The Environmental Determinants Of Diabetes In The Young Research Articles

JOINT MODELING OF MULTISTATE AND NONPARAMETRIC MULTIVARIATE LONGITUDINAL DATA.

It is oftentimes the case in studies of disease progression that subjects can move into one of several disease states of interest. Multistate models are an indispensable tool to analyze data from such studies. The Environmental Determinants of Diabetes in the Young (TEDDY) is an observational study of at-risk children from birth to onset of type-1 diabetes (T1D) up through the age of 15. A joint model for simultaneous inference of multistate and multivariate nonparametric longitudinal data is proposed to analyze data and answer the research questions brought up in the study. The proposed method allows us to make statistical inferences, test hypotheses, and make predictions about future state occupation in the TEDDY study. The performance of the proposed method is evaluated by simulation studies. The proposed method is applied to the motivating example to demonstrate the capabilities of the method.

Early appearance of thyroid autoimmunity in children followed from birth for type 1 diabetes risk.

Autoantibodies to thyroid peroxidase (TPOAb) and thyroglobulin (TgAb) define pre-clinical autoimmune thyroid disease (AITD) which can progress to either clinical hypo- or hyperthyroidism. We determined the age at seroconversion in children genetically at risk for type 1 diabetes. TPOAb and TgAb seropositivity were determined in 5066 healthy children with HLA DR3 or DR4 containing haplogenotypes from The Environmental Determinants of Diabetes in the Young (TEDDY) Study. Children seropositive on the cross-sectional initial screen at 8-13 years of age had longitudinally collected samples (from 3.5 months of age) screened retrospectively and prospectively for thyroid autoantibodies to identify the age at seroconversion. First-appearing autoantibody was related to sex, HLA genotype, family history of AITD, and subsequent thyroid dysfunction and disease. The youngest appearance of TPOAb and TgAb was 10 and 15 months of age, respectively. Girls had higher incidence rates of both autoantibodies. Family history of AITD was associated with a higher risk of TPOAb hazard ratio [HR] 1.90, 95% confidence interval [CI] 1.17, 3.08; and TgAb HR 2.55, 95% CI 1.91, 3.41. The risk of progressing to hypo- or hyperthyroidism was not different between TgAb and TPOAb, but children with both autoantibodies appearing at the same visit had a higher risk compared to TPOAb appearing first (HR 6.34, 95% CI 2.72, 14.76). Thyroid autoantibodies may appear during the first years of life, especially in girls, and in children with a family history of AITD. Simultaneous appearance of both autoantibodies increases the risk for hypo- or hyperthyroidism.

Structures and Strategies for Retaining an International Pediatric Cohort from Birth: Lessons from The Environmental Determinants of Diabetes in the Young (TEDDY) Study.

Retention of study participants in observational studies is essential to maintaining the representativeness of the population, minimizing selection bias, and assuring sufficient statistical power. The aim of this report is to describe the structures and strategies used to retain participants in The Environmental Determinants of Diabetes in the Young (TEDDY) Study, an observational study of children at increased genetic risk for type 1 diabetes followed in an intense protocol with frequent clinic visits from birth until age 15. A systematic review of methodologies used to retain research subjects identified four domains: barrier reduction strategies; community building strategies; follow-up/reminder strategies; and tracing strategies. Independent reviewers categorized the retention strategies implemented by the TEDDY Study into each of these domains. Strategies not fitting into any of these categories were placed into a fifth category unique to TEDDY. TEDDY identified over one hundred retention strategies used during the 15 years of follow-up; most could be categorized in these domains. Those unique to TEDDY included (1) study organization and structures to support retention; (2) efforts to meet the changing developmental needs of the TEDDY population, (3) implementation of efforts to address protocol challenges in real-time; and (4) employment of a re-engagement protocol for those who had dropped out of the study. Pediatric cohort studies should include strategies, structures, and resources addressing retention at the study's initiation. It is recommended that child and parent engagement in addition to the developmental needs of the child be an integrated focus of all strategies. Putting mechanisms in place to address protocol and retention challenges in real time would facilitate effectively addressing challenges as they arise. ClinicalTrials.gov Identifier: NCT00279318.

