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

OBJECTIVE: To characterize distinct islet autoantibody profiles preceding stage 3 type 1 diabetes. RESEARCH DESIGN AND METHODS: The T1DI (Type 1 Diabetes Intelligence) study combined data from 1,845 genetically susceptible prospectively observed children who were positive for at least one islet autoantibody: insulin autoantibody (IAA), GAD antibody (GADA), or islet antigen 2 antibody (IA-2A). Using a novel similarity algorithm that considers an individual's temporal autoantibody profile, age at autoantibody appearance, and variation in the positivity of autoantibody types, we performed an unsupervised hierarchical clustering analysis. Progression rates to diabetes were analyzed via survival analysis. RESULTS: We identified five main clusters of individuals with distinct autoantibody profiles characterized by seroconversion age and sequence of appearance of the three autoantibodies. The highest 5-year risk from first positive autoantibody to type 1 diabetes (69.9%; 95% CI 60.0-79.2) was observed in children who first developed IAA in early life (median age 1.6 years) followed by GADA (1.9 years) and then IA-2A (2.1 years). Their 10-year risk was 89.9% (95% CI 81.9-95.4). A high 5-year risk was also found in children with persistent IAA and GADA (39.1%) and children with persistent GADA and IA-2A (30.9%). A lower 5-year risk (10.5%) was observed in children with a late appearance of persistent GADA (6.1 years). The lowest 5-year diabetes risk (1.6%) was associated with positivity for a single, often reverting, autoantibody. CONCLUSIONS: The novel clustering algorithm identified children with distinct islet autoantibody profiles and progression rates to diabetes. These results are useful for prediction, selection of individuals for prevention trials, and studies investigating various pathways to type 1 diabetes.

Infection episodes and islet autoantibodies in children at increased risk for type 1 diabetes before and during the COVID-19 pandemic.

OBJECTIVES: To determine the impact of the COVID-19 pandemic on the incidence rates of infection and islet autoimmunity in children at risk for type 1 diabetes. METHODS: 1050 children aged 4 to 7 months with an elevated genetic risk for type 1 diabetes were recruited from Germany, Poland, Sweden, Belgium and the UK. Reported infection episodes and islet autoantibody development were monitored until age 40 months from February 2018 to February 2023. RESULTS: The overall infection rate was 311 (95% Confidence Interval [CI], 304-318) per 100 person years. Infection rates differed by age, country, family history of type 1 diabetes, and period relative to the pandemic. Total infection rates were 321 per 100 person-years (95% CI 304-338) in the pre-pandemic period (until February 2020), 160 (95% CI 148-173) per 100 person-years in the first pandemic year (March 2020-February 2021; P < 0.001) and 337 (95% CI 315-363) per 100 person-years in subsequent years. Similar trends were observed for respiratory and gastrointestinal infections. Islet autoantibody incidence rates were 1.6 (95% CI 1.0-2.4) per 100 person-years in the pre-pandemic period, 1.2 (95% CI 0.8-1.9) per 100 person-years in the first pandemic year (P = 0.46), and 3.4 (95% CI 2.3-4.8) per 100 person-years in subsequent years (P = 0.005 vs. pre-pandemic year; P < 0.001 vs. first pandemic year). CONCLUSIONS: The COVID-19 pandemic was associated with significantly altered infection patterns. Islet autoantibody incidence rates increased two-fold when infection rates returned to pre-pandemic levels.

