The implications of autoantibodies to a single islet antigen in relatives with normal glucose tolerance: development of other autoantibodies and progression to type 1 diabetes

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.

Network Cluster Analysis of PPI and Phenotype Ontology for Type 1 Diabetes Mellitus

Background

Our knowledge of Type 1 Diabetes Mellitus (T1DM) etiology is incomplete; however, the pathogenesis of the disease includes T-cell-mediated destruction of β-cells.

Objective

The present study aimed to investigate the key gene pathways and co-expression networks in T1DM disease.

Material and Methods

TIDM-associated genes were identified from 13 databases, enrichment of pathways annotated with functional annotations, and analysis of protein-protein network interactions. Next, functional modules and transcription factor networks were constructed. The analysis of gene co-expression networks was conducted to discover associated pivotal modules.

Results

A total of 172 expressed genes and four variants (SNP) were filtered in the of T1DM disease; pathway enrichment analysis identified key pathways, such as inflammatory bowel disease, type I diabetes mellitus, cytokine-cytokine receptor interaction, Th17 cell differentiation, JAK-STAT signaling pathway, and graft-versus-host disease. A weighted correlation network analysis revealed one module that was strongly correlated with T1DM. Functional annotation revealed that the module was mainly enriched in pathways such as T cell activation, regulation of immune system process, and response to the organic substance. IRF2, IRF4, IRF8, and CDX2 were regulated in the module at a significant level.

Conclusion

The study identified IL-2 as a significant T1DM hotspot and highlighted the role of hub genes and transcription factors in the autoimmune disease, offering potentials for treatment and prevention.

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.

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

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

Identification of an anergic BND cell-derived activated B cell population (BND2) in young-onset type 1 diabetes patients

Recent evidence suggests a role for B cells in the pathogenesis of young-onset type 1 diabetes (T1D), wherein rapid progression occurs. However, little is known regarding the specificity, phenotype, and function of B cells in young-onset T1D. We performed a cross-sectional analysis comparing insulin-reactive to tetanus-reactive B cells in the blood of T1D and controls using mass cytometry. Unsupervised clustering revealed the existence of a highly activated B cell subset we term BND2 that falls within the previously defined anergic BND subset. We found a specific increase in the frequency of insulin-reactive BND2 cells in the blood of young-onset T1D donors, which was further enriched in the pancreatic lymph nodes of T1D donors. The frequency of insulin-binding BND2 cells correlated with anti-insulin autoantibody levels. We demonstrate BND2 cells are pre-plasma cells and can likely act as APCs to T cells. These findings identify an antigen-specific B cell subset that may play a role in the rapid progression of young-onset T1D.

Possible heterogeneity of initial pancreatic islet beta-cell autoimmunity heralding type 1 diabetes

The etiology of type 1 diabetes (T1D) foreshadows the pancreatic islet beta-cell autoimmune pathogenesis that heralds the clinical onset of T1D. Standardized and harmonized tests of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A), and ZnT8 transporter (ZnT8A) allowed children to be followed from birth until the appearance of a first islet autoantibody. In the Environmental Determinants of Diabetes in the Young (TEDDY) study, a multicenter (Finland, Germany, Sweden, and the United States) observational study, children were identified at birth for the T1D high-risk HLA haploid genotypes DQ2/DQ8, DQ2/DQ2, DQ8/DQ8, and DQ4/DQ8. The TEDDY study was preceded by smaller studies in Finland, Germany, Colorado, Washington, and Sweden. The aims were to follow children at increased genetic risk to identify environmental factors that trigger the first-appearing autoantibody (etiology) and progress to T1D (pathogenesis). The larger TEDDY study found that the incidence rate of the first-appearing autoantibody was split into two patterns. IAA first peaked already during the first year of life and tapered off by 3-4 years of age. GADA first appeared by 2-3 years of age to reach a plateau by about 4 years. Prior to the first-appearing autoantibody, genetic variants were either common or unique to either pattern. A split was also observed in whole blood transcriptomics, metabolomics, dietary factors, and exposures such as gestational life events and early infections associated with prolonged shedding of virus. An innate immune reaction prior to the adaptive response cannot be excluded. Clarifying the mechanisms by which autoimmunity is triggered to either insulin or GAD65 is key to uncovering the etiology of autoimmune T1D.

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.

The relationship between GAD65 autoantibody and the risk of T1DM onset

Objectives

Type 1 diabetes mellitus (T1DM) is a well-known autoimmune disease, characterized by β-cell destruction in pancreas islet cells, which results insulin deficiency and subsequent hyperglycemic sequelae. While there is screening for type 2 DM that leads to better glycemic control and outcome, the majority of T1DM patients are diagnosed when much of the pancreatic cells and their function are disturbed. The aim of this article is to present an overview of the effective factors in the positivity of Glutamic acid decarboxylase antibody )GADA( and identifying the high-risk individuals for T1DM.

Methods

We searched English literature available at National Library of Medicine via PubMed, and Google Scholar through December 2020. Finally, 79 papers have been included in the study. Studies were summarized based on the number of positive autoantibodies and onset of T1DM over time and GADA correlation with different variables.

Conclusions

GADA is an easy marker to measure that can be detected many months prior to the clinical presentation and remains positive even after early childhood.

Characterising the age-dependent effects of risk factors on type 1 diabetes progression

AIMS/HYPOTHESIS

Age is known to be one of the most important stratifiers of disease progression in type 1 diabetes. However, what drives the difference in rate of progression between adults and children is poorly understood. Evidence suggests that many type 1 diabetes disease predictors do not have the same effect across the age spectrum. Without a comprehensive analysis describing the varying risk profiles of predictors over the age continuum, researchers and clinicians are susceptible to inappropriate assessment of risk when examining populations of differing ages. We aimed to systematically assess and characterise how the effect of key type 1 diabetes risk predictors changes with age.

METHODS

Using longitudinal data from single- and multiple-autoantibody-positive at-risk individuals recruited between the ages of 1 and 45 years in TrialNet's Pathway to Prevention Study, we assessed and visually characterised the age-varying effect of key demographic, immune and metabolic predictors of type 1 diabetes by employing a flexible spline model. Two progression outcomes were defined: participants with single autoantibodies (n=4893) were analysed for progression to multiple autoantibodies or type 1 diabetes, and participants with multiple autoantibodies were analysed (n=3856) for progression to type 1 diabetes.

