Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report

Innovate therapeutic targets for autoimmune diseases: insights from proteome-wide mendelian randomization and Bayesian colocalization

BACKGROUND

Despite growing knowledge regarding the pathogenesis of autoimmune diseases (ADs) onset, the current treatment remains unsatisfactory. This study aimed to identify innovative therapeutic targets for ADs through various analytical approaches.

RESEARCH DESIGN AND METHODS

Utilizing Mendelian randomization, Bayesian co-localization, phenotype scanning, and protein-protein interaction network, we explored potential therapeutic targets for 14 ADs and externally validated our preliminary findings.

RESULTS

This study identified 12 circulating proteins as potential therapeutic targets for six ADs. Specifically, IL12B was judged to be a risk factor for ankylosing spondylitis (p = 1.61E - 07). TYMP (p = 6.28E - 06) was identified as a protective factor for ulcerative colitis. For Crohn's disease, ERAP2 (p = 4.47E - 14), HP (p = 2.08E - 05), and RSPO3 (p = 6.52E - 07), were identified as facilitators, whereas FLRT3 (p = 3.42E - 07) had a protective effect. In rheumatoid arthritis, SWAP70 (p = 3.26E - 10), SIGLEC6 (p = 2.47E - 05), ISG15 (p = 3.69E - 05), and FCRL3 (p = 1.10E - 10) were identified as risk factors. B4GALT1 (p = 6.59E - 05) was associated with a lower risk of Type 1 diabetes (T1D). Interestingly, CTSH was identified as a protective factor for narcolepsy (p = 1.58E - 09) but a risk factor for T1D (p = 7.36E - 11), respectively. External validation supported the associations of eight of these proteins with three ADs.

CONCLUSIONS

Our integrated study identified 12 potential therapeutic targets for ADs and provided novel insights into future drug development for ADs.

Identification of type 1 diabetes risk phenotypes using an outcome-guided clustering analysis

AIMS/HYPOTHESIS

Although statistical models for predicting type 1 diabetes risk have been developed, approaches that reveal the heterogeneity of the at-risk population by identifying clinically meaningful clusters are lacking. We aimed to identify and characterise clusters of islet autoantibody-positive individuals who share similar characteristics and type 1 diabetes risk.

METHODS

We tested a novel outcome-guided clustering method in initially non-diabetic autoantibody-positive relatives of individuals with type 1 diabetes, using the TrialNet Pathway to Prevention study data (n=1123). The outcome of the analysis was the time to development of type 1 diabetes, and variables in the model included demographic characteristics, genetics, metabolic factors and islet autoantibodies. An independent dataset (the Diabetes Prevention Trial of Type 1 Diabetes Study) (n=706) was used for validation.

RESULTS

The analysis revealed six clusters with varying type 1 diabetes risks, categorised into three groups based on the hierarchy of clusters. Group A comprised one cluster with high glucose levels (median for glucose mean AUC 9.48 mmol/l; IQR 9.16-10.02) and high risk (2-year diabetes-free survival probability 0.42; 95% CI 0.34, 0.51). Group B comprised one cluster with high IA-2A titres (median 287 DK units/ml; IQR 250-319) and elevated autoantibody titres (2-year diabetes-free survival probability 0.73; 95% CI 0.67, 0.80). Group C comprised four lower-risk clusters with lower autoantibody titres and glucose levels (with 2-year diabetes-free survival probability ranging from 0.84-0.99 in the four clusters). Within group C, the clusters exhibit variations in characteristics such as glucose levels, C-peptide levels and age. A decision rule for assigning individuals to clusters was developed. Use of the validation dataset confirmed that the clusters can identify individuals with similar characteristics.

CONCLUSIONS/INTERPRETATION

Demographic, metabolic, immunological and genetic markers may be used to identify clusters of distinctive characteristics and different risks of progression to type 1 diabetes among autoantibody-positive individuals with a family history of type 1 diabetes. The results also revealed the heterogeneity in the population and complex interactions between variables.

MiR-375: it could be a general biomarker of metabolic changes and inflammation in type 1 diabetes patients and their siblings

PURPOSE

Type 1 diabetes (T1D) is a chronic autoimmune illness that results in loss of pancreatic beta cells and insulin insufficiency. MicroRNAs (miRNAs) are linked to immune system functions contributing to the pathophysiology of T1D, miRNA-375 is significantly expressed in the human pancreas and its circulatory levels might correspond to beta cell alterations. Pancreatic islet cell antibodies (ICA) and Glutamic acid decarboxylase antibodies (GADA) have roles in autoimmune pathogenesis and are predictive markers of T1D. The aim of this work was to detect serum level changes of miRNA-375, ICA, and GADA in T1D patients, and their siblings compared to healthy controls and correlate them with T1D biochemical parameters.

METHODS

The study included 66 T1D patients (32 males and 34 females; age range 3-18 years), 22 patients' siblings (13 males and 9 females; age range 4-17 years), and 23 healthy controls (7 males and 16 females; age range 4-17 years). MiRNA-375 levels were measured using quantitative reverse transcription polymerase chain reaction (RT-qPCR), while ICA and GADA levels were measured using enzyme-linked immunosorbent assay (ELISA). Data analysis was done utilizing SPSS-17 software.

RESULTS

MiR-375 levels were downregulated in T1D patients and further decreased in their siblings when compared to healthy controls. Furthermore, miR-375 exhibited inverse correlations with HbA1c levels but no correlations with Total Insulin Dose, disease duration, or autoantibodies (GADA & ICA).

CONCLUSION

Our study indicates that miR-375 is significantly downregulated in children with T1D and their siblings, suggesting its potential role as a biomarker for beta-cell function and glycemic control.

Mechanisms underlying the development of type 1 diabetes in ART-treated people living with HIV: an enigmatic puzzle

The immunopathogenesis of HIV infection remains poorly understood. Despite the widespread use of effective modern antiretroviral therapy (ART), people living with HIV (PLWH) are known to develop several comorbidities, including type 1 diabetes (T1DM). However, the etiology and critical mechanisms accounting for the onset of T1DM in the preceding context remain unknown. This article proposes to address this topic in order to provide further understanding and future research directions.

