigens within the HLA class I peptidome of human islets and documentation of their recognition by CD8+ T cells from peripheral blood and human islets. In the current study, we applied a systematic discovery process to identify novel CD4+ T cell epitopes derived from these candidate antigens. We predicted 145 potential epitopes spanning unique splice junctions and within conventional secretory granule antigens and measured their in vitro binding to DRB1*04:01. We generated HLA class II tetramers for the 35 peptides with detectable binding and used these to assess immunogenicity and isolate T cell clones. Tetramers corresponding to peptides with verified immunogenicity were then used to label T cells specific for these putative epitopes in peripheral blood. T cells that recognize distinct epitopes derived from a cyclin I splice variant, neuroendocrine convertase 2, and urocortin-3 were detected at frequencies that were similar to those of an immunodominant proinsulin epitope. Cells specific for these novel epitopes predominantly exhibited a Th1-like surface phenotype. Among the three epitopes, responses to the cyclin I peptide exhibited a distinct memory profile. Responses to neuroendocrine convertase 2 were detected among pancreatic infiltrating T cells. These results further establish the contribution of unconventional antigens to the loss of tolerance in autoimmune diabetes.

Clinical and experimental treatment of type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease resulting in the destruction of the insulin-producing pancreatic beta cells. Disease progression occurs along a trajectory from genetic risk, the development of islet autoantibodies, and autoreactive T cells ultimately progressing to clinical disease. Natural history studies and mechanistic studies linked to clinical trials have provided insight into the role of the immune system in disease pathogenesis. Here, we review our current understanding of the underlying etiology of T1D, focusing on the immune cell types that have been implicated in progression from pre-symptomatic T1D to clinical diagnosis and established disease. This knowledge has been foundational for the development of immunotherapies aimed at the prevention and treatment of T1D.

HbA1c as a time predictive biomarker for an additional islet autoantibody and type 1 diabetes in seroconverted TEDDY children

OBJECTIVE

Increased level of glycated hemoglobin (HbA1c) is associated with type 1 diabetes onset that in turn is preceded by one to several autoantibodies against the pancreatic islet beta cell autoantigens; insulin (IA), glutamic acid decarboxylase (GAD), islet antigen-2 (IA-2) and zinc transporter 8 (ZnT8). The risk for type 1 diabetes diagnosis increases by autoantibody number. Biomarkers predicting the development of a second or a subsequent autoantibody and type 1 diabetes are needed to predict disease stages and improve secondary prevention trials. This study aimed to investigate whether HbA1c possibly predicts the progression from first to a subsequent autoantibody or type 1 diabetes in healthy children participating in the Environmental Determinants of Diabetes in the Young (TEDDY) study.

RESEARCH DESIGN AND METHODS

A joint model was designed to assess the association of longitudinal HbA1c levels with the development of first (insulin or GAD autoantibodies) to a second, second to third, third to fourth autoantibody or type 1 diabetes in healthy children prospectively followed from birth until 15 years of age.

RESULTS

It was found that increased levels of HbA1c were associated with a higher risk of type 1 diabetes (HR 1.82, 95% CI [1.57-2.10], p < 0.001) regardless of first appearing autoantibody, autoantibody number or type. A decrease in HbA1c levels was associated with the development of IA-2A as a second autoantibody following GADA (HR 0.85, 95% CI [0.75, 0.97], p = 0.017) and a fourth autoantibody following GADA, IAA and ZnT8A (HR 0.90, 95% CI [0.82, 0.99], p = 0.036). HbA1c trajectory analyses showed a significant increase of HbA1c over time (p < 0.001) and that the increase is more rapid as the number of autoantibodies increased from one to three (p < 0.001).

CONCLUSION

In conclusion, increased HbA1c is a reliable time predictive marker for type 1 diabetes onset. The increased rate of increase of HbA1c from first to third autoantibody and the decrease in HbA1c predicting the development of IA-2A are novel findings proving the link between HbA1c and the appearance of autoantibodies.

Predictors of the Initiation of Islet Autoimmunity and Progression to Multiple Autoantibodies and Clinical Diabetes: The TEDDY Study

OBJECTIVE

To distinguish among predictors of seroconversion, progression to multiple autoantibodies and from multiple autoantibodies to type 1 diabetes in young children.

RESEARCH DESIGN AND METHODS

Genetically high-risk newborns (n = 8,502) were followed for a median of 11.2 years (interquartile range 9.3-12.6); 835 (9.8%) developed islet autoantibodies and 283 (3.3%) were diagnosed with type 1 diabetes. Predictors were examined using Cox proportional hazards models.

