Caesarean section and risk of type 1 diabetes.

AIMS/HYPOTHESIS: Delivery by Caesarean section continues to rise globally and has been associated with the risk of developing type 1 diabetes and the rate of progression from pre-symptomatic stage 1 or 2 type 1 diabetes to symptomatic stage 3 disease. The aim of this study was to examine the association between Caesarean delivery and progression to stage 3 type 1 diabetes in children with pre-symptomatic early-stage type 1 diabetes. METHODS: Caesarean section was examined in 8135 children from the TEDDY study who had an increased genetic risk for type 1 diabetes and were followed from birth for the development of islet autoantibodies and type 1 diabetes. RESULTS: The likelihood of delivery by Caesarean section was higher in children born to mothers with type 1 diabetes (adjusted OR 4.61, 95% CI 3.60, 5.90, p<0.0001), in non-singleton births (adjusted OR 4.35, 95% CI 3.21, 5.88, p<0.0001), in premature births (adjusted OR 1.91, 95% CI 1.53, 2.39, p<0.0001), in children born in the USA (adjusted OR 2.71, 95% CI 2.43, 3.02, p<0.0001) and in children born to older mothers (age group >28-33 years: adjusted OR 1.19, 95% CI 1.04, 1.35, p=0.01; age group >33 years: adjusted OR 1.80, 95% CI 1.58, 2.06, p<0.0001). Caesarean section was not associated with an increased risk of developing pre-symptomatic early-stage type 1 diabetes (risk by age 10 years 5.7% [95% CI 4.6%, 6.7%] for Caesarean delivery vs 6.6% [95% CI 6.0%, 7.3%] for vaginal delivery, p=0.07). Delivery by Caesarean section was associated with a modestly increased rate of progression to stage 3 type 1 diabetes in children who had developed multiple islet autoantibody-positive pre-symptomatic early-stage type 1 diabetes (adjusted HR 1.36, 95% CI 1.03, 1.79, p=0.02). No interaction was observed between Caesarean section and non-HLA SNPs conferring susceptibility for type 1 diabetes. CONCLUSIONS/INTERPRETATION: Caesarean section increased the rate of progression to stage 3 type 1 diabetes in children with pre-symptomatic early-stage type 1 diabetes. DATA AVAILABILITY: Data from the TEDDY study ( https://doi.org/10.58020/y3jk-x087 ) reported here will be made available for request at the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository (NIDDK-CR) Resources for Research (R4R) ( https://repository.niddk.nih.gov/ ).

Diabetes Study of Children of Diverse Ethnicity and Race: Study design.

AIMS: Determining diabetes type in children has become increasingly difficult due to an overlap in typical characteristics between type 1 diabetes (T1D) and type 2 diabetes (T2D). The Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) programme is a National Institutes of Health (NIH)-supported multicenter, prospective, observational study that enrols children and adolescents with non-secondary diabetes. The primary aim of the study was to develop improved models to differentiate between T1D and T2D in diverse youth. MATERIALS AND METHODS: The proposed models will evaluate the utility of three existing T1D genetic risk scores in combination with data on islet autoantibodies and other parameters typically available at the time of diabetes onset. Low non-fasting serum C-peptide (<0.6 nmol/L) between 3 and 10 years after diabetes diagnosis will be considered a biomarker for T1D as it reflects the loss of insulin secretion ability. Participating centres are enrolling youth (<19 years old) either with established diabetes (duration 3-10 years) for a cross-sectional evaluation or with recent onset diabetes (duration 3 weeks-15 months) for the longitudinal observation with annual visits for 3 years. Cross-sectional data will be used to develop models. Longitudinal data will be used to externally validate the best-fitting model. RESULTS: The results are expected to improve the ability to classify diabetes type in a large and growing subset of children who have an unclear form of diabetes at diagnosis. CONCLUSIONS: Accurate and timely classification of diabetes type will help establish the correct clinical management early in the course of the disease.

The human gut microbiome in early-onset type 1 diabetes from the TEDDY study.