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

BACKGROUND: Two or more autoantibodies against either insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A) or zinc transporter 8 (ZnT8A) denote stage 1 (normoglycemia) or stage 2 (dysglycemia) type 1 diabetes prior to stage 3 type 1 diabetes. Automated multiplex Antibody Detection by Agglutination-PCR (ADAP) assays in two laboratories were compared to single plex radiobinding assays (RBA) to define threshold levels for diagnostic specificity and sensitivity. METHODS: IAA, GADA, IA-2A and ZnT8A were analysed in 1504 (54% females) population based controls (PBC), 456 (55% females) doctor's office controls (DOC) and 535 (41% females) blood donor controls (BDC) as well as in 2300 (48% females) patients newly diagnosed (1-10 years of age) with stage 3 type 1 diabetes. The thresholds for autoantibody positivity were computed in 100 10-fold cross-validations to separate patients from controls either by maximizing the χ2-statistics (chisq) or using the 98th percentile of specificity (Spec98). Mean and 95% CI for threshold, sensitivity and specificity are presented. FINDINGS: The ADAP ROC curves of the four autoantibodies showed comparable AUC in the two ADAP laboratories and were higher than RBA. Detection of two or more autoantibodies using chisq showed 0.97 (0.95, 0.99) sensitivity and 0.94 (0.91, 0.97) specificity in ADAP compared to 0.90 (0.88, 0.95) sensitivity and 0.97 (0.94, 0.98) specificity in RBA. Using Spec98, ADAP showed 0.92 (0.89, 0.95) sensitivity and 0.99 (0.98, 1.00) specificity compared to 0.89 (0.77, 0.86) sensitivity and 1.00 (0.99, 1.00) specificity in the RBA. The diagnostic sensitivity and specificity were higher in PBC compared to DOC and BDC. INTERPRETATION: ADAP was comparable in two laboratories, both comparable to or better than RBA, to define threshold levels for two or more autoantibodies to stage type 1 diabetes. FUNDING: Supported by The Leona M. and Harry B. Helmsley Charitable Trust (grant number 2009-04078), the Swedish Foundation for Strategic Research (Dnr IRC15-0067) and the Swedish Research Council, Strategic Research Area (Dnr 2009-1039). AL was supported by the DiaUnion collaborative study, co-financed by EU Interreg ÖKS, Capital Region of Denmark, Region Skåne and the Novo Nordisk Foundation.

Home capillary sampling and screening for type 1 diabetes, celiac disease, and autoimmune thyroid disease in a Swedish general pediatric population: the TRIAD study.

Objective: To screen a general pediatric population for type 1 diabetes (T1D), celiac disease (CD), and autoimmune thyroid disease (AITD) after home capillary sampling. Methods: Swedish schoolchildren between 6-9 years and 13-16 years of age were invited to screening by taking a capillary sample at home. Samples were returned by mail and assessed for autoantibodies associated with T1D, CD, and AITD. Persistently autoantibody-positive children were referred for clinical follow-up. Results: Of 19,593 invited, 3,527 (18.0%) consented to participate and 2,315/3,527 (65.6%) returned a blood sample of sufficient volume. Hemolysis occurred in 830/2,301 (36.1%) samples. After exclusion of 42 children with previously known T1D, CD, or AITD, and two autoantibody-positive children who declined a confirmatory sample, 2,271/19,593 (11.6%) were included. 211/2,271 (9.3%) had persistent autoantibodies: 60/2,271 (2.6%) with T1D autoantibodies, 61/2,271 (2.7%) with CD autoantibodies, and 99/2,271 (4.4%) with AITD autoantibodies; 9/2,271 (0.4%) were autoantibody positive for ≥1 disease. After clinical follow-up, 3/2,271 (0.1%) were diagnosed with T1D, 26/2,271 (1.1%) with CD, and 6/2,271 (0.3%) with AITD. Children with a first-degree relative (FDR) with T1D, CD, and/or AITD, had higher occurrence of autoantibodies compared to children without an FDR (63/344, 18.3%, vs. 148/1,810, 8.2%) (p < 0.0001, OR 2.52, 95% CI 1.83-3.47), and higher occurrence of screening-detected diagnosis (14/344, 4.1%, vs. 21/1,810, 1.2%) (p < 0.0001, OR 3.61, 95% CI 1.82-7.18). Half of these children screened positive for another disease than the FDR. Conclusion: Screening for T1D, CD, and AITD by home capillary sampling in a Swedish general pediatric population detected autoimmunity in 9.3% and undiagnosed disease in 1.5%.

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

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

Clinical care advice for monitoring of islet autoantibody positive individuals with presymptomatic type 1 diabetes.

BACKGROUND/AIM: Type 1 diabetes is an autoimmune disease that involves the development of autoantibodies against pancreatic islet beta-cell antigens, preceding clinical diagnosis by a period of preclinical disease activity. As screening activity to identify autoantibody-positive individuals increases, a rise in presymptomatic type 1 diabetes individuals seeking medical attention is expected. Current guidance on how to monitor these individuals in a safe but minimally invasive way is limited. This article aims to provide clinical guidance for monitoring individuals with presymptomatic type 1 diabetes to reduce the risk of diabetic ketoacidosis (DKA) at diagnosis. METHODS: Expert consensus was obtained from members of the Fr1da, GPPAD, and INNODIA consortia, three European diabetes research groups. The guidance covers both specialist and primary care follow-up strategies. RESULTS: The guidance outlines recommended monitoring approaches based on age, disease stage and clinical setting. Individuals with presymptomatic type 1 diabetes are best followed up in specialist care. For stage 1, biannual assessments of random plasma glucose and HbA1c are suggested for children, while annual assessments are recommended for adolescents and adults. For stage 2, 3-monthly clinic visits with additional home monitoring are advised. The value of repeat OGTT in stage 1 and the use of continuous glucose monitoring in stage 2 are discussed. Primary care is encouraged to monitor individuals who decline specialist care, following the guidance presented. CONCLUSIONS: As type 1 diabetes screening programs become more prevalent, effective monitoring strategies are essential to mitigate the risk of complications such as DKA. This guidance serves as a valuable resource for clinicians, providing practical recommendations tailored to an individual's age and disease stage, both within specialist and primary care settings.

