Development of autoantibodies in the TrialNet Natural History Study

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

AIMS/HYPOTHESIS

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

METHODS

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

RESULTS

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

CONCLUSIONS/INTERPRETATION

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

The potential Association of Bisphenol A exposure and type 1 diabetes mellitus among Dakahlia Governorate's children sample, Egypt

Background

Bisphenol A (BPA) is an endocrine disrupter affecting glucose homeostasis.

Objectives

This study aimed to investigate BPA's relationship with Type 1 Diabetes Mellitus (T1DM) in Dakahlia Governorate's children, in Egypt.

Subjects materials and methods

The study had two parts: clinical and experimental. Clinical Study was conducted on 200 children, equally divided into control and T1DM groups. They underwent: demographic data, height, weight, body mass index, glycosylated HbA1C, random blood glucose, and urinary BPA measurements. Experimental Study was conducted on 60 adult albino rats. Rats were randomly divided into three equal groups: control group: received 0.5 mL of pure olive oil, group 1: received 20 mg/kg/day BPA, and group 2: received 100 mg/kg/day BPA orally for 6 weeks. Fasting and two hours postprandial glucose levels were measured at the beginning and end of the study. Histopathological examination and imaging study of the pancreas were done.

Results

In clinical study: HbA1C and random blood glucose levels in diabetic children showed a significant increase compared to control. Children in control group showed controlled HbA1C, while the T1DM group showed 86% with poor diabetic control. There was a significant increase in BPA level in the T1DM group compared to the control. Rats that received BPA showed a marked increase in fasting and two hours postprandial glucose levels, histopathological changes in the pancreas with more changes determined in the high dose group, and a significant decrease in the islets of Langerhans diameters with group 2 more affected.

Conclusion

So, BPA exposure could be considered a risk factor for T1DM in children.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Type 1 Diabetes Risk Phenotypes Using Cluster Analysis

Background

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

Methods

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

Findings

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

Interpretation

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

Matching for HLA-DR excluding diabetogenic HLA-DR3 and HLA-DR4 predicts insulin independence after pancreatic islet transplantation

Introduction

In pancreatic islet transplantation, the exact contribution of human leukocyte antigen (HLA) matching to graft survival remains unclear. Islets may be exposed to allogenic rejection but also the recurrence of type 1 diabetes (T1D). We evaluated the HLA-DR matching, including the impact of diabetogenic HLA-DR3 or HLA-DR4 matches.

Methods

We retrospectively examined the HLA profile in 965 transplant recipients and 2327 islet donors. The study population was obtained from patients enrolled in the Collaborative Islet Transplant Registry. We then identified 87 recipients who received a single-islet infusion. Islet-kidney recipients, 2nd islet infusion, and patients with missing data were excluded from the analysis (n=878).

Results

HLA-DR3 and HLA-DR4 were present in 29.7% and 32.6% of T1D recipients and 11.6% and 15.8% of the donors, respectively. We identified 52 T1D islet recipients mismatched for HLA-DR (group A), 11 with 1 or 2 HLA-DR-matches but excluding HLA-DR3 and HLA- DR4 (group B), and 24 matched for HLA-DR3 or HLA-DR4 (group C). Insulin-independence was maintained in a significantly higher percentage of group B recipients from year one through five post-transplantation (p<0.01). At five-year post-transplantation, 78% of group B was insulin-independent compared to 24% (group A) and 35% (group C). Insulin-independence correlated with significantly better glycemic control (HbA1c <7%), fasting blood glucose, and reduced severe hypoglycemic events. Matching HLA-A-B-DR (≥3) independently of HLA- DR3 or HLA-DR4 matching did not improve graft survival.

Conclusion

This study suggests that matching HLA-DR but excluding the diabetogenic HLA-DR3 and/or 4 is a significant predictor for long-term islet survival.

Evaluation of the RSR 3 screen ICA™ and 2 screen ICA™ as screening assays for type 1 diabetes in Sweden

AIM

The study aim was to evaluate the RSR 3 Screen ICA™ and 2 Screen ICA™ for detection of islet cell autoimmunity in healthy Swedish subjects and patients with newly diagnosed type 1 diabetes (T1D).

METHODS

3 Screen is designed for combined detection of autoantibodies to glutamic acid decarboxylase (GADA), to the islet antigen IA-2 (IA-2A) and to zinc transporter 8 (ZnT8A), while 2 Screen detects GADA and IA-2A. Serum samples from 100 T1D patients at onset and 200 healthy controls were studied.

RESULTS

3 Screen achieved 93% assay sensitivity and 97.5% specificity, while 2 Screen achieved 91% assay sensitivity and 98.5% specificity. Samples were also tested in assays for individual autoantibodies. There was only one 3 Screen positive healthy control sample (0.5%) that was positive for multiple autoantibodies (IA-2A and ZnT8A). In contrast, most of the 93 3 Screen positive patients were positive for multiple autoantibodies with 72% (67/93) positive for both GADA and IA-2A and 57% (53/93) positive for three autoantibodies (GADA, IA-2A and ZnT8A). Insulin autoantibodies (IAA, measured by radioimmunoassay) were positive in 13 patients and two healthy controls.

CONCLUSION

3 Screen achieved high sensitivity and specificity, suitable for islet cell autoimmunity screening in a healthy population. In the case of 3 Screen positivity, further assays for GADA, IA-2A and ZnT8A are required to check for multiple autoantibody positivity, a hallmark for progression to T1D. In addition, testing for IAA in children below two years of age is warranted.

Modeling human T1D-associated autoimmune processes

BACKGROUND

Type 1 diabetes (T1D) is an autoimmune disease characterized by impaired immune tolerance to β-cell antigens and progressive destruction of insulin-producing β-cells. Animal models have provided valuable insights for understanding the etiology and pathogenesis of this disease, but they fall short of reflecting the extensive heterogeneity of the disease in humans, which is contributed by various combinations of risk gene alleles and unique environmental factors. Collectively, these factors have been used to define subgroups of patients, termed endotypes, with distinct predominating disease characteristics.

SCOPE OF REVIEW

Here, we review the gaps filled by these models in understanding the intricate involvement and regulation of the immune system in human T1D pathogenesis. We describe the various models developed so far and the scientific questions that have been addressed using them. Finally, we discuss the limitations of these models, primarily ascribed to hosting a human immune system (HIS) in a xenogeneic recipient, and what remains to be done to improve their physiological relevance.

MAJOR CONCLUSIONS

To understand the role of genetic and environmental factors or evaluate immune-modifying therapies in humans, it is critical to develop and apply models in which human cells can be manipulated and their functions studied under conditions that recapitulate as closely as possible the physiological conditions of the human body. While microphysiological systems and living tissue slices provide some of these conditions, HIS mice enable more extensive analyses using in vivo systems.

