Reversion of β-Cell Autoimmunity Changes Risk of Type 1 Diabetes: TEDDY Study

EDENT1FI Master Protocol for screening of presymptomatic early-stage type 1 diabetes in children and adolescents

INTRODUCTION

The identification of type 1 diabetes at an early presymptomatic stage has clinical benefits. These include a reduced risk of diabetic ketoacidosis (DKA) at the clinical manifestation of the disease and a significant reduction in clinical symptoms. The European action for the Diagnosis of Early Non-clinical Type 1 diabetes For disease Interception (EDENT1FI) represents a pioneering effort to advance early detection of type 1 diabetes through public health screening. With the EDENT1FI Master Protocol, the project aims to harmonise and standardise screening for early-stage type 1 diabetes and care.

METHODS AND ANALYSIS

Public health islet autoantibody screening is conducted in the Czech Republic, Denmark, Germany, Italy, Poland, Portugal, Sweden and the UK. Between November 2023 (start date) and October 2028 (planned end date), an estimated number of 200 000 children and adolescents aged 1-17 years are expected to be screened. Screening is performed in capillary blood, examining different islet autoantibodies (autoantibodies against insulin, glutamic acid decarboxylase-65, insulinoma-associated antigen-2 and/or zinc transporter-8). Positive screening results undergo confirmation through a second antibody method. A second (venous) blood sample is requested if at least two autoantibodies are detected, to confirm the autoantibody status. Children and adolescents with confirmed two or more autoantibodies are invited to metabolic staging (oral glucose tolerance test, haemoglobin A1c (HbA1c), random glucose, optionally continuous glucose monitoring); an educational programme and recommendations for monitoring are provided. The feasibility and acceptability of screening are evaluated by feedback questionnaires. Pseudonymised data is collated in the EDENT1FI Registry. Study outcomes include country-specific screening rates, prevalences of stage 1 and stage 2 type 1 diabetes, number in EDENT1FI Registry, proportion with DKA and symptoms at clinical diagnosis and median HbA1c.

ETHICS AND DISSEMINATION

Following the EDENT1FI Master Protocol, site-specific protocols are developed and approved by local ethics committees (Technical University of Munich, Medical Faculty, Nr. 70/14; Medizinische Hochschule Hannover, Nr. 9588_BO_S_2021; Technische Universität Dresden, Nr. BO-EK-356082020; Center for Sundhed Region Hovedstaden, Nr. H-22053116; Swedish Ethical Review Authority, Nr. 2023-00312-01; National Health Service Health Research Authority and Health Care Research Wales, IRAS (Integrated Research Application System) project ID 309252; Italian National Institute of Health, National ethics committee for clinical trials of public research bodies (EPR) and other national public institutions, Prot. PRE BIO CE Nr. 0059835; Charles University in Prague, Ethics Committee for Multi-Centric Clinical Trials of the University Hopital Motol and 2nd Faculty of Medicine, Nr. 1271/23; Bioethics Committee at the Medical University of Warsaw, Nr. 21/2024 and KB/6/R/2024; Associação Protectora dos Diabéticos de Portugal, Nr. 211/2024). Results are disseminated through peer-reviewed journals and conference presentations and will be shared openly.

Emerging Concepts and Success Stories in Type 1 Diabetes Research: A Road Map for a Bright Future

Type 1 diabetes treatment stands at a crucial and exciting crossroad since the 2022 U.S. Food and Drug Administration approval of teplizumab to delay disease development. In this article, we discuss four major conceptual and practical issues that emerged as key to further advancement in type 1 diabetes research and therapies. First, collaborative networks leveraging the synergy between the type 1 diabetes research and care community members are key to fostering innovation, know-how, and translation into the clinical arena worldwide. Second, recent clinical trials in presymptomatic stage 2 and recent-onset stage 3 disease have shown the promise, and potential pitfalls, of using immunomodulatory and/or β-cell protective agents to achieve sustained remission or prevention. Third, the increasingly appreciated heterogeneity of clinical, immunological, and metabolic phenotypes and disease trajectories is of critical importance to advance the decision-making process for tailored type 1 diabetes care and therapy. Fourth, the clinical benefits of early diagnosis of β-cell autoimmunity warrant consideration of general population screening for islet autoantibodies, which requires further efforts to address the technical, organizational, and ethical challenges inherent to a sustainable program. Efforts are underway to integrate these four concepts into the future directions of type 1 diabetes research and therapy.

ARTICLE HIGHLIGHTS

[Early Detection Of Type 1 Diabetes By Islet Autoantibody Screening: A Position Paper Of The Fr1daplex Project Leaders And Training Centres, Bvkj Bavaria And Paednetz (Registered) Bavaria]

This position paper is based on the authors' many years of clinical experience and basic science research on the diagnosis and treatment of children and adolescents with a presymptomatic early stage of type 1 diabetes. The benefits as well as potential disadvantages of early detection of type 1 diabetes by islet autoantibody screening are critically discussed. In addition, the perspectives of delaying the onset of the clinical metabolic disease through treatment with teplizumab are addressed. Today, we see the chance for a relevant improvement in therapeutic options and life perspectives of affected children and adolescents. Important next steps for the implementation of islet autoantibody screening in Germany are the training of pediatricians who should inform families about the screening, establishment of a few transregional laboratories that carry out the test, and expansion of regional capacities for the training and care of children with an early stage of type 1 diabetes.

Screening and care for preclinical stage 1-2 type 1 diabetes in first-degree relatives: French expert position statement

The natural history of type 1 diabetes (T1D) evolves from stage 1 (islet autoimmunity with normoglycemia; ICD-10 diagnostic code E10.A1) to stage 2 (autoimmunity with dysglycemia; E10.A2) and subsequent clinical stage 3 (overt hyperglycemia), which is commonly the first time of referral. Autoantibody testing can diagnose T1D at its preclinical stages 1-2 and lead to earlier initiation of care, particularly for first-degree relatives of people living with T1D, who are at higher genetic risk. Preclinical T1D screening and monitoring aims to avoid inaugural ketoacidosis and prolong preservation of endogenous insulin secretion, thereby improving glycemic control and reducing long-term morbidity. Moreover, early management can help coping with T1D and correct modifiable risk factors (obesity, sedentary lifestyle). New treatments currently under clinical deployment or trials also offer the possibility of delaying clinical progression. All these arguments lead to the proposition of a national screening and care pathway open to interested first-degree relatives. This pathway represents a new expertise to acquire for healthcare professionals. By adapting international consensus guidance to the French specificities, the proposed screening strategy involves testing for ≥ 2 autoantibodies (among IAA, anti-GAD, anti-IA-2) in relatives aged 2-45 years. Negative screening (∼95 % of cases) should be repeated every 4 years until the age of 12. A management workflow is proposed for relatives screening positive (∼5 % of cases), with immuno-metabolic monitoring by autoantibody testing, OGTT, glycemia and/or HbA1c of variable frequency, depending on T1D stage, age, patient preference and available resources, as well as the definition of expert centers for preclinical T1D.