RESULTS

Several predictors exhibited significant age-varying effects on disease progression. Amongst single-autoantibody participants, HLA-DR3 (p=0.007), GAD65 autoantibody positivity (p=0.008), elevated BMI (p=0.007) and HOMA-IR (p=0.002) showed a significant increase in effect on disease progression with increasing age. Insulin autoantibody positivity had a diminishing effect with older age in single-autoantibody-positive participants (p<0.001). Amongst multiple-autoantibody-positive participants, male sex (p=0.002) was associated with an increase in risk for progression, and HLA DR3/4 (p=0.05) showed a decreased effect on disease progression with older age. In both single- and multiple-autoantibody-positive individuals, significant changes in HR with age were seen for multiple measures of islet function. Risk estimation using prediction risk score Index60 was found to be better at a younger age for both single- and multiple-autoantibody-positive individuals (p=0.007 and p<0.001, respectively). No age-varying effect was seen for prediction risk score DPTRS (p=0.861 and p=0.178, respectively). Multivariable analyses suggested that incorporating the age-varying effect of the individual components of these validated risk scores has the potential to enhance the risk estimate.

CONCLUSIONS/INTERPRETATION

Analysing the age-varying effect of disease predictors improves understanding and prediction of type 1 diabetes disease progression, and should be leveraged to refine prediction models and guide mechanistic studies.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The Multifactorial Progression from the Islet Autoimmunity to Type 1 Diabetes in Children

Type 1 Diabetes (T1D) results from autoimmune destruction of insulin producing pancreatic ß-cells. This disease, with a peak incidence in childhood, causes the lifelong need for insulin injections and necessitates careful monitoring of blood glucose levels. However, despite the current insulin therapies, it still shortens life expectancy due to complications affecting multiple organs. Recently, the incidence of T1D in childhood has increased by 3-5% per year in most developed Western countries. The heterogeneity of the disease process is supported by the findings of follow-up studies started early in infancy. The development of T1D is usually preceded by the appearance of autoantibodies targeted against antigens expressed in the pancreatic islets. The risk of T1D increases significantly with an increasing number of positive autoantibodies. The order of autoantibody appearance affects the disease risk. Genetic susceptibility, mainly defined by the human leukocyte antigen (HLA) class II gene region and environmental factors, is important in the development of islet autoimmunity and T1D. Environmental factors, mainly those linked to the changes in the gut microbiome as well as several pathogens, especially viruses, and diet are key modulators of T1D. The aim of this paper is to expand the understanding of the aetiology and pathogenesis of T1D in childhood by detailed description and comparison of factors affecting the progression from the islet autoimmunity to T1D in children.

Beta cell function in participants with single or multiple islet autoantibodies at baseline in the TEDDY Family Prevention Study: TEFA

Aim

The aim of the present study was to assess beta cell function based on an oral glucose tolerance test (OGTT) in participants with single islet autoantibody or an intravenous glucose tolerance test (IvGTT) in participants with multiple islet autoantibodies.

Materials and methods

Healthy participants in Sweden and Finland, between 2 and 49.99 years of age previously identified as positive for a single (n = 30) autoantibody to either insulin, glutamic acid decarboxylase, islet antigen-2, zinc transporter 8 or islet cell antibodies or multiple autoantibodies (n = 46), were included. Participants positive for a single autoantibody underwent a 6-point OGTT while participants positive for multiple autoantibodies underwent an IvGTT. Glucose, insulin and C-peptide were measured from OGTT and IvGTT samples.

Results

All participants positive for a single autoantibody had a normal glucose tolerance test with 120 minutes glucose below 7.70 mmol/L and HbA1c values within the normal range (<42 mmol/mol). Insulin responses to the glucose challenge on OGTT ranged between 13.0 and 143 mIU/L after 120 minutes with C-peptide values between 0.74 and 4.60 nmol/L. In Swedish participants, the first-phase insulin response (FPIR) on IvGTT was lower in those positive for three or more autoantibodies (n = 13; median 83.0 mIU/L; range 20.0-343) compared to those with two autoantibodies (n = 15; median 146 mIU/L; range 19.0-545; P = .0330).

Conclusion

Participants positive for a single autoantibody appeared to have a normal beta cell function. Participants positive for three or more autoantibodies had a lower FPIR as compared to participants with two autoantibodies, supporting the view that their beta cell function had deteriorated.

Presumption of guilt for T cells in type 1 diabetes: lead culprits or partners in crime depending on age of onset?

Available evidence provides arguments both for and against a primary pathogenic role for T cells in human type 1 diabetes. Genetic susceptibility linked to HLA Class II lends strong support. Histopathology documents HLA Class I hyperexpression and islet infiltrates dominated by CD8+ T cells. While both hallmarks are near absent in autoantibody-positive donors, the variable insulitis and residual beta cells of recent-onset donors suggests the existence of a younger-onset endotype with more aggressive autoimmunity and an older-onset endotype with more vulnerable beta cells. Functional arguments from ex vivo and in vitro human studies and in vivo 'humanised' mouse models are instead neutral or against a T cell role. Clinical support is provided by the appearance of islet autoantibodies before disease onset. The faster C-peptide loss and superior benefits of immunotherapies in individuals with younger-onset type 1 diabetes reinforce the view of age-related endotypes. Clarifying the relative role of T cells will require technical advances in the identification of their target antigens, in their detection and phenotyping in the blood and pancreas, and in the study of the T cell/beta cell crosstalk. Critical steps toward this goal include the understanding of the link with environmental triggers, the description of T cell changes along the natural history of disease, and their relationship with age and the 'benign' islet autoimmunity of healthy individuals. Graphical abstract.

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

OBJECTIVE

The first-appearing β-cell autoantibody has been shown to influence risk of type 1 diabetes (T1D). Here, we assessed the risk of autoantibody spreading to the second-appearing autoantibody and further progression to clinical disease in The Environmental Determinants of Diabetes in the Young (TEDDY) study.

RESEARCH DESIGN AND METHODS

Eligible children with increased HLA-DR-DQ genetic risk for T1D were followed quarterly from age 3 months up to 15 years for development of a single first-appearing autoantibody (GAD antibody [GADA], insulin autoantibody [IAA], or insulinoma antigen-2 autoantibody [IA-2A]) and subsequent development of a single second-appearing autoantibody and progression to T1D. Autoantibody positivity was defined as positivity for a specific autoantibody at two consecutive visits confirmed in two laboratories. Zinc transporter 8 autoantibody (ZnT8A) was measured in children who developed another autoantibody.

RESULTS

There were 608 children who developed a single first-appearing autoantibody (IAA, n = 282, or GADA, n = 326) with a median follow-up of 12.5 years from birth. The risk of a second-appearing autoantibody was independent of GADA versus IAA as a first-appearing autoantibody (adjusted hazard ratio [HR] 1.12; 95% CI 0.88-1.42; P = 0.36). Second-appearing GADA, IAA, IA-2A, or ZnT8A conferred an increased risk of T1D compared with children who remained positive for a single autoantibody, e.g., IAA or GADA second (adjusted HR 6.44; 95% CI 3.78-10.98), IA-2A second (adjusted HR 16.33; 95% CI 9.10-29.29; P < 0.0001), or ZnT8A second (adjusted HR 5.35; 95% CI 2.61-10.95; P < 0.0001). In children who developed a distinct second autoantibody, IA-2A (adjusted HR 3.08; 95% CI 2.04-4.65; P < 0.0001) conferred a greater risk of progression to T1D as compared with GADA or IAA. Additionally, both a younger initial age at seroconversion and shorter time to the development of the second-appearing autoantibody increased the risk for T1D.