Relationships among consanguinity, family history, and the onset of type 1 diabetes in children from Saudi Arabia

AIMS

We aimed to demonstrate the relationship between parental consanguinity and positive family histories of type 1 diabetes mellitus (T1DM) and autoimmune disease and the development of T1DM among children in Saudi Arabia.

METHODS

This was a cross-sectional case-control study. In total, 192 patients and 188 healthy controls were enrolled from the Pediatric Diabetes Clinic at King Salman Military Hospital between January 2000 and December 2010. Detailed patients' data recorded while distributing questionnaires to control samples included various gradations of consanguinity and family histories of T1DM and autoimmune disease.

RESULTS

Parental consanguinity was not significantly associated with T1DM; however, children of first-cousin parents showed a higher risk of developing T1DM than did children of second-cousin parents. The presence of a family history of T1DM significantly differed between those with and without T1DM (p < 0.05). No association was observed between a family history of autoimmune disorders and the development of T1DM.

CONCLUSIONS

Parental consanguinity and family history of autoimmunity were not clearly linked to T1DM development in children, indicating that T1DM is a multifactorial disease. A history of affected first-cousin parents increases the risk of T1DM.

Index60 Identifies Individuals at Appreciable Risk for Stage 3 Among an Autoantibody-Positive Population With Normal 2-Hour Glucose Levels: Implications for Current Staging Criteria of Type 1 Diabetes

OBJECTIVE

We assessed whether Index60, a composite measure of fasting C-peptide, 60-min C-peptide, and 60-min glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody-positive (Ab+) individuals with normal 2-h glucose values (<140 mg/dL).

RESEARCH DESIGN AND METHODS

We analyzed 3,058 Type 1 Diabetes TrialNet Pathway to Prevention participants with 2-h glucose <140 mg/dL and Index60 <1.00 values from baseline oral glucose tolerance tests. Characteristics associated with type 1 diabetes (younger age, greater Ab+, higher HLA DR3-DQ2/DR4-DQ8 prevalence, and lower C-peptide) were compared among four mutually exclusive groups: top 2-h glucose quartile only (HI-2HGLU), top Index60 quartile only (HI-IND60), both top quartiles (HI-BOTH), and neither top quartile (LO-BOTH). Additionally, within the 2-h glucose distribution of <140 mg/dL and separately within the Index60 <1.00 distribution, comparisons were made between those above or below the medians.

RESULTS

HI-IND60 and HI-BOTH were younger, with greater frequency of more than two Ab+, and lower C-peptide levels, than either HI-2HGLU or LO-BOTH (all P < 0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than for either HI-2HGLU or LO-BOTH (all P < 0.001). Those with Index60 values above the median were younger and had higher frequency of two or more Ab+ (P < 0.001) and DR3-DQ2/DR4-DQ8 prevalence (P < 0.001) and lower area under the curve (AUC) C-peptide levels (P < 0.001) than those below. Those above the 2-h glucose median had higher AUC C-peptide levels (P < 0.001), but otherwise did not differ from those below.

CONCLUSIONS

Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-h glucose staging criteria.

HOMA2-B enhances assessment of type 1 diabetes risk among TrialNet Pathway to Prevention participants

AIMS/HYPOTHESIS

Methods to identify individuals at highest risk for type 1 diabetes are essential for the successful implementation of disease-modifying interventions. Simple metabolic measures are needed to help stratify autoantibody-positive (Aab+) individuals who are at risk of developing type 1 diabetes. HOMA2-B is a validated mathematical tool commonly used to estimate beta cell function in type 2 diabetes using fasting glucose and insulin. The utility of HOMA2-B in association with type 1 diabetes progression has not been tested.

METHODS

Baseline HOMA2-B values from single-Aab+ (n = 2652; mean age, 21.1 ± 14.0 years) and multiple-Aab+ (n = 3794; mean age, 14.5 ± 11.2 years) individuals enrolled in the TrialNet Pathway to Prevention study were compared. Cox proportional hazard models were used to determine associations between HOMA2-B tertiles and time to progression to type 1 diabetes, with adjustments for age, sex, HLA status and BMI z score. Receiver operating characteristic (ROC) analysis was used to test the association of HOMA2-B with type 1 diabetes development in 1, 2, 5 and 10 years.

RESULTS

At study entry, HOMA2-B values were higher in single- compared with multiple-Aab+ Pathway to Prevention participants (91.1 ± 44.5 vs 83.9 ± 38.9; p < 0.001). Single- and multiple-Aab+ individuals in the lowest HOMA2-B tertile had a higher risk and faster rate of progression to type 1 diabetes. For progression to type 1 diabetes within 1 year, area under the ROC curve (AUC-ROC) was 0.685, 0.666 and 0.680 for all Aab+, single-Aab+ and multiple-Aab+ individuals, respectively. When correlation between HOMA2-B and type 1 diabetes risk was assessed in combination with additional factors known to influence type 1 diabetes progression (insulin sensitivity, age and HLA status), AUC-ROC was highest for the single-Aab+ group's risk of progression at 2 years (AUC-ROC 0.723 [95% CI 0.652, 0.794]).

CONCLUSIONS/INTERPRETATION

These data suggest that HOMA2-B may have utility as a single-time-point measurement to stratify risk of type 1 diabetes development in Aab+ individuals.

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.

β cell responses to inflammation

Background

The extended and clinically silent progression of Type 1 diabetes (T1D) creates a challenge for clinical interventions and for understanding the mechanisms that underlie its pathogenesis. Over the course of the development of Type 1 diabetes, studies in animal models and of human tissues have identified adaptive changes in β cells that may affect their immunogenicity and susceptibility to killing. Loss of β cells has traditionally been identified by impairment in function but environmental factors may affect these measurements.

Scope of Review

In this review we will highlight features of β cell responses to cell death, particularly in the setting of inflammation, and focus on methods of detecting β cell death in vivo.

Major conclusions

We developed an assay to measure β cell death in vivo by detecting cell free DNA with epigenetic modifications of the INS gene that are found in β cells. This assay has robust technical performance and identifies killing in individuals at very high risk for disease, but its ability to identify β cell killing in at-risk relatives is limited by the short half-life of the cell free DNA and the need for repeated sampling over an extended course. We present results from the Diabetes Prevention Trial-1 using this assay. In addition, recent studies have identified cellular adaptations in some β cells that may avoid killing but impair metabolic function. Cells with these characteristics may aggravate the autoimmune response but also may represent a potentially recoverable source of functional β cells.

Changing the landscape for type 1 diabetes: the first step to prevention

Over several decades, studies have described the progression of autoimmune diabetes, from the first appearance of autoantibodies until, and after, the diagnosis of clinical disease with hyperglycaemia and insulin dependence. Despite the improved management of type 1 diabetes with exogenous insulin, most patients do not meet clinical glycaemic goals, and diabetes remains an important medical problem that affects children and adults. Clinical and preclinical studies have suggested strategies to prevent the diagnosis of type 1 diabetes in people at risk, but the outcomes of previous clinical trials have not met their primary endpoints of disease prevention or delay. The results from the TN-10 teplizumab prevention trial show that the diagnosis of type 1 diabetes can be delayed by treatment with a FcR non-binding monoclonal antibody to CD3 in people at high risk for disease. This Series paper discusses how this clinical achievement raises new questions about for whom, and when, immunological strategies might be developed to prevent type 1 diabetes, and how to achieve this goal.