2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Time to reframe the disease staging system for type 1 diabetes

In 2015, introduction of a disease staging system offered a framework for benchmarking progression to clinical type 1 diabetes. This model, based on islet autoantibodies (stage 1) and dysglycaemia (stage 2) before type 1 diabetes diagnosis (stage 3), has facilitated screening and identification of people at risk. Yet, there are many limitations to this model as the stages combine a very heterogeneous group of individuals; do not have high specificity for type 1 diabetes; can occur without persistence (ie, reversion to an earlier risk stage); and exclude age and other influential risk factors. The current staging system also infers that individuals at risk of type 1 diabetes progress linearly from stage 1 to stage 2 and subsequently stage 3, whereas such movements are often more complex. With the approval of teplizumab by the US Food and Drug Administration in 2022 to delay type 1 diabetes in people at stage 2, there is a need to refine the definition and accuracy of type 1 diabetes staging. Theoretically, we propose that a type 1 diabetes risk calculator should incorporate any available demographic, genetic, autoantibody, metabolic, and immune data that could be continuously updated. Additionally, we call to action for the field to increase the breadth of knowledge regarding type 1 diabetes risk in non-relatives, adults, and individuals from minority populations.

Insights into Knowledge and Attitudes About Autoantibody Screening from People Affected by Type 1 Diabetes: A Brief Report

INTRODUCTION

Screening for islet-specific autoantibodies can identify individuals at risk for type 1 diabetes (T1D). Despite calls for increased nationwide autoantibody screening efforts, it is unclear how many individuals have participated in screening among people who may benefit from it. Moreover, knowledge and perceptions of autoantibody screening in real-world samples are not well understood.

METHODS

We surveyed a sample of individuals (aged 18+ years old) from T1D Exchange Registry with a personal or family history of T1D to assess their self-reported T1D autoantibody knowledge, experiences, and attitudes. Participants belonged to one of three groups: adults with T1D who had a biological child without T1D or future plans for a child (PWD); parents without T1D who had a biological child with T1D and one or more biological children without T1D (Caregivers); and first-degree adult children or siblings to a person with T1D (Relatives). Descriptive analyses (means, standard deviations, frequencies) are presented by participant groups.

RESULTS

A total of 510 participants enrolled in the study. Across groups, participants reported feeling a little to somewhat knowledgeable about autoantibody screening and positive perceptions of autoantibody screening in general. However, few participants had screened their child without T1D (PWDs, 21.94%; Caregivers, 46.30%) or themselves (Relatives, 19.23%). Among those who had screened, participants reported generally positive experiences. Among those who had not screened, many participants were "undecided" about autoantibody screening (PWD, 38.46%; Caregivers, 40.52%; Relatives, 44.44%). Influences reported for participants' decisions to screen, not screen, or their current indecision differed by group: PWDs (21.70%) and Caregivers (26.87%) most often reported self-initiated research as an influence and Relatives reported they had not previously considered screening (48.28%).

CONCLUSION

Results highlight the need for more accessible information about screening, including real experiences from those who have screened.

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.

Untangling the genetics of beta cell dysfunction and death in type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise.

SCOPE OF REVIEW

Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D.

MAJOR CONCLUSIONS

We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.

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 programs are being increasingly emphasized. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk for (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 nonspecialized 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 emphasizes significant unmet needs for further research on early-stage type 1 diabetes to increase the rigor of future recommendations and inform clinical care.

Data-Driven Phenotyping of Presymptomatic Type 1 Diabetes Using Longitudinal Autoantibody Profiles

OBJECTIVE

To characterize distinct islet autoantibody profiles preceding stage 3 type 1 diabetes.

RESEARCH DESIGN AND METHODS

The T1DI (Type 1 Diabetes Intelligence) study combined data from 1,845 genetically susceptible prospectively observed children who were positive for at least one islet autoantibody: insulin autoantibody (IAA), GAD antibody (GADA), or islet antigen 2 antibody (IA-2A). Using a novel similarity algorithm that considers an individual's temporal autoantibody profile, age at autoantibody appearance, and variation in the positivity of autoantibody types, we performed an unsupervised hierarchical clustering analysis. Progression rates to diabetes were analyzed via survival analysis.

RESULTS

We identified five main clusters of individuals with distinct autoantibody profiles characterized by seroconversion age and sequence of appearance of the three autoantibodies. The highest 5-year risk from first positive autoantibody to type 1 diabetes (69.9%; 95% CI 60.0-79.2) was observed in children who first developed IAA in early life (median age 1.6 years) followed by GADA (1.9 years) and then IA-2A (2.1 years). Their 10-year risk was 89.9% (95% CI 81.9-95.4). A high 5-year risk was also found in children with persistent IAA and GADA (39.1%) and children with persistent GADA and IA-2A (30.9%). A lower 5-year risk (10.5%) was observed in children with a late appearance of persistent GADA (6.1 years). The lowest 5-year diabetes risk (1.6%) was associated with positivity for a single, often reverting, autoantibody.

CONCLUSIONS

The novel clustering algorithm identified children with distinct islet autoantibody profiles and progression rates to diabetes. These results are useful for prediction, selection of individuals for prevention trials, and studies investigating various pathways to type 1 diabetes.

Longitudinal changes in DNA methylation during the onset of islet autoimmunity differentiate between reversion versus progression of islet autoimmunity

Background

Type 1 diabetes (T1D) is preceded by a heterogenous pre-clinical phase, islet autoimmunity (IA). We aimed to identify pre vs. post-IA seroconversion (SV) changes in DNAm that differed across three IA progression phenotypes, those who lose autoantibodies (reverters), progress to clinical T1D (progressors), or maintain autoantibody levels (maintainers).

Methods

This epigenome-wide association study (EWAS) included longitudinal DNAm measurements in blood (Illumina 450K and EPIC) from participants in Diabetes Autoimmunity Study in the Young (DAISY) who developed IA, one or more islet autoantibodies on at least two consecutive visits. We compared reverters - individuals who sero-reverted, negative for all autoantibodies on at least two consecutive visits and did not develop T1D (n=41); maintainers - continued to test positive for autoantibodies but did not develop T1D (n=60); progressors - developed clinical T1D (n=42). DNAm data were measured before (pre-SV visit) and after IA (post-SV visit). Linear mixed models were used to test for differences in pre- vs post-SV changes in DNAm across the three groups. Linear mixed models were also used to test for group differences in average DNAm. Cell proportions, age, and sex were adjusted for in all models. Median follow-up across all participants was 15.5 yrs. (interquartile range (IQR): 10.8-18.7).

Results

The median age at the pre-SV visit was 2.2 yrs. (IQR: 0.8-5.3) in progressors, compared to 6.0 yrs. (IQR: 1.3-8.4) in reverters, and 5.7 yrs. (IQR: 1.4-9.7) in maintainers. Median time between the visits was similar in reverters 1.4 yrs. (IQR: 1-1.9), maintainers 1.3 yrs. (IQR: 1.0-2.0), and progressors 1.8 yrs. (IQR: 1.0-2.0). Changes in DNAm, pre- vs post-SV, differed across the groups at one site (cg16066195) and 11 regions. Average DNAm (mean of pre- and post-SV) differed across 22 regions.

Conclusion

Differentially changing DNAm regions were located in genomic areas related to beta cell function, immune cell differentiation, and immune cell function.