Early-childhood body mass index and its association with the COVID-19 pandemic, containment measures and islet autoimmunity in children with increased risk for type 1 diabetes.

AIMS/HYPOTHESIS: The aim of this study was to determine whether BMI in early childhood was affected by the COVID-19 pandemic and containment measures, and whether it was associated with the risk for islet autoimmunity. METHODS: Between February 2018 and May 2023, data on BMI and islet autoimmunity were collected from 1050 children enrolled in the Primary Oral Insulin Trial, aged from 4.0 months to 5.5 years of age. The start of the COVID-19 pandemic was defined as 18 March 2020, and a stringency index was used to assess the stringency of containment measures. Islet autoimmunity was defined as either the development of persistent confirmed multiple islet autoantibodies, or the development of one or more islet autoantibodies and type 1 diabetes. Multivariate linear mixed-effect, linear and logistic regression methods were applied to assess the effect of the COVID-19 pandemic and the stringency index on early-childhood BMI measurements (BMI as a time-varying variable, BMI at 9 months of age and overweight risk at 9 months of age), and Cox proportional hazard models were used to assess the effect of BMI measurements on islet autoimmunity risk. RESULTS: The COVID-19 pandemic was associated with increased time-varying BMI (ß = 0.39; 95% CI 0.30, 0.47) and overweight risk at 9 months (ß = 0.44; 95% CI 0.03, 0.84). During the COVID-19 pandemic, a higher stringency index was positively associated with time-varying BMI (ß = 0.02; 95% CI 0.00, 0.04 per 10 units increase), BMI at 9 months (ß = 0.13; 95% CI 0.01, 0.25) and overweight risk at 9 months (ß = 0.23; 95% CI 0.03, 0.43). A higher age-corrected BMI and overweight risk at 9 months were associated with increased risk for developing islet autoimmunity up to 5.5 years of age (HR 1.16; 95% CI 1.01, 1.32 and HR 1.68, 95% CI 1.00, 2.82, respectively). CONCLUSIONS/INTERPRETATION: Early-childhood BMI increased during the COVID-19 pandemic, and was influenced by the level of restrictions during the pandemic. Controlling for the COVID-19 pandemic, elevated BMI during early childhood was associated with increased risk for childhood islet autoimmunity in children with genetic susceptibility to type 1 diabetes.

Vitamin D insufficiency in infants with increased risk of developing type 1 diabetes: a secondary analysis of the POInT Study.

BACKGROUND: Vitamin D insufficiency (VDI) may be a factor in the development of type 1 diabetes (T1D). The aim of this study is to investigate the presence and persistence of VDI in a large cohort of infants with increased risk of developing T1D, in light of the differences in local supplementation guidelines. METHODS: In the POInT Study, a multicentre primary prevention study between February 2018 and March 2021 in Germany, Poland, Belgium, England and Sweden, including infants aged 4-7 months at high genetic risk of developing ß-cell autoantibodies, vitamin D levels were analysed at each study visit from inclusion (4-7 months) until 3 years, with an interval of 2 months (first three visits) or 4-6 months (visits 4-8). The protocol actively promotes vitamin D sufficiency to optimise immune tolerance. VDI was defined as a concentration below 30 ng/mL and was treated according to local guidelines of participating centres. Recovery from VDI was defined as a concentration above or equal to 30 ng/mL on the subsequent visit after VDI. RESULTS: 1050 infants were included, of which 5937 vitamin D levels were available for analyses. VDI was observed in 1464 (24.7%) visits and 507 (46.1%) of these were not resolved at the next visit. The risk of having VDI was independently associated with season (higher in winter), weight (higher with increased weight), age (higher with increased age) and country (higher in England). The risk of not recovering from VDI was independently associated with the season of the previously determined VDI, which was higher if VDI was identified in winter. CONCLUSIONS: VDI is frequent in infants with increased risk of developing T1D. Treatment guidelines for VDI do not seem effective. Increasing supplementation dosages in this patient population seems warranted, especially during winter, and increasing dosages more aggressively after VDI should be considered.