The Influence of Pubertal Development on Autoantibody Appearance and Progression to Type 1 Diabetes in the TEDDY Study.

The 2 peaks of type 1 diabetes incidence occur during early childhood and puberty. We sought to better understand the relationship between puberty, islet autoimmunity, and type 1 diabetes. The relationships between puberty, islet autoimmunity, and progression to type 1 diabetes were investigated prospectively in children followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Onset of puberty was determined by subject self-assessment of Tanner stages. Associations between speed of pubertal progression, pubertal growth, weight gain, homeostasis model assessment of insulin resistance (HOMA-IR), islet autoimmunity, and progression to type 1 diabetes were assessed. The influence of individual factors was analyzed using Cox proportional hazard ratios. Out of 5677 children who were still in the study at age 8 years, 95% reported at least 1 Tanner Stage score and were included in the study. Children at puberty (Tanner Stage ≥2) had a lower risk (HR 0.65, 95% CI 0.45-0.93; P = .019) for incident autoimmunity than prepubertal children (Tanner Stage 1). An increase of body mass index Z-score was associated with a higher risk (HR 2.88, 95% CI 1.61-5.15; P < .001) of incident insulin autoantibodies. In children with multiple autoantibodies, neither HOMA-IR nor rate of progression to Tanner Stage 4 were associated with progression to type 1 diabetes. Rapid weight gain during puberty is associated with development of islet autoimmunity. Puberty itself had no significant influence on the appearance of autoantibodies or type 1 diabetes. Further studies are needed to better understand the underlying mechanisms.

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

Purpose The aim was to study the association between dietary intake of B vitamins in childhood and the risk of islet autoimmunity (IA) and progression to type 1 diabetes (T1D) by the age of 10 years. MethodsWe followed 8500 T1D-susceptible children born in the U.S., Finland, Sweden, and Germany in 2004 -2010 from the Environmental Determinants of Diabetes in the Young (TEDDY) study, which is a prospective observational birth cohort. Dietary intake of seven B vitamins was calculated from foods and dietary supplements based on 24-h recall at 3 months and 3-day food records collected regularly from 6 months to 10 years of age. Cox proportional hazard models were adjusted for energy, HLA-genotype, first-degree relative with T1D, sex, and country. ResultsA total of 778 (9.2) children developed at least one autoantibody (any IA), and 335 (3.9%) developed multiple autoantibodies. 280 (3.3%) children had IAA and 319 (3.8%) GADA as the first autoantibody. 344 (44%) children with IA progressed to T1D. We observed that higher intake of niacin was associated with a decreased risk of developing multiple autoantibodies (HR 0.95; 95% CI 0.92, 0.98) per 1 mg/1000 kcal in niacin intake. Higher intake of pyridoxine (HR 0.66; 95% CI 0.46, 0.96) and vitamin B12 (HR 0.87; 95% CI 0.77, 0.97) was associated with a decreased risk of IAA-first autoimmunity. Higher intake of riboflavin (HR 1.38; 95% CI 1.05, 1.80) was associated with an increased risk of GADA-first autoimmunity. There were no associations between any of the B vitamins and the outcomes “any IA” and progression from IA to T1D. ConclusionIn this multinational, prospective birth cohort of children with genetic susceptibility to T1D, we observed some direct and inverse associations between different B vitamins and risk of IA.

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

BackgroundCompliance 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.MethodsSociodemographic 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.ResultsStudy 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.ConclusionsSociodemographic 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.

Extremely Early Appearance of Islet Autoantibodies in Genetically Susceptible Children