Childhood screening for type 1 diabetes comparing automated multiplex Antibody Detection by Agglutination-PCR (ADAP) with single plex islet autoantibody radiobinding assays

BACKGROUND

Two or more autoantibodies against either insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A) or zinc transporter 8 (ZnT8A) denote stage 1 (normoglycemia) or stage 2 (dysglycemia) type 1 diabetes prior to stage 3 type 1 diabetes. Automated multiplex Antibody Detection by Agglutination-PCR (ADAP) assays in two laboratories were compared to single plex radiobinding assays (RBA) to define threshold levels for diagnostic specificity and sensitivity.

METHODS

IAA, GADA, IA-2A and ZnT8A were analysed in 1504 (54% females) population based controls (PBC), 456 (55% females) doctor's office controls (DOC) and 535 (41% females) blood donor controls (BDC) as well as in 2300 (48% females) patients newly diagnosed (1-10 years of age) with stage 3 type 1 diabetes. The thresholds for autoantibody positivity were computed in 100 10-fold cross-validations to separate patients from controls either by maximizing the χ2-statistics (chisq) or using the 98th percentile of specificity (Spec98). Mean and 95% CI for threshold, sensitivity and specificity are presented.

FINDINGS

The ADAP ROC curves of the four autoantibodies showed comparable AUC in the two ADAP laboratories and were higher than RBA. Detection of two or more autoantibodies using chisq showed 0.97 (0.95, 0.99) sensitivity and 0.94 (0.91, 0.97) specificity in ADAP compared to 0.90 (0.88, 0.95) sensitivity and 0.97 (0.94, 0.98) specificity in RBA. Using Spec98, ADAP showed 0.92 (0.89, 0.95) sensitivity and 0.99 (0.98, 1.00) specificity compared to 0.89 (0.77, 0.86) sensitivity and 1.00 (0.99, 1.00) specificity in the RBA. The diagnostic sensitivity and specificity were higher in PBC compared to DOC and BDC.

INTERPRETATION

ADAP was comparable in two laboratories, both comparable to or better than RBA, to define threshold levels for two or more autoantibodies to stage type 1 diabetes.

FUNDING

Supported by The Leona M. and Harry B. Helmsley Charitable Trust (grant number 2009-04078), the Swedish Foundation for Strategic Research (Dnr IRC15-0067) and the Swedish Research Council, Strategic Research Area (Dnr 2009-1039). AL was supported by the DiaUnion collaborative study, co-financed by EU Interreg ÖKS, Capital Region of Denmark, Region Skåne and the Novo Nordisk Foundation.

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.

Progression of type 1 diabetes is associated with high levels of soluble PD-1 in islet autoantibody-positive children

AIMS/HYPOTHESIS

Type 1 diabetes is an autoimmune disorder that is characterised by destruction of pancreatic beta cells by autoreactive T lymphocytes. Although islet autoantibodies (AAb) are an indicator of disease progression, specific immune biomarkers that can be used as target molecules to halt development of type 1 diabetes have not been discovered. Soluble immune checkpoint molecules (sICM) play a pivotal role in counteracting excessive lymphocyte responses, but their role in type 1 diabetes is unexplored. In this longitudinal study, we measured sICM levels in AAb-positive (AAb+) children to identify molecules related to type 1 diabetes progression.

METHODS

We measured the levels of 14 sICM in the sera of AAb+ children (n=57) compared to those with recent-onset type 1 diabetes (n=79) and healthy children (n=44), obtained from two cohorts. AAb+ children were followed up and divided based on their progression to type 1 diabetes (AAbP) or not (AAbNP) (if they lost islet autoimmunity and did not develop disease in subsequent years). sICM were also measured in the sample taken at the visit closest to disease onset in AAbP children.

RESULTS

We found that AAb+ children had a distinct sICM profile compared with healthy children and those with recent-onset type 1 diabetes. In addition, AAb+ children who progressed to type 1 diabetes (AAbP) had higher sICM concentrations than non-progressors (AAbNP). Further, sICM levels decreased in AAbP children close to disease onset. Application of Cox regression models highlighted that high concentrations of soluble programmed cell death protein 1 (sPD-1) are associated with type 1 diabetes progression (HR 1.71; 95% CI 1.16, 2.51; p=0.007).

CONCLUSIONS/INTERPRETATION

This study reveals an sICM profile that is dysregulated during the preclinical stage of type 1 diabetes, and identifies sPD-1 as a pathophysiologically-relevant molecule that is associated with disease progression, offering a potential target for early interventions in autoimmune diabetes.

Understanding Islet Autoantibodies in Prediction of Type 1 Diabetes

As screening studies and preventive interventions for type 1 diabetes (T1D) advance rapidly, the utility of islet autoantibodies (IAbs) in T1D prediction comes with challenges for early and accurate disease progression prediction. Refining features of IAbs can provide more accurate risk assessment. The advances in islet autoantibodies assay techniques help to screen out islet autoantibodies with high efficiency and high disease specificity. Exploring new islet autoantibodies to neoepitopes/neoantigens remains a hot research field for improving prediction and disease pathogenesis. We will review the recent research progresses of islet autoantibodies to better understand the utility of islet autoantibodies in prediction of T1D.

Refining the Definition of Stage 1 Type 1 Diabetes: An Ontology-Driven Analysis of the Heterogeneity of Multiple Islet Autoimmunity

OBJECTIVE

To estimate the risk of progression to stage 3 type 1 diabetes based on varying definitions of multiple islet autoantibody positivity (mIA).

RESEARCH DESIGN AND METHODS

Type 1 Diabetes Intelligence (T1DI) is a combined prospective data set of children from Finland, Germany, Sweden, and the U.S. who have an increased genetic risk for type 1 diabetes. Analysis included 16,709 infants-toddlers enrolled by age 2.5 years and comparison between groups using Kaplan-Meier survival analysis.

RESULTS

Of 865 (5%) children with mIA, 537 (62%) progressed to type 1 diabetes. The 15-year cumulative incidence of diabetes varied from the most stringent definition (mIA/Persistent/2: two or more islet autoantibodies positive at the same visit with two or more antibodies persistent at next visit; 88% [95% CI 85-92%]) to the least stringent (mIA/Any: positivity for two islet autoantibodies without co-occurring positivity or persistence; 18% [5-40%]). Progression in mIA/Persistent/2 was significantly higher than all other groups (P < 0.0001). Intermediate stringency definitions showed intermediate risk and were significantly different than mIA/Any (P < 0.05); however, differences waned over the 2-year follow-up among those who did not subsequently reach higher stringency. Among mIA/Persistent/2 individuals with three autoantibodies, loss of one autoantibody by the 2-year follow-up was associated with accelerated progression. Age was significantly associated with time from seroconversion to mIA/Persistent/2 status and mIA to stage 3 type 1 diabetes.

CONCLUSIONS

The 15-year risk of progression to type 1 diabetes risk varies markedly from 18 to 88% based on the stringency of mIA definition. While initial categorization identifies highest-risk individuals, short-term follow-up over 2 years may help stratify evolving risk, especially for those with less stringent definitions of mIA.