Factors assessed in the first year of a longitudinal study predict subsequent study visit compliance: the TEDDY study.

BACKGROUND: Compliance with a study protocol is central to meeting its research goals. In longitudinal research studies, data loss due to missed visits limit statistical power and introduce bias. The Environmental Determinants of Diabetes in the Young (TEDDY) study is a longitudinal multinational (US, Finland, Germany, and Sweden) investigation of children at risk for type 1 diabetes (T1D) that seeks to identify the environmental triggers of islet autoimmunity and T1D. The purpose of the current study was to identify sociodemographic variables and maternal characteristics assessed in the first year of TEDDY that were associated with study visit compliance in the subsequent 3 years. METHODS: Sociodemographic variables, maternal life-style behaviors, post-partum depression, maternal reactions to the child's T1D risk, and study-related variables were collected at child-age 6 months and 15 months. Multiple linear regression was used to examine the association of these variables to study visit compliance in the subsequent 3 years. RESULTS: Study visit compliance was highest in Sweden (p > 0.001), in children who were their mother's first child (p > 0.001), and whose mothers were older (p > 0.001) and more satisfied with the TEDDY study (p > 0.001). Father participation was also associated with better study visit compliance (p > 0.001). In contrast, children whose mothers smoked (p > 0.001), suffered from post-partum depression (p = 0.034), and were more anxious about their child's T1D risk (p = 0.002), completed fewer visits. Father's study satisfaction was also associated with study visit compliance (p = 0.029); however, it was not significant in models that included maternal study satisfaction. CONCLUSIONS: Sociodemographic variables, maternal characteristics-including study satisfaction-and fathers' participation in the first year of a longitudinal study were associated with subsequent study visit compliance in a sample of children genetically at-risk for T1D followed for 4 years. This information can inform future strategies designed to improve study visit compliance in longitudinal pediatric studies. TRIAL REGISTRATION: NCT00279318, 06/09/2004.

SARS-CoV-2 Infection and Development of Islet Autoimmunity in Early Childhood.

Importance: The incidence of diabetes in childhood has increased during the COVID-19 pandemic. Elucidating whether SARS-CoV-2 infection is associated with islet autoimmunity, which precedes type 1 diabetes onset, is relevant to disease etiology and future childhood diabetes trends. Objective: To determine whether there is a temporal relationship between SARS-CoV-2 infection and the development of islet autoimmunity in early childhood. Design, Setting, and Participants: Between February 2018 and March 2021, the Primary Oral Insulin Trial, a European multicenter study, enrolled 1050 infants (517 girls) aged 4 to 7 months with a more than 10% genetically defined risk of type 1 diabetes. Children were followed up through September 2022. Exposure: SARS-CoV-2 infection identified by SARS-CoV-2 antibody development in follow-up visits conducted at 2- to 6-month intervals until age 2 years from April 2018 through June 2022. Main Outcomes and Measures: The development of multiple (≥2) islet autoantibodies in follow-up in consecutive samples or single islet antibodies and type 1 diabetes. Antibody incidence rates and risk of developing islet autoantibodies were analyzed. Results: Consent was obtained for 885 (441 girls) children who were included in follow-up antibody measurements from age 6 months. SARS-CoV-2 antibodies developed in 170 children at a median age of 18 months (range, 6-25 months). Islet autoantibodies developed in 60 children. Six of these children tested positive for islet autoantibodies at the same time as they tested positive for SARS-CoV-2 antibodies and 6 at the visit after having tested positive for SARS-CoV-2 antibodies. The sex-, age-, and country-adjusted hazard ratio for developing islet autoantibodies when the children tested positive for SARS-CoV-2 antibodies was 3.5 (95% CI, 1.6-7.7; P = .002). The incidence rate of islet autoantibodies was 3.5 (95% CI, 2.2-5.1) per 100 person-years in children without SARS-CoV-2 antibodies and 7.8 (95% CI, 5.3-19.0) per 100 person-years in children with SARS-CoV-2 antibodies (P = .02). Islet autoantibody risk in children with SARS-CoV-2 antibodies was associated with younger age (<18 months) of SARS-CoV-2 antibody development (HR, 5.3; 95% CI, 1.5-18.3; P = .009). Conclusion and relevance: In young children with high genetic risk of type 1 diabetes, SARS-CoV-2 infection was temporally associated with the development of islet autoantibodies.