RESULTS

Predictors of seroconversion and progression differed, depending on the type of first appearing autoantibody. Male sex, Finnish residence, having a sibling with type 1 diabetes, the HLA DR4 allele, probiotic use before age 28 days, and single nucleotide polymorphism (SNP) rs689_A (INS) predicted seroconversion to IAA-first (having islet autoantibody to insulin as the first appearing autoantibody). Increased weight at 12 months and SNPs rs12708716_G (CLEC16A) and rs2292239_T (ERBB3) predicted GADA-first (autoantibody to GAD as the first appearing). For those having a father with type 1 diabetes, the SNPs rs2476601_A (PTPN22) and rs3184504_T (SH2B3) predicted both. Younger age at seroconversion predicted progression from single to multiple autoantibodies as well as progression to diabetes, except for those presenting with GADA-first. Family history of type 1 diabetes and the HLA DR4 allele predicted progression to multiple autoantibodies but not diabetes. Sex did not predict progression to multiple autoantibodies, but males progressed more slowly than females from multiple autoantibodies to diabetes. SKAP2 and MIR3681HG SNPs are newly reported to be significantly associated with progression from multiple autoantibodies to type 1 diabetes.

CONCLUSIONS

Predictors of IAA-first versus GADA-first autoimmunity differ from each other and from the predictors of progression to diabetes.

Antigen-specific immunotherapies in type 1 diabetes

Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by the destruction of pancreatic beta cells, in which immune system disorder plays an important role. Finding a cure for T1DM and restoring beta cell function has been a long-standing goal. Research has shown that immune regulation with pancreatic islet auto-antigens may be the most specific and safe treatment for T1DM. Immunological intervention using diabetogenic auto-antigens as a target can help identify T1DM in high-risk individuals by early screening of autoantibodies (AAbs) before the loss of pancreatic islet function and thus achieve primary prevention of T1DM. However, induction of self-tolerance in patients with pre-diabetes can also slow down the attack of autoimmunity, and achieve secondary prevention. Antigen-based immune therapy opens up new avenues for the prevention and treatment of T1DM. The zinc transporter 8 (ZnT8) protein, presents in the serum of pre-diabetic and diabetic patients, is immunogenic and can cause T1D autoimmune responses. ZnT8 has become a potential target of humoral autoimmunity; it is of great significance for the early diagnosis of T1D. ZnT8-specific CD8⁺ T cells can be detected in most T1DM patients, and play a key role in the progression of T1D. As an immunotherapy target, it can improve the dysfunction of beta cells in T1DM and provide new ideas for the treatment of T1D. In this review, we summarize research surrounding antigen-specific immunotherapies (ASI) over the past 10 years and the ZnT8 antigen as an autoimmune target to induce self-tolerance for T1DM.

Evaluating the Immunopathogenesis of Diabetes After Acute Pancreatitis in the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium

ABSTRACT

The association between acute pancreatitis (AP) and diabetes mellitus (DM) has long been established, with the initial descriptions of AP patients presenting with DM after a bout of AP published in the 1940s and 50s. However, the potential mechanisms involved, particularly those components related to the immune system, have not been well defined. The Diabetes RElated to Acute pancreatitis and its Mechanisms (DREAM) study is a multicenter clinical study designed to understand the frequency and phenotype of DM developing after AP. This article describes one objective of the DREAM study: to determine the immunologic mechanisms of DM after AP, including the contribution of β-cell autoimmunity. This component of the study will assess the presence of islet autoimmunity, as well as the magnitude and kinetics of the innate and adaptive immune response at enrollment and during longitudinal follow-up after 1 or more episodes of AP. Finally, DREAM will evaluate the relationship between immune features, DM development, and pancreatitis etiology and severity.

Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories

Development of islet autoimmunity precedes the onset of type 1 diabetes in children, however, the presence of autoantibodies does not necessarily lead to manifest disease and the onset of clinical symptoms is hard to predict. Here we show, by longitudinal sampling of islet autoantibodies (IAb) to insulin, glutamic acid decarboxylase and islet antigen-2 that disease progression follows distinct trajectories. Of the combined Type 1 Data Intelligence cohort of 24662 participants, 2172 individuals fulfill the criteria of two or more follow-up visits and IAb positivity at least once, with 652 progressing to type 1 diabetes during the 15 years course of the study. Our Continuous-Time Hidden Markov Models, that are developed to discover and visualize latent states based on the collected data and clinical characteristics of the patients, show that the health state of participants progresses from 11 distinct latent states as per three trajectories (TR1, TR2 and TR3), with associated 5-year cumulative diabetes-free survival of 40% (95% confidence interval [CI], 35% to 47%), 62% (95% CI, 57% to 67%), and 88% (95% CI, 85% to 91%), respectively (p < 0.0001). Age, sex, and HLA-DR status further refine the progression rates within trajectories, enabling clinically useful prediction of disease onset.