Secondary Prevention of Diabetes Type 1 with Oral Calcitriol and Analogs, the PRECAL Study

Screening for Type 1 Diabetes (T1D, incidence 1:300) with T1D autoantibodies (T1Ab) at ages 2 and 6, while sensitive, lacks a preventive strategy. Cholecalciferol 2000 IU daily since birth reduced T1D by 80% at 1 year. T1D-associated T1Ab negativized within 0.6 years with oral calcitriol in 12 children. To further investigate secondary prevention of T1D with calcitriol and its less calcemic analog, paricalcitol, we initiated a prospective interventional non-randomized clinical trial, the PRECAL study (ISRCTN17354692). In total, 50 high-risk children were included: 44 were positive for T1Ab, and 6 had predisposing for T1D HLA genotypes. Nine T1Ab+ patients had variable impaired glucose tolerance (IGT), four had pre-T1D (3 T1Ab+, 1 HLA+), nine had T1Ab+ new-onset T1D not requiring insulin at diagnosis. T1Ab, thyroid/anti-transglutaminase Abs, glucose/calcium metabolism were determined prior and q3-6 months on calcitriol, 0.05 mcg/Kg/day, or paricalcitol 1-4 mcg × 1-3 times/day p.o. while on cholecalciferol repletion. Available data on 42 (7 dropouts, 1 follow-up < 3 months) patients included: all 26 without pre-T1D/T1D followed for 3.06 (0.5-10) years negativized T1Ab (15 +IAA, 3 IA2, 4 ICA, 2 +GAD, 1 +IAA/+GAD, 1 +ICA/+GAD) within 0.57 (0.32-1.3) years or did not develop to T1D (5 +HLA, follow-up 3 (1-4) years). From four pre-T1D cases, one negativized T1Ab (follow-up 1 year), one +HLA did not progress to T1D (follow-up 3.3 years) and two +T1Ab patients developed T1D in 6 months/3 years. Three out of nine T1D cases progressed immediately to overt disease, six underwent complete remission for 1 year (1 month-2 years). Five +T1Ab patients relapsed and negativized again after resuming therapy. Four (aged <3 years) negativized anti-TPO/TG, and two anti-transglutaminase-IgA. Eight presented mild hypercalciuria/hypercalcemia, resolving with dose titration/discontinuation. Secondary prevention of T1D with calcitriol and paricalcitol seems possible and reasonably safe, if started soon enough after seroconversion.

Investigating iron intake in risk of progression from islet autoimmunity to type 1 diabetes: The diabetes autoimmunity study in the young

Background

Studies of the role of iron in the risk of type 1 diabetes (T1D) have been inconsistent. Given that iron generates reactive oxygen radicals, which can lead to oxidative damage and apoptosis in the beta cells of the pancreas, we examined whether iron intake was associated with the risk of progressing to T1D in individuals with islet autoimmunity (IA), the pre-clinical phase of T1D.

Methods

DAISY is a prospective cohort following 2,547 children at increased risk for IA and progression to T1D. IA is defined as at least two consecutive serum samples positive for at least one autoantibody (insulin, GAD, IA-2, or ZnT8). We measured dietary intake at the time of IA seroconversion in 175 children with IA, and of these, 64 progressed to T1D. We used Cox regression to examine the association between energy-adjusted iron intake and progression to T1D, adjusting for HLA-DR3/4 genotype, race/ethnicity, age at seroconversion, presence of multiple autoantibodies at seroconversion, and multiple vitamin use. In addition, we tested whether this association was modified by vitamin C or calcium intake.

Results

In children with IA, high iron intake (as defined as above the 75th percentile, > 20.3 mg/day) was associated with decreased risk of progression to T1D compared to moderate iron intake (as defined by the middle 25-75th percentiles, 12.7-20.3 mg/day) (adjusted hazard ratio (HR): 0.35; 95% confidence interval (CI): 0.15, 0.79). The association between iron intake and T1D was not modified by vitamin C nor calcium intake. In a sensitivity analysis, the removal of six children who had been diagnosed with celiac disease prior to IA seroconversion did not affect this association.

Conclusion

Higher iron intake at the time of IA seroconversion is associated with a lower risk of progression to T1D, independent of multivitamin supplement use. Further research that includes plasma biomarkers of iron status is needed to investigate the relationship between iron and the risk of T1D.

Islet Autoantibody Levels Differentiate Progression Trajectories in Individuals With Presymptomatic Type 1 Diabetes

In our previous data-driven analysis of evolving patterns of islet autoantibodies (IAb) against insulin (IAA), GAD (GADA), and islet antigen 2 (IA-2A), we discovered three trajectories, characterized according to multiple IAb (TR1), IAA (TR2), or GADA (TR3) as the first appearing autoantibodies. Here we examined the evolution of IAb levels within these trajectories in 2,145 IAb-positive participants followed from early life and compared those who progressed to type 1 diabetes (n = 643) with those remaining undiagnosed (n = 1,502). With use of thresholds determined by 5-year diabetes risk, four levels were defined for each IAb and overlaid onto each visit. In diagnosed participants, high IAA levels were seen in TR1 and TR2 at ages <3 years, whereas IAA remained at lower levels in the undiagnosed. Proportions of dwell times (total duration of follow-up at a given level) at the four IAb levels differed between the diagnosed and undiagnosed for GADA and IA-2A in all three trajectories (P < 0.001), but for IAA dwell times differed only within TR2 (P < 0.05). Overall, undiagnosed participants more frequently had low IAb levels and later appearance of IAb than diagnosed participants. In conclusion, while it has long been appreciated that the number of autoantibodies is an important predictor of type 1 diabetes, consideration of autoantibody levels within the three autoimmune trajectories improved differentiation of IAb-positive children who progressed to type 1 diabetes from those who did not.

Early glucose metabolism in children at risk for type 1 diabetes based on islet autoantibodies compared to low-risk control groups

Background

Anatomic variation or early differences in glucose metabolism have been linked to the development of type 1 diabetes. We aimed to describe early glucose metabolism based on HbA1c, oral glucose tolerance test (OGTT), and random plasma glucose years before the presentation of type 1 diabetes in five risk groups based on autoantibody combinations. For the first time, we were able to include for comparison children with very low risk of progression to type 1 diabetes.

Methods

The Finnish Diabetes Prediction and Prevention birth cohort study screened newborn infants for HLA susceptibility to type 1 diabetes since 1994. Those carrying a risk genotype were prospectively followed up with islet autoantibody testing. Glucose parameters were obtained starting from the time of seroconversion. By 31 August 2014, 1162 children had developed at least one islet autoantibody and were included in the current study. Type 1 diabetes was diagnosed in 335 children (progressors). In the non-progressor groups, 207 developed multiple (≥2) biochemical islet autoantibodies, 229 a single biochemical autoantibody, 370 ICA only, and 64 transient autoantibodies. Children were divided into five risk groups. Glucose metabolism was evaluated.

Results

We observed lower HbA1c values in early follow-up 4.5 to 6.0 years before diagnosis in the progressors when compared to the same time in children with a single biochemical autoantibody or low-risk (ICA only and transient) participants, who did not progress to clinical type 1 diabetes. However, no such differences were observed in OGTTs or random plasma glucose. The variation was minimal in glucose values in the low-risk groups.

