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AIMS/HYPOTHESIS: Prognostic factors and characteristics of children diagnosed with type 1 diabetes before 6years of age were compared with those diagnosed at 6-13years of age in the TEDDY study. METHODS: Genetically high-risk children (n = 8502) were followed from birth for a median of 9.9years; 328 (3.9%) were diagnosed with type 1 diabetes. Cox proportional hazard model was used to assess the association of prognostic factors with the risk of type 1 diabetes in the two age groups. RESULTS: Children in the younger group tended to develop autoantibodies earlier than those in the older group did (mean age 1.5 vs 3.5years), especially insulin autoantibodies (IAA), which developed earlier than GAD autoantibodies (GADA). Children in the younger group also progressed to diabetes more rapidly than the children in the older group did (mean duration 1.9 vs 5.4 years). Children with autoantibodies first appearing against insulinoma antigen-2 (IA-2A) were found only in the older group. The significant diabetes risk associated with the country of origin in the younger group was no longer significant in the older group. Conversely, the diabetes risk associated with HLA genotypes was statistically significant also in the older group. Initial seroconversion after and before 2years of age was associated with decreased risk for diabetes diagnosis in children positive for multiple autoantibodies, but the diabetes risk did not decrease further with increasing age if initial seroconversion occurred after age 2. Diabetes risk associated with the minor alleles of rs1004446 (INS) was decreased in both the younger and older groups compared with other genotypes (HR 0.67). Diabetes risk was significantly increased with the minor alleles of rs2476601 (PTPN22) (HR 2.04 and 1.72), rs428595 (PPIL2) (HR 2.13 and 2.10), rs113306148 (PLEKHA1) (HR 2.34 and 2.21) and rs73043122 (RNASET2) (HR 2.31 and 2.54) (HR values represent the younger and older groups, respectively). CONCLUSIONS/INTERPRETATIONS: Diabetes at an early age is likely to be preceded by IAA autoantibodies and is a more aggressive form of the disease. Among older children, once multiple autoantibodies have been observed there does not seem to be any association between progression to diabetes and the age of the child or family history. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00279318.

BACKGROUND: Breastfeeding has beneficial effects on numerous health outcomes. OBJECTIVES: We investigated whether breastfeeding duration is associated with the development of early childhood autoimmunity, allergies, or obesity in a multinational prospective birth cohort. METHODS: Infants with genetic susceptibility for type 1 diabetes (n=8676) were followed for the development of autoantibodies to islet autoantigens or transglutaminase, allergies, and for anthropometric measurements to a median age of 8.3 y (IQR: 2.8-10.2y). Information on breastfeeding was collected at 3 mo of age and prospectively thereafter. A propensity score for longer breastfeeding was calculated from the variables that were likely to influence any or exclusive breastfeeding. The risks of developing autoimmunity or allergy were assessed using Cox proportional hazards models, and the risk of obesity at 5.5 y of age was assessed using logistic regression with adjustment by the propensity score. RESULTS: Breastfeeding duration was not associated with a lower risk of either islet or transglutaminase autoimmunity (any breastfeeding>6 mo, adjusted HR: 1.07; 95% CI: 0.96, 1.19; exclusive breastfeeding>3 mo, adjusted HR: 1.03; 95% CI: 0.92, 1.15). Exclusive breastfeeding>3 mo was associated with a decreased risk of seasonal allergic rhinitis (adjusted HR: 0.70; 95% CI: 0.53, 0.92; P6 mo and exclusive breastfeeding>3mo were associated with decreased risk of obesity (adjusted OR: 0.62; 95% CI: 0.47, 0.81; P&nbsp