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

OBJECTIVE: To estimate the risk of progression to stage 3 type 1 diabetes based on varying definitions of multiple islet autoantibody positivity (mIA). RESEARCH DESIGN AND METHODS: Type 1 Diabetes Intelligence (T1DI) is a combined prospective data set of children from Finland, Germany, Sweden, and the U.S. who have an increased genetic risk for type 1 diabetes. Analysis included 16,709 infants-toddlers enrolled by age 2.5 years and comparison between groups using Kaplan-Meier survival analysis. RESULTS: Of 865 (5%) children with mIA, 537 (62%) progressed to type 1 diabetes. The 15-year cumulative incidence of diabetes varied from the most stringent definition (mIA/Persistent/2: two or more islet autoantibodies positive at the same visit with two or more antibodies persistent at next visit; 88% [95% CI 85-92%]) to the least stringent (mIA/Any: positivity for two islet autoantibodies without co-occurring positivity or persistence; 18% [5-40%]). Progression in mIA/Persistent/2 was significantly higher than all other groups (P < 0.0001). Intermediate stringency definitions showed intermediate risk and were significantly different than mIA/Any (P < 0.05); however, differences waned over the 2-year follow-up among those who did not subsequently reach higher stringency. Among mIA/Persistent/2 individuals with three autoantibodies, loss of one autoantibody by the 2-year follow-up was associated with accelerated progression. Age was significantly associated with time from seroconversion to mIA/Persistent/2 status and mIA to stage 3 type 1 diabetes. CONCLUSIONS: The 15-year risk of progression to type 1 diabetes risk varies markedly from 18 to 88% based on the stringency of mIA definition. While initial categorization identifies highest-risk individuals, short-term follow-up over 2 years may help stratify evolving risk, especially for those with less stringent definitions of mIA.

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

AIMS/HYPOTHESIS: The aim of this study was to explore the utility of islet autoantibody (IAb) levels for the prediction of type 1 diabetes in autoantibody-positive children. METHODS: Prospective cohort studies in Finland, Germany, Sweden and the USA followed 24,662 children at increased genetic or familial risk of developing islet autoimmunity and diabetes. For the 1403 who developed IAbs (523 of whom developed diabetes), levels of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA) and insulinoma-associated antigen-2 (IA-2A) were harmonised for analysis. Diabetes prediction models using multivariate logistic regression with inverse probability censored weighting (IPCW) were trained using 10-fold cross-validation. Discriminative power for disease was estimated using the IPCW concordance index (C index) with 95% CI estimated via bootstrap. RESULTS: A baseline model with covariates for data source, sex, diabetes family history, HLA risk group and age at seroconversion with a 10-year follow-up period yielded a C index of 0.61 (95% CI 0.58, 0.63). The performance improved after adding the IAb positivity status for IAA, GADA and IA-2A at seroconversion: C index 0.72 (95% CI 0.71, 0.74). Using the IAb levels instead of positivity indicators resulted in even better performance: C index 0.76 (95% CI 0.74, 0.77). The predictive power was maintained when using the IAb levels alone: C index 0.76 (95% CI 0.75, 0.76). The prediction was better for shorter follow-up periods, with a C index of 0.82 (95% CI 0.81, 0.83) at 2 years, and remained reasonable for longer follow-up periods, with a C index of 0.76 (95% CI 0.75, 0.76) at 11 years. Inclusion of the results of a third IAb test added to the predictive power, and a suitable interval between seroconversion and the third test was approximately 1.5 years, with a C index of 0.78 (95% CI 0.77, 0.78) at 10 years follow-up. CONCLUSIONS/INTERPRETATION: Consideration of quantitative patterns of IAb levels improved the predictive power for type 1 diabetes in IAb-positive children beyond qualitative IAb positivity status.

The emotional well-being of parents with children at genetic risk for type 1 diabetes before and during participation in the POInT-study.