Conclusion

We report the possibility of early alteration in glucose metabolism in future progressors. This could suggest early defects in multiple glucose-regulating hormones.

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.

Recent information on test utilization and intraindividual change in anti-glutamic acid decarboxylase antibody in Korea: a retrospective study

INTRODUCTION

This study aimed to evaluate the test utilization and intraindividual changes of anti-glutamic acid decarboxylase antibody (GADA), a biomarker for autoimmune diabetes in Korean adults.

RESEARCH DESIGN AND METHODS

We retrospectively investigated longitudinally measured GADA test results to assess test utilization and intraindividual changes through a laboratory information system.

RESULTS

During the 3-year study period, 11 668 GADA tests were performed in 11 184 Korean adults. The overall rate of GADA positivity at initial measurement was 7.8%. Among the 11 668 test results, 871 GADA test results from 401 Korean patients (228 men and 173 women) requested by 54 hospitals were analyzed for intraindividual changes. Among these 401 patients, 80 (20.0%) had positive (≥2.0 U/mL) and 35 (8.7%) had gray zone GADA (1.0-1.9 U/mL) level at initial measurement. The prevalence of GADA-positive patients based on initial measurement was significantly different by type of medical institution. Among 80 patients with initial positive results, 5 (6.3%) experienced qualitative GADA changes during follow-up. Among the 321 patients with initially negative or gray zone GADA, 9 (2.8%) changed to GADA positive at least once during follow-up.

CONCLUSIONS

Although most patients had stable GADA results, some exhibited qualitative changes during follow-up. This study can help to understand the variation in GADA positivity in the monitored patients.

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.

Diagnostic Capabilities of Islet Autoantibodies in Children with New-Onset Type 1 Diabetes Mellitus and Healthy Siblings

The aim of the study is to determine the diagnostic utility of several islet autoantibodies and their combinations in order to identify individuals susceptible to type 1 diabetes mellitus (T1DM) among healthy siblings in the pediatric population within the scope of the development of a screening program.

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.

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.

Phospholipid Levels at Seroconversion Are Associated With Resolution of Persistent Islet Autoimmunity: The Diabetes Autoimmunity Study in the Young

Reversion of islet autoimmunity (IA) may point to mechanisms that prevent IA progression. We followed 199 individuals who developed IA during the Diabetes Autoimmunity Study in the Young. Untargeted metabolomics was performed in serum samples following IA. Cox proportional hazards models were used to test whether the metabolites (2,487) predicted IA reversion: two or more consecutive visits negative for all autoantibodies. We conducted a principal components analysis (PCA) of the top metabolites; |hazard ratio (HR) >1.25| and nominal P < 0.01. Phosphatidylcholine (16:0_18:1(9Z)) was the strongest individual metabolite (HR per 1 SD 2.16, false discovery rate (FDR)-adjusted P = 0.0037). Enrichment analysis identified four clusters (FDR P < 0.10) characterized by an overabundance of sphingomyelin (d40:0), phosphatidylcholine (16:0_18:1(9Z)), phosphatidylcholine (30:0), and l-decanoylcarnitine. Overall, 63 metabolites met the criteria for inclusion in the PCA. PC1 (HR 1.4, P < 0.0001), PC2 (HR 0.85, P = 0.0185), and PC4 (HR 1.28, P = 0.0103) were associated with IA reversion. Given the potential influence of diet on the metabolome, we investigated whether nutrients were correlated with PCs. We identified 20 nutrients that were correlated with the PCs (P < 0.05). Total sugar intake was the top nutrient. Overall, we identified an association between phosphatidylcholine, sphingomyelin, and carnitine levels and reversion of IA.

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.

Complete blood counts with red blood cell determinants associate with reduced beta-cell function in seroconverted Swedish TEDDY children

OBJECTIVES

To investigate whether changes in complete blood count (CBC) in islet autoantibody positive children with increased genetic risk for type 1 diabetes are associated with oral glucose tolerance tests (OGTT) and HbA1c over time.

METHODS

The Environmental Determinants of Diabetes in the Young (TEDDY) study follows children with increased risk for type 1 diabetes in the United States, Germany, Sweden and Finland. In the current study, 89 Swedish TEDDY children (median age 8.8 years) positive for one or multiple islet autoantibodies were followed up to 5 (median 2.3) years for CBC, OGTT and HbA1c. A statistical mixed effect model was used to investigate the association between CBC and OGTT or HbA1c.

RESULTS

HbA1c over time increased by the number of autoantibodies (p < .001). Reduction in mean corpuscular haemoglobin (MCH) and mean cell volume (MCV) was both associated with an increase in HbA1c (p < .001). A reduction in red blood cell (RBC) counts (p = .003), haemoglobin (p = .002) and haematocrit (p = .006) levels was associated with increased fasting glucose. Increased red blood cells, haemoglobin, haematocrit and MCH but decreased levels of red blood cell distribution widths (RDW) were all associated with increased fasting insulin.

CONCLUSIONS

The decrease in RBC indices with increasing HbA1c and the decrease in RBC and its parameters with increasing fasting glucose in seroconverted children may reflect an insidious deterioration in glucose metabolism associated with islet beta-cell autoimmunity.

Islet Autoimmunity and HLA Markers of Presymptomatic and Clinical Type 1 Diabetes: Joint Analyses of Prospective Cohort Studies in Finland, Germany, Sweden, and the U.S

OBJECTIVE

To combine prospective cohort studies, by including HLA harmonization, and estimate risk of islet autoimmunity and progression to clinical diabetes.

RESEARCH DESIGN AND METHODS

For prospective cohorts in Finland, Germany, Sweden, and the U.S., 24,662 children at increased genetic risk for development of islet autoantibodies and type 1 diabetes have been followed. Following harmonization, the outcomes were analyzed in 16,709 infants-toddlers enrolled by age 2.5 years.

RESULTS

In the infant-toddler cohort, 1,413 (8.5%) developed at least one autoantibody confirmed at two or more consecutive visits (seroconversion), 865 (5%) developed multiple autoantibodies, and 655 (4%) progressed to diabetes. The 15-year cumulative incidence of diabetes varied in children with one, two, or three autoantibodies at seroconversion: 45% (95% CI 40-52), 85% (78-90), and 92% (85-97), respectively. Among those with a single autoantibody, status 2 years after seroconversion predicted diabetes risk: 12% (10-25) if reverting to autoantibody negative, 30% (20-40) if retaining a single autoantibody, and 82% (80-95) if developing multiple autoantibodies. HLA-DR-DQ affected the risk of confirmed seroconversion and progression to diabetes in children with stable single-autoantibody status. Their 15-year diabetes incidence for higher- versus lower-risk genotypes was 40% (28-50) vs. 12% (5-38). The rate of progression to diabetes was inversely related to age at development of multiple autoantibodies, ranging from 20% per year to 6% per year in children developing multipositivity in ≤2 years or >7.4 years, respectively.

CONCLUSIONS

The number of islet autoantibodies at seroconversion reliably predicts 15-year type 1 diabetes risk. In children retaining a single autoantibody, HLA-DR-DQ genotypes can further refine risk of progression.