The insulin secretory granule is a hotspot for autoantigen formation in type 1 diabetes

In type 1 diabetes, the insulin-producing beta cells of the pancreas are destroyed through the activity of autoreactive T cells. In addition to strong and well-documented HLA class II risk haplotypes, type 1 diabetes is associated with noncoding polymorphisms within the insulin gene locus. Furthermore, autoantibody prevalence data and murine studies implicate insulin as a crucial autoantigen for the disease. Studies identify secretory granules, where proinsulin is processed into mature insulin, stored and released in response to glucose stimulation, as a source of antigenic epitopes and neoepitopes. In this review, we integrate established concepts, including the role that susceptible HLA and thymic selection of the T cell repertoire play in setting the stage for autoimmunity, with emerging insights about beta cell and insulin secretory granule biology. In particular, the acidic, peptide-rich environment of secretory granules combined with its array of enzymes generates a distinct proteome that is unique to functional beta cells. These factors converge to generate non-templated peptide sequences that are recognised by autoreactive T cells. Although unanswered questions remain, formation and presentation of these epitopes and the resulting immune responses appear to be key aspects of disease initiation. In addition, these pathways may represent important opportunities for therapeutic intervention.

Fecal microbiota transplantation in autoimmune diseases - An extensive paper on a pathogenetic therapy

The role of infections in the pathogenesis of autoimmune diseases has long been recognized and reported. In addition to infectious agents, the internal composition of the "friendly" living bacteria, (microbiome) and its correlation to immune balance and dysregulation have drawn the attention of researchers for decades. Nevertheless, only recently, scientific papers regarding the potential role of transferring microbiome from healthy donor subjects to patients with autoimmune diseases has been proposed. Fecal microbiota transplantation or FMT, carries the logic of transferring microorganisms responsible for immune balance from healthy donors to individuals with immune dysregulation or more accurately for our paper, autoimmune diseases. Viewing the microbiome as a pathogenetic player allows us to consider FMT as a pathogenetic-based treatment. Promising results alongside improved outcomes have been demonstrated in patients with different autoimmune diseases following FMT. Therefore, in our current extensive review, we aimed to highlight the implication of FMT in various autoimmune diseases, such as inflammatory bowel disease, autoimmune thyroid and liver diseases, systemic lupus erythematosus, and type 1 diabetes mellitus, among others. Presenting all the aspects of FMT in more than 12 autoimmune diseases in one paper, to the best of our knowledge, is the first time presented in medical literature. Viewing FMT as such could contribute to better understanding and newer application of the model in the therapy of autoimmune diseases, indeed.

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.

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.

Intake of B vitamins and the risk of developing islet autoimmunity and type 1 diabetes in the TEDDY study

PURPOSE

The aim was to study the association between dietary intake of B vitamins in childhood and the risk of islet autoimmunity (IA) and progression to type 1 diabetes (T1D) by the age of 10 years.

METHODS

We followed 8500 T1D-susceptible children born in the U.S., Finland, Sweden, and Germany in 2004 -2010 from the Environmental Determinants of Diabetes in the Young (TEDDY) study, which is a prospective observational birth cohort. Dietary intake of seven B vitamins was calculated from foods and dietary supplements based on 24-h recall at 3 months and 3-day food records collected regularly from 6 months to 10 years of age. Cox proportional hazard models were adjusted for energy, HLA-genotype, first-degree relative with T1D, sex, and country.

RESULTS

A total of 778 (9.2) children developed at least one autoantibody (any IA), and 335 (3.9%) developed multiple autoantibodies. 280 (3.3%) children had IAA and 319 (3.8%) GADA as the first autoantibody. 344 (44%) children with IA progressed to T1D. We observed that higher intake of niacin was associated with a decreased risk of developing multiple autoantibodies (HR 0.95; 95% CI 0.92, 0.98) per 1 mg/1000 kcal in niacin intake. Higher intake of pyridoxine (HR 0.66; 95% CI 0.46, 0.96) and vitamin B12 (HR 0.87; 95% CI 0.77, 0.97) was associated with a decreased risk of IAA-first autoimmunity. Higher intake of riboflavin (HR 1.38; 95% CI 1.05, 1.80) was associated with an increased risk of GADA-first autoimmunity. There were no associations between any of the B vitamins and the outcomes "any IA" and progression from IA to T1D.  CONCLUSION: In this multinational, prospective birth cohort of children with genetic susceptibility to T1D, we observed some direct and inverse associations between different B vitamins and risk of IA.

Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals. ASSET (AI for Sustainable Prevention of Autoimmunity in the Society; www.asset.healthcare ) is a public/private consortium that was established to contribute to research around screening for type 1 diabetes and particularly to how AI can drive the implementation of a precision medicine approach to disease prevention. ASSET will additionally focus on issues pertaining to operational implementation of screening. The authors of this article, researchers and clinicians active in the field of type 1 diabetes, met in an open forum to independently debate key issues around screening for type 1 diabetes and to advise ASSET. The potential use of AI in the analysis of longitudinal data from observational cohort studies to inform the design of improved, more individualised screening programmes was also discussed. A key issue was whether AI would allow the research community and industry to capitalise on large publicly available data repositories to design screening programmes that allow the early detection of individuals at high risk and enable clinical evaluation of preventive therapies. Overall, AI has the potential to revolutionise type 1 diabetes screening, in particular to help identify individuals who are at increased risk of disease and aid in the design of appropriate follow-up plans. We hope that this initiative will stimulate further research on this very timely topic.

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.

Autoimmune diseases: targets, biology, and drug discovery

Autoimmune diseases (AIDs) arise from a breakdown in immunological self-tolerance, wherein the adaptive immune system mistakenly attacks healthy cells, tissues and organs. AIDs impose excessive treatment costs and currently rely on non-specific and universal immunosuppression, which only offer symptomatic relief without addressing the underlying causes. AIDs are driven by autoantigens, targeting the autoantigens holds great promise in transforming the treatment of these diseases. To achieve this goal, a comprehensive understanding of the pathogenic mechanisms underlying different AIDs and the identification of specific autoantigens are critical. In this review, we categorize AIDs based on their underlying causes and compile information on autoantigens implicated in each disease, providing a roadmap for the development of novel immunotherapy regimens. We will focus on type 1 diabetes (T1D), which is an autoimmune disease characterized by irreversible destruction of insulin-producing β cells in the Langerhans islets of the pancreas. We will discuss insulin as possible autoantigen of T1D and its role in T1D pathogenesis. Finally, we will review current treatments of TID and propose a potentially effective immunotherapy targeting autoantigens.

Genetic and Epigenetic Aspects of Type 1 Diabetes Mellitus: Modern View on the Problem

Omics technologies accumulated an enormous amount of data that advanced knowledge about the molecular pathogenesis of type 1 diabetes mellitus and identified a number of fundamental problems focused on the transition to personalized diabetology in the future. Among them, the most significant are the following: (1) clinical and genetic heterogeneity of type 1 diabetes mellitus; (2) the prognostic significance of DNA markers beyond the HLA genes; (3) assessment of the contribution of a large number of DNA markers to the polygenic risk of disease progress; (4) the existence of ethnic population differences in the distribution of frequencies of risk alleles and genotypes; (5) the infancy of epigenetic research into type 1 diabetes mellitus. Disclosure of these issues is one of the priorities of fundamental diabetology and practical healthcare. The purpose of this review is the systemization of the results of modern molecular genetic, transcriptomic, and epigenetic investigations of type 1 diabetes mellitus in general, as well as its individual forms. The paper summarizes data on the role of risk HLA haplotypes and a number of other candidate genes and loci, identified through genome-wide association studies, in the development of this disease and in alterations in T cell signaling. In addition, this review assesses the contribution of differential DNA methylation and the role of microRNAs in the formation of the molecular pathogenesis of type 1 diabetes mellitus, as well as discusses the most currently central trends in the context of early diagnosis of type 1 diabetes mellitus.