Type 1 diabetes (T1D) is an autoimmune disease that targets pancreatic islet beta cells and incorporates genetic and environmental factors1, including complex genetic elements2, patient exposures3 and the gut microbiome4. Viral infections5 and broader gut dysbioses6 have been identified as potential causes or contributing factors; however, human studies have not yet identified microbial compositional or functional triggers that are predictive of islet autoimmunity or T1D. Here we analyse 10,913 metagenomes in stool samples from 783 mostly white, non-Hispanic children. The samples were collected monthly from three months of age until the clinical end point (islet autoimmunity or T1D) in the The Environmental Determinants of Diabetes in the Young (TEDDY) study, to characterize the natural history of the early gut microbiome in connection to islet autoimmunity, T1D diagnosis, and other common early life events such as antibiotic treatments and probiotics. The microbiomes of control children contained more genes that were related to fermentation and the biosynthesis of short-chain fatty acids, but these were not consistently associated with particular taxa across geographically diverse clinical centres, suggesting that microbial factors associated with T1D are taxonomically diffuse but functionally more coherent. When we investigated the broader establishment and development of the infant microbiome, both taxonomic and functional profiles were dynamic and highly individualized, and dominated in the first year of life by one of three largely exclusive Bifidobacterium species (B. bifidum, B. breve or B. longum) or by the phylum Proteobacteria. In particular, the strain-specific carriage of genes for the utilization of human milk oligosaccharide within a subset of B. longum was present specifically in breast-fed infants. These analyses of TEDDY gut metagenomes provide, to our knowledge, the largest and most detailed longitudinal functional profile of the developing gut microbiome in relation to islet autoimmunity, T1D and other early childhood events. Together with existing evidence from human cohorts7,8 and a T1D mouse model9, these data support the protective effects of short-chain fatty acids in early-onset human T1D.

Temporal development of the gut microbiome in early childhood from the TEDDY study.

The development of the microbiome from infancy to childhood is dependent on a range of factors, with microbial-immune crosstalk during this time thought to be involved in the pathobiology of later life diseases1-9 such as persistent islet autoimmunity and type 1 diabetes10-12. However, to our knowledge, no studies have performed extensive characterization of the microbiome in early life in a large, multi-centre population. Here we analyse longitudinal stool samples from 903 children between 3 and 46 months of age by 16S rRNA gene sequencing (n = 12,005) and metagenomic sequencing (n = 10,867), as part of the The Environmental Determinants of Diabetes in the Young (TEDDY) study. We show that the developing gut microbiome undergoes three distinct phases of microbiome progression: a developmental phase (months 3-14), a transitional phase (months 15-30), and a stable phase (months 31-46). Receipt of breast milk, either exclusive or partial, was the most significant factor associated with the microbiome structure. Breastfeeding was associated with higher levels of Bifidobacterium species (B. breve and B. bifidum), and the cessation of breast milk resulted in faster maturation of the gut microbiome, as marked by the phylum Firmicutes. Birth mode was also significantly associated with the microbiome during the developmental phase, driven by higher levels of Bacteroides species (particularly B. fragilis) in infants delivered vaginally. Bacteroides was also associated with increased gut diversity and faster maturation, regardless of the birth mode. Environmental factors including geographical location and household exposures (such as siblings and furry pets) also represented important covariates. A nested case-control analysis revealed subtle associations between microbial taxonomy and the development of islet autoimmunity or type 1 diabetes. These data determine the structural and functional assembly of the microbiome in early life and provide a foundation for targeted mechanistic investigation into the consequences of microbial-immune crosstalk for long-term health.

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.

Dietary Intake and Body Mass Index Influence the Risk of Islet Autoimmunity in Genetically At-Risk Children: A Mediation Analysis Using the TEDDY Cohort.

Background/Objective: Growth and obesity have been associated with increased risk of islet autoimmunity (IA) and progression to type 1 diabetes. We aimed to estimate the effect of energy-yielding macronutrient intake on the development of IA through BMI. Research Design and Methods: Genetically at-risk children (n = 5,084) in Finland, Germany, Sweden, and the USA, who were autoantibody negative at 2 years of age, were followed to the age of 8 years, with anthropometric measurements and 3-day food records collected biannually. Of these, 495 (9.7%) children developed IA. Mediation analysis for time-varying covariates (BMI z-score) and exposure (energy intake) was conducted. Cox proportional hazard method was used in sensitivity analysis. Results: We found an indirect effect of total energy intake (estimates: indirect effect 0.13 [0.05, 0.21]) and energy from protein (estimates: indirect effect 0.06 [0.02, 0.11]), fat (estimates: indirect effect 0.03 [0.01, 0.05]), and carbohydrates (estimates: indirect effect 0.02 [0.00, 0.04]) (kcal/day) on the development of IA. A direct effect was found for protein, expressed both as kcal/day (estimates: direct effect 1.09 [0.35, 1.56]) and energy percentage (estimates: direct effect 72.8 [3.0, 98.0]) and the development of GAD autoantibodies (GADA). In the sensitivity analysis, energy from protein (kcal/day) was associated with increased risk for GADA, hazard ratio 1.24 (95% CI: 1.09, 1.53), p = 0.042. Conclusions: This study confirms that higher total energy intake is associated with higher BMI, which leads to higher risk of the development of IA. A diet with larger proportion of energy from protein has a direct effect on the development of GADA.