Presence of islet autoantibodies precedes the onset of type 1 diabetes but it does not predict whether and how fast symptomatic disease appears. Here authors present a model to predict and visualize progression to diabetes by using a large longitudinal data set on autoantibodies and clinical parameters as input.

Screening Strategy for Islet Autoantibodies in Diabetes Patients of Different Ages

Background: The detection of islet autoantibodies is essential for the accurate classification and diagnosis of diabetes mellitus (DM). The islet autoantibody distribution varies by age. However, screening strategies for DM patients with different onset ages remain lacking. Materials and Methods: This cross-sectional study included 17,536 DM patients from 46 medical centers across China. The seroprevalence of glutamic acid decarboxylase autoantibody (GADA), insulinoma-associated-2 autoantibody (IA-2A), zinc transporter 8 autoantibody (ZnT8A), and insulin autoantibody (IAA) was determined in younger and older patients with type 1 DM (T1DM) (n = 287 and 285, respectively), younger and older patients with latent autoimmune diabetes (LAD) (n = 140 and 121, respectively), and younger and older patients with type 2 DM (n = 200 in each group). Results: The cutoff age between younger and older patients was 35 years using restricted cubic spline method (n = 17,536, adjusted R² = 0.97, residual standard error = 1.32; P < 0.001). The seroprevalence rates of four islet autoantibodies were higher in patients aged 15-35 years than in those ≥35 years (GADA: 17% vs. 5.6%, IA-2A: 8.5% vs. 1.3%, ZnT8A: 6.3% vs. 2.3%, IAA: 2.2% vs. 1.0%). The prevalence of ZnT8A was higher in LAD patients than in T1DM patients, especially in older LAD patients. The results indicated that ZnT8A detection can increase the detection rate of older LAD patients from 70.2% (based on GADA detection alone) to 91.7%. Conclusions: In patients stratified according to the cutoff age of 35 years, the optimal detection sequence should be GADA, IA-2A, and ZnT8A in younger patients and GADA, ZnT8A, and IA-2A in older patients, so as to reduce the screening cost while improving the detection rate. Particularly, the ZnT8A test is recommended in older patients to avoid a missed LAD diagnosis.

Enteroviruses and Type 1 Diabetes: Multiple Mechanisms and Factors?

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by insulin deficiency and resultant hyperglycemia. Complex interactions of genetic and environmental factors trigger the onset of autoimmune mechanisms responsible for development of autoimmunity to β cell antigens and subsequent development of T1D. A potential role of virus infections has long been hypothesized, and growing evidence continues to implicate enteroviruses as the most probable triggering viruses. Recent studies have strengthened the association between enteroviruses and development of autoimmunity in T1D patients, potentially through persistent infections. Enterovirus infections may contribute to different stages of disease development. We review data from both human cohort studies and experimental research exploring the potential roles and molecular mechanisms by which enterovirus infections can impact disease outcome.

Enteroviruses and Type 1 Diabetes: Multiple Mechanisms and Factors?

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by insulin deficiency and resultant hyperglycemia. Complex interactions of genetic and environmental factors trigger the onset of autoimmune mechanisms responsible for development of autoimmunity to β cell antigens and subsequent development of T1D. A potential role of virus infections has long been hypothesized, and growing evidence continues to implicate enteroviruses as the most probable triggering viruses. Recent studies have strengthened the association between enteroviruses and development of autoimmunity in T1D patients, potentially through persistent infections. Enterovirus infections may contribute to different stages of disease development. We review data from both human cohort studies and experimental research exploring the potential roles and molecular mechanisms by which enterovirus infections can impact disease outcome.