AIMS/HYPOTHESIS: We aimed to investigate the association between maternal consumption of gluten-containing foods and other selected foods during late pregnancy and offspring risk of islet autoimmunity (IA) and type 1 diabetes in The Environmental Determinants of Diabetes in the Young (TEDDY) study. METHODS: The TEDDY study recruited children at high genetic risk for type 1 diabetes at birth, and prospectively follows them for the development of IA and type 1 diabetes (n=8556). A questionnaire on the mother’s diet in late pregnancy was completed by 3-4 months postpartum. The maternal daily intake was estimated from a food frequency questionnaire for eight food groups: gluten-containing foods, non-gluten cereals, fresh milk, sour milk, cheese products, soy products, lean/medium-fat fish and fatty fish. For each food, we described the distribution of maternal intake among the four participating countries in the TEDDY study and tested the association of tertile of maternal food consumption with risk of IA and type 1 diabetes using forward selection time-to-event Cox regression. RESULTS: By 28 February 2019, 791 cases of IA and 328 cases of type 1 diabetes developed in TEDDY. There was no association between maternal late-pregnancy consumption of gluten-containing foods or any of the other selected foods and risk of IA, type 1 diabetes, insulin autoantibody-first IA or GAD autoantibody-first IA (all p≥0.01). Maternal gluten-containing food consumption in late pregnancy was higher in Sweden (242 g/day), Germany (247 g/day) and Finland (221 g/day) than in the USA (199 g/day) (pairwise p

Altered maternal haemoglobin levels during pregnancy are associated with pre-clinical and clinical conditions affecting the fetus. Evidence from animal models suggests that these associations may be partially explained by differential DNA methylation in the newborn with possible long-term consequences. To test this in humans, we meta-analyzed the epigenome-wide associations of maternal haemoglobin levels during pregnancy with offspring DNA methylation in 3,967 newborn cord blood and 1,534 children and 1,962 adolescent whole-blood samples derived from 10 cohorts. DNA methylation was measured using Illumina Infinium Methylation 450K or MethylationEPIC arrays covering 450,000 and 850,000 methylation sites, respectively. There was no statistical support for the association of maternal haemoglobin levels with offspring DNA methylation either at individual methylation sites or clustered in regions. For most participants, maternal haemoglobin levels were within the normal range in the current study, whereas adverse perinatal outcomes often arise at the extremes. Thus, this study does not rule out the possibility that associations with offspring DNA methylation might be seen in studies with more extreme maternal haemoglobin levels. Study-specific funding information can be found in the Supplementary Methods. JR, AH, EL, and SS were supported by the European Union’s Horizon 2020 research and innovation program [grant numbers 633595 (DynaHEALTH) and 733206 (LifeCycle)], Academy of Finland [grant number 285547 (EGEA)] and the Biocenter Oulu. ACJ was funded by the National Institute of Environmental Health Sciences [grant number R00ES023450]. AK was supported by the National Institute of Environmental Health Sciences [grant number R01ES021357]. DCa was funded by the UK Medical Research Council [grant number MC_UU_00011/7]. EKa received funding from the Horizon2020 grant for RECAP Research on Children and Adults Born Preterm [grant number 733280], Academy of Finland [grant number 315690], Foundation for Pediatric Research, Novo Nordisk Foundation, Signe and Ane Gyllenberg Foundation and Sigrid Jusélius Foundation. EKe received funding from the Finnish Medical Association. MG was supported by Miguel Servet fellowship from the Institute of Health Carlos III [grant numbers MS13/00054, CP18/00018]. MVä received funding from the Research Funds of Oulu University Hospital, Juho Vainio Foundation and Signe and Ane Gyllenberg Foundation. RCH was supported by the National Health and Medical Research Council Fellowship Grants [grant number 1053384]. SJL was supported by the intramural research program of the National Institutes of Health, National Institute of Environmental Health Sciences. SM received funding from the University of Oulu Graduate School. SR was supported by National Health and Medical Research Council EU [grant number 1142858] and the Department of Health, Western Australia FutureHealth fund in connection with the European Union’s Horizon 2020 [grant number 733206].

Type 1 diabetes (T1D)—an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency—often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6–9. Autoantibody surveillance programs effectively prevent most ketoacidosis10–12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve ≥ 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection. In a study of children with high genetic risk aged 2 years or older, a risk score integrating pancreatic islet autoantibodies, genetic factors and family history is highly predictive of type 1 diabetes in the subsequent 8 years.