A robust and transformation-free joint model with matching and regularization for metagenomic trajectory and disease onset.

BACKGROUND: To identify operational taxonomy units (OTUs) signaling disease onset in an observational study, a powerful strategy was selecting participants by matched sets and profiling temporal metagenomes, followed by trajectory analysis. Existing trajectory analyses modeled individual OTU or microbial community without adjusting for the within-community correlation and matched-set-specific latent factors. RESULTS: We proposed a joint model with matching and regularization (JMR) to detect OTU-specific trajectory predictive of host disease status. The between- and within-matched-sets heterogeneity in OTU relative abundance and disease risk were modeled by nested random effects. The inherent negative correlation in microbiota composition was adjusted by incorporating and regularizing the top-correlated taxa as longitudinal covariate, pre-selected by Bray-Curtis distance and elastic net regression. We designed a simulation pipeline to generate true biomarkers for disease onset and the pseudo biomarkers caused by compositionality. We demonstrated that JMR effectively controlled the false discovery and pseudo biomarkers in a simulation study generating temporal high-dimensional metagenomic counts with random intercept or slope. Application of the competing methods in the simulated data and the TEDDY cohort showed that JMR outperformed the other methods and identified important taxa in infants' fecal samples with dynamics preceding host disease status. CONCLUSION: Our method JMR is a robust framework that models taxon-specific trajectory and host disease status for matched participants without transformation of relative abundance, improving the power of detecting disease-associated microbial features in certain scenarios. JMR is available in R package mtradeR at https://github.com/qianli10000/mtradeR.

The clinical consequences of heterogeneity within and between different diabetes types.

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Progression from islet autoimmunity to clinical type 1 diabetes is influenced by genetic factors: results from the prospective TEDDY study.

BACKGROUND: Progression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown. METHODS: In 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression. RESULTS: Islet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93). CONCLUSIONS: Genetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children.

OBJECTIVE: The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. METHODS: Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and presence of insulinoma-associated-2 autoantibodies (IA-2A). RESULTS: A total of 363 subjects had at least one autoantibody at age 3. Twenty-one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors - IA-2A status, hemoglobin A1c, body mass index Z-score, single-nucleotide polymorphism rs12708716_G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models. CONCLUSIONS: This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3-year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches.

Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: A prospective study in children.

BACKGROUND: Around 0.3% of newborns will develop autoimmunity to pancreatic beta cells in childhood and subsequently develop type 1 diabetes before adulthood. Primary prevention of type 1 diabetes will require early intervention in genetically at-risk infants. The objective of this study was to determine to what extent genetic scores (two previous genetic scores and a merged genetic score) can improve the prediction of type 1 diabetes. METHODS AND FINDINGS: The Environmental Determinants of Diabetes in the Young (TEDDY) study followed genetically at-risk children at 3- to 6-monthly intervals from birth for the development of islet autoantibodies and type 1 diabetes. Infants were enrolled between 1 September 2004 and 28 February 2010 and monitored until 31 May 2016. The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. In the children with the HLA risk genotypes, risk for developing multiple islet autoantibodies was 5.8% (95% CI 5.0%-6.6%) by age 6 years, and risk for diabetes by age 10 years was 3.7% (95% CI 3.0%-4.4%). Risk for developing multiple islet autoantibodies was 11.0% (95% CI 8.7%-13.3%) in children with a merged genetic score of >14.4 (upper quartile; n = 907) compared to 4.1% (95% CI 3.3%-4.9%, P < 0.001) in children with a genetic score of ≤14.4 (n = 2,591). Risk for developing diabetes by age 10 years was 7.6% (95% CI 5.3%-9.9%) in children with a merged score of >14.4 compared with 2.7% (95% CI 1.9%-3.6%) in children with a score of ≤14.4 (P < 0.001). Of 173 children with multiple islet autoantibodies by age 6 years and 107 children with diabetes by age 10 years, 82 (sensitivity, 47.4%; 95% CI 40.1%-54.8%) and 52 (sensitivity, 48.6%, 95% CI 39.3%-60.0%), respectively, had a score >14.4. Scores were higher in European versus US children (P = 0.003). In children with a merged score of >14.4, risk for multiple islet autoantibodies was similar and consistently >10% in Europe and in the US; risk was greater in males than in females (P = 0.01). Limitations of the study include that the genetic scores were originally developed from case-control studies of clinical diabetes in individuals of mainly European decent. It is, therefore, possible that it may not be suitable to all populations. CONCLUSIONS: A type 1 diabetes genetic score identified infants without family history of type 1 diabetes who had a greater than 10% risk for pre-symptomatic type 1 diabetes, and a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone. This finding extends the possibilities for enrolling children into type 1 diabetes primary prevention trials.