Objective. We studied the characteristics of children who developed islet autoantibodies by the age of 0.50 years and hypothesized that the appearance of extremely early islet autoimmunity differs between four birth cohorts within 1994–2019 according to the change in the incidence of Type 1 diabetes (T1D) in Finland. Methods. Data from Finnish children participating in the Type 1 Diabetes Prediction and Prevention (DIPP) study, or the Environmental Determinants of Diabetes in the Young (TEDDY) study were analyzed. These studies follow children with increased HLA-conferred risk for T1D with regular measurements of islet autoantibodies. Maternally transferred antibodies were excluded by comparing islet autoantibodies in cord serum, child’s first follow-up serum and the maternal serum. Results. Among 20,979 Finnish children at increased risk to T1D, 53 (0.25%) developed at least one islet autoantibody at the age of ≤0.50 years. During a mean follow-up of 8.1 years, 15.1% progressed to T1D (median age at diagnosis 2.0 years), 43.4% developed confirmed islet autoimmunity but no T1D, and 41.5% had only transient islet autoantibodies. IAA was the most common first-appearing autoantibody. Among progressors, age at diagnosis was 1.0–2.4 years in children with IAA-initiated autoimmunity and 4.5–16.1 years in ZnT8A-initiated autoimmunity. When comparing children developing autoantibodies either at the age of ≤0.50 years or 0.51–0.75 years, confirmed positivity during follow-up was more common in the older group (81.7% vs. 58.5%; p = 0.002 ). In four birth cohorts within 1994–2019 appearance of islet autoantibodies at the age of ≤0.50 years decreased towards the most recent birth cohorts ( p = 0.016 ). Conclusion. Islet autoimmunity by the age of 0.50 years was rare in genetically susceptible children and was typically initiated with IAA. Confirmed positivity was less common in children with autoantibodies at age ≤0.50 than at slightly older age. The secular decrease of islet autoimmunity before age 0.50 years was observed. This trial is registered with NCT03269084 and NCT00279318.

Associations of dietary patterns between age 9 and 24 months with risk of celiac disease autoimmunity and celiac disease among children at increased risk

BackgroundHigher gluten intake in childhood is associated with increased incidence of celiac disease autoimmunity (CDA) and celiac disease. It remains to be studied whether different dietary patterns independent of gluten intake contribute to the incidence. ObjectivesThis study aimed to explore associations of dietary patterns by age 2 y with risk of CDA and celiac disease in genetically susceptible children. MethodsData was used from 6726 participants at genetic risk of type 1 diabetes and celiac disease enrolled in the observational cohort, The Environmental Determinants of Diabetes in the Young (TEDDY) study. Children were annually screened for tissue transglutaminase autoantibodies (tTGAs) from age 2 y. Principal component analysis extracted dietary patterns, based on intake of 27 food groups assessed by 3-d food records at age 9 to 24 mo. The primary outcome was CDA (i.e., persistently tTGA-positive in at least 2 consecutive samples), and the secondary outcome was celiac disease. During follow-up to mean age 11.0 (standard deviation 3.6) y, 1296 (19.3%) children developed CDA, and 529 (7.9%) were diagnosed with celiac disease. Associations of adherence to dietary patterns (per 5-unit increase) with the study outcomes were estimated by Cox regression models adjusted for risk factors including gluten intake. ResultsAt age 9 mo, a dietary pattern higher in the food groups vegetable fats and milk was associated with reduced risk of CDA (hazard ratio [HR]: 0.88; 95% confidence interval [CI]: 0.79, 0.98; P = 0.02). At 24 mo, a dietary pattern higher in the food groups wheat, vegetable fats, and juices, and lower in milk, meat, and oats at age 24 mo was associated with increased risk of CDA (HR: 1.18; 95% CI: 1.05, 1.33; P < 0.001) and celiac disease (HR: 1.24; 95% CI: 1.03, 1.50; P = 0.03). ConclusionsDietary patterns in early childhood are associated with risk of CDA and celiac disease in genetically predisposed children, independent of gluten intake.

SAI-CH-6: Development of a Short Form of the State Anxiety Inventory for Children At-Risk for Type 1 Diabetes.