The beta cell-immune cell interface in type 1 diabetes (T1D)

BACKGROUND

T1D is an autoimmune disease in which pancreatic islets of Langerhans are infiltrated by immune cells resulting in the specific destruction of insulin-producing islet beta cells. Our understanding of the factors leading to islet infiltration and the interplay of the immune cells with target beta cells is incomplete, especially in human disease. While murine models of T1D have provided crucial information for both beta cell and autoimmune cell function, the translation of successful therapies in the murine model to human disease has been a challenge.

SCOPE OF REVIEW

Here, we discuss current state of the art and consider knowledge gaps concerning the interface of the islet beta cell with immune infiltrates, with a focus on T cells. We discuss pancreatic and immune cell phenotypes and their impact on cell function in health and disease, which we deem important to investigate further to attain a more comprehensive understanding of human T1D disease etiology.

MAJOR CONCLUSIONS

The last years have seen accelerated development of approaches that allow comprehensive study of human T1D. Critically, recent studies have contributed to our revised understanding that the pancreatic beta cell assumes an active role, rather than a passive position, during autoimmune disease progression. The T cell-beta cell interface is a critical axis that dictates beta cell fate and shapes autoimmune responses. This includes the state of the beta cell after processing internal and external cues (e.g., stress, inflammation, genetic risk) that that contributes to the breaking of tolerance by hyperexpression of human leukocyte antigen (HLA) class I with presentation of native and neoepitopes and secretion of chemotactic factors to attract immune cells. We anticipate that emerging insights about the molecular and cellular aspects of disease initiation and progression processes will catalyze the development of novel and innovative intervention points to provide additional therapies to individuals affected by T1D.

Distinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection

Although the genetic basis and pathogenesis of type 1 diabetes have been studied extensively, how host responses to environmental factors might contribute to autoantibody development remains largely unknown. Here, we use longitudinal blood transcriptome sequencing data to characterize host responses in children within 12 months prior to the appearance of type 1 diabetes-linked islet autoantibodies, as well as matched control children. We report that children who present with insulin-specific autoantibodies first have distinct transcriptional profiles from those who develop GADA autoantibodies first. In particular, gene dosage-driven expression of GSTM1 is associated with GADA autoantibody positivity. Moreover, compared with controls, we observe increased monocyte and decreased B cell proportions 9-12 months prior to autoantibody positivity, especially in children who developed antibodies against insulin first. Lastly, we show that control children present transcriptional signatures consistent with robust immune responses to enterovirus infection, whereas children who later developed islet autoimmunity do not. These findings highlight distinct immune-related transcriptomic differences between case and control children prior to case progression to islet autoimmunity and uncover deficient antiviral response in children who later develop islet autoimmunity.

Clinical outcome is distinct between radiological stricture and endoscopic stricture in ileal Crohn's disease

OBJECTIVES

Differences in clinical adverse outcomes (CAO) based on different intestinal stricturing definitions in Crohn's disease (CD) are poorly documented. This study aims to compare CAO between radiological strictures (RS) and endoscopic strictures (ES) in ileal CD and explore the significance of upstream dilatation in RS.

METHODS

This retrospective double-center study included 199 patients (derivation cohort, n = 157; validation cohort, n = 42) with bowel strictures who simultaneously underwent endoscopic and radiologic examinations. RS was defined as a luminal narrowing with wall thickening relative to the normal gut on cross-sectional imaging (group 1 (G1)), which further divided into G1a (without upstream dilatation) and G1b (with upstream dilatation). ES was defined as an endoscopic non-passable stricture (group 2 (G2)). Strictures met the definitions of RS (with or without upstream dilatation) and ES were categorized as group 3 (G3). CAO referred to stricture-related surgery or penetrating disease.

RESULTS

In the derivation cohort, G1b (93.3%) had the highest CAO occurrence rate, followed by G3 (32.6%), G1a (3.2%), and G2 (0%) (p < 0.0001); the same order was found in the validation cohort. The CAO-free survival time was significantly different among the four groups (p < 0.0001). Upstream dilatation (hazard ratio, 1.126) was a risk factor for predicting CAO in RS. Furthermore, when upstream dilatation was added to diagnose RS, 17.6% of high-risk strictures were neglected.

CONCLUSIONS

CAO differs significantly between RS and ES, and clinicians should pay more attention to strictures in G1b and G3. Upstream dilatation has an important impact on the clinical outcome of RS but may not be an essential factor for RS diagnosis.

CLINICAL RELEVANCE STATEMENT

This study explored the definition of intestinal stricture with the greatest significance for the clinical diagnosis and prognosis of patients with CD, and consequently provided effective auxiliary information for clinicians to formulate strategies for the treatment of CD intestinal strictures.

KEY POINTS

• The retrospective double-center study showed that clinical adverse outcome is different between radiological strictures and endoscopic strictures in CD. • Upstream dilatation has an important impact on the clinical outcome of radiological strictures but may not be an essential factor for diagnosis of radiological strictures. • Radiological stricture with upstream dilatation and simultaneous radiological and endoscopic stricture were at increased risk for clinical adverse outcomes; thus, closer monitoring should be considered.

Type 1 Diabetes Risk Phenotypes Using Cluster Analysis

Background

Although statistical models for predicting type 1 diabetes risk have been developed, approaches that reveal clinically meaningful clusters in the at-risk population and allow for non-linear relationships between predictors are lacking. We aimed to identify and characterize clusters of islet autoantibody-positive individuals that share similar characteristics and type 1 diabetes risk.

Methods

We tested a novel outcome-guided clustering method in initially non-diabetic autoantibody-positive relatives of individuals with type 1 diabetes, using the TrialNet Pathway to Prevention (PTP) study data (n=1127). The outcome of the analysis was time to type 1 diabetes and variables in the model included demographics, genetics, metabolic factors and islet autoantibodies. An independent dataset (Diabetes Prevention Trial of Type 1 Diabetes, DPT-1 study) (n=704) was used for validation.