Gestational respiratory infections interacting with offspring HLA and CTLA-4 modifies incident ß-cell autoantibodies.

ß-cell autoantibodies against insulin (IAA), GAD65 (GADA) and IA-2 (IA-2A) precede onset of childhood type 1 diabetes (T1D). Incidence of the first appearing ß-cell autoantibodies peaks at a young age and is patterned by T1D-associated genes, suggesting an early environmental influence. Here, we tested if gestational infections and interactions with child's human leukocyte antigen (HLA) and non-HLA genes affected the appearance of the first ß-cell autoantibody. Singletons of mothers without diabetes (n = 7472) with T1D-associated HLA-DR-DQ genotypes were prospectively followed quarterly through the first 4 years of life, then semiannually until age 6 years, using standardized autoantibody analyses. Maternal infections during pregnancy were assessed via questionnaire 3-4.5 months post-delivery. Polymorphisms in twelve non-HLA genes associated with the first appearing ß-cell autoantibodies were included in a Cox regression analysis. IAA predominated as the first appearing ß-cell autoantibody in younger children (n = 226, median age at seroconversion 1.8 years) and GADA (n = 212; 3.2 years) in children aged ≥2 years. Gestational infections were not associated with the first appearing ß-cell autoantibodies overall. However, gestational respiratory infections (G-RI) showed a consistent protective influence on IAA (HR 0.64, 95% CI 0.45-0.91) among CTLA4-(AG, GG) children (G-RI*CTLA4 interaction, p = 0.002). The predominant associations of HLA-DR-DQ 4-8/8-4 with IAA and HLA-DR-DQ 3-2/3-2 with GADA were not observed if a G-RI was reported (G-RI*HLA-DR-DQ interaction, p = 0.03). The role of G-RI may depend on offspring HLA and CTLA-4 alleles and supports a bidirectional trigger for IAA or GADA as a first appearing ß-cell autoantibody in early life.

The feasibility of salivary sample collection in an international pediatric cohort: The the TEDDY study.

Saliva offers a relatively noninvasive method for measuring analytes such as cortisol, holding particular promise for use in pediatric populations on a large scale if a rigorous collection protocol is feasible in diverse settings. The Environmental Determinants of Diabetes in the Young study protocol, conducted in centers in the United States, Sweden, Finland, and Germany, used salivary collection to assess cortisol level as a physiologic marker of stress. Saliva was collected using Sorbettes from subjects at 3.5, 4.5, and 5.5 years of age. Parents collected a morning sample, and staff collected pre- and post-blood draw samples. Feasibility was assessed based on protocol completion, adherence with instructions, factors affecting adherence, and sufficiency of saliva sample for cortisol determination. Collection of saliva samples in a diverse pediatric population is feasible. Establishing non-invasive and acceptable methods for collecting physiological parameters of stress will allow better exploration of determinants of health in this important population.

Age at first introduction to complementary foods is associated with sociodemographic factors in children with increased genetic risk of developing type 1 diabetes.