Heterogeneity of beta-cell function in subjects with multiple islet autoantibodies in the TEDDY family prevention study - TEFA

BACKGROUND

Individuals with multiple islet autoantibodies are at increased risk for clinical type 1 diabetes and may proceed gradually from stage to stage complicating the recruitment to secondary prevention studies. We evaluated multiple islet autoantibody positive subjects before randomisation for a clinical trial 1 month apart for beta-cell function, glucose metabolism and continuous glucose monitoring (CGM). We hypothesized that the number and type of islet autoantibodies in combination with different measures of glucose metabolism including fasting glucose, HbA1c, oral glucose tolerance test (OGTT), intra venous glucose tolerance test (IvGTT) and CGM allows for more precise staging of autoimmune type 1 diabetes than the number of islet autoantibodies alone.

METHODS

Subjects (n = 57) at 2-50 years of age, positive for two or more islet autoantibodies were assessed by fasting plasma insulin, glucose, HbA1c as well as First Phase Insulin Response (FPIR) in IvGTT, followed 1 month later by OGTT, and 1 week of CGM (n = 24).

RESULTS

Autoantibodies against GAD65 (GADA; n = 52), ZnT8 (ZnT8A; n = 40), IA-2 (IA-2A; n = 38) and insulin (IAA; n = 28) were present in 9 different combinations of 2-4 autoantibodies. Fasting glucose and HbA1c did not differ between the two visits. The estimate of the linear relationship between log2-transformed FPIR as the outcome and log2-transformed area under the OGTT glucose curve (AUC) as the predictor, adjusting for age and sex was - 1.88 (- 2.71, - 1.05) p = 3.49 × 10-5. The direction of the estimates for all glucose metabolism measures was positive except for FPIR, which was negative. FPIR was associated with higher blood glucose. Both the median and the spread of the CGM glucose data were significantly associated with higher glucose values based on OGTT, higher HbA1c, and lower FPIR. There was no association between glucose metabolism, autoantibody number and type except that there was an indication that the presence of at least one of ZnT8(Q/R/W) A was associated with a lower log2-transformed FPIR (- 0.80 (- 1.58, - 0.02), p = 0.046).

CONCLUSIONS

The sole use of two or more islet autoantibodies as inclusion criterion for Stage 1 diabetes in prevention trials is unsatisfactory. Staging type 1 diabetes needs to take the heterogeneity in beta-cell function and glucose metabolism into account.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02605148 , November 16, 2015.

Four decades of the Bart's Oxford study: Improved tests to predict type 1 diabetes

Recent success in clinical trials to delay the onset of type 1 diabetes has heralded a new era of type 1 diabetes research focused on the most accurate methods to predict risk and progression rate in the general population. Risk prediction for type 1 diabetes has been ongoing since the 1970s and 1980s when human leucocyte antigen (HLA) variants and islet autoantibodies associated with type 1 diabetes were first described. Development of prediction methodologies has relied on well-characterised cohorts and samples. The Bart's Oxford (BOX) study of type 1 diabetes has been recruiting children with type 1 diabetes and their first (and second)-degree relatives since 1985. In this review, we use the timeline of the study to review the accompanying basic science developments which have facilitated improved prediction by genetic (HLA analysis through to genetic risk scores) and biochemical strategies (islet cell autoantibodies through to improved individual tests for antibodies to insulin, glutamate decarboxylase, the tyrosine phosphatase IA-2, zinc transporter 8 and tetraspanin 7). The type 1 diabetes community are poised to move forward using the best predictive markers to predict and delay the onset of type 1 diabetes.

100 Years of Insulin: Lifesaver, immune target, and potential remedy for prevention

In this review, we bring our personal experiences to showcase insulin from its breakthrough discovery as a life-saving drug 100 years ago to its uncovering as the autoantigen and potential cause of type 1 diabetes and eventually as an opportunity to prevent autoimmune diabetes. The work covers the birth of insulin to treat patients, which is now 100 years ago, the development of human insulin, insulin analogues, devices, and the way into automated insulin delivery, the realization that insulin is the primary autoimmune target of type 1 diabetes in children, novel approaches of immunotherapy using insulin for immune tolerance induction, the possible limitations of insulin immunotherapy, and an outlook how modern vaccines could remove the need for another 100 years of insulin therapy.

Advances in Type 1 Diabetes Prediction Using Islet Autoantibodies: Beyond a Simple Count

Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression among multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials and for identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in presymptomatic subjects using immunotherapy, and as the field moves toward population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics, such as epitope targets and affinity; longitudinal patterns, such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject's age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific preclinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease.