Findings

The analysis revealed 8 clusters with varying type 1 diabetes risks, categorized into three groups. Group A had three clusters with high glucose levels and high risk. Group B included four clusters with elevated autoantibody titers. Group C had three lower-risk clusters with lower autoantibody titers and glucose levels. Within the groups, the clusters exhibit variations in characteristics such as glucose levels, C-peptide levels, age, and genetic risk. A decision rule for assigning individuals to clusters was developed. The validation dataset confirms that the clusters can identify individuals with similar characteristics.

Interpretation

Demographic, metabolic, immunological, and genetic markers can be used to identify clusters of distinctive characteristics and different risks of progression to type 1 diabetes among autoantibody-positive individuals with a family history of type 1 diabetes. The results also revealed the heterogeneity in the population and complex interactions between variables.

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.

CGM Metrics Identify Dysglycemic States in Participants From the TrialNet Pathway to Prevention Study

OBJECTIVE

Continuous glucose monitoring (CGM) parameters may identify individuals at risk for progression to overt type 1 diabetes. We aimed to determine whether CGM metrics provide additional insights into progression to clinical stage 3 type 1 diabetes.

RESEARCH DESIGN AND METHODS

One hundred five relatives of individuals in type 1 diabetes probands (median age 16.8 years; 89% non-Hispanic White; 43.8% female) from the TrialNet Pathway to Prevention study underwent 7-day CGM assessments and oral glucose tolerance tests (OGTTs) at 6-month intervals. The baseline data are reported here. Three groups were evaluated: individuals with 1) stage 2 type 1 diabetes (n = 42) with two or more diabetes-related autoantibodies and abnormal OGTT; 2) stage 1 type 1 diabetes (n = 53) with two or more diabetes-related autoantibodies and normal OGTT; and 3) negative test for all diabetes-related autoantibodies and normal OGTT (n = 10).

RESULTS

Multiple CGM metrics were associated with progression to stage 3 type 1 diabetes. Specifically, spending ≥5% time with glucose levels ≥140 mg/dL (P = 0.01), ≥8% time with glucose levels ≥140 mg/dL (P = 0.02), ≥5% time with glucose levels ≥160 mg/dL (P = 0.0001), and ≥8% time with glucose levels ≥160 mg/dL (P = 0.02) were all associated with progression to stage 3 disease. Stage 2 participants and those who progressed to stage 3 also exhibited higher mean daytime glucose values; spent more time with glucose values over 120, 140, and 160 mg/dL; and had greater variability.

CONCLUSIONS

CGM could aid in the identification of individuals, including those with a normal OGTT, who are likely to rapidly progress to stage 3 type 1 diabetes.

Consortium-based approach to receiving an EMA qualification opinion on the use of islet autoantibodies as enrichment biomarkers in type 1 diabetes clinical studies

The development of medical products that can delay or prevent progression to stage 3 type 1 diabetes faces many challenges. Of note, optimising patient selection for type 1 diabetes prevention clinical trials is hindered by significant patient heterogeneity and a lack of characterisation of the time-varying probability of progression to stage 3 type 1 diabetes in individuals positive for two or more islet autoantibodies. To meet these needs, the Critical Path Institute's Type 1 Diabetes Consortium was launched in 2017 as a pre-competitive public-private partnership between stakeholders from the pharmaceutical industry, patient advocacy groups, philanthropic organisations, clinical researchers, the National Institutes of Health and the Food and Drug Administration. The Type 1 Diabetes Consortium acquired and aggregated data from three longitudinal observational studies, Environmental Determinants of Diabetes in the Young (TEDDY), Diabetes Autoimmunity Study in the Young (DAISY) and TrialNet Pathway to Prevention (TN01), and used analysis subsets of these data to support the model-based qualification of islet autoantibodies as enrichment biomarkers for patient selection in type 1 diabetes prevention trials, including registration studies. The Type 1 Diabetes Consortium has now received a qualification opinion from the European Medicines Agency for the use of these biomarkers, a major success for the field of type 1 diabetes. This endorsement will improve product developers' ability to design clinical trials of agents intended to prevent or delay type 1 diabetes that are reduced in size and/or length, while being adequately powered.

Risk Modeling to Reduce Monitoring of an Autoantibody-Positive Population to Prevent DKA at Type 1 Diabetes Diagnosis

CONTEXT

The presence of islet autoimmunity identifies individuals likely to progress to clinical type 1 diabetes (T1D). In clinical research studies, autoantibody screening followed by regular metabolic monitoring every 6 months reduces incidence of diabetic ketoacidosis (DKA) at diagnosis.

OBJECTIVE

We hypothesized that DKA reduction can be achieved on a population basis with a reduced frequency of metabolic monitoring visits. We reasoned that prolonged time between the development of T1D and the time of clinical diagnosis ("undiagnosed time") would more commonly result in DKA and thus that limiting undiagnosed time would decrease DKA.

METHODS

An analysis was conducted of data from TrialNet's Pathway to Prevention (PTP), a cross-sectional longitudinal study that identifies and follows at-risk relatives of people with T1D. PTP is a population-based study enrolling across multiple countries. A total of 6193 autoantibody (AAB)-positive individuals participated in PTP from March 2004 to April 2019. We developed models of progression to clinical diagnosis for pediatric and adult populations with single or multiple AAB, and summarized results using estimated hazard rate. An optimal monitoring visit schedule was determined for each model to achieve a minimum average level of undiagnosed time for each population.

RESULTS

Halving the number of monitoring visits usually conducted in research studies is likely to substantially lower the population incidence of DKA at diagnosis of T1D.

CONCLUSION

Our study has clinical implications for the metabolic monitoring of at-risk individuals. Fewer monitoring visits would reduce the clinical burden, suggesting a path toward transitioning monitoring beyond the research setting.