IntroductionThe Global Platform for the Prevention of Autoimmune Diabetes-SINT1A Study is designed as a randomised, placebo-controlled, double-blind, multicentre, multinational, primary prevention study aiming to assess whether daily administration of Bifidobacterium infantis from age 7 days to 6 weeks until age 12 months to children with elevated genetic risk for type 1 diabetes reduces the cumulative incidence of beta-cell autoantibodies in childhood.Methods and analysisInfants aged 7 days to 6 weeks from Germany, Poland, Belgium, UK and Sweden are eligible for study participation if they have a >10.0% expected risk for developing multiple beta-cell autoantibodies by age 6 years as determined by genetic risk score or family history and HLA genotype. Infants are randomised 1:1 to daily administration of B. infantis EVC001 or placebo until age 12 months and followed for a maximum of 5.5 years thereafter. The primary outcome is the development of persistent confirmed multiple beta-cell autoantibodies. Secondary outcomes are (1) Any persistent confirmed beta-cell autoantibody, defined as at least one confirmed autoantibody in two consecutive samples, including insulin autoantibodies, glutamic acid decarboxylase, islet tyrosine phosphatase 2 or zinc transporter 8, (2) Diabetes, (3) Transglutaminase autoantibodies associated with coeliac disease, (4) Respiratory infection rate in first year of life during supplementation and (5) Safety. Exploratory outcomes include allergy, antibody response to vaccines, alterations of the gut microbiome or blood metabolome, stool pH and calprotectin.Ethics and disseminationThe study was approved by the local ethical committees of the Technical University Munich, Medical Faculty, the Technische Universität Dresden, the Medizinische Hochschule Hannover, the Medical University of Warsaw, EC Research UZ Leuven and the Swedish ethical review authority. The results will be disseminated through peer-reviewed journals and conference presentations and will be openly shared after completion of the study.Trial registration numberNCT04769037.

Viruses are implicated in autoimmune destruction of pancreatic islet beta cells, which results in insulin deficiency and type 1 diabetes (T1D)(1-4). Certain enteroviruses can infect beta cells in vitro(5), have been detected in the pancreatic islets of patients with T1D(6) and have shown an association with T1D in meta-analyses(4). However, establishing consistency in findings across studies has proven difficult. Obstacles to convincingly linking RNA viruses to islet autoimmunity may be attributed to rapid viral mutation rates, the cyclical periodicity of viruses(7) and the selection of variants with altered pathogenicity and ability to spread in populations. beta cells strongly express cell-surface coxsackie and adenovirus receptor (CXADR) genes, which can facilitate enterovirus infection(8). Studies of human pancreata and cultured islets have shown significant variation in enteroviral virulence to beta cells between serotypes and within the same serotype(9,10). In this large-scale study of known eukaryotic DNA and RNA viruses in stools from children, we evaluated fecally shed viruses in relation to islet autoimmunity and T1D. This study showed that prolonged enterovirus B rather than independent, short-duration enterovirus B infections may be involved in the development of islet autoimmunity, but not T1D, in some young children. Furthermore, we found that fewer early-life human mastadenovirus C infections, as well as CXADR rs6517774, independently correlated with islet autoimmunity.

Aims/hypothesis We studied the association of plasma ascorbic acid with the risk of developing islet autoimmunity and type 1 diabetes and examined whether SNPs in vitamin C transport genes modify these associations. Furthermore, we aimed to determine whether the SNPs themselves are associated with the risk of islet autoimmunity or type 1 diabetes. Methods We used a risk set sampled nested case–control design within an ongoing international multicentre observational study: The Environmental Determinants of Diabetes in the Young (TEDDY). The TEDDY study followed children with increased genetic risk from birth to endpoints of islet autoantibodies (350 cases, 974 controls) and type 1 diabetes (102 cases, 282 controls) in six clinical centres. Control participants were matched for family history of type 1 diabetes, clinical centre and sex. Plasma ascorbic acid concentration was measured at ages 6 and 12 months and then annually up to age 6 years. SNPs in vitamin C transport genes were genotyped using the ImmunoChip custom microarray. Comparisons were adjusted for HLA genotypes and for background population stratification. Results Childhood plasma ascorbic acid (mean ± SD 10.76 ± 3.54 mg/l in controls) was inversely associated with islet autoimmunity risk (adjusted OR 0.96 [95% CI 0.92, 0.99] per +1 mg/l), particularly islet autoimmunity, starting with insulin autoantibodies (OR 0.94 [95% CI 0.88, 0.99]), but not with type 1 diabetes risk (OR 0.93 [95% Cl 0.86, 1.02]). The SLC2A2 rs5400 SNP was associated with increased risk of type 1 diabetes (OR 1.77 [95% CI 1.12, 2.80]), independent of plasma ascorbic acid (OR 0.92 [95% CI 0.84, 1.00]). Conclusions/interpretation Higher plasma ascorbic acid levels may protect against islet autoimmunity in children genetically at risk for type 1 diabetes. Further studies are warranted to confirm these findings. Data availability The datasets generated and analysed during the current study will be made available in the NIDDK Central Repository at https://www.niddkrepository.org/studies/teddy.