INTRODUCTION: This study examined the emotional impact that parents experience when confronted with an increased genetic risk of type 1 diabetes (T1D) in their child. Population-based screening of neonates for genetic risk of chronic disease carries the risk of increased emotional burden for parents. METHODS: Information was collected using a well-being questionnaire for parents of infants identified as having an increased risk for T1D in a multinational research study. Parents were asked to complete this questionnaire after they were told their child had an increased risk for T1D (Freder1k-study) and at several time points during an intervention study (POInT-study), where oral insulin was administered daily. RESULTS: Data were collected from 2595 parents of 1371 children across five countries. Panic-related anxiety symptoms were reported by only 4.9% after hearing about their child having an increased risk. Symptoms of depression were limited to 19.4% of the parents at the result-communication visit and declined over time during the intervention study. When thinking about their child's risk for developing T1D (disease-specific anxiety), 47.2% worried, felt nervous and tense. Mothers and parents with a first-degree relative (FDR) with T1D reported more symptoms of depression and disease-specific anxiety (p < 0.001) than fathers and parents without a FDR. CONCLUSION: Overall, symptoms of depression and panic-related anxiety are comparable with the German population. When asked about their child's risk for T1D during the intervention study, some parents reported disease-specific anxiety, which should be kept in mind when considering population-based screening. As certain subgroups are more prone, it will be important to continue psychological screening and, when necessary, to provide support by an experienced, multidisciplinary team.

Elevations in blood glucose before and after the appearance of islet autoantibodies in children.

The etiology of type 1 diabetes has polygenic and environmental determinants that lead to autoimmune responses against pancreatic ß cells and promote ß cell death. The autoimmunity is considered silent without metabolic consequences until late preclinical stages,and it remains unknown how early in the disease process the pancreatic ß cell is compromised. To address this, we investigated preprandial nonfasting and postprandial blood glucose concentrations and islet autoantibody development in 1,050 children with high genetic risk of type 1 diabetes. Pre- and postprandial blood glucose decreased between 4 and 18 months of age and gradually increased until the final measurements at 3.6 years of age. Determinants of blood glucose trajectories in the first year of life included sex, body mass index, glucose-related genetic risk scores, and the type 1 diabetes-susceptible INS gene. Children who developed islet autoantibodies had early elevations in blood glucose concentrations. A sharp and sustained rise in postprandial blood glucose was observed at around 2 months prior to autoantibody seroconversion, with further increases in postprandial and, subsequently, preprandial values after seroconversion. These findings show heterogeneity in blood glucose control in infancy and early childhood and suggest that islet autoimmunity is concurrent or subsequent to insults on the pancreatic islets.

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

OBJECTIVE: Increased level of glycated hemoglobin (HbA1c) is associated with type 1 diabetes onset that in turn is preceded by one to several autoantibodies against the pancreatic islet beta cell autoantigens; insulin (IA), glutamic acid decarboxylase (GAD), islet antigen-2 (IA-2) and zinc transporter 8 (ZnT8). The risk for type 1 diabetes diagnosis increases by autoantibody number. Biomarkers predicting the development of a second or a subsequent autoantibody and type 1 diabetes are needed to predict disease stages and improve secondary prevention trials. This study aimed to investigate whether HbA1c possibly predicts the progression from first to a subsequent autoantibody or type 1 diabetes in healthy children participating in the Environmental Determinants of Diabetes in the Young (TEDDY) study. RESEARCH DESIGN AND METHODS: A joint model was designed to assess the association of longitudinal HbA1c levels with the development of first (insulin or GAD autoantibodies) to a second, second to third, third to fourth autoantibody or type 1 diabetes in healthy children prospectively followed from birth until 15 years of age. RESULTS: It was found that increased levels of HbA1c were associated with a higher risk of type 1 diabetes (HR 1.82, 95% CI [1.57-2.10], p < 0.001) regardless of first appearing autoantibody, autoantibody number or type. A decrease in HbA1c levels was associated with the development of IA-2A as a second autoantibody following GADA (HR 0.85, 95% CI [0.75, 0.97], p = 0.017) and a fourth autoantibody following GADA, IAA and ZnT8A (HR 0.90, 95% CI [0.82, 0.99], p = 0.036). HbA1c trajectory analyses showed a significant increase of HbA1c over time (p < 0.001) and that the increase is more rapid as the number of autoantibodies increased from one to three (p < 0.001). CONCLUSION: In conclusion, increased HbA1c is a reliable time predictive marker for type 1 diabetes onset. The increased rate of increase of HbA1c from first to third autoantibody and the decrease in HbA1c predicting the development of IA-2A are novel findings proving the link between HbA1c and the appearance of autoantibodies.