High-expression of the innate-immune related gene UNC93B1 predicts inferior outcomes in acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy with dismal prognosis. Identification of better biomarkers remained a priority to improve established stratification and guide therapeutic decisions. Therefore, we extracted the RNA sequence data and clinical characteristics of AML from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression database (GTEx) to identify the key factors for prognosis. We found UNC93B1 was highly expressed in AML patients and significantly linked to poor clinical features (p < 0.05). We further validated the high expression of UNC93B1 in another independent AML cohort from GEO datasets (p < 0.001) and performed quantitative PCR of patient samples to confirm the overexpression of UNC93B1 in AML (p < 0.005). Moreover, we discovered high level of UNC93B1 was an independent prognostic factor for poorer outcome both in univariate analysis and multivariate regression (p < 0.001). Then we built a nomogram model based on UNC93B1 expression, age, FAB subtype and cytogenetic risk, the concordance index of which for predicting overall survival was 0.729 (p < 0.001). Time-dependent ROC analysis for predicting survival outcome at different time points by UNC93B1 showed the cumulative 2-year survival rate was 43.7%, and 5-year survival rate was 21.9%. The differentially expressed genes (DEGs) between two groups divided by UNC93B1 expression level were enriched in innate immune signaling and metabolic process pathway. Protein-protein interaction (PPI) network indicated four hub genes (S100A9, CCR1, MRC1 and CD1C) interacted with UNC93B1, three of which were also significantly linked to inferior outcome. Furthermore, we discovered high UNC93B1 tended to be infiltrated by innate immune cells, including Macrophages, Dendritic cells, Neutrophils, Eosinophils, and NK CD56dim cells. We also found UNC93B1 had a significantly positive correlation with CD14, CD68 and almost all Toll-like receptors. Finally, we revealed negatively correlated expression of UNC93B1 and BCL2 in AML and conjectured that high-UNC93B1 monocytic AML is more resistant to venetoclax. And we found high MCL-1 expression compensated for BCL-2 loss, thus, we proposed MCL-1 inhibitor might overcome the resistance of venetoclax in AML. Altogether, our findings demonstrated the utility of UNC93B1 as a powerful poor prognostic predictor and alternative therapeutic target.

Glutamine deamidation does not increase the immunogenicity of C-peptide in people with type 1 diabetes

Type 1 diabetes (T1D) is a T-cell mediated autoimmune disease in which the insulin-producing beta cells are destroyed. While it is clear that full-length C-peptide, derived from proinsulin, is a major antigen in human T1D it is not clear how and why C-peptide becomes a target of the autoimmune CD4⁺ T-cell responses in T1D. Neoepitopes formed by the conversion of glutamine (Q) residues to glutamic acid (E) by deamidation are central to the immune pathogenesis of coeliac disease and have been implicated in autoimmune responses in T1D. Here, we asked if the immunogenicity of full-length C-peptide, which comprises four glutamine residues, was enhanced by deamidation, which we mimicked by substituting glutamic acid for glutamine residue. First, we used a panel of 18 well characterized CD4⁺ T-cell lines specific for epitopes derived from human C-peptide. In all cases, when the substitution fell within the cognate epitope the response was diminished, or in a few cases unchanged. In contrast, when the substitution fell outside the epitope recognized by the TCR responses were unchanged or slightly augmented. Second, we compared CD4⁺ T-cell proliferation responses, against deamidated and unmodified C-peptide, in the peripheral blood of people with or without T1D using the CFSE-based proliferation assay. While, as reported previously, responses were detected to unmodified C-peptide, no deamidated C-peptide was consistently more stimulatory than native C-peptide. Overall responses were weaker to deamidated C-peptide compared to unmodified C-peptide. Hence, we conclude that deamidated C-peptide does not play a role in beta-cell autoimmunity in people with T1D.

Incomplete time-series gene expression in integrative study for islet autoimmunity prediction

Type 1 diabetes (T1D) outcome prediction plays a vital role in identifying novel risk factors, ensuring early patient care and designing cohort studies. TEDDY is a longitudinal cohort study that collects a vast amount of multi-omics and clinical data from its participants to explore the progression and markers of T1D. However, missing data in the omics profiles make the outcome prediction a difficult task. TEDDY collected time series gene expression for less than 6% of enrolled participants. Additionally, for the participants whose gene expressions are collected, 79% time steps are missing. This study introduces an advanced bioinformatics framework for gene expression imputation and islet autoimmunity (IA) prediction. The imputation model generates synthetic data for participants with partially or entirely missing gene expression. The prediction model integrates the synthetic gene expression with other risk factors to achieve better predictive performance. Comprehensive experiments on TEDDY datasets show that: (1) Our pipeline can effectively integrate synthetic gene expression with family history, HLA genotype and SNPs to better predict IA status at 2 years (sensitivity 0.622, AUC 0.715) compared with the individual datasets and state-of-the-art results in the literature (AUC 0.682). (2) The synthetic gene expression contains predictive signals as strong as the true gene expression, reducing reliance on expensive and long-term longitudinal data collection. (3) Time series gene expression is crucial to the proposed improvement and shows significantly better predictive ability than cross-sectional gene expression. (4) Our pipeline is robust to limited data availability. Availability: Code is available at https://github.com/compbiolabucf/TEDDY.

Fecal microbiota transplantation treatment of autoimmune-mediated type 1 diabetes: A systematic review

There is a strong link between fecal microbiota and the development of type 1 diabetes. As an emerging therapeutic modality, fecal microbiota transplantation has been shown to be safe and effective in the treatment of many intestinal and extraintestinal diseases. Various studies have found that fecal microbiota transplantation can treat diseases by correcting patients' immune disorders. Besides, many studies have found that fecal microbiota transplantation can improve glycemic control and insulin resistance in diabetic patients. Therefore, this paper reviews the mechanism of action of fecal microbiota transplantation on autoimmune-mediated T1DM and the current research progress, feasibility, and issues that need to be addressed in the future development of fecal microbiota transplantation in the treatment of autoimmune-mediated T1DM.

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.

Comprehensive Diabetes Autoantibody Laboratory-Based Clinical Service Testing in 6044 Consecutive Patients: Analysis of Age and Sex Effects

Background

In 2017, Mayo Clinic Laboratories commenced offering a comprehensive type 1 diabetes mellitus (T1DM) autoantibody (Ab) evaluation including 4 known Abs targeting glutamic acid decarboxylase (GAD65), protein tyrosine phosphatase-like islet antigen 2 (IA2), insulin (IAA), and zinc transporter 8 protein (ZnT8) antigens.

Methods

The objective of this study was to evaluate real-time data on the frequency and patterns of all 4 Abs stratified by age and sex from 6044 unique consecutive adult and pediatric patients undergoing evaluation for suspected diabetes.

Results

At least one Ab was found in 3370 (56%) of all samples: 67% of children (aged 0–17), 49% of young adults (aged 18–35), and 41% for both middle-aged (aged 36–55) and older (aged &gt;55) adults (P ≤ 0.0001). GAD65-Abs were the most common in all age groups, followed by ZnT8-Ab in those &lt;36 years, or IAA-Ab in those ≥36. Frequencies of IA2- and ZnT8-Abs drop significantly with increasing age. Clusters of 3 or 4 Abs were more frequently encountered in younger patients (41% of children vs 12% in middle- and 13% in older age groups, P ≤ 0.0001).

Conclusions

Children undergoing serological evaluation for T1DM were more commonly positive for autoantibodies than older age groups. The frequency of ZnT8- and IA2-Abs decreases, and IAA-Ab frequency increases with increasing age, and clusters of 2 to 4 autoantibodies are more common in children. In clinical practice, comprehensive testing for diabetes autoantibodies resulted in a switch in diagnosis to T1DM for patients previously classified as type 2 diabetes mellitus.