Associated autoimmunity in Type 1 Diabetes and latent autoimmune diabetes of adults: The role of glutamic-acid decarboxylase autoantibodies

AIMS

To determine the prevalence of Associated Autoimmune Diseases (AADs) in Latent Autoimmune Diabetes of Adults (LADA) versus autoimmune Type 1 Diabetes (T1D) and the role of glutamic-acid decarboxylase antibodies (GADA) and other factors.

METHODS

Adults with autoimmune diabetes mellitus (DM) were recruited from the Diabetes Center of Nikaia-Piraeus Hospital. Demographic and clinical parameters were recorded and anti-pancreatic and organ-specific antibodies were measured.

RESULTS

Of 160 patients, 33.75% had one AAD and 24.37% had two or more. Patients with LADA had higher overall prevalence of AADs, mainly autoimmune thyroiditis and gastritis. Celiac disease was present only in T1D. GADA positive patients had higher prevalence of AADs and multiple autoimmunity, especially thyroiditis and gastritis. Patients with LADA had higher rates of positive GADA or islet-cell antibodies (ICA). After controlling for LADA, GADA remained a significant predictor of AADs. Female gender and chronological age were also significant predictors of AADs.

CONCLUSIONS

AADs were present in 58.13% of patients. Patients with LADA were more prone to a generalized autoimmune disorder than those with T1D. AADs development was significantly associated with female sex, older age and positive GADA, which proved an independent marker of associated autoimmunity.

Plasma Metabolome and Circulating Vitamins Stratified Onset Age of an Initial Islet Autoantibody and Progression to Type 1 Diabetes: The TEDDY Study

Children's plasma metabolome, especially lipidome, reflects gene regulation and dietary exposures, heralding the development of islet autoantibodies (IA) and type 1 diabetes (T1D). The Environmental Determinants of Diabetes in the Young (TEDDY) study enrolled 8,676 newborns by screening of HLA-DR-DQ genotypes at six clinical centers in four countries, profiled metabolome, and measured concentrations of ascorbic acid, 25-hydroxyvitamin D [25(OH)D], and erythrocyte membrane fatty acids following birth until IA seroconversion under a nested case-control design. We grouped children having an initial autoantibody only against insulin (IAA-first) or GAD (GADA-first) by unsupervised clustering of temporal lipidome, identifying a subgroup of children having early onset of each initial autoantibody, i.e., IAA-first by 12 months and GADA-first by 21 months, consistent with population-wide early seroconversion age. Differential analysis showed that infants having reduced plasma ascorbic acid and cholesterol experienced IAA-first earlier, while early onset of GADA-first was preceded by reduced sphingomyelins at infancy. Plasma 25(OH)D prior to either autoantibody was lower in T1D progressors compared with nonprogressors, with simultaneous lower diglycerides, lysophosphatidylcholines, triglycerides, and alanine before GADA-first. Plasma ascorbic acid and 25(OH)D at infancy were lower in HLA-DR3/DR4 children among IA case subjects but not in matched control subjects, implying gene expression dysregulation of circulating vitamins as latent signals for IA or T1D progression.

Dynamics of Islet Autoantibodies During Prospective Follow-Up From Birth to Age 15 Years

CONTEXT

We set out to characterize the dynamics of islet autoantibodies over the first 15 years of life in children carrying genetic susceptibility to type 1 diabetes (T1D). We also assessed systematically the role of zinc transporter 8 autoantibodies (ZnT8A) in this context.

DESIGN

HLA-predisposed children (N = 1006, 53.0% boys) recruited from the general population during 1994 to 1997 were observed from birth over a median time of 14.9 years (range, 1.9-15.5 years) for ZnT8A, islet cell (ICA), insulin (IAA), glutamate decarboxylase (GADA), and islet antigen-2 (IA-2A) antibodies, and for T1D.

RESULTS

By age 15.5 years, 35 (3.5%) children had progressed to T1D. Islet autoimmunity developed in 275 (27.3%) children at a median age of 7.4 years (range, 0.3-15.1 years). The ICA seroconversion rate increased toward puberty, but the biochemically defined autoantibodies peaked at a young age. Before age 2 years, ZnT8A and IAA appeared commonly as the first autoantibody, but in the preschool years IA-2A- and especially GADA-initiated autoimmunity increased. Thereafter, GADA-positive seroconversions continued to appear steadily until ages 10 to 15 years. Inverse IAA seroconversions occurred frequently (49.3% turned negative) and marked a prolonged delay from seroconversion to diagnosis compared to persistent IAA (8.2 vs 3.4 years; P = .01).

CONCLUSIONS

In HLA-predisposed children, the primary autoantibody is characteristic of age and might reflect the events driving the disease process toward clinical T1D. Autoantibody persistence affects the risk of T1D. These findings provide a framework for identifying disease subpopulations and for personalizing the efforts to predict and prevent T1D.

Motifs of Three HLA-DQ Amino Acid Residues (α44, β57, β135) Capture Full Association With the Risk of Type 1 Diabetes in DQ2 and DQ8 Children

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next-generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1- to 18 year-old patients (n = 962) and control subjects (n = 636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically organized haplotype (HOH) association analysis allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (odds ratio [OR] 3.29, P = 2.38 * 10^-85) and β57A (OR 3.44, P = 3.80 * 10^-84) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, β57) due to complete linkage disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and β135D to share the risk for T1D (OR 2.10, P = 1.96 * 10^-20). The motif "QAD" of α44, β57, and β135 captured the T1D risk association of DQ8.1 (OR 3.44, P = 3.80 * 10^-84), and the corresponding motif "CAD" captured the risk association of DQ2.5 (OR 2.10, P = 1.96 * 10^-20). Two risk associations were related to GAD65 autoantibody (GADA) and IA-2 autoantibody (IA-2A) but in opposite directions. CAD was positively associated with GADA (OR 1.56, P = 6.35 * 10^-8) but negatively with IA-2A (OR 0.59, P = 6.55 * 10^-11). QAD was negatively associated with GADA (OR 0.88; P = 3.70 * 10^-3) but positively with IA-2A (OR 1.64; P = 2.40 * 10^-14), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential T-cell receptor contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AAs (α44, β57, β135) conferring T1D risk should sharpen functional and translational studies.

Targeting Glycoproteins as a therapeutic strategy for diabetes mellitus and its complications

OBJECTIVES

Glycoproteins are organic compounds formed from proteins and carbohydrates, which are found in many parts of the living systems including the cell membranes. Furthermore, impaired metabolism of glycoprotein components plays the main role in the pathogenesis of diabetes mellitus. The aim of this study is to investigate the influence of glycoprotein levels in the treatment of diabetes mellitus.

METHODS

All relevant papers in the English language were compiled by searching electronic databases, including Scopus, PubMed and Cochrane library. The keywords of glycoprotein, diabetes mellitus, glycan, glycosylation, and inhibitor were searched until January 2019.