To develop a reliable and valid short form of the State Anxiety Subscale of the State-Trait Anxiety Inventory for Children (STAI-CH) in the Environmental Determinants of Diabetes in the Young (TEDDY) study. A Development Sample of 842 10-year-old TEDDY children completed the STAI-CH State Subscale about their type 1 diabetes (T1D) risk. The best 6 items (three anxiety-present and three anxiety-absent) for use in a short form (SAI-CH-6) were identified via item-total correlations. SAI-CH-6 reliability was examined in a Validation Sample (n = 257) of children who completed the full 20-item STAI-CH State Subscale and then again in an Application Sample (n = 2,710) who completed only the SAI-CH-6. Expected associations between the children's SAI-CH-6 scores and country of residence, sex, T1D family history, accuracy of T1D risk perception, worry about getting T1D, and their parents' anxiety scores were examined. The SAI-CH-6 was reliable (α = 0.81-0.87) and highly correlated with the full 20-item STAI-CH State Subscale (Development Sample: r = 0.94; Validation Sample: r = 0.92). SAI-CH-6 scores detected significant differences in state anxiety symptoms associated with T1D risk by country, T1D family history, accuracy of T1D risk perception, and worry about getting T1D and were correlated with the child's parent's anxiety. The SAI-CH-6 appears useful for assessing children's state anxiety symptoms when burden and time limitations prohibit the use of the STAI-CH. The utility of the SAI-CH-6 in older children with and without chronic conditions needs to be assessed.

Gastrointestinal Infections Modulate the Risk for Insulin Autoantibodies as the First-Appearing Autoantibody in the TEDDY Study.

To investigate gastrointestinal infection episodes (GIEs) in relation to the appearance of islet autoantibodies in The Environmental Determinants of Diabetes in the Young (TEDDY) cohort. GIEs on risk of autoantibodies against either insulin (IAA) or GAD (GADA) as the first-appearing autoantibody were assessed in a 10-year follow-up of 7,867 children. Stool virome was characterized in a nested case-control study. GIE reports (odds ratio [OR] 2.17 [95% CI 1.39-3.39]) as well as Norwalk viruses found in stool (OR 5.69 [1.36-23.7]) at <1 year of age were associated with an increased IAA risk at 2-4 years of age. GIEs reported at age 1 to <2 years correlated with a lower risk of IAA up to 10 years of age (OR 0.48 [0.35-0.68]). GIE reports at any other age were associated with an increase in IAA risk (OR 2.04 for IAA when GIE was observed 12-23 months prior [1.41-2.96]). Impacts on GADA risk were limited to GIEs <6 months prior to autoantibody development in children <4 years of age (OR 2.16 [1.54-3.02]). Bidirectional associations were observed. GIEs were associated with increased IAA risk when reported before 1 year of age or 12-23 months prior to IAA. Norwalk virus was identified as one possible candidate factor. GIEs reported during the 2nd year of life were associated with a decreased IAA risk.

137-OR: Metabolite Ratios and Development of Type 1 Diabetes

Ratios between metabolites more directly reflect flux through chemical reactions than individual metabolites. Variation in metabolites and their ratios are determined, in part, by genetic factors. Thus, genetic loci associated with variation in metabolite ratios may help disentangle genetic from non-genetic processes captured by the metabolome. We integrated metabolite ratios with genetics to predict changes preceding type 1 diabetes (T1D) in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Quantitative trait loci (QTLs) were identified for 132 metabolite ratios previously associated with progression from islet autoimmunity (IA) to T1D. Ratios were calculated from untargeted metabolomics data available at the time of seroconversion to IA for 338 cases and 921 matched controls in TEDDY. Genotyping was performed using a genome-wide array with custom content with imputation to the TOPMed reference panel. Ratio-SNP associations were estimated using Matrix eQTL software, adjusting for case-control status and genetic relatedness. Genome-wide significant association (P &amp;lt; 4.9×10-9) was observed at 202 independent loci, involving 49 metabolite ratios. Twenty-six loci (12.9%) involved ratios between polyunsaturated fatty-acids (PUFAs) and fatty acid esters of hydroxy fatty acids (FAHFAs), a novel class of bioactive lipids with antidiabetic and anti-inflammatory effects. Variation in the metabolite ratio of eicosadienoic acid to FAHFA (18:1/O-15:1) was significantly determined by a site on chromosome 3 (ITPR1); ITPR1 encodes a receptor integral to calcium signaling and glucose-induced insulin secretion. Other genetic loci contributing to variation of PUFA:FAHFA ratios reside in genes controlling inflammatory and innate immune response (e.g., TSPO, TTLL12, NCAM1) and apoptosis (PPM1L). These novel metabolite ratio QTLs, some with known association with T1D risk, expand potential biomarkers of T1D risk, with PUFA:FAHFA ratios representing candidate FAHFA biosynthesis genes. Disclosure R.K. Johnson: None. A. Romero: None. E. Willems: Employee; Amgen Inc. S.S. Rich: None. M. Rewers: Research Support; Provention Bio, Juvenile Diabetes Research Foundation (JDRF), Hemsley Charitable Trust, Dexcom, Inc., Janssen Research &amp; Development, LLC. O. Fiehn: None. J.M. Norris: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R03DK127472); National Institute of Allergy and Infectious Diseases; National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; JDRF; Centers for Disease Control and Prevention