General population screening for childhood type 1 diabetes: is it time for a UK strategy?

Type 1 diabetes (T1D) is a chronic autoimmune disease of childhood affecting 1:500 children aged under 15 years, with around 25% presenting with life-threatening diabetic ketoacidosis (DKA). While first-degree relatives have the highest risk of T1D, more than 85% of children who develop T1D do not have a family history. Despite public health awareness campaigns, DKA rates have not fallen over the last decade. T1D has a long prodrome, and it is now possible to identify children who go on to develop T1D with a high degree of certainty. The reasons for identifying children presymptomatically include prevention of DKA and related morbidities and mortality, reducing the need for hospitalisation, time to provide emotional support and education to ensure a smooth transition to insulin treatment, and opportunities for new treatments to prevent or delay progression. Research studies of population-based screening strategies include using islet autoantibodies alone or in combination with genetic risk factors, both of which can be measured from a capillary sample. If found during screening, the presence of two or more islet autoantibodies has a high positive predictive value for future T1D in childhood (under 18 years), offering an opportunity for DKA prevention. However, a single time-point test will not identify all children who go on to develop T1D, and so combining with genetic risk factors for T1D may be an alternative approach. Here we discuss the pros and cons of T1D screening in the UK, the different strategies available, the knowledge gaps and why a T1D screening strategy is needed.

A classification and regression tree analysis identifies subgroups of childhood type 1 diabetes

Background

Diabetes in childhood and adolescence includes autoimmune and non-autoimmune forms with heterogeneity in clinical and biochemical presentations. An unresolved question is whether there are subtypes, endotypes, or theratypes within these forms of diabetes.

Methods

The multivariable classification and regression tree (CART) analysis method was used to identify subgroups of diabetes with differing residual C-peptide levels in patients with newly diagnosed diabetes before 20 years of age (n=1192). The robustness of the model was assessed in a confirmation and prognosis cohort (n=2722).

Findings

The analysis selected age, haemoglobin A1c (HbA1c), and body mass index (BMI) as split parameters that classified patients into seven islet autoantibody-positive and three autoantibody-negative groups. There were substantial differences in genetics, inflammatory markers, diabetes family history, lipids, 25-OH-Vitamin D3, insulin treatment, insulin sensitivity and insulin autoimmunity among the groups, and the method stratified patients with potentially different pathogeneses and prognoses. Interferon-ɣ and/or tumour necrosis factor inflammatory signatures were enriched in the youngest islet autoantibody-positive groups and in patients with the lowest C-peptide values, while higher BMI and type 2 diabetes characteristics were found in older patients. The prognostic relevance was demonstrated by persistent differences in HbA1c at 7 years median follow-up.

Interpretation

This multivariable analysis revealed subgroups of young patients with diabetes that have potential pathogenetic and therapeutic relevance.

Funding

The work was supported by funds from the German Federal Ministry of Education and Research (01KX1818; FKZ 01GI0805; DZD e.V.), the Innovative Medicine Initiative 2 Joint Undertaking INNODIA (grant agreement No. 115797), the German Robert Koch Institute, and the German Diabetes Association.

Association of HLA-DQ Heterodimer Residues -18β and β57 With Progression From Islet Autoimmunity to Diabetes in the Diabetes Prevention Trial-Type 1

OBJECTIVE

The purpose was to test the hypothesis that the HLA-DQαβ heterodimer structure is related to 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 HLA-DQA1-B1 class II genes in 670 subjects in the Diabetes Prevention Trial-Type 1 (DPT-1). Coding sequences were translated into DQ α- and β-chain amino acid residues and used in hierarchically organized haplotype (HOH) association analysis to identify motifs associated with diabetes onset.

RESULTS

The opposite diabetes risks were confirmed for HLA DQA1*03:01-B1*03:02 (hazard ratio [HR] 1.36; P = 2.01 ∗ 10-3) and DQA1*03:03-B1*03:01 (HR 0.62; P = 0.037). The HOH analysis uncovered residue -18β in the signal peptide and β57 in the β-chain to form six motifs. DQ*VA was associated with faster (HR 1.49; P = 6.36 ∗ 10-4) and DQ*AD with slower (HR 0.64; P = 0.020) progression to diabetes onset. VA/VA, representing DQA1*03:01-B1*03:02 (DQ8/8), had a greater HR of 1.98 (P = 2.80 ∗ 10-3). The DQ*VA motif was associated with both islet cell antibodies (P = 0.023) and insulin autoantibodies (IAAs) (P = 3.34 ∗ 10-3), while the DQ*AD motif was associated with a decreased IAA frequency (P = 0.015). Subjects with DQ*VA and DQ*AD experienced, respectively, increasing and decreasing trends of HbA1c levels throughout the follow-up.

CONCLUSIONS

HLA-DQ structural motifs appear to modulate progression from islet autoimmunity to diabetes among at-risk relatives with islet autoantibodies. Residue -18β within the signal peptide may be related to levels of protein synthesis and β57 to stability of the peptide-DQab trimolecular complex.

Altered Tim-1 and IL-10 Expression in Regulatory B Cell Subsets in Type 1 Diabetes

Background

Type 1 diabetes (T1D) is an autoimmune disease with a complex aetiology. B cells play an important role in the pathogenesis of T1D. Regulatory B cells (Bregs) are a subset of B cells that produce and secrete the inhibitory factor interleukin-10 (IL-10), thereby exerting an anti-inflammatory effect. It was recently discovered that T-cell immunoglobulin mucin domain 1 (Tim-1) is essential for maintaining Bregs function related to immune tolerance. However, the detailed understanding of Tim-1⁺ Bregs and IL-10⁺ Bregs in T1D patients is lacking. This study aimed to characterize the profile of B cell subsets in T1D patients compared with that in controls and determine whether Tim-1⁺ Bregs and IL-10⁺ Bregs play roles in T1D.

Materials and Methods

A total of 47 patients with T1D, 30 patients with type 2 diabetes (T2D) and 24 healthy controls were recruited in this study. Flow cytometry was used to measure the levels of different B cell subsets (including B cells, plasmablasts, and Bregs) in the peripheral blood. Radiobinding assays were performed to detect the antibody titres of T1D patients. In addition, the correlations between different B cell subsets and patient parameters were investigated.