Possible Relationship between the HLA-DRA1 Intron Haplotype of Three Single-Nucleotide Polymorphisms in Intron 1 of the HLA-DRA1 Gene and Autoantibodies in Children at Increased Genetic Risk for Autoimmune Type 1 Diabetes.

Recently, a haplotype of three single-nucleotide polymorphisms (tri-SNP) in intron 1 of the HLA-DRA1 gene was found to be strongly associated with type 1 diabetes risk in HLA-DR3/3 individuals. The tri-SNP reportedly function as "expression quantitative trait loci," modulating HLA-DR and -DQ expression. The aim was to investigate HLA-DRA1 tri-SNPs in relation to extended HLA class II haplotypes and human peripheral blood cell HLA-DQ cell-surface median fluorescence intensity (MFI), the first-appearing islet autoantibody, and autoimmunity burden. A total of 67 healthy subjects (10-15 y) at increased HLA risk for type 1 diabetes and with (n = 54) or without (n = 13) islet autoantibodies were followed longitudinally in the Diabetes Prediction in Skåne study. Among four tri-SNPs, AGG (n = 67), GCA (n = 47), ACG (n = 11), and ACA (n = 9), HLA-DQ cell-surface MFI on CD4+ T cells was lower in AGG than GCA (p = 0.030) subjects. Cumulative autoimmunity burden was associated with reduced HLA-DQ cell-surface MFI in AGG compared with GCA in CD16+ cells (p = 0.0013), CD4+ T cells (p = 0.0018), and CD8+ T cells (p = 0.016). The results suggest that HLA-DRA1 tri-SNPs may be related to HLA-DQ cell-surface expression and autoimmunity burden.

Two-age islet-autoantibody screening for childhood type 1 diabetes: a prospective cohort study.

BACKGROUND: Early prediction of childhood type 1 diabetes reduces ketoacidosis at diagnosis and provides opportunities for disease prevention. However, only highly efficient approaches are likely to succeed in public health settings. We sought to identify efficient strategies for initial islet autoantibody screening in children younger than 15 years. METHODS: We harmonised data from five prospective cohorts from Finland (DIPP), Germany (BABYDIAB), Sweden (DiPiS), and the USA (DAISY and DEW-IT) into the Type 1 Diabetes Intelligence (T1DI) cohort. 24 662 children at high risk of diabetes enrolled before age 2 years were included and followed up for islet autoantibodies and diabetes until age 15 years, or type 1 diabetes onset, whichever occurred first. Islet autoantibodies measured included those against glutamic acid decarboxylase, insulinoma antigen 2, and insulin. Main outcomes were sensitivity and positive predictive value (PPV) of detected islet autoantibodies, tested at one or two fixed ages, for diagnosis of clinical type 1 diabetes. FINDINGS: Of the 24 662 participants enrolled in the Type 1 Diabetes Intelligence cohort, 6722 total were followed up to age 15 years or until onset of type 1 diabetes. Type 1 diabetes developed by age 15 years in 672 children, but did not develop in 6050 children. Optimal screening ages for two measurements were 2 years and 6 years, yielding sensitivity of 82% (95% CI 79-86) and PPV of 79% (95% CI 75-80) for diabetes by age 15 years. Autoantibody positivity at the beginning of each test age was highly predictive of diagnosis in the subsequent 2-5·99 year or 6-15-year age intervals. Autoantibodies usually appeared before age 6 years even in children diagnosed with diabetes much later in childhood. INTERPRETATION: Our results show that initial screening for islet autoantibodies at two ages (2 years and 6 years) is sensitive and efficient for public health translation but might require adjustment by country on the basis of population-specific disease characteristics. FUNDING: Juvenile Diabetes Research Foundation.

Long-Term GAD-alum Treatment Effect on Different T-Cell Subpopulations in Healthy Children Positive for Multiple Beta Cell Autoantibodies.