Background Autoimmune diseases are often preceded by an asymptomatic autoantibody-positive phase. In type 1 diabetes, the detection of autoantibodies to pancreatic islet antigens in genetically at-risk children is prognostic for future clinical diabetes. Testing for islet autoantibodies is, therefore, performed in a range of clinical studies. Accurate risk estimates that consider the a priori genetic risk and other risk modifiers are an important component of screening. The age of an individual is an under-appreciated risk modifier. The aim of this study was to provide age-adjusted risk estimates for the development of autoantibodies across childhood in genetically at-risk children. Methods The prospective BABYDIAB and BABYDIET studies included 2441 children from birth who had a first-degree relative with type 1 diabetes. Children were born between 1989 and 2006 and were regularly followed from birth for the development of islet autoantibodies and diabetes. A landmark analysis was performed to estimate the risk of islet autoantibodies at birth and at the age 3.5, 6.5 and 12.5 years. Exponential decay curves were fitted for the risk by the age of 20 years. Results The risk of islet autoantibodies by the age of 20 years was 8%, 4.6%, 2.6% and 0.9%, at the landmark ages of birth, 3.5, 6.5 and 12.5 years, respectively. The short-term risks (within 6 years of follow-up) at these landmark ages were 5.3%, 2.9%, 1.8% and 1%, respectively. The decline in autoantibody risk with age was modelled using a one-phase exponential decay curve (r = 0.99) with a risk half-life of 3.7 years. This risk decay model was remarkably consistent when the outcome was defined as islet autoantibody-positive or multiple islet autoantibody-positive and when the study cohort was stratified by HLA risk genotype. A similar decay model was observed for coeliac disease-associated transglutaminase antibodies in the same cohort. Unlike the risk of developing islet autoantibodies, the rate of developing clinical diabetes in children who were islet autoantibody-positive did not decline with age. Conclusion The risk of developing autoantibodies drops exponentially with age in children with a first-degree relative with type 1 diabetes. Electronic supplementary material The online version of this article (10.1186/s12916-019-1360-3) contains supplementary material, which is available to authorized users.

Aims/hypothesis: Psychological stress has long been considered a possible trigger of type 1 diabetes, although prospective studies examining the link between psychological stress or life events during pregnancy and the child’s type 1 diabetes risk are rare. The objective of this study was to examine the association between life events during pregnancy and first-appearing islet autoantibodies (IA) in young children, conditioned by the child’s type 1 diabetes-related genetic risk. Methods: The IA status of 7317 genetically at-risk The Environmental Determinants of Diabetes in the Young (TEDDY) participants was assessed every 3months from 3months to 4years, and bi-annually thereafter. Reports of major life events during pregnancy were collected at study inception when the child was 3months of age and placed into one of six categories. Life events during pregnancy were examined for association with first-appearing insulin (IAA) (N = 222) or GAD (GADA) (N = 209) autoantibodies in the child until 6years of age using proportional hazard models. Relative excess risk due to interaction (RERI) by the child’s HLA-DR and SNP profile was estimated. Results: Overall, 65% of mothers reported a life event during pregnancy; disease/injury (25%), serious interpersonal (28%) and job-related (25%) life events were most common. The association of life events during pregnancy differed between IAA and GADA as the first-appearing autoantibody. Serious interpersonal life events correlated with increased risk of GADA-first only in HLA-DR3 children with the BACH2-T allele (HR 2.28, p < 0.0001), an additive interaction (RERI 1.87, p = 0.0004). Job-related life events were also associated with increased risk of GADA-first among HLA-DR3/4 children (HR 1.53, p = 0.04) independent of serious interpersonal life events (HR 1.90, p = 0.002), an additive interaction (RERI 1.19, p = 0.004). Job-related life events correlated with reduced risk of IAA-first (HR 0.55, p = 0.004), particularly in children with the BTNL2-GG allele (HR 0.48; 95% CI 0.31, 0.76). Conclusions/interpretation: Specific life events during pregnancy are differentially related to IAA vs GADA as first-appearing IA and interact with different HLA and non-HLA genetic factors, supporting the concept of different endotypes underlying type 1 diabetes. However, the mechanisms underlying these associations remain to be discovered. Life events may be markers for other yet-to-be-identified factors important to the development of first-appearing IA. Graphical abstract: [Figure not available: see fulltext.]