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.

Study of the difficult glycemic control in relation to the presence of diabetes-autoantibodies in a sample of Egyptians with type 1 diabetes

BACKGROUND

T1DM is divided into 1A (immune-mediated), 1B (virus-triggered, genetic and idiopathic). Presence of auto-antibodies may be correlated to glycemic control.

AIM

Assessment relation between the autoantibodies and the poor glycemic control in T1DM.

METHODS

60 patients T1DM 30 males, 30 females, subjected to full history, clinical, anthropometric assessment and laboratory assessment of fasting C-peptide, FBS, 2 h PP glucose, HbA1c, GADA, ICA and IAA level. Classified into two groups; Group I: negative auto-antibodies, Group II: positive auto-antibodies, Group II was further classified into 3 sub-groups, Group II a:1 positive autoantibody, Group II b: 2 positive autoantibodies and Group II c: 3 positive autoantibodies.

RESULTS

HbA1c was significantly higher in group II than group I (11.85 ± 1.61% vs. 8.52 ± 0.41%, p = 0.000). HbA1c was highest in group IIc followed by IIb then IIa (12.25 ± 1.48% vs. 11.57 ± 1.59% vs. 10.78 ± 1.73%, p = 0.038). Total insulin units per day was significantly higher in group II than group I (109.83 ± 7.77 U/day vs. 100.83 ± 1.83 U/day, p = 0.007). Duration of diabetes was significantly higher in group I than group II (10.17 ± 1.94 years vs. 8.11 ± 2.20 years, p = 0.033). HbA1c, total insulin units per day and duration of diabetes were independent predictive factors for presence of autoantibodies (p = 0.007, p = 0.033 and p = 0.043 respectively).

CONCLUSION

Autoantibodies affect the glycemic control presented by high HbA1c; also it causes increase in total insulin units needed by patients; the more autoantibodies, the higher HbA1c, the more insulin units required to control glycemic state.

Biomarker discovery in pre-Type 1 Diabetes; Th40 cells as a predictive risk factor

CONTEXT

The incidence of Type 1 Diabetes (T1D) is increasing worldwide. The quest to understand T1D etiology as well as how to predict diabetes is ongoing and, in many ways, those goals intertwine. While genetic components associate with T1D, not all T1D individuals have those components and not all subjects with those components develop disease.

OBJECTIVE

More robust methods for prediction of T1D are needed. Can high CD4+CD40+ T cell (Th40) levels be used as a biomarker in addition to other markers?

METHODS

Th40 levels were assessed along with other parameters in blood collected from prediabetic TrialNet subjects.

RESULTS

Pre-diabetic subjects, stratified according to their Th40 cell levels, demonstrate patterns that parallel those seen between control and T1D subjects. Cytokine patterns are significantly different between Th40-high and -low subjects and a CD4/CD8 double-positive population is more represented in Th40-high groups. Subjects experiencing impaired glucose tolerance present a significantly higher Th40 level than control subjects do. HLA DR4/DR4 and DQ8/DQ8, HLAs associated with T1D, are more likely found among Th40-high subjects. Interestingly, HLA DR4/DR4 subjects were significantly older compared with all other subjects, suggesting that this haplotype together with a high Th40 level may represent someone who will onset after age 30, which is reported for 42% of T1D cases.

CONCLUSION

Considering the differences found in relation to prediabetic Th40 cell level, it may be possible to devise methods that more accurately predicts who will proceed toward diabetes and, possibly, at what stage of prediabetes a subject is.

Soluble Antigen Arrays for Selective Desensitization of Insulin-Reactive B Cells

Autoimmune diseases are believed to be highly dependent on loss of immune tolerance to self-antigens. Currently, no treatments have been successful clinically in inducing autoantigen-specific tolerance, including efforts to utilize antigen-specific immunotherapy (ASIT) to selectively correct the aberrant autoimmunity. Soluble antigen arrays (SAgAs) represent a novel autoantigen delivery system composed of a linear polymer, hyaluronic acid (HA), displaying multiple copies of conjugated autoantigen. We have previously reported that soluble antigen arrays displaying proteolipid peptide (SAgA_PLP) induced tolerance to this specific multiple sclerosis (MS) autoantigen. Utilizing SAgA technology, we have developed a new ASIT as a possible type 1 diabetes (T1D) therapeutic by conjugating human insulin to HA, known as soluble antigen array insulin (SAgA_Ins). Three types were synthesized, low valency _lvSAgA_Ins (2 insulins per HA), medium valency _mvSAgA_Ins (4 insulins per HA), and, high valency _hvSAgA_Ins (9 insulins per HA), to determine if valency differentially modulates the ex vivo activity of insulin-binding B cells (IBCs). Extensive biophysical characterization was performed for the SAgA molecules. SAgA_Ins molecules were successfully used to affect the biologic activity of IBCs by inducing desensitization of the B cell antigen receptors (BCR). SAgA_Ins bound specifically to insulin-reactive B cells without blocking epitopes recognized by antibodies against the Fc regions of membrane immunoglobulin or CD79 transducer components of the BCR. Preincubation of IBCs (125Tg) with SAgA_Ins, but not HA alone, rendered the IBCs refractory to restimulation. SAgA_Ins induced a decrease in BCR expression and IP3R-mediated intracellular calcium release. Surprisingly, SAgA_Ins binding to BCR on the surface of IBCs induced the observed effects at both high and low SAgA_Ins valency. Future studies aim to test the effects of SAgA_Ins on disease progression in the VH125.NOD mouse model of T1D.

Oxidative Modifications in Tissue Pathology and Autoimmune Disease

SIGNIFICANCE

Various autoimmune syndromes are characterized by abnormalities found at the level of tissues and cells, as well as by microenvironmental influences, such as reactive oxygen species (ROS), that alter intracellular metabolism and protein expression. Moreover, the convergence of genetic, epigenetic, and even environmental influences can result in B and T lymphocyte autoimmunity and tissue pathology. Recent Advances: This review describes how oxidative stress to cells and tissues may alter post-translational protein modifications, both directly and indirectly, as well as potentially lead to aberrant gene expression. For example, it has been clearly observed in many systems how oxidative stress directly amplifies carbonyl protein modifications. However, ROS also lead to a number of nonenzymatic spontaneous modifications including deamidation and isoaspartate modification as well as to enzyme-mediated citrullination of self-proteins. ROS have direct effects on DNA methylation, leading to influences in gene expression, chromosome inactivation, and the silencing of genetic elements. Finally, ROS can alter many other cellular pathways, including the initiation of apoptosis and NETosis, triggering the release of modified intracellular autoantigens.