CONCLUSIONS

The hierarchical order of distinct autoantibody spreading was independent of the first-appearing autoantibody type and was age-dependent and augmented the risk of progression to T1D.

Zonulin as a potential putative biomarker of risk for shared type 1 diabetes and celiac disease autoimmunity

The incidence of type 1 diabetes (T1D) is increasing annually, in addition to other childhood-onset autoimmune diseases. This review is inspired by recent strides in research defining the pathophysiology of autoimmunity in celiac disease, a disease that has significant genetic overlap with T1D. Population genetic studies have demonstrated an increased proportion of newly diagnosed young children with T1D also have a higher genetic risk of celiac disease, suggesting that shared environmental risk factors are driving the incidence of both diseases. The small intestine barrier forms a tightly regulated interface of the immune system with the outside world and largely controls the mucosal immune response to non-self-antigens, dictating the balance between tolerance and immune response. Zonulin is the only known physiological modulator of the intercellular tight junctions, important in antigen trafficking, and therefore, is a key player in regulation of the mucosal immune response. While usually tightly controlled, when the zonulin pathway is dysregulated by changes in microbiome composition and function, antigen trafficking control is lost, leading to loss of mucosal tolerance in genetically susceptible individuals. The tenant of this hypothesis is that loss of tolerance would not occur if the zonulin-dependent intestinal barrier function is restored, thereby preventing the influence of environmental triggers in individuals genetically susceptible to autoimmunity. This review outlines the current research and a structured hypothesis on how a dysregulated small intestinal epithelial barrier, a "leaky gut," may be important in the pathogenesis of autoimmunity in certain individuals at risk of both T1D and celiac disease.

Risk of Islet and Celiac Autoimmunity in Cotwins of Probands With Type 1 Diabetes

Context

Concordance for persistent islet autoimmunity (IA) and type 1 diabetes in monozygotic twins after probands are diagnosed is variable (30%-70%). Risk for development of IA in dizygotic twins is thought to be similar to nontwin siblings. Little is known in regard to the development of celiac autoimmunity (CDA) in twins of subjects with type 1 diabetes.

Objective

Our aim was to investigate the development of IA and CDA in cotwins of probands with type 1 diabetes.

Methods

Since 1995, the Twin Family Study has followed 336 twins (168 twin probands with type 1 diabetes and 168 cotwins) for a median of 14 years (interquartile range:10-18 years). Cotwins were followed for the development of IA, type 1 diabetes, and CDA.

Results

In monozygotic cotwins, cumulative incidence by age 20 was 14% for IA and 10% for CDA. Development of IA and CDA by age 20 was 9% and 12% in dizygotic cotwins, respectively. While the numbers are small, IA by age 30 years was 26% in monozygotic and 39% in dizygotic twins. In proportional hazards models, the proband’s younger age at diagnosis, but not sex or human leukocyte antigen were associated with time to IA and CDA in cotwins.

Conclusion

CDA risk by age 20 in cotwins was 10% to 12%. With long-term follow-up, cumulative incidence for IA is high in dizygotic twins, similar to monozygotic twins, suggesting a role of possible early environmental factors shared by type 1 diabetes discordant cotwins.

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.

Hyaluronan deposition in islets may precede and direct the location of islet immune-cell infiltrates

AIMS/HYPOTHESIS

Substantial deposition of the extracellular matrix component hyaluronan (HA) is characteristic of insulitis in overt type 1 diabetes. We investigated whether HA accumulation is detectable in islets early in disease pathogenesis and how this affects the development of insulitis and beta cell mass.

METHODS

Pancreas tissue from 15 non-diabetic organ donors who were positive for islet autoantibodies (aAbs) and from 14 similarly aged aAb^- control donors were examined for the amount of islet HA staining and the presence of insulitis. The kinetics of HA deposition in islets, along with the onset and progression of insulitis and changes in beta cell mass, were investigated in BioBreeding DRLyp/Lyp rats (a model of spontaneous autoimmune diabetes) from 40 days of age until diabetes onset.

RESULTS

Abundant islet HA deposits were observed in pancreas tissues from n = 3 single- and n = 4 double-aAb⁺ donors (aAb⁺HA^high). In these seven tissues, the HA-stained areas in islets measured 1000 ± 240 μm² (mean ± SEM) and were fourfold larger than those from aAb^- control tissues. The aAb⁺HA^high tissues also had a greater prevalence of islets that were highly rich in HA (21% of the islets in these tissues contained the largest HA-stained areas [>2000 μm²] vs less than 1% in tissues from aAb^- control donors). The amount of HA staining in islets was associated with the number of aAbs (i.e. single- or double-aAb positivity) but not with HLA genotype or changes in beta cell mass. Among the seven aAb⁺HA^high tissues, three from single- and one from double-aAb⁺ donors did not show any islet immune-cell infiltrates, indicating that HA accumulates in aAb⁺ donors independently of insulitis. The three aAb⁺HA^high tissues that exhibited insulitis had the largest HA-stained areas and, in these tissues, islet-infiltrating immune cells co-localised with the most prominent HA deposits (i.e. with HA-stained areas >2000 μm²). Accumulation of HA in islets was evident prior to insulitis in 7-8-week-old presymptomatic DRLyp/Lyp rats, in which the islet HA-stained area measured 2370 ± 170 μm² (mean ± SEM), which was threefold larger than in 6-week-old rats. This initial islet HA deposition was not concurrent with beta cell loss. Insulitis was first detected in 9-10-week-old rats, in which the HA-stained areas were 4980 ± 500 μm². At this age, the rats also exhibited a 44% reduction in beta cell mass. Further enlargement of the HA-positive areas (mean ± SEM: 7220 ± 880 μm²) was associated with invasive insulitis. HA deposits remained abundant in the islets of rats with destructive insulitis, which had lost 85% of their beta cells.

CONCLUSIONS/INTERPRETATION

This study indicates that HA deposition in islets occurs early in type 1 diabetes and prior to insulitis, and points to a potential role of HA in triggering islet immune-cell infiltration and the promotion of insulitis.

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.

Excess BMI Accelerates Islet Autoimmunity in Older Children and Adolescents

OBJECTIVE

Sustained excess BMI increases the risk of type 1 diabetes (T1D) in autoantibody-positive relatives without diabetes of patients. We tested whether elevated BMI also accelerates the progression of islet autoimmunity before T1D diagnosis.

RESEARCH DESIGN AND METHODS

We studied 706 single autoantibody-positive pediatric TrialNet participants (ages 1.6-18.6 years at baseline). Cumulative excess BMI (ceBMI) was calculated for each participant based on longitudinally accumulated BMI ≥85th age- and sex-adjusted percentile. Recursive partitioning analysis and multivariable modeling defined the age cut point differentiating the risk for progression to multiple positive autoantibodies.