Shared metabolomic patterns at delivery have been suggested to underlie the mother-to-child transmission of adverse metabolic health. This study aimed to investigate whether mothers with gestational diabetes mellitus (GDM) and their offspring show similar metabolomic patterns several years postpartum. Targeted metabolomics (including 137 metabolites) was performed in plasma samples obtained during an oral glucose tolerance test from 48 mothers with GDM and their offspring at a cross-sectional study visit 8 years after delivery. Partial Pearson&rsquo, s correlations between the area under the curve (AUC) of maternal and offspring metabolites were calculated, yielding so-called Gaussian graphical models. Spearman&rsquo, s correlations were applied to investigate correlations of body mass index (BMI), Matsuda insulin sensitivity index (ISI-M), dietary intake, and physical activity between generations, and correlations of metabolite AUCs with lifestyle variables. This study revealed that BMI, ISI-M, and the AUC of six metabolites (carnitine, taurine, proline, SM(-OH) C14:1, creatinine, and PC ae C34:3) were significantly correlated between mothers and offspring several years postpartum. Intergenerational metabolite correlations were independent of shared BMI, ISI-M, age, sex, and all other metabolites. Furthermore, creatinine was correlated with physical activity in mothers. This study suggests that there is long-term metabolic programming in the offspring of mothers with GDM and informs us about targets that could be addressed by future intervention studies.

Here we report a case where the manifestations of insulin-dependent diabetes occurred following SARS-CoV-2 infection in a young individual in the absence of autoantibodies typical for type 1 diabetes mellitus. Specifically, a 19-year-old white male presented at our emergency department with diabetic ketoacidosis, C-peptide level of 0.62 µg l–1, blood glucose concentration of 30.6 mmol l–1 (552 mg dl–1) and haemoglobin A1c of 16.8%. The patient´s case history revealed probable COVID-19 infection 5–7 weeks before admission, based on a positive test for antibodies against SARS-CoV-2 proteins as determined by enzyme-linked immunosorbent assay. Interestingly, the patient carried a human leukocyte antigen genotype (HLA DR1-DR3-DQ2) considered to provide only a slightly elevated risk of developing autoimmune type 1 diabetes mellitus. However, as noted, no serum autoantibodies were observed against islet cells, glutamic acid decarboxylase, tyrosine phosphatase, insulin and zinc-transporter 8. Although our report cannot fully establish causality between COVID-19 and the development of diabetes in this patient, considering that SARS-CoV-2 entry receptors, including angiotensin-converting enzyme 2, are expressed on pancreatic β-cells and, given the circumstances of this case, we suggest that SARS-CoV-2 infection, or COVID-19, might negatively affect pancreatic function, perhaps through direct cytolytic effects of the virus on β-cells. The authors report the case of a young patient who displayed insulin-dependent diabetes after SARS-CoV-2 infection in the absence of autoantibodies indicative of autoimmune type 1 diabetes.