CRITICAL ISSUES

This review will detail specific post-translational protein modifications, the pathways that control autoimmunity to modified self-proteins, and how products of ROS may be important biomarkers of tissue pathogenesis.

FUTURE DIRECTIONS

A clear understanding of the many pathways affected by ROS will lead to potential therapeutic manipulations to alter the onset and/or progression of autoimmune disease.

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.

β Cell dysfunction exists more than 5 years before type 1 diabetes diagnosis

BACKGROUND

The duration and patterns of β cell dysfunction during type 1 diabetes (T1D) development have not been fully defined.

METHODS

Metabolic measures derived from oral glucose tolerance tests (OGTTs) were compared between autoantibody-positive (aAb+) individuals followed in the TrialNet Pathway to Prevention study who developed diabetes after 5 or more years or less than 5 years of longitudinal follow-up (Progressors≥5, n = 75; Progressors<5, n = 474) and 144 aAb-negative (aAb-) relatives.

RESULTS

Mean age at study entry was 15.0 ± 12.6 years for Progressors≥5; 12.0 ± 9.1 for Progressors<5; and 16.3 ± 10.4 for aAb- relatives. At baseline, Progressors≥5 already exhibited significantly lower fasting C-peptide (P < 0.01), C-peptide AUC (P < 0.001), and early C-peptide responses (30- to 0-minute C-peptide; P < 0.001) compared with aAb- relatives, while 2-hour glucose (P = 0.03), glucose AUC (<0.001), and Index60 (<0.001) were all higher. Despite significant baseline impairment, metabolic measures in Progressors≥5 were relatively stable until 2 years prior to T1D diagnosis, when there was accelerated C-peptide decline and rising glycemia from 2 years until diabetes diagnosis. Remarkably, patterns of progression within 3 years of diagnosis were nearly identical between Progressors≥5 and Progressors<5.

CONCLUSION

These data provide insight into the chronicity of β cell dysfunction in T1D and indicate that β cell dysfunction may precede diabetes diagnosis by more than 5 years in a subset of aAb+ individuals. Even among individuals with varying lengths of aAb positivity, our findings indicate that patterns of metabolic decline are uniform within the last 3 years of progression to T1D.

TRIAL REGISTRATION

Clinicaltrials.gov NCT00097292.

FUNDING

The Type 1 Diabetes TrialNet Study Group is a clinical trials network currently funded by the NIH through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, and The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Juvenile Diabetes Research Foundation.

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.

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.

Increasing ICA512 autoantibody titers predict development of abnormal oral glucose tolerance tests

OBJECTIVE

Determine if autoantibody titer magnitude and variability predict glucose abnormalities in subjects at risk for type 1 diabetes.

RESEARCH DESIGNS AND METHODS

Demographic information, longitudinal autoantibody titers, and oral glucose tolerance test (OGTT) data were obtained from the TrialNet Pathway to Prevention study. Subjects (first and second degree relatives of individuals with type 1 diabetes) with at least 2 diabetes autoantibodies were selected for analysis. Autoantibody titer means were calculated for each subject for the duration of study participation and the relationship between titer tertiles and glucose value tertiles from OGTTs (normal, impaired, and diabetes) was assessed with a proportional odds ordinal regression model. A matched pairs analysis was used to examine the relationship between changes in individual autoantibody titers and 120-minute glucose values. Titer variability was quantified using cumulative titer standard deviations.

RESULTS

We studied 778 subjects recruited in the TrialNet Pathway to Prevention study between 2006 and 2014. Increased cumulative mean titer values for both ICA512 and GAD65 (estimated increase in proportional odds = 1.61, 95% CI = 1.39, 1.87, P < 1 × 10^-9 and 1.17, 95% CI = 1.03, 1.32, P = .016, respectively) were associated with peak 120-minute glucose values. While fluctuating titer levels were observed in some subjects, no significant relationship between titer standard deviation and glucose values was observed.

CONCLUSION

ICA512 autoantibody titers associate with progressive abnormalities in glucose metabolism in subjects at risk for type 1 diabetes. Fluctuations in autoantibody titers do not correlate with lower rates of progression to clinical disease.

The Role of Age and Excess Body Mass Index in Progression to Type 1 Diabetes in At-Risk Adults

Background

Given the global rise in both type 1 diabetes incidence and obesity, the role of body mass index (BMI) on type 1 diabetes pathophysiology has gained great interest. Sustained excess BMI in pediatric participants of the TrialNet Pathway to Prevention (PTP) cohort increased risk for progression to type 1 diabetes, but the effects of age and obesity in adults remain largely unknown.

Objective

To determine the effect of age and sustained obesity on the risk for type 1 diabetes in adult participants in the TrialNet PTP cohort (i.e., nondiabetic autoantibody-positive relatives of patients with type 1 diabetes).

Research Design and Methods

Longitudinally accumulated BMI >25 kg/m2 was calculated to generate a cumulative excess BMI (ceBMI) for each participant, with ceBMI values ≥0 kg/m2 and ≥5 kg/m2 representing sustained overweight or obese status, respectively. Recursive partitioning analysis yielded sex- and age-specific thresholds for ceBMI that confer the greatest risk for type 1 diabetes progression.

Results

In this cohort of 665 adults (age 20 to 50 years; median follow-up, 3.9 years), 49 participants developed type 1 diabetes. Age was an independent protective factor for type 1 diabetes progression (hazard ratio, 0.95; P = 0.008), with a threshold of >35 years that reduced risk for type 1 diabetes. In men age >35 years and women age <35 years, sustained obesity (ceBMI ≥5 kg/m2) increased the risk for type 1 diabetes.

Conclusions

Age is an important factor for type 1 diabetes progression in adults and influences the impact of elevated BMI, indicating an interplay of excess weight, age, and sex in adult type 1 diabetes pathophysiology.

Have we pushed the needle for treatment of Type 1 diabetes?

Studies with immunologics have shown that the natural history of Type 1 diabetes can be modified. These studies have targeted key mediators of the disease and recent analyses, together with studies in preclinical models have identified mechanisms that may be involved in the clinical effects. Several issues remain including specificity of the interventions, adverse effects of the treatments, and duration of their effects. Future studies are likely to include more specific approaches with agents such as cell therapies with selected immune regulatory subsets, antigen specific therapies, and combinations of agents with complementary mechanisms of activity.