Results

Compared with healthy controls, differences in frequency of Tim-1⁺ Bregs were significantly decreased in patients with T1D (36.53 ± 6.51 vs. 42.25 ± 6.83, P=0.02^*), and frequency of IL-10⁺ Bregs were lower than healthy controls (17.64 ± 7.21vs. 24.52 ± 11.69, P=0.009^**), the frequency of total Bregs in PBMC was also decreased in patients with T1D (1.42 ± 0.53vs. 1.99 ± 0.93, P=0.002.^**). We analyzed whether these alterations in B cells subsets were associated with clinical features. The frequencies of Tim-1⁺ Bregs and IL-10⁺ Bregs were negatively related to fasting blood glucose (FBG) (r=-0.25 and -0.22; P=0.01^* and 0.03^*, respectively). The frequencies of Tim-1⁺ Bregs and IL-10⁺ Bregs are positively correlated with fast C-peptide (FCP) (r=0.23 and 0.37; P=0.02^* and 0.0001^***, respectively). In addition, the frequency of IL-10⁺ Breg was also negatively related to glycosylated haemoglobin (HbA1c) (r=-0.20, P=0.04^*). The frequencies of Tim-1⁺ Bregs, IL-10⁺ Bregs and Bregs in T2D patients were reduced, but no statistically significant difference was found between other groups. Interestingly, there was positive correlation between the frequencies of Tim-1⁺ Bregs and IL-10⁺ Bregs in T1D (r=0.37, P=0.01^*). Of note, it is worth noting that our study did not observe any correlations between B cell subsets and autoantibody titres.

Conclusions

Our study showed altered Tim-1 and IL-10 expression in regulatory B cell in T1D patients. Tim-1, as suggested by the present study, is associated with islet function and blood glucose levels. These findings indicate that Tim-1⁺ Bregs and IL-10⁺ Bregs were involved in the pathogenesis of T1D.

Non-HLA Gene Polymorphisms in the Pathogenesis of Type 1 Diabetes: Phase and Endotype Specific Effects

The non-HLA loci conferring susceptibility to type 1 diabetes determine approximately half of the genetic disease risk, and several of them have been shown to affect immune-cell or pancreatic β-cell functions. A number of these loci have shown associations with the appearance of autoantibodies or with progression from seroconversion to clinical type 1 diabetes. In the current study, we have re-analyzed 21 of our loci with prior association evidence using an expanded DIPP follow-up cohort of 976 autoantibody positive cases and 1,910 matched controls. Survival analysis using Cox regression was applied for time periods from birth to seroconversion and from seroconversion to type 1 diabetes. The appearance of autoantibodies was also analyzed in endotypes, which are defined by the first appearing autoantibody, either IAA or GADA. Analyzing the time period from birth to seroconversion, we were able to replicate our previous association findings at PTPN22, INS, and NRP1. Novel findings included associations with ERBB3, UBASH3A, PTPN2, and FUT2. In the time period from seroconversion to clinical type 1 diabetes, prior associations with PTPN2, CD226, and PTPN22 were replicated, and a novel association with STAT4 was observed. Analyzing the appearance of autoantibodies in endotypes, the PTPN22 association was specific for IAA-first. In the progression phase, STAT4 was specific for IAA-first and ERBB3 to GADA-first. In conclusion, our results further the knowledge of the function of non-HLA risk polymorphisms in detailing endotype specificity and timing of disease development.

GAD65 Antibody Epitopes and Genetic Background in Latent Autoimmune Diabetes in Youth (LADY)

Epitope-specific GAD65Abs and HLA-DR-DQ gene assays help improve the value of risk stratification in autoimmune diabetes mellitus and protect islet function. Identification and early intervention are important for latent autoimmune diabetes in youth (LADY). The aims of this study were to investigate 1) the frequencies of the epitope-specific GAD65Abs and HLA-DR-DQ genes in LADY and 2) the association between HLA-DR-DQ genes and epitope-specific GAD65Abs. Higher frequencies of GAD65-CAb and multiepitope GAD65Abs were observed in young type 1 diabetes, LADY, and old type 1 diabetes subjects than those in latent autoimmune diabetes in adult (LADA) patients. The frequencies of the specific susceptible HLA haplotype DR3, total susceptible HLA haplotypes, and high-risk genotypes were higher in type 1 diabetes and LADY patients than those in LADA patients. In contrast, type 1 diabetes and LADY patients had lower frequencies of low/no genetic risk genotypes (DRX/X) than those of LADA patients. Logistic regression analysis suggested that the susceptible HLA haplotypes were risk factors for glutamic acid decarboxylase antibody (GADA) multiepitope positivity in autoimmune diabetes mellitus. LADY may be more severe than LADA, and LADY seemed to be a transitional type of type 1 diabetes and LADA. GADA epitope and HLA-DR-DQ gene assays are important for risk stratification in autoimmune diabetes mellitus and protection of islet function.

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.

Environmental Determinants of Type 1 Diabetes: From Association to Proving Causality

The rising incidence of type 1 diabetes (T1D) cannot be ascribed to genetics alone, and causative environmental triggers and drivers must also be contributing. The prospective TEDDY study has provided the greatest contributions in modern time, by addressing misconceptions and refining the search strategy for the future. This review outlines the evidence to date to support the pathways from association to causality, across all stages of T1D (seroconversion to beta cell failure). We focus on infections and vaccinations; infant growth and childhood obesity; the gut microbiome and the lifestyle factors which cultivate it. Of these, the environmental determinants which have the most supporting evidence are enterovirus infection, rapid weight gain in early life, and the microbiome. We provide an infographic illustrating the key environmental determinants in T1D and their likelihood of effect. The next steps are to investigate these environmental triggers, ideally though gold-standard randomised controlled trials and further prospective studies, to help explore public health prevention strategies.

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.

The β Cell in Diabetes: Integrating Biomarkers With Functional Measures

The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet β cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the β cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of β-cell secretory function that themselves could be considered biomarkers.

Neutralizing Ljungan virus antibodies in children with newly diagnosed type 1 diabetes

Ljungan virus (LV), a Parechovirus of the Picornavirus family, first isolated from a bank vole at the Ljungan river in Sweden, has been implicated in the risk for autoimmune type 1 diabetes. An assay for neutralizing Ljungan virus antibodies (NLVA) was developed using the original 87-012 LV isolate. The goal was to determine NLVA titres in incident 0-18 years old newly diagnosed type 1 diabetes patients (n=67) and school children controls (n=292) from Jämtland county in Sweden. NLVA were found in 41 of 67 (61 %) patients compared to 127 of 292 (44 %) controls (P=0.009). In the type 1 diabetes patients, NLVA titres were associated with autoantibodies to glutamic acid decarboxylase (GADA) (P=0.023), but not to autoantibodies against insulin (IAA) or islet antigen-2 (IA-2A). The NLVA assay should prove useful for further investigations to determine levels of LV antibodies in patients and future studies to determine a possible role of LV in autoimmune type 1 diabetes.