RESULTS

At baseline, 175 children (25%) had a BMI ≥85th percentile. ceBMI range was -9.2 to 15.6 kg/m² (median -1.91), with ceBMI ≥0 kg/m² corresponding to persistently elevated BMI ≥85th percentile. Younger age increased the progression to multiple autoantibodies, with age cutoff of 9 years defined by recursive partitioning analysis. Although ceBMI was not significantly associated with progression from single to multiple autoantibodies overall, there was an interaction with ceBMI ≥0 kg/m², age, and HLA (P = 0.009). Among children ≥9 years old without HLA DR3-DQ2 and DR4-DQ8, ceBMI ≥0 kg/m² increased the rate of progression from single to multiple positive autoantibodies (hazard ratio 7.32, P = 0.004) and conferred a risk similar to that in those with T1D-associated HLA haplotypes. In participants <9 years old, the effect of ceBMI on progression to multiple autoantibodies was not significant regardless of HLA type.

CONCLUSIONS

These data support that elevated BMI may exacerbate islet autoimmunity prior to clinical T1D, particularly in children with lower risk based on age and HLA. Interventions to maintain normal BMI may prevent or delay the progression of islet autoimmunity.

Birth and coming of age of islet autoantibodies

This review takes the reader through 45 years of islet autoantibody research, from the discovery of islet‐cell antibodies in 1974 to today’s population‐based screening for presymptomatic early‐stage type 1 diabetes. The review emphasizes the current practical value of, and factors to be considered in, the measurement of islet autoantibodies.

Autoantibodies Directed Toward a Novel IA-2 Variant Protein Enhance Prediction of Type 1 Diabetes

We identified autoantibodies (AAb) reacting with a variant IA-2 molecule (IA-2var) that has three amino acid substitutions (Cys27, Gly608, and Pro671) within the full-length molecule. We examined IA-2var AAb in first-degree relatives of type 1 diabetes (T1D) probands from the TrialNet Pathway to Prevention Study. The presence of IA-2var-specific AAb in relatives was associated with accelerated progression to T1D in those positive for AAb to GAD65 and/or insulin but negative in the standard test for IA-2 AAb. Furthermore, relatives with single islet AAb (by traditional assays) and carrying both IA-2var AAb and the high-risk HLA-DRB1*04-DQB1*03:02 haplotype progress rapidly to onset of T1D. Molecular modeling of IA-2var predicts that the genomic variation that alters the three amino acids induces changes in the three-dimensional structure of the molecule, which may lead to epitope unmasking in the IA-2 extracellular domain. Our observations suggest that the presence of AAb to IA-2var would identify high-risk subjects who would benefit from participation in prevention trials who have one islet antibody by traditional testing and otherwise would be misclassified as "low risk" relatives.

The Influence of Type 2 Diabetes-Associated Factors on Type 1 Diabetes

Current efforts to prevent progression from islet autoimmunity to type 1 diabetes largely focus on immunomodulatory approaches. However, emerging data suggest that the development of diabetes in islet autoantibody-positive individuals may also involve factors such as obesity and genetic variants associated with type 2 diabetes, and the influence of these factors increases with age at diagnosis. Although these factors have been linked with metabolic outcomes, particularly through their impact on β-cell function and insulin sensitivity, growing evidence suggests that they might also interact with the immune system to amplify the autoimmune response. The presence of factors shared by both forms of diabetes contributes to disease heterogeneity and thus has important implications. Characteristics that are typically considered to be nonimmune should be incorporated into predictive algorithms that seek to identify at-risk individuals and into the designs of trials for disease prevention. The heterogeneity of diabetes also poses a challenge in diagnostic classification. Finally, after clinically diagnosing type 1 diabetes, addressing nonimmune elements may help to prevent further deterioration of β-cell function and thus improve clinical outcomes. This Perspectives in Care article highlights the role of type 2 diabetes-associated genetic factors (e.g., gene variants at transcription factor 7-like 2 [TCF7L2]) and obesity (via insulin resistance, inflammation, β-cell stress, or all three) in the pathogenesis of type 1 diabetes and their impacts on age at diagnosis. Recognizing that type 1 diabetes might result from the sum of effects from islet autoimmunity and type 2 diabetes-associated factors, their interactions, or both affects disease prediction, prevention, diagnosis, and treatment.

Latent autoimmunity across disease-specific boundaries in at-risk first-degree relatives of SLE and RA patients

BACKGROUND

Autoimmune disease prevention requires tools to assess an individual's risk of developing a specific disease. One tool is disease-associated autoantibodies, which accumulate in an asymptomatic preclinical period. However, patients sometimes exhibit autoantibodies associated with a different disease classification. When and how these alternative autoantibodies first appear remain unknown. This cross-sectional study characterizes alternative autoimmunity, and associated genetic and environmental factors, in unaffected first-degree relatives (FDRs) of patients, who exhibit increased future risk for the same disease.

METHODS

Samples (n = 1321) from disease-specific autoantibody-positive (aAb+) systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and type 1 diabetes (T1D) patients; and unaffected aAb+ and autoantibody-negative (aAb-) SLE and RA FDRs were tested for SLE, RA, and T1D aAbs, as well as anti-tissue transglutaminase, anti-cardiolipin and anti-thyroperoxidase. FDR SLE and RA genetic risk scores (GRS) were calculated.

FINDINGS

Alternative autoimmunity occurred in SLE patients (56%) and FDRs (57·4%), RA patients (32·6%) and FDRs (34·8%), and T1D patients (43%). Expanded autoimmunity, defined as autoantibodies spanning at least two other diseases, occurred in 18·5% of SLE patients, 16·4% of SLE FDRs, 7·8% of RA patients, 5·3% of RA FDRs, and 10·8% of T1D patients. SLE FDRs were more likely to have alternative (odds ratio [OR] 2·44) and expanded (OR 3·27) autoimmunity than RA FDRs. Alternative and expanded autoimmunity were associated with several environmental exposures. Alternative autoimmunity was associated with a higher RA GRS in RA FDRs (OR 1·41), and a higher SLE GRS in aAb+ RA FDRs (OR 1·87), but not in SLE FDRs.

INTERPRETATION

Autoimmunity commonly crosses disease-specific boundaries in systemic (RA, SLE) and organ-specific (T1D) autoimmune diseases. Alternative autoimmunity is more common in SLE FDRs than RA FDRs, and is influenced by genetic and environmental factors. These findings have substantial implications for preclinical disease pathogenesis and autoimmune disease prevention studies. FUND: NIH U01AI101981, R01AR051394, U19AI082714, P30AR053483, P30GM103510, U54GM104938, U01AI101934, R01AI024717, U01AI130830, I01BX001834, & U01HG008666.