Objective: The objective of this study was to explore whether recombinant GAD65 conjugated hydroxide (GAD-alum) treatment affected peripheral blood T-cell subpopulations in healthy children with multiple beta cell autoantibodies. Method: The Diabetes Prevention-Immune Tolerance 2 (DiAPREV-IT 2) clinical trial enrolled 26 children between 4 and 13 years of age, positive for glutamic acid decarboxylase autoantibody (GADA) and at least one other autoantibody (insulin, insulinoma antigen-2, or zinc transporter 8 autoantibody (IAA, IA-2A, or ZnT8A)) at baseline. The children were randomized to two doses of subcutaneously administered GAD-alum treatment or placebo, 30 days apart. Complete blood count (CBC) and immunophenotyping of T-cell subpopulations by flow cytometry were performed regularly during the 24 months of follow-up posttreatment. Cross-sectional analyses were performed comparing lymphocyte and T-cell subpopulations between GAD-alum and placebo-treated subjects. Results: GAD-alum-treated children had lower levels of lymphocytes (109 cells/L) (p = 0.006), T-cells (103 cells/µL) (p = 0.008), T-helper cells (103 cells/µL) (p = 0.014), and cytotoxic T-cells (103 cells/µL) (p = 0.023) compared to the placebo-treated children 18 months from first GAD-alum injection. This difference remained 24 months after the first treatment for lymphocytes (p = 0.027), T-cells (p = 0.022), T-helper cells (p = 0.048), and cytotoxic T-cells (p = 0.018). Conclusion: Our findings suggest that levels of total T-cells and T-cell subpopulations declined 18 and 24 months after GAD-alum treatment in healthy children with multiple beta-cell autoantibodies including GADA.

Childhood Height Growth Rate Association With the Risk of Islet Autoimmunity and Development of Type 1 Diabetes.

CONTEXT: Rapid growth has been suggested to promote islet autoimmunity and progression to type 1 diabetes (T1D). Childhood growth has not been analyzed separately from the infant growth period in most previous studies, but it may have distinct features due to differences between the stages of development. OBJECTIVE: We aimed to analyze the association of childhood growth with development of islet autoimmunity and progression to T1D diagnosis in children 1 to 8 years of age. METHODS: Longitudinal data of childhood growth and development of islet autoimmunity and T1D were analyzed in a prospective cohort study including 10 145 children from Finland, Germany, Sweden, and the United States, 1-8 years of age with at least 3 height and weight measurements and at least 1 measurement of islet autoantibodies. The primary outcome was the appearance of islet autoimmunity and progression from islet autoimmunity to T1D. RESULTS: Rapid increase in height (cm/year) was associated with increased risk of seroconversion to glutamic acid decarboxylase autoantibody, insulin autoantibody, or insulinoma-like antigen-2 autoantibody (hazard ratio [HR] = 1.26 [95% CI = 1.05, 1.51] for 1-3 years of age and HR = 1.48 [95% CI = 1.28, 1.73] for >3 years of age). Furthermore, height rate was positively associated with development of T1D (HR = 1.80 [95% CI = 1.15, 2.81]) in the analyses from seroconversion with insulin autoantibody to diabetes. CONCLUSION: Rapid height growth rate in childhood is associated with increased risk of islet autoimmunity and progression to T1D. Further work is needed to investigate the biological mechanism that may explain this association.

Multiplex agglutination-PCR (ADAP) autoantibody assays compared to radiobinding autoantibodies in type 1 diabetes and celiac disease.

Multiplex Antibody-Detection by Agglutination-PCR (ADAP) assay was compared to singleplex standard radiobinding assays (RBA) to detect autoantibodies against insulin (IAA), GAD65 (GADA), islet antigen-2 (IA-2A), ZnT8 (ZnT8A) and tissue transglutaminase (TGA). Serum samples from 273 (114F/158M), 15-73 years of age healthy controls and 227 (109F/118M) newly diagnosed type 1 diabetes children, 1-11 years of age, were analyzed in both assay systems.The original WHO standard 97/550 and in-house reference standards for RBA were compared to ADAP. The ADAP and RBA generated parallel reference standards in all assays except TGA. Lower detection limits were observed in the ADAP assay for GADA,IAA and ZnT8A, markedly for TGA, but not for IA-2A. The Receiver Operating Characteristics (ROC) curve AUC analyses for pairwise comparison of ADAP with RBA showed no difference for GADA (n.s.), ADAP greater AUC for IAA (p = 0.005), RBA greater AUC for IA-2A (p = 0.0004) and ZnT8A (p < 0.0001) while ADAP TGA had a greater AUC compared to both RBA TGA-IgG (p < 0.0001) and TGA-IgA (p < 0.0001). These data suggest that the ADAP and RBA assays are comparable with equal performance for GADA, better ADAP performance for IAA while the RBA showed better performance in both IA-2A and ZnT8A associated with greater heterogeneity in autoantibody levels. The simultaneous analysis of 5 different autoantibodies by ADAP in sample volume reduced to only 4 µL and at an increased lower detection limit in all assays except IA-2A makes the ADAP automated autoantibody assay a distinct advantage for high throughput screening.