Clinical and genetic features of maturity-onset diabetes of the young in pediatric patients: a 12-year monocentric experience

BACKGROUND

A retrospective observational study was conducted to assess the prevalence of maturity onset diabetes of the young (MODY) in a large paediatric population of Southern Italy newly diagnosed with diabetes. Clinical and genetic features of the identified MODY patients were also described.

METHODS

Genetic testing was performed in children and adolescents newly diagnosed with diabetes who presented autoantibody negativity and fasting C-peptide levels ≥ 0.8 ng/mL. Patients with a low insulin daily dose and optimal glycaemic control after two years from diabetes onset were also investigated for monogenic diabetes, regardless of their autoimmunity status and/or C-peptide levels.

RESULTS

A prevalence of 6.5% of MODY was found. In particular, glucokinase-MODY was the most common type of MODY. The mean age at diagnosis was 9.1 years. Clinical presentation and biochemical data were heterogeneous also among patients belonging to the same MODY group.

CONCLUSIONS

We found a relatively high prevalence of MODY among paediatric patients with a new diagnosis of diabetes in comparison to literature data. Our findings highlight that a more detailed clinical evaluation along with easier and less expensive approachability to genetic testing may allow diagnosing an increasing number of MODY cases. A correct, prompt diagnosis is crucial to choose the most appropriate treatment and offer adequate genetic counselling.

Islet autoantibody types mark differential clinical characteristics at diagnosis of pediatric type 1 diabetes

BACKGROUND

We aimed to study whether islet autoantibody type marks differential characteristics at the time of type 1 diabetes (T1D) diagnosis.

METHODS

We studied 711 children with newly diagnosed autoimmune T1D. We compared demographic (sex, age, race/ethnicity), clinical (pubertal development, BMI percentile, diabetic ketoacidosis [DKA]) and laboratory (glucose, hemoglobin A1c [HbA1c], C-peptide, tissue transglutaminase antibodies [tTGA], thyroglobulin antibodies, and thyroid peroxidase antibodies [TPOA]) characteristics by presence/absence of autoantibodies to insulin (IAA), GAD65 (GADA), or IA-2/ICA512 (IA-2A). Islet autoantibody titers were evaluated among the children positive for the relevant autoantibody type. We used multivariable analysis to adjust for potential confounders.

RESULTS

IAA+ was statistically associated with younger age (p < 0.0001) and lower HbA1c (p = 0.049) while Tanner stage, GADA status and number of positive islet autoantibodies were not significant in the multivariable model. GADA+ was associated with female sex (OR = 4.0, p = 0.002) and negatively with elevated tTGA titers (>50 U/mL) (OR = 0.21, p = 0.026) but not with age, IAA status, IA-2A status, islet autoantibody number, or thyroid autoimmunity. None of the associations with IA-2A positivity was statistically significant in the multivariable analysis. In multivariable models, IAA titer was significantly associated with younger age (p = 0.006), DKA (p = 0.017) and higher tTGA levels (p = 0.002); GADA titer with female sex (p = 0.028), racial minority (p = 0.046) and TPOA positivity (p = 0.021); and IA-2A titer with older age (p = 0.001) and not being African American (p = 0.024).

CONCLUSIONS

Islet autoantibody type is associated with differential characteristics at diagnosis of pediatric T1D. Longitudinal and mechanistic studies are needed to evaluate T1D endotypes by autoantibody type.

The dark side of insulin: A primary autoantigen and instrument of self-destruction in type 1 diabetes

Background

Since its discovery 100 years ago, insulin, as the ‘cure’ for type 1 diabetes, has rescued the lives of countless individuals. As the century unfolded and the autoimmune nature of type 1 diabetes was recognised, a darker side of insulin emerged. Autoimmunity to insulin was found to be an early marker of risk for type 1 diabetes in young children. In humans, it remains unclear if autoimmunity to insulin is primarily due to a defect in the beta cell itself or to dysregulated immune activation. Conversely, it may be secondary to beta-cell damage from an environmental agent (e.g., virus). Nevertheless, direct, interventional studies in non-obese diabetic (NOD) mouse models of type 1 diabetes point to a critical role for (pro)insulin as a primary autoantigen that drives beta cell pathology.

Scope of review

Modelled on Koch's postulates for the pathogenicity of an infectious agent, evidence for a pathogenic role of (pro)insulin as an autoantigen in type 1 diabetes, particularly applicable to the NOD mouse model, is reviewed. Evidence in humans remains circumstantial. Additionally, as (pro)insulin is a target of autoimmunity in type 1 diabetes, its application as a therapeutic tool to elicit antigen-specific immune tolerance is assessed.