B cells in type 1 diabetes mellitus and diabetic kidney disease

Type 1 diabetes mellitus (T1DM) is an autoimmune disorder that affects an estimated 30 million people worldwide. It is characterized by the destruction of pancreatic β cells by the immune system, which leads to lifelong dependency on exogenous insulin and imposes an enormous burden on patients and health-care resources. T1DM is also associated with an increased risk of comorbidities, such as cardiovascular disease, retinopathy, and diabetic kidney disease (DKD), further contributing to the burden of this disease. Although T cells are largely considered to be responsible for β-cell destruction in T1DM, increasing evidence points towards a role for B cells in disease pathogenesis. B cell-depletion, for example, delays disease progression in patients with newly diagnosed T1DM. Loss of tolerance of islet antigen-reactive B cells occurs early in disease and numbers of pancreatic CD20⁺ B cells correlate with β-cell loss. Although the importance of B cells in T1DM is increasingly apparent, exactly how these cells contribute to disease and its comorbidities, such as DKD, is not well understood. Here we discuss the role of B cells in the pathogenesis of T1DM and how these cells are activated during disease development. Finally, we speculate on how B cells might contribute to the development of DKD.

Understanding and preventing type 1 diabetes through the unique working model of TrialNet

Type 1 diabetes is an autoimmune disease arising from the destruction of pancreatic insulin-producing beta cells. The disease represents a continuum, progressing sequentially at variable rates through identifiable stages prior to the onset of symptoms, through diagnosis and into the critical periods that follow, culminating in a variable depth of beta cell depletion. The ability to identify the very earliest of these presymptomatic stages has provided a setting in which prevention strategies can be trialled, as well as furnishing an unprecedented opportunity to study disease evolution, including intrinsic and extrinsic initiators and drivers. This niche opportunity is occupied by Type 1 Diabetes TrialNet, an international consortium of clinical trial centres that leads the field in intervention and prevention studies, accompanied by deep longitudinal bio-sampling. In this review, we focus on discoveries arising from this unique bioresource, comprising more than 70,000 samples, and outline the processes and science that have led to new biomarkers and mechanistic insights, as well as identifying new challenges and opportunities. We conclude that via integration of clinical trials and mechanistic studies, drawing in clinicians and scientists and developing partnership with industry, TrialNet embodies an enviable and unique working model for understanding a disease that to date has no cure and for designing new therapeutic approaches.

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.

Type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM), also known as autoimmune diabetes, is a chronic disease characterized by insulin deficiency due to pancreatic β-cell loss and leads to hyperglycaemia. Although the age of symptomatic onset is usually during childhood or adolescence, symptoms can sometimes develop much later. Although the aetiology of T1DM is not completely understood, the pathogenesis of the disease is thought to involve T cell-mediated destruction of β-cells. Islet-targeting autoantibodies that target insulin, 65 kDa glutamic acid decarboxylase, insulinoma-associated protein 2 and zinc transporter 8 - all of which are proteins associated with secretory granules in β-cells - are biomarkers of T1DM-associated autoimmunity that are found months to years before symptom onset, and can be used to identify and study individuals who are at risk of developing T1DM. The type of autoantibody that appears first depends on the environmental trigger and on genetic factors. The pathogenesis of T1DM can be divided into three stages depending on the absence or presence of hyperglycaemia and hyperglycaemia-associated symptoms (such as polyuria and thirst). A cure is not available, and patients depend on lifelong insulin injections; novel approaches to insulin treatment, such as insulin pumps, continuous glucose monitoring and hybrid closed-loop systems, are in development. Although intensive glycaemic control has reduced the incidence of microvascular and macrovascular complications, the majority of patients with T1DM are still developing these complications. Major research efforts are needed to achieve early diagnosis, prevent β-cell loss and develop better treatment options to improve the quality of life and prognosis of those affected.

Do Electrochemiluminescence Assays Improve Prediction of Time to Type 1 Diabetes in Autoantibody-Positive TrialNet Subjects?

OBJECTIVE

To explore whether electrochemiluminescence (ECL) assays can help improve prediction of time to type 1 diabetes in the TrialNet autoantibody-positive population.

RESEARCH DESIGN AND METHODS

TrialNet subjects who were positive for one or more autoantibodies (microinsulin autoantibody, GAD65 autoantibody [GADA], IA-2A, and ZnT8A) with available ECL-insulin autoantibody (IAA) and ECL-GADA data at their initial visit were analyzed; after a median follow-up of 24 months, 177 of these 1,287 subjects developed diabetes.

RESULTS

Univariate analyses showed that autoantibodies by radioimmunoassays (RIAs), ECL-IAA, ECL-GADA, age, sex, number of positive autoantibodies, presence of HLA DR3/4-DQ8 genotype, HbA1c, and oral glucose tolerance test (OGTT) measurements were all significantly associated with progression to diabetes. Subjects who were ECL positive had a risk of progression to diabetes within 6 years of 58% compared with 5% for the ECL-negative subjects (P < 0.0001). Multivariate Cox proportional hazards models were compared, with the base model including age, sex, OGTT measurements, and number of positive autoantibodies by RIAs. The model with positivity for ECL-GADA and/or ECL-IAA was the best, and factors that remained significantly associated with time to diabetes were area under the curve (AUC) C-peptide, fasting C-peptide, AUC glucose, number of positive autoantibodies by RIAs, and ECL positivity. Adding ECL to the Diabetes Prevention Trial risk score (DPTRS) improved the receiver operating characteristic curves with AUC of 0.83 (P < 0.0001).

CONCLUSIONS

ECL assays improved the ability to predict time to diabetes in these autoantibody-positive relatives at risk for developing diabetes. These findings might be helpful in the design and eligibility criteria for prevention trials in the future.

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

OBJECTIVE

β-Cell autoantibodies are a feature of the preclinical phase of type 1 diabetes. Here, we asked how frequently they revert in a cohort of children at risk for type 1 diabetes and whether reversion has any effect on type 1 diabetes risk.

RESEARCH DESIGN AND METHODS

Children were up to 10 years of age and screened more than once for insulin autoantibody, GAD antibody, and insulinoma antigen-2 antibodies. Persistent autoantibody was defined as an autoantibody present on two or more consecutive visits and confirmed in two reference laboratories. Reversion was defined as two or more consecutive negative visits after persistence. Time-dependent Cox regression was used to examine how reversion modified the risk of development of multiple autoantibodies and type 1 diabetes.

RESULTS

Reversion was relatively frequent for autoantibodies to GAD65 (19%) and insulin (29%), but was largely restricted to children who had single autoantibodies (24%) and rare in children who had developed multiple autoantibodies (<1%). Most (85%) reversion of single autoantibodies occurred within 2 years of seroconversion. Reversion was associated with HLA genotype, age, and decreasing titer. Children who reverted from single autoantibodies to autoantibody negative had, from birth, a risk for type 1 diabetes of 0.14 per 100 person-years; children who never developed autoantibodies, 0.06 per 100 person-years; and, children who remained single-autoantibody positive, 1.8 per 100 person-years.

CONCLUSIONS

Type 1 diabetes risk remained high in children who had developed multiple β-cell autoantibodies even when individual autoantibodies reverted. We suggest that monitoring children with single autoantibodies for at least 1 year after seroconversion is beneficial for stratification of type 1 diabetes risk.