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

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

Sequential data mining of infection patterns as predictors for onset of type 1 diabetes in genetically at-risk individuals

Infections are implicated in the etiology of type 1 diabetes mellitus (T1DM); however, conflicting epidemiologic evidence makes designing effective strategies for presymptomatic screening and disease prevention difficult. Considering the temporality and combination in which infections occur may provide valuable insights into understanding T1DM etiology but is rarely studied due to limited longitudinal datasets and insufficient analytical techniques. The objective of this work was to demonstrate a computational approach to classify the temporality and combination of infections in presymptomatic T1DM. We present a sequential data mining pipeline that leverages routinely collected infectious disease data from a prospective cohort study, the Environmental Determinants of Diabetes in the Young (TEDDY) study, to extract, interpret, and compare infection sequences. We then utilize this pipeline to assess risk for developing presymptomatic biomarkers of islet autoimmunity and clinical onset of T1DM. Overall, we identified 229 significant sequential rules that increased the risk for developing presymptomatic biomarkers of islet autoimmunity or clinical onset of T1DM. Multiple significant sequential rules involving varicella increased the risk for all presymptomatic biomarker-specific outcomes, while a single significant sequential rule involving parasites significantly increased risk for T1DM. Significant sequential rules involving respiratory illnesses were differentially represented among the presymptomatic biomarkers of islet autoimmunity and clinical onset of T1DM. Risk for T1DM was significantly increased by a single episode of sixth disease at 12 months, representing the only single-event sequence that increased disease risk. Together, these findings provide the first insights into the timing and combination of infections in T1DM etiology, which may ultimately lead to personalized disease screening and prevention strategies. The sequential data mining pipeline developed in this work demonstrates how temporal data mining can be used to address clinically meaningful questions. This method can be adapted to other presymptomatic factors and clinical conditions.

297 Identifying Opportunities and Challenges for Translational Informatics Approaches to Real-World Data: A Diabetes Case Study

OBJECTIVES/GOALS: Diabetes is a group of chronic metabolic diseases and significant gaps remain in our understanding of disease etiology, treatment regimens, and diabetes-related complications. The objective of study is to demonstrate how informatics techniques can leverage real-world data for diabetes research and identify barriers for implementation. METHODS/STUDY POPULATION: We evaluated informatics applications of real-world data in diabetes research conducted by the Facelli Research Group. The types of real-world data were categorized into clinical records, diabetes-related repositories, wearable sensors, and other data sources. Translational informatics applications were characterized into thematic groups of 1.) use of electronic health records, registries, and claims and other data sources to generate real-world evidence, 2.) evolution of novel methods to accelerate generation and use of real-world data, and 3.) infrastructure to support the generation and use of real-world data in translational science. A literature review is being conducted to identify additional articles meeting these themes focused on diabetes research. RESULTS/ANTICIPATED RESULTS: 6 research projects were included for analysis. The diabetes-focus spanned type 1 diabetes, type 2 diabetes, and general diabetes mellitus. Informatics methods included machine learning and data mining while real-world data sources included electronic medical records, the Environmental Determinants of Diabetes in the Young (TEDDY) study, continuous glucose monitors, and the U.S. Environmental Protection Agency (EPA) air pollution monitors. Overall, computability of real-world data, linkage of medical concepts to standardized terminologies, volume of data, and adoption of novel artificial intelligence methods were major determinants of successful implementation. Future work will systematically evaluate informatics applications of real-world data in diabetes from the academic community at large. DISCUSSION/SIGNIFICANCE: Translational informatics approaches are poised to leverage real-world data and better understand diabetes etiology, treatment regimens, and diabetes-related complications. By understanding barriers and opportunities for informatics methods, we can expedite translational applications in diabetes research.