Major conclusions

Paradoxically, insulin is both a ‘cure’ and a potential ‘cause’ of type 1 diabetes, actively participating as an autoantigen to drive autoimmune destruction of beta cells - the instrument of its own destruction.

Etiology of Autoimmune Islet Disease: Timing Is Everything

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

The KAG motif of HLA-DRB1 (β71, β74, β86) predicts seroconversion and development of type 1 diabetes

BACKGROUND

HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated.

METHODS

We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions.

FINDINGS

Three amino acid residues of HLA-DRB1 (β71, β74, β86) were found to be predictive of T1D risk in the population-based study. The "KAG" motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10-64). Three less frequent motifs ("EAV", OR = 2.55, p = 0.025; "RAG", OR = 1.93, p = 0.043; and "RAV", OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs ("REG" and "REV") were equally protective (OR = 0.11, p = 4.23 × 10-4). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the "KAG" motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10-14) after adjusting potential confounders.

INTERPRETATIONS

DNA sequence variation in HLA-DRB1 at positions β71, β74, and β86 are non-conservative (β74 A→E, β71 E vs K vs R and β86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65.

FUNDING

National Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council.

Loss of Znt8 function in diabetes mellitus: risk or benefit?

The zinc transporter 8 (ZnT8) plays an essential role in zinc homeostasis inside pancreatic β cells, its function is related to the stabilization of insulin hexameric form. Genome-wide association studies (GWAS) have established a positive and negative relationship of ZnT8 variants with type 2 diabetes mellitus (T2DM), exposing a dual and controversial role. The first hypotheses about its role in T2DM indicated a higher risk of developing T2DM for loss of function; nevertheless, recent GWAS of ZnT8 loss-of-function mutations in humans have shown protection against T2DM. With regard to the ZnT8 role in T2DM, most studies have focused on rodent models and common high-risk variants; however, considerable differences between human and rodent models have been found and the new approaches have included lower-frequency variants as a tool to clarify gene functions, allowing a better understanding of the disease and offering possible therapeutic targets. Therefore, this review will discuss the physiological effects of the ZnT8 variants associated with a major and lower risk of T2DM, emphasizing the low- and rare-frequency variants.

Differential HLA Association of GAD65 and IA2 Autoantibodies in North Indian Type 1 Diabetes Patients

The human leucocyte antigen (HLA) association with type 1 diabetes (T1D) is well known but there are limited studies investigating the association between β-cell autoantibodies and HLA genes. We evaluated the prevalence of GAD65 and IA-2 autoantibodies (GADA and IA2A) in 252 T1D patients from North India and investigated the genetic association of GADA and IA2A with HLA class I and class II genes/haplotypes. GADA and IA2A were detected in 50.79% and 15.87% of T1D patients, respectively, while only 8.73% had both GADA and IA2A. HLA-DRB1^∗03 was observed to be significantly higher in GADA+ T1D patients as compared to GADA- (91.41% vs. 66.13%, Bonferroni-corrected P (P _c) = 1.11 × 10^-5; OR = 5.45; 95% CI: 2.67-11.08). Similarly, HLA-DQB1^∗02 was found to be significantly increased in GADA+ patients (94.53%, P _c = 2.19 × 10^-5; OR = 6.27; 95% CI: 2.7-14.49) as compared to GADA- (73.39%). The frequencies of HLA-DRB1^∗04 and DQB1^∗03 were increased in IA2A+ patients (45.0% and 52.5%, respectively) as compared to that in IA2A- (25.94% and 33.96%, respectively). Further, the frequency of DRB1^∗03-DQB1^∗02 haplotype was found to be significantly increased in GADA+ T1D patients as compared to GADA- (60.55% vs. 41.94%, P = 3.94 × 10^-5; OR = 2.13; 95%CI = 1.49-3.03). Similarly, HLA-DRB1^∗04-DQB1^∗03 haplotype was found to be significantly increased in IA2A+ T1D patients compared to IA2A- patients (22.5% vs. 12.97%; P = 0.041; OR = 1.95; 95%CI = 1.08-3.52). None of the HLA class I genes (HLA-A, B, and Cw) was found to be associated with GADA or IA2A in people with T1D. Our findings suggest that HLA-DRB1^∗03/DQB1^∗02 and HLA-DRB1^∗04/DQB1^∗03 might play an important role in the development of GADA and IA2A, respectively.