Insulitis in the pathogenesis of type 1 diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disease in which autoreactive T-cells and inflammation cause severe loss of pancreatic beta cells. Insulitis, the pathologic hallmark of T1D, is an inflammatory lesion consisting of immune cell infiltrates around and within the islets. New research initiatives and methodologies are advancing our understanding of pancreas pathology. Studies have revealed the predominant cellular types that infiltrate the islets, novel molecular aspects associated with insulitis, and the coexistence of additional pathological abnormalities. While insulitis is a critical element of T1D pathology and pathogenesis, it is typically present only in a modest proportion of islets at any given time, even at diagnosis, with overall limited relation to disease duration. Thus, the relative importance of insulitis as a determining factor of diabetes symptoms at disease onset appears to have been overestimated; growing evidence also shows that beta cell loss at diagnosis is more modest than previously thought. Thus, the sole targeting of the immune system may not afford full therapeutic efficacy if dysfunction affects beta cells that are not under immune attack and this is a key contributor to symptoms. Combination therapies that promote both immunoregulation and address beta cell dysfunction should be more effective in treating this chronic disease process. It remains a major goal to clarify the relation of insulitis with the dynamics of beta cell loss and coexisting mechanisms of dysfunction, according to clinical stage; such improved understanding is key to design therapeutic strategies that target multiple pathogenic mechanisms.

ECL-IAA and ECL-GADA Can Identify High-Risk Single Autoantibody-Positive Relatives in the TrialNet Pathway to Prevention Study

BACKGROUND

Relatives with single positive islet autoantibodies have a much lower risk of progression to diabetes than those with multiple autoantibodies.

MATERIALS AND METHODS

TrialNet subjects positive for single autoantibody to insulin (mIAA) (n = 50) or single autoantibody to glutamic acid decarboxylase (GADA) (n = 50) were analyzed using new electrochemiluminescence (ECL) assays (ECL-IAA and ECL-GADA, respectively) at their initial visit and longitudinally over time. Affinity assays were performed on a subset of single autoantibody-positive subjects at initial and most recent visits.

RESULTS

After a mean follow-up of 5.3 years, 20 subjects developed type 1 diabetes. Among either single GADA or single mIAA subjects, those who were positive in the ECL assay showed higher affinity at the initial visit, and affinity results stayed consistent over time. No converting events from low to high or high to low affinity were seen over time.

CONCLUSIONS

Confirmed positivity for ECL is associated with high affinity and can help staging of risk for type 1 diabetes in single autoantibody-positive subjects.

The relationship between BMI and insulin resistance and progression from single to multiple autoantibody positivity and type 1 diabetes among TrialNet Pathway to Prevention participants

AIMS/HYPOTHESIS

The incidence of type 1 diabetes is increasing at a rate of 3-5% per year. Genetics cannot fully account for this trend, suggesting an influence of environmental factors. The accelerator hypothesis proposes an effect of metabolic factors on type 1 diabetes risk. To test this in the TrialNet Pathway to Prevention (PTP) cohort, we analysed the influence of BMI, weight status and insulin resistance on progression from single to multiple islet autoantibodies (Aab) and progression from normoglycaemia to diabetes.

METHODS

HOMA1-IR was used to estimate insulin resistance in Aab-positive PTP participants. Cox proportional hazards models were used to evaluate the effects of BMI, BMI percentile (BMI%), weight status and HOMA1-IR on the progression of autoimmunity or the development of diabetes.

RESULTS

Data from 1,310 single and 1,897 multiple Aab-positive PTP participants were included. We found no significant relationships between BMI, BMI%, weight status or HOMA1-IR and the progression from one to multiple Aabs. Similarly, among all Aab-positive participants, no significant relationships were found between BMI, weight status or HOMA1-IR and progression to diabetes. Diabetes risk was modestly increased with increasing BMI% among the entire cohort, in obese participants 13-20 years of age and with increasing HOMA1-IR in adult Aab-positive participants.

CONCLUSIONS/INTERPRETATION

Analysis of the accelerator hypothesis in the TrialNet PTP cohort does not suggest a broad influence of metabolic variables on diabetes risk. Efforts to identify other potentially modifiable environmental factors should continue.

HLA-G 14-bp polymorphism affects the age of onset in Type I Diabetes Mellitus

Type I diabetes mellitus (T1DM) is an organ-specific autoimmune disorder affecting the insulin-producing pancreatic cells. T1DM genetic association studies have so far revealed the involvement of more than 40 loci, with particularly strong associations for the human leucocyte antigens (HLA). Further to the well-established HLA class II associations, the immunomodulatory elements in the telomeric major histocompatibility complex locus, specifically nonclassical HLA class I, were also associated with T1DM, either in conferring susceptibility or by contributing to the overall pathogenesis. This study investigates the involvement of a 14-bp deletion polymorphism (rs371194629) at the 3' untranslated region of HLA-G in the context of T1DM and age of onset. The frequency of the polymorphism was determined in unrelated T1DM Cypriot patients and findings that emerge from this study show a strong association between the HLA-G 14-bp polymorphism and T1DM with respect to the age of onset. Specifically, the deletion/deletion (DEL/DEL) genotype was found to be associated with an early age of onset (P = 0.001), while the presence of the insertion allele (INS) was associated to a later age of onset (P = 0.0001), portraying a possible dominant effect over the deletion allele, a role in delaying disease onset and an overall involvement of HLA-G in the pathogenesis of type I diabetes mellitus.

HLA-DRB1*15:01-DQA1*01:02-DQB1*06:02 Haplotype Protects Autoantibody-Positive Relatives From Type 1 Diabetes Throughout the Stages of Disease Progression

The HLA-DRB1*15:01-DQA1*01:02-DQB1*06:02 haplotype is linked to protection from the development of type 1 diabetes (T1D). However, it is not known at which stages in the natural history of T1D development this haplotype affords protection. We examined a cohort of 3,358 autoantibody-positive relatives of T1D patients in the Pathway to Prevention (PTP) Study of the Type 1 Diabetes TrialNet. The PTP study examines risk factors for T1D and disease progression in relatives. HLA typing revealed that 155 relatives carried this protective haplotype. A comparison with 60 autoantibody-negative relatives suggested protection from autoantibody development. Moreover, the relatives with DRB1*15:01-DQA1*01:02-DQB1*06:02 less frequently expressed autoantibodies associated with higher T1D risk, were less likely to have multiple autoantibodies at baseline, and rarely converted from single to multiple autoantibody positivity on follow-up. These relatives also had lower frequencies of metabolic abnormalities at baseline and exhibited no overall metabolic worsening on follow-up. Ultimately, they had a very low 5-year cumulative incidence of T1D. In conclusion, the protective influence of DRB1*15:01-DQA1*01:02-DQB1*06:02 spans from autoantibody development through all stages of progression, and relatives with this allele only rarely develop T1D.