Marie M, Stickney K, VanBuecken D, Vellek B, Webber C, Allen L, Bollyk J, Hilderman N, Ismail H, Lamola S, Sanda S, Vendettuoli H, Tridgell D, Monzavi R, Bock M, Fisher L, Halvorson M, Jeandron D, Kim M, Wood J, Geffner M, Kaufman F, Parkman R, Salazar C, Goland R, Clynes R, Cook S, Freeby M, Pat Gallagher M, Gandica R, Greenberg E, Kurland A, Pollak S, Wolk A, Chan M, Koplimae L, Levine E, Smith K, Trast J, DiMeglio L, Blum J, Evans-Molina C, Hufferd R, Jagielo B, Kruse C, Patrick V, Rigby M, Spall M, Swinney K, Terrell J, Christner L, Ford L, Lynch S, Menendez M, Merrill P, Pescovitz M, Rodriguez H, Alleyn C, Baidal D, Fay S, Gaglia J, Resnick B, Szubowicz S, Weir G, Benjamin R, Conboy D, deManbey A, Jackson R, Jalahej H, Orban T, Ricker A, Wolfsdorf J, Zhang HH, Wilson D, Aye T, Baker B, Barahona K, Buckingham B, Esrey K, Esrey T, Fathman G, Snyder R, Aneja B, Chatav M, Espinoza O, Frank E, Liu J, Perry J, Pyle R, Rigby A, Riley K, Soto A, Gitelman S, Adi S, Anderson M, Berhel A, Breen K, Fraser K, Gerard-Gonzalez A, Jossan P, Lustig R, Moassesfar S, Mugg A, Ng D, Prahalod P, Rangel-Lugo M, Sanda S, Tarkoff J, Torok C, Wesch R, Aslan I, Buchanan J, Cordier J, Hamilton C, Hawkins L, Ho T, Jain A, Ko K, Lee T, Phelps S, Rosenthal S, Sahakitrungruang T, Stehl L, Taylor L, Wertz M, Wong J, Philipson L, Briars R, Devine N, Littlejohn E, Grant T, Gottlieb P, Klingensmith G, Steck A, Alkanani A, Bautista K, Bedoy R, Blau A, Burke B, Cory L, Dang M, Fitzgerald-Miller L, Fouts A, Gage V, Garg S, Gesauldo P, Gutin R, Hayes C, Hoffman M, Ketchum K, Logsden-Sackett N, Maahs D, Messer L, Meyers L, Michels A, Peacock S, Rewers M, Rodriguez P, Sepulbeda F, Sippl R, Steck A, Taki I, Tran BK, Tran T, Wadwa RP, Zeitler P, Barker J, Barry S, Birks L, Bomsburger L, Bookert T, Briggs L, Burdick P, Cabrera R, Chase P, Cobry E, Conley A, Cook G, Daniels J, DiDomenico D, Eckert J, Ehler A, Eisenbarth G, Fain P, Fiallo-Scharer R, Frank N, Goettle H, Haarhues M, Harris S, Horton L, Hutton J, Jeffrrey J, Jenison R, Jones K, Kastelic W, King MA, Lehr D, Lungaro J, Mason K, Maurer H, Nguyen L, Proto A, Realsen J, Schmitt K, Schwartz M, Skovgaard S, Smith J, Vanderwel B, Voelmle M, Wagner R, Wallace A, Walravens P, Weiner L, Westerhoff B, Westfall E, Widmer K, Wright H, Schatz D, Abraham A, Atkinson M, Cintron M, Clare-Salzler M, Ferguson J, Haller M, Hosford J, Mancini D, Rohrs H, Silverstein J, Thomas J, Winter W, Cole G, Cook R, Coy R, Hicks E, Lewis N, Marks J, Pugliese A, Blaschke C, Matheson D, Pugliese A, Sanders-Branca N, Ray Arce LA, Cisneros M, Sabbag S, Moran A, Gibson C, Fife B, Hering B, Kwong C, Leschyshyn J, Nathan B, Pappenfus B, Street A, Boes MA, Peterson Eck S, Finney L, Albright Fischer T, Martin A, Jacqueline Muzamhindo C, Rhodes M, Smith J, Wagner J, Wood B, Becker D, Delallo K, Diaz A, Elnyczky B, Libman I, Pasek B, Riley K, Trucco M, Copemen B, Gwynn D, Toledo F, Rodriguez H, Bollepalli S, Diamond F, Eyth E, Henson D, Lenz A, Shulman D, Raskin P, Adhikari S, Dickson B, Dunnigan E, Lingvay I, Pruneda L, Ramos-Roman M, Raskin P, Rhee C, Richard J, Siegelman M, Sturges D, Sumpter K, White P, Alford M, Arthur J, Aviles-Santa ML, Cordova E, Davis R, Fernandez S, Fordan S, Hardin T, Jacobs A, Kaloyanova P, Lukacova-Zib I, Mirfakhraee S, Mohan A, Noto H, Smith O, Torres N, Wherrett D, Balmer D, Eisel L, Kovalakovska R, Mehan M, Sultan F, Ahenkorah B, Cevallos J, Razack N, Jo Ricci M, Rhode A, Srikandarajah M, Steger R, Russell WE, Black M, Brendle F, Brown A, Moore D, Pittel E, Robertson A, Shannon A, Thomas JW, Herold K, Feldman L, Sherwin R, Tamborlane W, Weinzimer S, Toppari J, Kallio T, Kärkkäinen M, Mäntymäki E, Niininen T, Nurmi B, Rajala P, Romo M, Suomenrinne S, Näntö-Salonen K, Simell O, Simell T, Bosi E, Battaglia M, Bianconi E, Bonfanti R, Grogan P, Laurenzi A, Martinenghi S, Meschi F, Pastore M, Falqui L, Teresa Muscato M, Viscardi M, Bingley P, Castleden H, Farthing N, Loud S, Matthews C, McGhee J, Morgan A, Pollitt J, Elliot-Jones R, Wheaton C, Knip M, Siljander H, Suomalainen H, Colman P, Healy F, Mesfin S, Redl L, Wentworth J, Willis J, Farley M, Harrison L, Perry C, Williams F, Mayo A, Paxton J, Thompson V, Volin L, Fenton C, Carr L, Lemon E, Swank M, Luidens M, Salgam M, Sharma V, Schade D, King C, Carano R, Heiden J, Means N, Holman L, Thomas I, Madrigal D, Muth T, Martin C, Plunkett C, Ramm C, Auchus R, Lane W, Avots E, Buford M, Hale C, Hoyle J, Lane B, Muir A, Shuler S, Raviele N, Ivie E, Jenkins M, Lindsley K, Hansen I, Fadoju D, Felner E, Bode B, Hosey R, Sax J, Jefferies C, Mannering S, Prentis R, She J, Stachura M, Hopkins D, Williams J, Steed L, Asatapova E, Nunez S, Knight S, Dixon P, Ching J, Donner T, Longnecker S, Abel K, Arcara K, Blackman S, Clark L, Cooke D, Plotnick L, Levin P, Bromberger L, Klein K, Sadurska K, Allen C, Michaud D, Snodgrass H, Burghen G, Chatha S, Clark C, Silverberg J, Wittmer C, Gardner J, LeBoeuf C, Bell P, McGlore O, Tennet H, Alba N, Carroll M, Baert L, Beaton H, Cordell E, Haynes A, Reed C, Lichter K, McCarthy P, McCarthy S, Monchamp T, Roach J, Manies S, Gunville F, Marosok L, Nelson T, Ackerman K, Rudolph J, Stewart M, McCormick K, May S, Falls T, Barrett T, Dale K, Makusha L, McTernana C, Penny-Thomas K, Sullivan K, Narendran P, Robbie J, Smith D, Christensen R, Koehler B, Royal C, Arthur T, Houser H, Renaldi J, Watsen S, Wu P, Lyons L, House B, Yu J, Holt H, Nation M, Vickers C, Watling R, Heptulla R, Trast J, Agarwal C, Newell D, Katikaneni R, Gardner C, Del A, Rio A, Logan H, Collier C, Rishton G, Whalley A, Ali S, Ramtoola T, Quattrin L, Mastrandea A, House M, Ecker C, Huang C, Gougeon J, Ho D, Pacuad D, Dunger J, May C, O’Brien C, Acerini B, Salgin A, Thankamony R, Williams J, Buse G, Fuller M, Duclos J, Tricome H, Brown D, Pittard D, Bowlby A, Blue T, Headley S, Bendre K, Lewis K, Sutphin C, Soloranzo J, Puskaric H, Madison M, Rincon M, Carlucci R, Shridharani B, Rusk E, Tessman D, Huffman H, Abrams B, Biederman M, Jones V, Leathers W, Brickman P, Petrie D, Zimmerman J, Howard L, Miller R, Alemzadeh D, Mihailescu R, Melgozza-Walker N, Abdulla C, Boucher-Berry D, Ize-Ludlow R, Levy C, Swenson, Brousell N, Crimmins D, Edler T, Weis C, Schultz D, Rogers D, Latham C, Mawhorter C, Switzer W, Spencer P, Konstantnopoulus S, Broder J, Klein L, Knight L, Szadek G, Welnick B, Thompson R, Hoffman A, Revell J, Cherko K, Carter E, Gilson J, Haines G, Arthur B, Bowen W, Zipf P, Graves R, Lozano D, Seiple K, Spicer A, Chang J, Fregosi J, Harbinson C, Paulson S, Stalters P, Wright D, Zlock A, Freeth J, Victory H, Maheshwari A, Maheshwari T, Holmstrom J, Bueno R, Arguello J, Ahern L, Noreika V, Watson S, Hourse P, Breyer C, Kissel Y, Nicholson M, Pfeifer S, Almazan J, Bajaj M, Quinn K, Funk J, McCance E, Moreno R, Veintimilla A, Wells J, Cook S, Trunnel J, Henske S, Desai K, Frizelis F, Khan R, Sjoberg K, Allen P, Manning G, Hendry B, Taylor S, Jones W, Strader M, Bencomo T, Bailey L, Bedolla C, Roldan C, Moudiotis B, Vaidya C, Anning S, Bunce S, Estcourt E, Folland E, Gordon C, Harrill J, Ireland J, Piper L, Scaife K, Sutton S, Wilkins M, Costelloe J, Palmer L, Casas C, Miller M, Burgard C, Erickson J, Hallanger-Johnson P, Clark W, Taylor A, Lafferty S, Gillett C, Nolan M, Pathak L, Sondrol T, Hjelle S, Hafner J, Kotrba R, Hendrickson A, Cemeroglu T, Symington M, Daniel Y, Appiagyei-Dankah D, Postellon M, Racine L, Kleis K, Barnes S, Godwin H, McCullough K, Shaheen G, Buck L, Noel M, Warren S, Weber S, Parker I, Gillespie B, Nelson C, Frost J, Amrhein E, Moreland A, Hayes J, Peggram J, Aisenberg M, Riordan J, Zasa E, Cummings K, Scott T, Pinto A, Mokashi K, McAssey E, Helden P, Hammond L, Dinning S, Rahman S, Ray C, Dimicri S, Guppy H, Nielsen C, Vogel C, Ariza L, Morales Y, Chang R, Gabbay L, Ambrocio L, Manley R, Nemery W, Charlton P, Smith L, Kerr B, Steindel-Kopp M, Alamaguer D, Liljenquist G, Browning T, Coughenour M, Sulk E, Tsalikan M, Tansey J, Cabbage N. Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes

OBJECTIVE

There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings.

RESEARCH DESIGN AND METHODS

Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years.

RESULTS

At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects.

CONCLUSIONS

Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.

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.

Abnormal T Cell Frequencies, Including Cytomegalovirus-Associated Expansions, Distinguish Seroconverted Subjects at Risk for Type 1 Diabetes

We analyzed T cell subsets from cryopreserved PBMC obtained from the TrialNet Pathway to Prevention archives. We compared subjects who had previously seroconverted for one or more autoantibodies with non-seroconverted, autoantibody negative individuals. We observed a reduced frequency of MAIT cells among seroconverted subjects. Seroconverted subjects also possessed decreased frequencies of CCR4-expressing CD4 T cells, including a regulatory-like subset. Interestingly, we found an elevation of CD57+, CD28–, CD127–, CD27– CD8 T cells (SLEC) among seroconverted subjects that was most pronounced among those that progressed to disease. The frequency of these SLEC was strongly correlated with CMV IgG abundance among seroconverted subjects, associated with IA-2 levels, and most elevated among CMV+ seroconverted subjects who progressed to disease. Combined, our data indicate discrete, yet profound T cell alterations are associated with islet autoimmunity among at-risk subjects.

Strength in Numbers: Opportunities for Enhancing the Development of Effective Treatments for Type 1 Diabetes-The TrialNet Experience

The early to mid-1980s were an inflection point in the history of type 1 diabetes research. Two landmark events occurred: the initiation of immune-based interventions seeking to prevent type 1 diabetes and the presentation of an innovative model describing the disorder's natural history. Both formed the basis for hundreds of subsequent studies designed to achieve a dramatic therapeutic goal-a means to prevent and/or reverse type 1 diabetes. However, the need to screen large numbers of individuals and prospectively monitor them using immunologic and metabolic tests for extended periods of time suggested such efforts would require a large collaborative network. Hence, the National Institutes of Health formed the landmark Diabetes Prevention Trial-Type 1 (DPT-1) in the mid-1990s, an effort that led to Type 1 Diabetes TrialNet. TrialNet studies have helped identify novel biomarkers; delineate type 1 diabetes progression, resulting in identification of highly predictable stages defined by the accumulation of autoantibodies (stage 1), dysglycemia (stage 2), and disease meeting clinical criteria for diagnosis (stage 3); and oversee numerous clinical trials aimed at preventing disease progression. Such efforts pave the way for stage-specific intervention trials with improved hope that a means to effectively disrupt the disorder's development will be identified.