RESULTS

Glycoproteins are pivotal elements in the regulation of cell proliferation, growth, maturation and signaling pathways. Moreover, they are involved in drug binding, drug transportation, efflux of chemicals and stability of therapeutic proteins. These functions, structure, composition, linkages, biosynthesis, significance and biological effects are discussed as related to their use as a therapeutic strategy for the treatment of diabetes mellitus and its complications.

CONCLUSIONS

The findings revealed several chemical and natural compounds have significant beneficial effects on glycoprotein metabolism. The comprehension of glycoprotein structure and functions are very essential and inevitable to enhance the knowledge of glycoengineering for glycoprotein-based therapeutics as may be required for the treatment of diabetes mellitus and its associated complications. Graphical abstract.

Association of HLA-dependent islet autoimmunity with systemic antibody responses to intestinal commensal bacteria in children

Microbiome sequence analyses have suggested that changes in gut bacterial composition are associated with autoimmune disease in humans and animal models. However, little is known of the mechanisms through which the gut microbiota influences autoimmune responses to distant tissues. Here, we evaluated systemic antibody responses against cultured human gut bacterial strains to determine whether observed patterns of anticommensal antibody (ACAb) responses are associated with type 1 diabetes (T1D) in two cohorts of pediatric study participants. In the first cohort, ACAb responses in sera collected from participants within 6 months of T1D diagnosis were compared with age-matched healthy controls and also with patients with recent onset Crohn's disease. ACAb responses against multiple bacterial species discriminated among these three groups. In the second cohort, we asked whether ACAb responses present before diagnosis were associated with later T1D development and with HLA genotype in participants who were discordant for subsequent progression to diabetes. Serum IgG2 antibodies against Roseburia faecis and against a bacterial consortium were associated with future T1D diagnosis in an HLA DR3/DR4 haplotype-dependent manner. These analyses reveal associations between antibody responses to intestinal microbes and HLA-DR genotype and islet autoantibody specificity and with a future diagnosis of T1D. Further, we present a platform to investigate antibacterial antibodies in biological fluids that is applicable to studies of autoimmune diseases and responses to therapeutic interventions.

Autoantibody Reversion: Changing Risk Categories in Multiple-Autoantibody-Positive Individuals

OBJECTIVE

Most individuals with two or more islet autoantibodies progress to clinical type 1 diabetes. However, in some individuals, autoantibodies are subsequently lost. Here, our objectives were to determine the frequency of autoantibody loss (reversion) in multiple-autoantibody-positive individuals and to determine the association between reversion and progression to clinical disease.

RESEARCH DESIGN AND METHODS

We analyzed multiple-autoantibody-positive individuals participating in TrialNet's Pathway to Prevention Study for reversion and determined the effect of reversion on progression to clinical disease using a Cox regression analysis.

RESULTS

Of 3,284 multiple-autoantibody-positive subjects, reversion occurred in 134 (4.1%) and was associated with reduced incidence of clinical disease. Reversion occurred more frequently with older age, lower autoantibody titers, and fewer positive autoantibodies.

CONCLUSIONS

Although reversion of multiple-autoantibody positivity is rare, when it occurs, the risk of progressing to clinical disease is reduced. This suggests unknown mechanisms promoting immune remission in some individuals.

The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening

AIMS/HYPOTHESIS

Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status.

METHODS

Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study.

RESULTS

Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%.

CONCLUSIONS/INTERPRETATION

Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress.

Targeting the receptor for advanced glycation end products (RAGE) in type 1 diabetes

Type 1 diabetes (T1D) is one of the most common chronic diseases manifesting in early life, with the prevalence increasing worldwide at a rate of approximately 3% per annum. The prolonged hyperglycaemia characteristic of T1D upregulates the receptor for advanced glycation end products (RAGE) and accelerates the formation of RAGE ligands, including advanced glycation end products, high-mobility group protein B1, S100 calcium-binding proteins, and amyloid-beta. Interestingly, changes in the expression of RAGE and these ligands are evident in patients before the onset of T1D. RAGE signals via various proinflammatory cascades, resulting in the production of reactive oxygen species and cytokines. A large number of proinflammatory ligands that can signal via RAGE have been implicated in several chronic diseases, including T1D. Therefore, it is unsurprising that RAGE has become a potential therapeutic target for the treatment and prevention of disease. In this review, we will explore how RAGE might be targeted to prevent the development of T1D.

Predictive Modeling of Type 1 Diabetes Stages Using Disparate Data Sources

This study aims to model genetic, immunologic, metabolomics, and proteomic biomarkers for development of islet autoimmunity (IA) and progression to type 1 diabetes in a prospective high-risk cohort. We studied 67 children: 42 who developed IA (20 of 42 progressed to diabetes) and 25 control subjects matched for sex and age. Biomarkers were assessed at four time points: earliest available sample, just prior to IA, just after IA, and just prior to diabetes onset. Predictors of IA and progression to diabetes were identified across disparate sources using an integrative machine learning algorithm and optimization-based feature selection. Our integrative approach was predictive of IA (area under the receiver operating characteristic curve [AUC] 0.91) and progression to diabetes (AUC 0.92) based on standard cross-validation (CV). Among the strongest predictors of IA were change in serum ascorbate, 3-methyl-oxobutyrate, and the PTPN22 (rs2476601) polymorphism. Serum glucose, ADP fibrinogen, and mannose were among the strongest predictors of progression to diabetes. This proof-of-principle analysis is the first study to integrate large, diverse biomarker data sets into a limited number of features, highlighting differences in pathways leading to IA from those predicting progression to diabetes. Integrated models, if validated in independent populations, could provide novel clues concerning the pathways leading to IA and type 1 diabetes.

The heterogeneous pathogenesis of type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) results from the destruction of pancreatic β-cells that is mediated by the immune system. Multiple genetic and environmental factors found in variable combinations in individual patients are involved in the development of T1DM. Genetic risk is defined by the presence of particular allele combinations, which in the major susceptibility locus (the HLA region) affect T cell recognition and tolerance to foreign and autologous molecules. Multiple other loci also regulate and affect features of specific immune responses and modify the vulnerability of β-cells to inflammatory mediators. Compared with the genetic factors, environmental factors that affect the development of T1DM are less well characterized but contact with particular microorganisms is emerging as an important factor. Certain infections might affect immune regulation, and the role of commensal microorganisms, such as the gut microbiota, are important in the education of the developing immune system. Some evidence also suggests that nutritional factors are important. Multiple islet-specific autoantibodies are found in the circulation from a few weeks to up to 20 years before the onset of clinical disease and this prediabetic phase provides a potential opportunity to manipulate the islet-specific immune response to prevent or postpone β-cell loss. The latest developments in understanding the heterogeneity of T1DM and characterization of major disease subtypes might help in the development of preventive treatments.