Interaction Between Dietary Iron Intake and Genetically Determined Iron Overload: Risk of Islet Autoimmunity and Progression to Type 1 Diabetes in the TEDDY Study.

To examine whether iron intake and genetically determined iron overload interact in predisposing to the development of childhood islet autoimmunity (IA) and type 1 diabetes (T1D). In The Environmental Determinants of Diabetes in the Young (TEDDY) study, 7,770 genetically high-risk children were followed from birth until the development of IA and progression to T1D. Exposures included energy-adjusted iron intake in the first 3 years of life and a genetic risk score (GRS) for increased circulating iron. We found a U-shaped association between iron intake and risk of GAD antibody as the first autoantibody. In children with GRS ≥2 iron risk alleles, high iron intake was associated with an increased risk of IA, with insulin as first autoantibody (adjusted hazard ratio 1.71 [95% CI 1.14; 2.58]) compared with moderate iron intake. Iron intake may alter the risk of IA in children with high-risk HLA haplogenotypes.

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

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. 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. 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). 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.

Rising Hemoglobin A1c in the Nondiabetic Range Predicts Progression of Type 1 Diabetes As Well As Oral Glucose Tolerance Tests.

Biomarkers predicting risk of type 1 diabetes (stage 3) among children with islet autoantibodies are greatly needed to prevent diabetic ketoacidosis and facilitate prevention therapies. Children in the prospective The Environmental Determinants of Diabetes in the Young (TEDDY) study (n = 707) with confirmed diabetes-associated autoantibodies (GAD antibody, IA-2A, and/or insulin autoantibody) and two or more HbA1c measurements were followed to diabetes or median age 11.1 years. Once confirmed autoantibody positive, HbA1c was measured quarterly. Cox models and receiver operative characteristic curve analyses revealed the prognostic utility for risk of stage 3 on a relative HbA1c increase from the baseline visit or an oral glucose tolerance test (OGTT) 2-h plasma glucose (2-hPG). This HbA1c approach was then validated in the Type 1 Diabetes TrialNet Pathway to Prevention Study (TrialNet) (n = 1,190). A 10% relative HbA1c increase from baseline best marked the increased risk of stage 3 in TEDDY (74% sensitive; 88% specific). Significant predictors of risk for HbA1c change were age and HbA1c at the baseline test, genetic sex, maximum number of autoantibodies, and maximum rate of HbA1c increase by time of change. The multivariable model featuring a HbA1c ≥10% increase and these additional factors revealed increased risk of stage 3 in TEDDY (hazard ratio [HR] 12.74, 95% CI 8.7-18.6, P < 0.0001) and TrialNet (HR 5.09, 95% CI 3.3-7.9, P < 0.0001). Furthermore, the composite model using HbA1c ≥10% increase performed similarly to an OGTT 2-hPG composite model (TEDDY area under the curve [AUC] 0.88 and 0.85, respectively) and to the HbA1c model in TrialNet (AUC 0.82). An increase of ≥10% in HbA1c from baseline is as informative as OGTT 2-hPG in predicting risk of stage 3 in youth with genetic risk and diabetes-associated autoantibodies.

Sources of dietary gluten in the first 2 years of life and associations with celiac disease autoimmunity and celiac disease in Swedish genetically predisposed children: The Environmental Determinants of Diabetes in the Young (TEDDY) study