Accelerated Progression to Type 1 Diabetes in the Presence of HLA-A*24 and -B*18 Is Restricted to Multiple Islet Autoantibody-Positive Individuals With Distinct HLA-DQ and Autoantibody Risk Profiles

OBJECTIVE

We investigated the effect of HLA class I risk alleles on disease progression in various phases of subclinical islet autoimmunity in first-degree relatives of patients with type 1 diabetes.

RESEARCH DESIGN AND METHODS

A registry-based group of siblings/offspring (aged 0-39 years) was monitored from single- to multiple-autoantibody positivity (n = 267) and from multiple-autoantibody positivity to clinical onset (n = 252) according to HLA-DQ, -A*24, -B*18, and -B*39 status. Genetic markers were determined by PCR sequence-specific oligotyping.

RESULTS

Unlike HLA-B*18 or -B*39, HLA-A*24 was associated with delayed progression from single- to multiple-autoantibody positivity (P = 0.009) but not to type 1 diabetes. This occurred independently from older age (P < 0.001) and absence of HLA-DQ2/DQ8 or -DQ8 (P < 0.001 and P = 0.003, respectively), and only in the presence of GAD autoantibodies. In contrast, HLA-A*24 was associated with accelerated progression from multiple-autoantibody positivity to clinical onset (P = 0.006), but its effects were restricted to HLA-DQ8⁺ relatives with IA-2 or zinc transporter 8 autoantibodies (P = 0.002). HLA-B*18, but not -B*39, was also associated with more rapid progression, but only in HLA-DQ2 carriers with double positivity for GAD and insulin autoantibodies (P = 0.004).

CONCLUSIONS

HLA-A*24 predisposes to a delayed antigen spreading of humoral autoimmunity, whereas HLA-A*24 and -B*18 are associated with accelerated progression of advanced subclinical autoimmunity in distinct risk groups. The relation of these alleles to the underlying disease process requires further investigation. Their typing should be relevant for the preparation and interpretation of observational and interventional studies in asymptomatic type 1 diabetes.

Type 1 Diabetes TrialNet: A Multifaceted Approach to Bringing Disease-Modifying Therapy to Clinical Use in Type 1 Diabetes

What will it take to bring disease-modifying therapy to clinical use in type 1 diabetes? Coordinated efforts of investigators involved in discovery, translational, and clinical research operating in partnership with funders and industry and in sync with regulatory agencies are needed. This Perspective describes one such effort, Type 1 Diabetes TrialNet, a National Institutes of Health-funded and JDRF-supported international clinical trials network that emerged from the Diabetes Prevention Trial-Type 1 (DPT-1). Through longitudinal natural history studies, as well as trials before and after clinical onset of disease combined with mechanistic and ancillary investigations to enhance scientific understanding and translation to clinical use, TrialNet is working to bring disease-modifying therapies to individuals with type 1 diabetes. Moreover, TrialNet uses its expertise and experience in clinical studies to increase efficiencies in the conduct of trials and to reduce the burden of participation on individuals and families. Herein, we highlight key contributions made by TrialNet toward a revised understanding of the natural history of disease and approaches to alter disease course and outline the consortium's plans for the future.

Curative potential of allogeneic hematopoietic stem cell transplant in type 1 diabetes

The mainstay of treatment for type 1 diabetes (T1D) is exogenous insulin. Here, we report a case in which exogenous insulin requirements were eliminated after an allogeneic hematopoietic stem cell transplant for aplastic anemia in a pediatric patient recently diagnosed with T1D, and explore the validity of this approach compared with current treatments.

Type 1 Diabetes: Disease Stratification

Type 1 diabetes, a disorder characterized by immune-mediated loss of functional pancreatic beta cells, is a disease continuum with specific presymptomatic stages with defined risk of progression to symptomatic disease. Prognostic biomarkers have been developed for disease staging and for stratification of subjects that address the heterogeneity in rate of disease progression. Using biomarkers for stratification of subjects at different stages of type 1 diabetes will enable smaller and shorter intervention clinical trials with greater effect size. Addressing the heterogeneity of the disease will allow precision medicine-based approaches to prevention and interception of presymptomatic stages of disease and treatment and cure of symptomatic disease.

Impact of Age and Antibody Type on Progression From Single to Multiple Autoantibodies in Type 1 Diabetes Relatives

Context

Islet autoantibodies are markers of type 1 diabetes, and an increase in number of autoantibodies detected during the preclinical phase predicts progression to overt disease.

Objective

To refine the effect of age in relation to islet antibody type on progression from single to multiple autoantibodies in relatives of people with type 1 diabetes.

Research Design and Methods

We examined 994 relatives with normal glucose tolerance who were positive for a single autoantibody, followed prospectively in the TrialNet Pathway to Prevention. Antibodies to glutamic acid decarboxylase (GADA), insulin (IAA), insulinoma-associated antigen 2, and zinc transporter 8 and islet cell antibodies were tested every 6 to 12 months. The primary outcome was confirmed development of multiple autoantibodies. Age was categorized as <8 years, 8 to 11 years, 12 to 17 years, and ≥18 years, and optimal age breakpoints were identified by recursive partitioning analysis.

Results

After median follow-up of 2 years, 141 relatives had developed at least one additional autoantibodies. Five-year risk was inversely related to age, but the pattern differed by antibody type: Relatives with GADA showed a gradual decrease in risk over the four age groups, whereas relatives with IAA showed a sharp decrease above age 8 years. Recursive partitioning analysis identified age breakpoints at 14 years in relatives with GADA and at 4 years in relatives with IAA.

Conclusions

In relatives with IAA, spread of islet autoimmunity is largely limited to early childhood, whereas immune responses initially directed at glutamic acid decarboxylase can mature over a longer period. These differences have important implications for monitoring these patients and for designing prevention trials.

Twenty-Year Progression Rate to Clinical Onset According to Autoantibody Profile, Age, and HLA-DQ Genotype in a Registry-Based Group of Children and Adults With a First-Degree Relative With Type 1 Diabetes

OBJECTIVE

We investigated whether islet autoantibody profile, HLA-DQ genotype, and age influenced a 20-year progression to diabetes from first autoantibody positivity (autoAb⁺) in first-degree relatives of patients with type 1 diabetes.

RESEARCH DESIGN AND METHODS

Persistently islet autoAb⁺ siblings and offspring (n = 462) under 40 years of age were followed by the Belgian Diabetes Registry. AutoAbs against insulin (IAA), GAD (GADA), IA-2 antigen (IA-2A), and zinc transporter 8 (ZnT8A) were determined by radiobinding assay.