Infant's age at introduction to certain complementary foods (CF) has in previous studies been associated with islet autoimmunity, which is an early marker for type 1 diabetes (T1D). Various maternal sociodemographic factors have been found to be associated with early introduction to CF. The aims of this study were to describe early infant feeding and identify sociodemographic factors associated with early introduction to CF in a multinational cohort of infants with an increased genetic risk for T1D. The Environmental Determinants of Diabetes in the Young study is a prospective longitudinal birth cohort study. Infants (N = 6404) screened for T1D high risk human leucocyte antigen-DQ genotypes (DR3/4, DR4/4, DR4/8, DR3/3, DR4/4, DR4/1, DR4/13, DR4/9 and DR3/9) were followed for 2 years at six clinical research centres: three in the United States (Colorado, Georgia/Florida, Washington) and three in Europe (Sweden, Finland, Germany). Age at first introduction to any food was reported at clinical visits every third month from the age of 3 months. Maternal sociodemographic data were self-reported through questionnaires. Age at first introduction to CF was primarily associated with country of residence. Root vegetables and fruits were usually the first CF introduced in Finland and Sweden and cereals were usually the first CF introduced in the United States. Between 15% and 20% of the infants were introduced to solid foods before the age of 4 months. Young maternal age (<25 years), low educational level (<12 years) and smoking during pregnancy were significant predictors of early introduction to CF in this cohort. Infants with a relative with T1D were more likely to be introduced to CF later.

Children followed in the TEDDY study are diagnosed with type 1 diabetes at an early stage of disease.

OBJECTIVE: The Environmental Determinants of Diabetes in the Young (TEDDY) study is designed to identify environmental exposures triggering islet autoimmunity and type 1 diabetes (T1D) in genetically high-risk children. We describe the first 100 participants diagnosed with T1D, hypothesizing that (i) they are diagnosed at an early stage of disease, (ii) a high proportion are diagnosed by an oral glucose tolerance test (OGTT), and (iii) risk for early T1D is related to country, population, human leukocyte antigen (HLA)-genotypes and immunological markers. METHODS: Autoantibodies to glutamic acid decarboxylase (GADA), insulinoma-associated protein 2 (IA-2) and insulin (IAA) were analyzed from 3 months of age in children with genetic risk. Symptoms and laboratory values at diagnosis were obtained and reviewed for ADA criteria. RESULTS: The first 100 children to develop T1D, 33 first-degree relatives (FDRs), with a median age 2.3 yr (0.69-6.27), were diagnosed between September 2005 and November 2011. Although young, 36% had no symptoms and ketoacidosis was rare (8%). An OGTT diagnosed 9/30 (30%) children above 3 yr of age but only 4/70 (5.7%) below the age of 3 yr. FDRs had higher cumulative incidence than children from the general population (p < 0.0001). Appearance of all three autoantibodies at seroconversion was associated with the most rapid development of T1D (HR = 4.52, p = 0.014), followed by the combination of GADA and IAA (HR = 2.82, p < 0.0001). CONCLUSIONS: Close follow-up of children with genetic risk enables early detection of T1D. Risk factors for rapid development of diabetes in this young population were FDR status and initial positivity for GADA, IA-2, and IAA or a combination of GADA and IAA.

Infant feeding patterns in families with a diabetes history - observations from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study.

OBJECTIVE: To assess the association between diabetes family history and infant feeding patterns. DESIGN: Data on breast-feeding duration and age at first introduction of cow's milk and gluten-containing cereals were collected in 3-month intervals during the first 24 months of life. SETTING: Data from the multicentre TEDDY (The Environmental Determinants of Diabetes in the Young) study, including centres in the USA, Sweden, Finland and Germany. SUBJECTS: A total of 7026 children, including children with a mother with type 1 diabetes (T1D; n 292), gestational diabetes mellitus (GDM; n 404) or without diabetes but with a father and/or sibling with T1D (n 464) and children without diabetes family history (n 5866). RESULTS: While exclusive breast-feeding ended earlier and cow's milk was introduced earlier in offspring of mothers with T1D and GDM, offspring of non-diabetic mothers but a father and/or sibling with T1D were exclusively breast-fed longer and introduced to cow's milk later compared with infants without diabetes family history. The association between maternal diabetes and shorter exclusive breast-feeding duration was attenuated after adjusting for clinical variables (delivery mode, gestational age, Apgar score and birth weight). Country-specific analyses revealed differences in these associations, with Sweden showing the strongest and Finland showing no association between maternal diabetes and breast-feeding duration. CONCLUSIONS: Family history of diabetes is associated with infant feeding patterns; however, the associations clearly differ by country, indicating that cultural differences are important determinants of infant feeding behaviour. These findings need to be considered when developing strategies to improve feeding patterns in infants with a diabetes family history.