Risk Factors for Type 1 Diabetes Recurrence in Immunosuppressed Recipients of Simultaneous Pancreas-Kidney Transplants

Patients with type 1 diabetes (T1D) who are recipients of pancreas transplants are believed to rarely develop T1D recurrence in the allograft if effectively immunosuppressed. We evaluated a cohort of 223 recipients of simultaneous pancreas-kidney allografts for T1D recurrence and its risk factors. With long-term follow-up, recurrence was observed in approximately 7% of patients. Comparing the therapeutic regimens employed in this cohort over time, lack of induction therapy was associated with recurrence, but this occurs even with the current regimen, which includes induction; there was no influence of maintenance regimens. Longitudinal testing for T1D-associated autoantibodies identified autoantibody positivity, number of autoantibodies, and autoantibody conversion after transplantation as critical risk factors. Autoantibodies to the zinc transporter 8 had the strongest and closest temporal association with recurrence, which was not explained by genetically encoded amino acid sequence donor-recipient mismatches for this autoantigen. Genetic risk factors included the presence of the T1D-predisposing HLA-DR3/DR4 genotype in the recipient and donor-recipient sharing of HLA-DR alleles, especially HLA-DR3. Thus, T1D recurrence is not uncommon and is developing in patients treated with current immunosuppression. The risk factors identified in this study can be assessed in the transplant clinic to identify recurrent T1D and may lead to therapeutic advances.

Can we prevent type 1 diabetes?

Type 1 diabetes (T1D) affects 1.93 in 1000 youth in the USA. Over the last 40 years, a combination of genetic and immunological markers has been developed allowing for the accurate prediction of progression to T1D. Despite our abilities to predict disease and the marked improvement in our understanding of the natural history of T1D, therapies capable of preventing or reversing T1D remain elusive. This article will review recent and ongoing efforts to understand the causes of T1D and related efforts to study potential therapies aimed at preventing T1D.

Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association

Insights from prospective, longitudinal studies of individuals at risk for developing type 1 diabetes have demonstrated that the disease is a continuum that progresses sequentially at variable but predictable rates through distinct identifiable stages prior to the onset of symptoms. Stage 1 is defined as the presence of β-cell autoimmunity as evidenced by the presence of two or more islet autoantibodies with normoglycemia and is presymptomatic, stage 2 as the presence of β-cell autoimmunity with dysglycemia and is presymptomatic, and stage 3 as onset of symptomatic disease. Adoption of this staging classification provides a standardized taxonomy for type 1 diabetes and will aid the development of therapies and the design of clinical trials to prevent symptomatic disease, promote precision medicine, and provide a framework for an optimized benefit/risk ratio that will impact regulatory approval, reimbursement, and adoption of interventions in the early stages of type 1 diabetes to prevent symptomatic disease.

Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation

Recognizing an increasing need for biomarkers that predict clinical outcomes in type 1 diabetes (T1D), JDRF, a major funding organization for T1D research, recently instituted the Core for Assay Validation (CAV) to accelerate the translation of promising assays from discovery to clinical implementation via a process of coordinated evaluation of biomarkers. In this model, the CAV facilitates the validation of candidate assay methods as well as qualification of proposed biomarkers for a specific clinical use in well-characterized patients. We describe here a CAV-driven pilot project aimed at identifying biomarkers that predict the rate of decline in beta cell function after diagnosis. In a formalized pipeline, candidate assays are first assessed for general rationale, technical precision, and biological associations in a cross-sectional cohort. Those with the most favorable characteristics are then applied to placebo arm subjects of T1D intervention trials to assess their predictive correlation with beta cell function. We outline a go/no-go process for advancing candidate assays in a defined qualification pipeline that also allows for the discovery of novel predictive biomarker combinations. This strategy could be a model for other collaborative biomarker development efforts in and beyond T1D.

β cell death and dysfunction during type 1 diabetes development in at-risk individuals

Role of the funding source: Funding from the NIH was used for support of the participating clinical centers and the coordinating center. The funding source did not participate in the collection or the analysis of the data.

BACKGROUND

The β cell killing that characterizes type 1 diabetes (T1D) is thought to begin years before patients present clinically with metabolic decompensation; however, this primary pathologic process of the disease has not been measured.

METHODS

Here, we measured β cell death with an assay that detects β cell-derived unmethylated insulin (INS) DNA. Using this assay, we performed an observational study of 50 participants from 2 cohorts at risk for developing T1D from the TrialNet Pathway to Prevention study and of 4 subjects who received islet autotransplants.

RESULTS

In at-risk subjects, those who progressed to T1D had average levels of unmethylated INS DNA that were elevated modestly compared with those of healthy control subjects. In at-risk individuals that progressed to T1D, the observed increases in unmethylated INS DNA were associated with decreases in insulin secretion, indicating that the changes in unmethylated INS DNA are indicative of β cell killing. Subjects at high risk for T1D had levels of unmethylated INS DNA that were higher than those of healthy controls and higher than the levels of unmethylated INS DNA in the at-risk progressor and at-risk nonprogressor groups followed for 4 years. Evaluation of insulin secretory kinetics also distinguished high-risk subjects who progressed to overt disease from those who did not.

CONCLUSION

We conclude that a blood test that measures unmethylated INS DNA serves as a marker of active β cell killing as the result of T1D-associated autoimmunity. Together, the data support the concept that β cell killing occurs sporadically during the years prior to diagnosis of T1D and is more intense in the peridiagnosis period.

TRIAL REGISTRATION

Clinicaltrials.gov NCT00097292.

FUNDING

Funding was from the NIH, the Juvenile Diabetes Research Foundation, and the American Diabetes Association.

Neuronal T-cell autoreactivity is amplified in overweight children with new-onset insulin-requiring diabetes

OBJECTIVE

Disease-associated T-cell autoreactivities are seen in most type 1 diabetic patients and are thought to emerge before islet autoantibodies, but host factors that impact autoimmune elements remain uncertain. We assessed if adiposity and measures of insulin sensitivity impact T- and B-cell autoimmunity in children with insulin-requiring diabetes.

RESEARCH DESIGN AND METHODS

Insulin-requiring children and adolescents diagnosed between January 2004 and June 2008 were studied (n = 261): age 9.7 ± 4 years, 92% white, and 60% male. T-cell responses to 10 diabetes-associated antigens, β-cell autoantibodies (GADA, IA-2A, IAA, and ICA), BMI z score (BMIz), and waist percentile were measured at onset and 3 months later.

RESULTS

All but one subject had either T- or B-cell autoimmunity. Diabetes-associated T-cell autoreactivities were found in 92% of subjects. Higher amplitude T-cell autoreactivities to neuronal diabetes-associated autoantigens were seen in those with the highest BMIz quintile, BMI ≥85th percentile (P < 0.05), and waist circumference ≥85th percentile (P < 0.05). There were no relationships between the number of T-cell reactivities or T-cell diversity with adiposity measures or autoantibody number or type. Patients with positive T-cell reactivities but without autoantibodies had the highest BMIz (P = 0.006).