Type 1 Diabetes-related Autoantibodies in Different Forms of Diabetes

Autoantibodies against Glutamic Acid Decarboxylase (GADA), insulinoma antigen-2 (IA- 2A), insulin (IAA) and the most recently Zinc Transporter 8 (ZnT8A) are one of the most reliable biomarkers for autoimmune diabetes in both children and adults. They are today the only biomarkers that can distinguish Latent Autoimmune Diabetes in Adults (LADA) from phenotypically type 2 diabetes. As the frequency of autoantibodies at diagnosis in childhood type 1 diabetes depends on age, GADA is by far the most common in adult onset autoimmune diabetes, especially LADA. Being multiple autoantibody positive have also shown to be more common in childhood diabetes compared to adult onset diabetes, and multiple autoantibody positivity have a high predictive value of childhood type 1 diabetes. Autoantibodies have shown inconsistent results to predict diabetes in adults. Levels of autoantibodies are reported to cause heterogeneity in LADA. Reports indicate that individuals with high levels of autoantibodies have a more type 1 diabetes like phenotype and individuals with low levels of autoantibody positivity have a more type 2 diabetes like phenotype. It is also well known that autoantibody levels can fluctuate and transient autoantibody positivity in adult onset autoimmune diabetes have been reported to affect the phenotype.

Time-Resolved Autoantibody Profiling Facilitates Stratification of Preclinical Type 1 Diabetes in Children

Progression to clinical type 1 diabetes varies among children who develop β-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5 years). Children who developed multiple autoantibody types (n = 370) were clustered, and progression from seroconversion to clinical diabetes within 5 years ranged between clusters from 6% (95% CI 0, 17.4) to 84% (59.2, 93.6). Children who seroconverted early in life (median age <2 years) and developed IAA and IA-2A that were stable-positive on follow-up had the highest risk of diabetes, and this risk was unaffected by GADA status. Clusters of children who lacked stable-positive GADA responses contained more boys and lower frequencies of the HLA-DR3 allele. Our novel algorithm allows refined grouping of β-cell autoantibody-positive children who distinctly progressed to clinical type 1 diabetes, and it provides new opportunities in searching for etiological factors and elucidating complex disease mechanisms.

Serum biomarkers for diagnosis and prediction of type 1 diabetes

Type 1 diabetes (T1D) culminates in the autoimmune destruction of the pancreatic βcells, leading to insufficient production of insulin and development of hyperglycemia. Serum biomarkers including a combination of glucose, glycated molecules, C-peptide, and autoantibodies have been well established for the diagnosis of T1D. However, these molecules often mark a late stage of the disease when ∼90% of the pancreatic insulin-producing β-cells have already been lost. With the prevalence of T1D increasing worldwide and because of the physical and psychological burden induced by this disease, there is a great need for prognostic biomarkers to predict T1D development or progression. This would allow us to identify individuals at high risk for early prevention and intervention. Therefore, considerable efforts have been dedicated to the understanding of disease etiology and the discovery of novel biomarkers in the last few decades. The advent of high-throughput and sensitive "-omics" technologies for the study of proteins, nucleic acids, and metabolites have allowed large scale profiling of protein expression and gene changes in T1D patients relative to disease-free controls. In this review, we briefly discuss the classical diagnostic biomarkers of T1D but mainly focus on the novel biomarkers that are identified as markers of β-cell destruction and screened with the use of state-of-the-art "-omics" technologies.

Reduction in White Blood Cell, Neutrophil, and Red Blood Cell Counts Related to Sex, HLA, and Islet Autoantibodies in Swedish TEDDY Children at Increased Risk for Type 1 Diabetes

Islet autoantibodies (IAs) precede the clinical onset of type 1 diabetes (T1D); however, the knowledge is limited about whether the prodrome affects complete blood counts (CBCs) in 4- to 12-year-old children with increased genetic risk for T1D. This study tested whether CBCs were altered in 4- to 12-year-old children without (n = 376) or with one or several IAs against insulin, GAD65, or IA-2 (n = 72). CBC was analyzed during longitudinal follow-up in 448 Swedish children enrolled in The Environmental Determinants of Diabetes in the Young (TEDDY) study. A linear mixed-effects model was used to assess potential association between IA and CBC measurements over time. The white blood cell and neutrophil counts were reduced in children with IAs, primarily in boys. In contrast, girls had lower levels of hemoglobin and hematocrit. Positivity for multiple IAs showed the lowest counts in white blood cells and neutrophils in boys and red blood cells, hemoglobin, and hematocrit in girls. These associations were primarily observed in children with the HLA-DR3-DQ2/DR4-DQ8 genotype. We conclude that the reduction in neutrophils and red blood cells in children with multiple IAs and HLA-DR3-DQ2/DR4-DQ8 genotype may signal a sex-dependent islet autoimmunity detected in longitudinal CBCs.

The Environmental Determinants of Diabetes in the Young (TEDDY) Study: 2018 Update

PURPOSE OF REVIEW

The environmental triggers of islet autoimmunity leading to type 1 diabetes (T1D) need to be elucidated to inform primary prevention. The Environmental Determinants of Diabetes in the Young (TEDDY) Study follows from birth 8676 children with T1D risk HLA-DR-DQ genotypes in the USA, Finland, Germany, and Sweden. Most study participants (89%) have no first-degree relative with T1D. The primary outcomes include the appearance of one or more persistent islet autoantibodies (islet autoimmunity, IA) and clinical T1D.

RECENT FINDINGS

As of February 28, 2018, 769 children had developed IA and 310 have progressed to T1D. Secondary outcomes include celiac disease and autoimmune thyroid disease. While the follow-up continues, TEDDY has already evaluated a number of candidate environmental triggers, including infections, probiotics, micronutrient, and microbiome. TEDDY results suggest that there are multiple pathways leading to the destruction of pancreatic beta-cells. Ongoing measurements of further specific exposures, gene variants, and gene-environment interactions and detailed "omics" studies will provide novel information on the pathogenesis of T1D.

Class II HLA Genotype Association With First-Phase Insulin Response Is Explained by Islet Autoantibodies

CONTEXT

A declining first-phase insulin response (FPIR) is characteristic of the disease process leading to clinical type 1 diabetes. It is not known whether reduced FPIR depends on class II human leukocyte antigen (HLA) genotype, islet autoimmunity, or both.

OBJECTIVE

To dissect the role of class II HLA DR-DQ genotypes and biochemical islet autoantibodies in the compromised FPIR.

DESIGN, SETTING, PARTICIPANTS

A total of 438 children with defined HLA DR-DQ genotype in the prospective Finnish Type 1 Diabetes Prediction and Prevention Study were analyzed for FPIR in a total of 1149 intravenous glucose tolerance tests and were categorized by their HLA DR-DQ genotype and the number of biochemical islet autoantibodies at the time of the first FPIR. Age-adjusted hierarchical linear mixed models were used to analyze repeated measurements of FPIR.

MAIN OUTCOME MEASURE

The associations between class II HLA DR-DQ genotype, islet autoantibody status, and FPIR.

RESULTS

A strong association between the degree of risk conferred by HLA DR-DQ genotype and positivity for islet autoantibodies existed (P < 0.0001). FPIR was inversely associated with the number of biochemical autoantibodies (P < 0.0001) irrespective of HLA DR-DQ risk group. FPIR decreased over time in children with multiple autoantibodies and increased in children with no biochemical autoantibodies (P < 0.0001 and P = 0.0013, respectively).

CONCLUSIONS

The class II HLA DR-DQ genotype association with FPIR was secondary to the association between HLA and islet autoimmunity. Declining FPIR was associated with positivity for multiple islet autoantibodies irrespective of class II HLA DR-DQ genotype.