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

Context: The 2 peaks of type 1 diabetes incidence occur during early childhood and puberty. Objective: We sought to better understand the relationship between puberty, islet autoimmunity, and type 1 diabetes. Methods: 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. Results: 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. Conclusion: 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.

Methods, quality control and specimen management in an international multicentre investigation of type 1 diabetes: TEDDY.

BACKGROUND: The vast array and quantity of longitudinal samples collected in The Environmental Determinants of Diabetes in the Young study present a series of challenges in terms of quality control procedures and data validity. To address this, pilot studies have been conducted to standardize and enhance both biospecimen collection and sample obtainment in terms of autoantibody collection, stool sample preservation, RNA, biomarker stability, metabolic biomarkers and T-cell viability. RESEARCH DESIGN AND METHODS: The Environmental Determinants of Diabetes in the Young is a multicentre, international prospective study (n = 8677) designed to identify environmental triggers of type 1 diabetes (T1D) in genetically at-risk children from ages 3 months until 15 years. The study is conducted through six primary clinical centres located in four countries. RESULTS: As of May 2012, over three million biological samples and 250 million total data points have been collected, which will be analysed to assess autoimmunity status, presence of inflammatory biomarkers, genetic factors, exposure to infectious agents, dietary biomarkers and other potentially important environmental exposures in relation to autoimmunity and progression to T1D. CONCLUSIONS: Detailed procedures were utilized to standardize both data harmonization and management when handling a large quantity of longitudinal samples obtained from multiple locations. In addition, a description of the available specimens is provided that serve as an invaluable repository for the elucidation of determinants in T1D focusing on autoantibody concordance and harmonization, transglutaminase autoantibody, inflammatory biomarkers (T-cells), genetic proficiency testing, RNA lab internal quality control testing, infectious agents (monitoring cross-contamination, virus preservation and nasal swab collection validity) and HbA1c testing.

The changing landscape of type 1 diabetes: recent developments and future frontiers.

Type 1 diabetes (T1D) research has made great strides over the past decade with advances in understanding the pathogenesis, natural history, candidate environmental exposures, exposure triggering time, disease prediction, and diagnosis. Major monitoring efforts have provided baseline historical measures, leading to better epidemiological studies incorporating longitudinal biosamples (ie, biobanks), which have allowed for new technologies ('omics') to further expose the etiological agents responsible for the initiation, progression, and eventual clinical onset of T1D. These new frontiers have brought forth high-dimensionality data, which have furthered the evidence of the heterogeneous nature of T1D pathogenesis and allowed for a more mechanistic approach in understanding the etiology of T1D. This review will expand on the most recent advances in the quest for T1D determinants, drawing upon novel research tools that epidemiology, genetics, microbiology, and immunology have provided, linking them to the major hypotheses associated with T1D etiology, and discussing the future frontiers.

Use of dietary supplements in pregnant women in relation to sociodemographic factors - a report from The Environmental Determinants of Diabetes in the Young (TEDDY) study.

OBJECTIVES: The aim of the present study was to examine the prevalence and associated factors of dietary supplement use, particularly supplements containing vitamin D and fatty acids, in pregnant women enrolled in a multi-national study. DESIGN: The Environmental Determinants of Diabetes in the Young (TEDDY) study is a prospective longitudinal cohort study. Maternal dietary supplement use was self-reported through questionnaires at month 3 to 4 postpartum. SETTING: Six clinical research centres; three in the USA (Colorado, Georgia/Florida and Washington) and three in Europe (Sweden, Finland and Germany). SUBJECTS: Mothers (n 7326) to infants screened for high-risk HLA-DQ genotypes of type 1 diabetes. RESULTS: Ninety-two per cent of the 7326 women used one or more types of supplement during pregnancy. Vitamin D supplements were taken by 65% of the women, with the highest proportion of users in the USA (80.5 %). Overall, 16% of the women reported taking fatty acid supplements and a growing trend was seen in all countries between 2004 and 2010 (P,0.0001). The use was more common in Germany (32 %) and the USA (24 %) compared with Finland (8.5%) and Sweden (7.0 %). Being pregnant with the first child was a strong predictor for any supplement use in all countries. Low maternal age (<25 years), higher education, BMI<=25.0 kg/m2 and smoking during pregnancy were factors associated with supplement use in some but not all countries. CONCLUSIONS: The majority of the women used dietary supplements during pregnancy. The use was associated with sociodemographic and behavioural factors, such as parity, maternal age, education, BMI and maternal smoking.