Novel autoantibodies to the β-cell surface epitopes of ZnT8 in patients progressing to type-1 diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by autoimmune destruction of insulin-producing β-cells in pancreatic islets. Seroconversions to islet autoantibodies (IAbs) precede the disease onset by many years, but the role of humoral autoimmunity in the disease initiation and progression are unclear. In the present study, we identified a new IAb directed to the extracellular epitopes of ZnT8 (ZnT8ec) in newly diagnosed patients with T1D, and demonstrated immunofluorescence staining of the surface of human β-cells by autoantibodies to ZnT8ec (ZnT8ecA). With the assay specificity set on 99th percentile of 336 healthy controls, the ZnT8ecA positivity rate was 23.6% (74/313) in patients with T1D. Moreover, 30 children in a longitudinal follow up of clinical T1D development were selected for sequential expression of four major IAbs (IAA, GADA, IA-2A and ZnT8icA). Among them, 10 children were ZnT8ecA positive. Remarkably, ZnT8ecA was the earliest IAb to appear in all 10 children. The identification of ZnT8ec as a cell surface target of humoral autoimmunity in the earliest phase of IAb responses opens a new avenue of investigation into the role of IAbs in the development of β-cell autoimmunity.

Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.

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.

De-coding genetic risk variants in type 1 diabetes

The conceptual basis for a genetic predisposition underlying the risk for developing type 1 diabetes (T1D) predates modern human molecular genetics. Over half of the genetic risk has been attributed to the human leukocyte antigen (HLA) class II gene region and to the insulin (INS) gene locus - both thought to confer direction of autoreactivity and tissue specificity. Notwithstanding, questions still remain regarding the functional contributions of a vast array of minor polygenic risk variants scattered throughout the genome that likely influence disease heterogeneity and clinical outcomes. Herein, we summarize the available literature related to the T1D-associated coding variants defined at the time of this review, for the genes PTPN22, IFIH1, SH2B3, CD226, TYK2, FUT2, SIRPG, CTLA4, CTSH and UBASH3A. Data from genotype-selected human cohorts are summarized, and studies from the non-obese diabetic (NOD) mouse are presented to describe the functional impact of these variants in relation to innate and adaptive immunity as well as to β-cell fragility, with expression profiles in tissues and peripheral blood highlighted. The contribution of each variant to progression through T1D staging, including environmental interactions, are discussed with consideration of how their respective protein products may serve as attractive targets for precision medicine-based therapeutics to prevent or suspend the development of T1D.

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

HLA-DQ molecules account over 50% genetic risk of type 1 diabetes (T1D), but little is known about associated residues. Through next generation targeted sequencing technology and deep learning of DQ residue sequences, the aim was to uncover critical residues and their motifs associated with T1D. Our analysis uncovered (αa1, α44, α157, α196) and (β9, β30, β57, β70, β135) on the HLA-DQ molecule. Their motifs captured all known susceptibility and resistant T1D associations. Three motifs, “DCAA-YSARD” (OR = 2.10, p = 1.96*10⁻²⁰), “DQAA-YYARD” (OR = 3.34, 2.69*10⁻⁷²) and “DQDA-YYARD” (OR = 3.71, 1.53*10⁻⁶) corresponding to DQ2.5 and DQ8.1 (the latter two motifs) associated with susceptibility. Ten motifs were significantly associated with resistance to T1D. Collectively, homozygous DQ risk motifs accounted for 43% of DQ-T1D risk, while homozygous DQ resistant motifs accounted for 25% protection to DQ-T1D risk. Of the identified nine residues five were within or near anchoring pockets of the antigenic peptide (α44, β9, β30, β57 and β70), one was the N-terminal of the alpha chain (αa1), one in the CD4-binding region (β135), one in the putative cognate TCR-induced αβ homodimerization process (α157), and one in the intra-membrane domain of the alpha chain (α196). Finding these critical residues should allow investigations of fundamental properties of host immunity that underlie tolerance to self and organ-specific autoimmunity.

Neoepitopes in Type 1 Diabetes: Etiological Insights, Biomarkers and Therapeutic Targets

The mechanisms underlying type 1 diabetes (T1D) pathogenesis remain largely unknown. While autoantibodies to pancreatic beta-cell antigens are often the first biological response and thereby a useful biomarker for identifying individuals in early stages of T1D, their role in T1D pathogenesis is not well understood. Recognition of these antigenic targets by autoreactive T-cells plays a pathological role in T1D development. Recently, several beta-cell neoantigens have been described, indicating that both neoantigens and known T1D antigens escape central or peripheral tolerance. Several questions regarding the mechanisms by which tolerance is broken in T1D remain unanswered. Further delineating the timing and nature of antigenic responses could allow their use as biomarkers to improve staging, as targets for therapeutic intervention, and lead to a better understanding of the mechanisms leading to loss of tolerance. Multiple factors that contribute to cellular stress may result in the generation of beta-cell derived neoepitopes and contribute to autoimmunity. Understanding the cellular mechanisms that induce beta-cells to produce neoantigens has direct implications on development of therapies to intercept T1D disease progression. In this perspective, we will discuss evidence for the role of neoantigens in the pathogenesis of T1D, including antigenic responses and cellular mechanisms. We will additionally discuss the pathways leading to neoepitope formation and the cross talk between the immune system and the beta-cells in this regard. Ultimately, delineating the timing of neoepitope generation in T1D pathogenesis will determine their role as biomarkers as well as therapeutic targets.

An Age-Related Exponential Decline in the Risk of Multiple Islet Autoantibody Seroconversion During Childhood

OBJECTIVE

Islet autoimmunity develops before clinical type 1 diabetes and includes multiple and single autoantibody phenotypes. The objective was to determine age-related risks of islet autoantibodies that reflect etiology and improve screening for presymptomatic type 1 diabetes.

RESEARCH DESIGN AND METHODS

The Environmental Determinants of Diabetes in the Young study prospectively monitored 8,556 genetically at-risk children at 3- to 6-month intervals from birth for the development of islet autoantibodies and type 1 diabetes. The age-related change in the risk of developing islet autoantibodies was determined using landmark and regression models.

RESULTS

The 5-year risk of developing multiple islet autoantibodies was 4.3% (95% CI 3.8-4.7) at 7.5 months of age and declined to 1.1% (95% CI 0.8-1.3) at a landmark age of 6.25 years (P < 0.0001). Risk decline was slight or absent in single insulin and GAD autoantibody phenotypes. The influence of sex, HLA, and other susceptibility genes on risk subsided with increasing age and was abrogated by age 6 years. Highest sensitivity and positive predictive value of multiple islet autoantibody phenotypes for type 1 diabetes was achieved by autoantibody screening at 2 years and again at 5-7 years of age.

CONCLUSIONS

The risk of developing islet autoimmunity declines exponentially with age, and the influence of major genetic factors on this risk is limited to the first few years of life.