RESULTS

The 20-year progression rate of multiple-autoAb⁺ relatives (n = 194) was higher than that for single-autoAb⁺ participants (n = 268) (88% vs. 54%; P < 0.001). Relatives positive for IAA and GADA (n = 54) progressed more slowly than double-autoAb⁺ individuals carrying IA-2A and/or ZnT8A (n = 38; P = 0.001). In multiple-autoAb⁺ relatives, Cox regression analysis identified the presence of IA-2A or ZnT8A as the only independent predictors of more rapid progression to diabetes (P < 0.001); in single-autoAb⁺ relatives, it identified younger age (P < 0.001), HLA-DQ2/DQ8 genotype (P < 0.001), and IAA (P = 0.028) as independent predictors of seroconversion to multiple positivity for autoAbs. In time-dependent Cox regression, younger age (P = 0.042), HLA-DQ2/DQ8 genotype (P = 0.009), and the development of additional autoAbs (P = 0.012) were associated with more rapid progression to diabetes.

CONCLUSIONS

In single-autoAb⁺ relatives, the time to multiple-autoAb positivity increases with age and the absence of IAA and HLA-DQ2/DQ8 genotype. The majority of multiple-autoAb⁺ individuals progress to diabetes within 20 years; this occurs more rapidly in the presence of IA-2A or ZnT8A, regardless of age, HLA-DQ genotype, and number of autoAbs. These data may help to refine the risk stratification of presymptomatic type 1 diabetes.

The Use of Electrochemiluminescence Assays to Predict Autoantibody and Glycemic Progression Toward Type 1 Diabetes in Individuals with Single Autoantibodies

BACKGROUND

Electrochemiluminescence (ECL) assays have shown promise for enhancing the prediction of type 1 diabetes (T1D) with autoantibodies. We thus studied relatives of T1D patients to determine whether ECL assays can be used to refine risk assessments for T1D among individuals either positive for single GADA or single mIAA autoantibodies.

SUBJECTS AND METHODS

TrialNet Pathway to Prevention (PTP) study participants with either GADA or mIAA single autoantibodies were tested for ECL positivity during their participation in the TrialNet PTP study. Those ECL positive (ECL⁺) were compared with those ECL negative (ECL^-) for conversion to multiple autoantibodies, 6-month glycemic progression (PS6M), and the progression to T1D.

RESULTS

The progression to multiple autoantibodies was significantly higher for those GADA/ECL⁺ (n = 107) than those GADA/ECL^- (n = 78) (P = 0.001) and for those mIAA/ECL⁺ (n = 24) than those mIAA/ECL^- (n = 63) (P < 0.001). The hazard ratios with 95% confidence intervals were 3.42 (1.58-7.39; P < 0.01) for GADA and 8.15 (3.02-22.00; P < 0.001) for mIAA. GADA/ECL⁺ and mIAA/ECL⁺ participants had significantly higher PS6M values than their ECL^- counterparts (P = 0.001 for GADA and P = 0.009 for mIAA). Of those GADA/ECL⁺, 14% progressed to T1D; of those mIAA/ECL⁺, 17% progressed to T1D. Only 1 individual (positive for GADA) of the 141 who was ECL^- progressed to T1D (median follow-up: 5 years).

CONCLUSION

ECL measurements appear to have utility for natural history studies and prevention trials of individuals with single autoantibodies. Those ECL⁺ are at appreciable risk for developing multiple autoantibodies and for glycemic progression toward T1D, whereas those ECL^- are at very low risk.

High prevalence of diabetes-specific autoimmunity in first-degree relatives of Sardinian patients with type 1 diabetes

BACKGROUND

The incidence of type 1 diabetes mellitus (T1DM) in Sardinia is among the highest in the world (44.8 cases/100,000 person-years). Recommendations of the Immunology of Diabetes Society advise evaluating autoantibody positivity in first-degree relatives (FDRs) of patients with T1DM, for their higher risk to develop the disease. The aim of this study was to determine the prevalence of beta-cell autoimmunity in FDRs of T1DM patients in Sardinia.

METHODS

A total of 188 Sardinian families were recruited in collaboration between diabetes and pediatric units of university and district hospitals in Sardinia. The recruitment involved 188 patients with diagnosed T1DM and all their available FDRs (n = 447). Autoantibodies (Aabs) against GAD, IA2, insulin, and ZnT8 were measured in all subjects. Human leukocyte antigen (HLA) risk genotypes (HLA-DR and DQ loci) were analyzed in 43 Aabs-positive FDR.

RESULTS

The prevalence of Aabs (any type of autoantibody, single or multiple) in FDR was 11.9% (53/447). Of those with autoantibodies, 62.3% (33/53) were positive to only 1 autoantibody, 22.6% (12/53) had 2 autoantibodies, 7.55% (4/53) had 3 autoantibodies, and 7.55% (4/53) had all 4 autoantibodies. Typing of HLA-DR and DQ loci showed that 89% of FDR carried moderate- to high-risk genotypes, with only 5 FDR with low-risk genotypes.

CONCLUSIONS

The prevalence of T1DM autoantibodies in FDRs of T1DM patients was very high (11.9%) in the Sardinian population, higher than in other populations from the United States and Europe, and similar to that observed in Finland. Autoantibody positivity strongly associated with HLA risk. This study provides evidence of the high risk of T1DM in FDR of T1DM patients in Sardinia and warrants longitudinal follow-up to estimate the risk of progression to T1DM in high-risk populations.

Prognostic Classification Factors Associated With Development of Multiple Autoantibodies, Dysglycemia, and Type 1 Diabetes-A Recursive Partitioning Analysis

OBJECTIVE

To define prognostic classification factors associated with the progression from single to multiple autoantibodies, multiple autoantibodies to dysglycemia, and dysglycemia to type 1 diabetes onset in relatives of individuals with type 1 diabetes.

RESEARCH DESIGN AND METHODS

Three distinct cohorts of subjects from the Type 1 Diabetes TrialNet Pathway to Prevention Study were investigated separately. A recursive partitioning analysis (RPA) was used to determine the risk classes. Clinical characteristics, including genotype, antibody titers, and metabolic markers were analyzed.

RESULTS

Age and GAD65 autoantibody (GAD65Ab) titers defined three risk classes for progression from single to multiple autoantibodies. The 5-year risk was 11% for those subjects >16 years of age with low GAD65Ab titers, 29% for those ≤16 years of age with low GAD65Ab titers, and 45% for those subjects with high GAD65Ab titers regardless of age. Progression to dysglycemia was associated with islet antigen 2 Ab titers, and 2-h glucose and fasting C-peptide levels. The 5-year risk is 28%, 39%, and 51% for respective risk classes defined by the three predictors. Progression to type 1 diabetes was associated with the number of positive autoantibodies, peak C-peptide level, HbA1c level, and age. Four risk classes defined by RPA had a 5-year risk of 9%, 33%, 62%, and 80%, respectively.

CONCLUSIONS

The use of RPA offered a new classification approach that could predict the timing of transitions from one preclinical stage to the next in the development of type 1 diabetes. Using these RPA classes, new prevention techniques can be tailored based on the individual prognostic risk characteristics at different preclinical stages.