ABSTRACTBackgroundHigh gluten intake is associated with increased risk of celiac disease (CD) in children at genetic risk.ObjectivesWe aimed to investigate if different dietary gluten sources up to age 2 y confer different risks of celiac disease autoimmunity (CDA) and CD in children at genetic risk.MethodsThree-day food records were collected at ages 6, 9, 12, 18, and 24 mo from 2088 Swedish genetically at-risk children participating in a 15-y follow-up cohort study on type 1 diabetes and CD. Screening for CD was performed with tissue transglutaminase autoantibodies (tTGA). The primary outcome was CDA, defined as persistent tTGA positivity. The secondary outcome was CD, defined as having a biopsy specimen showing Marsh score ≥ 2 or an averaged tTGA level ≥ 100 Units. Cox regression adjusted for total gluten intake estimated HRs with 95% CIs for daily intake of gluten sources.ResultsDuring follow-up, 487 (23.3%) children developed CDA and 242 (11.6%) developed CD. Daily intake of ≤158 g porridge at age 9 mo was associated with increased risk of CDA (HR: 1.53; 95% CI: 1.05, 2.23; P = 0.026) compared with no intake. A high daily bread intake (>18.3 g) at age 12 mo was associated with increased risk of both CDA (HR: 1.47; 95% CI: 1.05, 2.05; P = 0.023) and CD (HR: 1.79; 95% CI: 1.10, 2.91; P = 0.019) compared with no intake. At age 18 mo, milk cereal drink was associated with an increased risk of CD (HR: 1.16; 95% CI: 1.00, 1.33; P = 0.047) per 200-g/d increased intake. No association was found for other gluten sources up to age 24 mo and risk of CDA or CD.ConclusionsHigh daily intakes of bread at age 12 mo and of milk cereal drink during the second year of life are associated with increased risk of both CDA and CD in genetically at-risk children.

The association of physical activity to oral glucose tolerance test outcomes in multiple autoantibody positive children: The TEDDY Study.

To examine the association of physical activity (PA), measured by accelerometry, to hemoglobin AIC (HbA1c) and oral glucose tolerance test (OGTT) outcomes in children who were multiple persistent confirmed autoantibody positive for type 1 diabetes (T1D). The Environmental Determinants of Diabetes in the Young (TEDDY) multinational study followed children from birth. Children ≥3 years of age who were multiple persistent confirmed autoantibody positive were monitored by OGTTs every 6 months. TEDDY children's PA was measured by accelerometry beginning at 5 years of age. We examined the relationship between moderate plus vigorous (mod + vig) PA, HbA1c, and OGTT in 209 multiple autoantibody children who had both OGTT and PA measurements. Mod + vig PA was associated with both glucose and C-peptide measures (fasting, 120-min, and AUC); higher mod + vig PA was associated with a better OGTT response primarily in children with longer duration of multiple autoantibody positivity. Mod + vig PA also interacted with child age; lower mod + vig PA was associated with a greater increase in C-peptide response across age. Mod + vig PA was not related to fasting insulin, HOMA-IR or HbA1c. The OGTT is the gold standard for diabetes diagnosis and is used to monitor those at high risk for T1D. We found higher levels of mod + vig PA were associated with better OGTT outcomes in children ≥5 years of age who have been multiple autoantibody positive for longer periods of time. Physical activity should be the focus of future efforts to better understand the determinants of disease progression in high-risk children.

Islet autoantibody seroconversion in type-1 diabetes is associated with metagenome-assembled genomes in infant gut microbiomes

The immune system of some genetically susceptible children can be triggered by certain environmental factors to produce islet autoantibodies (IA) against pancreatic β cells, which greatly increases their risk for Type-1 diabetes. An environmental factor under active investigation is the gut microbiome due to its important role in immune system education. Here, we study gut metagenomes that are de-novo-assembled in 887 at-risk children in the Environmental Determinants of Diabetes in the Young (TEDDY) project. Our results reveal a small set of core protein families, present in >50% of the subjects, which account for 64% of the sequencing reads. Time-series binning generates 21,536 high-quality metagenome-assembled genomes (MAGs) from 883 species, including 176 species that hitherto have no MAG representation in previous comprehensive human microbiome surveys. IA seroconversion is positively associated with 2373 MAGs and negatively with 1549 MAGs. Comparative genomics analysis identifies lipopolysaccharides biosynthesis in Bacteroides MAGs and sulfate reduction in Anaerostipes MAGs as functional signatures of MAGs with positive IA-association. The functional signatures in the MAGs with negative IA-association include carbohydrate degradation in lactic acid bacteria MAGs and nitrate reduction in Escherichia MAGs. Overall, our results show a distinct set of gut microorganisms associated with IA seroconversion and uncovered the functional genomics signatures of these IA-associated microorganisms