CONCLUSIONS

Our observations link obesity and diabetes-related autoimmunity, suggesting an amplification of neuronal T-cell autoimmunity associated with adiposity and/or insulin resistance, with obesity-related inflammation possibly enhancing islet autoimmunity.

B cells and type 1 diabetes ...in mice and men

Nearly 70% of newly produced B cells express autoreactive antigen receptors and must be silenced to prevent autoimmunity. Failure of silencing mechanisms is apparent in type 1 diabetes (T1D), where islet antigen-specific B cells appear critical for development of disease. Evidence for a B cell role in T1D includes success of B cell targeted anti-CD20 therapy, which delays T1D progression in both NOD mice and new onset patients. Demonstrating the importance of specificity, NOD mice whose B cell repertoire is biased toward insulin reactivity show increased disease development, while bias away from insulin reactivity largely prevents disease. Finally, though not required for illness, high affinity insulin autoantibodies are often the first harbingers of T1D. B cell cytokine production and auto-antigen presentation to self-reactive T cells are likely important in pathogenesis. Here we review B cell function, as described above, in T1D in humans and the non-obese diabetic (NOD) mouse. We will discuss recent broad-based B cell depletion studies and how they may provide the basis for refinement of future treatments for the disorder.

Role of B lymphocytes in the pathogenesis of type 1 diabetes

Though type 1 diabetes (T1D) is considered a T cell-mediated autoimmune disorder, recent evidence indicates that B cells play a critical role in disease. This conclusion is based in part on the success of anti-CD20 (rituximab) therapy, which by broadly depleting B cells delays disease progression in non-obese diabetic (NOD) mice and new-onset patients. B cell receptor (BCR) specificity to islet autoantigen is key. NOD mice whose B cell repertoire is biased toward insulin reactivity show increased disease development, while bias away from insulin reactivity largely prevents disease. Although the operative disease-promoting B cell effector function remains undefined, islet-antigen reactive B cells function in antigen presentation to diabetogenic CD4 T cells. Other studies implicate B cells in antigen presentation to CD8 T cells. B cell participation in TID appears predicated on faulty B cell tolerance. Here, we review extant findings implicating B cells in T1D in mice and men.

The multiple origins of Type 1 diabetes

It is widely accepted that Type 1 diabetes is a complex disease. Genetic predisposition and environmental factors favour the triggering of autoimmune responses against pancreatic β-cells, eventually leading to β-cell destruction. Over 40 susceptibility loci have been identified, many now mapped to known genes, largely supporting a dominant role for an immune-mediated pathogenesis. This role is also supported by the identification of several islet autoantigens and antigen-specific responses in patients with recent onset diabetes and subjects with pre-diabetes. Increasing evidence suggests certain viruses as a common environmental factor, together with diet and the gut microbiome. Inflammation and insulin resistance are emerging as additional cofactors, which might be interrelated with environmental factors. The heterogeneity of disease progression and clinical manifestations is likely a reflection of this multifactorial pathogenesis. So far, clinical trials have been mostly ineffective in delaying progression to overt diabetes in relatives at increased risk, or in reducing further loss of insulin secretion in patients with new-onset diabetes. This limited success may reflect, in part, our incomplete understanding of key pathogenic mechanisms, the lack of truly robust biomarkers of both disease activity and β-cell destruction, and the inability to assess the relative contributions of various pathogenic mechanisms at various time points during the course of the natural history of Type 1 diabetes. Emerging data and a re-evaluation of histopathological, immunological and metabolic findings suggest the hypothesis that unknown mechanisms of β-cell dysfunction may be present at diagnosis, and may contribute to the development of hyperglycaemia and clinical symptoms.

Network for Pancreatic Organ Donors with Diabetes (nPOD): developing a tissue biobank for type 1 diabetes

BACKGROUND

The Network for Pancreatic Organ Donors with Diabetes (nPOD) was established to recover and characterize pancreata and related organs from cadaveric organ donors with various risk levels for type 1 diabetes (T1D). These biospecimens are available to investigators for collaborative studies aimed at addressing questions related to T1D natural history and pathogenesis.

RESEARCH DESIGN AND METHODS

Organ donors included T1D patients (new onset to long term), non-diabetic autoantibody-positive subjects, non-diabetic controls and individuals with disorders relevant to β-cell function. Pancreas recovery and transport met transplant-grade criteria. Additional samples recovered included serum, whole blood, spleen and pancreatic and non-pancreatic lymph nodes. Biospecimens were processed for cryopreserved cells, fixed paraffin and fresh frozen blocks and snap frozen samples. T1D autoantibodies, C-peptide levels and high-resolution HLA genotyping for risk alleles were also determined.

RESULTS

Over 160 donors have been enrolled (ages of 1 day to >90 years). Standard operating procedures were established along with a quality management system. Donor demographics, laboratory assays and histopathological characterizations were shared through an open online informatics system. Biospecimens were distributed to more than 60 investigators.

CONCLUSIONS

The nPOD programme provides access to high quality biospecimens without cost to investigators. Collaborations and open data sharing are emphasized to maximize research potential of each donor. On the basis of initial successes, the nPOD programme is expanding to recover additional organs relevant to T1D pathogenesis and complications from European countries (PanFin network).

An important minority of prediabetic first-degree relatives of type 1 diabetic patients derives from seroconversion to persistent autoantibody positivity after 10 years of age

AIMS/HYPOTHESIS

The appearance of autoantibodies (Abs) before diabetes onset has mainly been studied in young children. However, most patients develop type 1 diabetes after the age of 15 years. In first-degree relatives aged under 40 years, we investigated the frequency of seroconversion to (persistent) Ab positivity, progression to diabetes and baseline characteristics of seroconverters according to age.

METHODS

Abs against insulin (IAA), glutamate decarboxylase (GADA), insulinoma-associated protein 2 (IA-2A) and zinc transporter 8 (ZnT8A) were measured during follow-up of 7,170 first-degree relatives.

RESULTS

We identified 379 (5.3%) relatives with positivity for IAA, GADA, IA-2A and/or ZnT8A (Ab(+)) at first sampling and 224 (3.1%) at a later time point. Most seroconversions occurred after the age of 10 years (63%). During follow-up, Abs persisted more often in relatives initially Ab(+) (76%) than in seroconverters (53%; p < 0.001). In both groups diabetes developed at a similar pace and almost exclusively with Ab persistence (136 of 139 prediabetic individuals). For both groups, progression was more rapid if Abs appeared before the age of 10 years. Baseline characteristics at seroconversion did not vary significantly according to age.

CONCLUSIONS/INTERPRETATION

Seroconversion to (persistent) Ab(+) occurs regardless of age. Although the progression rate to diabetes is higher under age 10 years, later seroconverters (up to age 40 years) have similar characteristics when compared with age-matched initially Ab(+) relatives and generate an important minority of prediabetic relatives, warranting their identification and, eventually, enrolment in prevention trials.