OBJECTIVE The first-appearing β-cell autoantibody has been shown to influence risk of type 1 diabetes (T1D). Here, we assessed the risk of autoantibody spreading to the second-appearing autoantibody and further progression to clinical disease in The Environmental Determinants of Diabetes in the Young (TEDDY) study. RESEARCH DESIGN AND METHODS Eligible children with increased HLA-DR-DQ genetic risk for T1D were followed quarterly from age 3 months up to 15 years for development of a single first-appearing autoantibody (GAD antibody [GADA], insulin autoantibody [IAA], or insulinoma antigen-2 autoantibody [IA-2A]) and subsequent development of a single second-appearing autoantibody and progression to T1D. Autoantibody positivity was defined as positivity for a specific autoantibody at two consecutive visits confirmed in two laboratories. Zinc transporter 8 autoantibody (ZnT8A) was measured in children who developed another autoantibody. RESULTS There were 608 children who developed a single first-appearing autoantibody (IAA, n = 282, or GADA, n = 326) with a median follow-up of 12.5 years from birth. The risk of a second-appearing autoantibody was independent of GADA versus IAA as a first-appearing autoantibody (adjusted hazard ratio [HR] 1.12; 95% CI 0.88–1.42; P = 0.36). Second-appearing GADA, IAA, IA-2A, or ZnT8A conferred an increased risk of T1D compared with children who remained positive for a single autoantibody, e.g., IAA or GADA second (adjusted HR 6.44; 95% CI 3.78–10.98), IA-2A second (adjusted HR 16.33; 95% CI 9.10–29.29; P < 0.0001), or ZnT8A second (adjusted HR 5.35; 95% CI 2.61–10.95; P < 0.0001). In children who developed a distinct second autoantibody, IA-2A (adjusted HR 3.08; 95% CI 2.04–4.65; P < 0.0001) conferred a greater risk of progression to T1D as compared with GADA or IAA. Additionally, both a younger initial age at seroconversion and shorter time to the development of the second-appearing autoantibody increased the risk for T1D. CONCLUSIONS The hierarchical order of distinct autoantibody spreading was independent of the first-appearing autoantibody type and was age-dependent and augmented the risk of progression to T1D.

Children’s plasma metabolome, especially lipidome, reflects gene regulation and dietary exposures, heralding the development of islet autoantibodies (IA) and type 1 diabetes (T1D). The Environmental Determinants of Diabetes in the Young (TEDDY) study enrolled 8,676 newborns by screening of HLA-DR-DQ genotypes at six clinical centers in four countries, profiled metabolome, and measured concentrations of ascorbic acid, 25-hydroxyvitamin D [25(OH)D], and erythrocyte membrane fatty acids following birth until IA seroconversion under a nested case-control design. We grouped children having an initial autoantibody only against insulin (IAA-first) or GAD (GADA-first) by unsupervised clustering of temporal lipidome, identifying a subgroup of children having early onset of each initial autoantibody, i.e., IAA-first by 12 months and GADA-first by 21 months, consistent with population-wide early seroconversion age. Differential analysis showed that infants having reduced plasma ascorbic acid and cholesterol experienced IAA-first earlier, while early onset of GADA-first was preceded by reduced sphingomyelins at infancy. Plasma 25(OH)D prior to either autoantibody was lower in T1D progressors compared with nonprogressors, with simultaneous lower diglycerides, lysophosphatidylcholines, triglycerides, and alanine before GADA-first. Plasma ascorbic acid and 25(OH)D at infancy were lower in HLA-DR3/DR4 children among IA case subjects but not in matched control subjects, implying gene expression dysregulation of circulating vitamins as latent signals for IA or T1D progression.

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.

The risk for autoimmunity and subsequently type 1 diabetes is 10-fold higher in children with a first-degree family history of type 1 diabetes (FDR children) than in children in the general population (GP children). We analyzed children with high-risk HLA genotypes (n = 4,573) in the longitudinal TEDDY birth cohort to determine how much of the divergent risk is attributable to genetic enrichment in affected families. Enrichment for susceptible genotypes of multiple type 1 diabetes–associated genes and a novel risk gene, BTNL2, was identified in FDR children compared with GP children. After correction for genetic enrichment, the risks in the FDR and GP children converged but were not identical for multiple islet autoantibodies (hazard ratio [HR] 2.26 [95% CI 1.6–3.02]) and for diabetes (HR 2.92 [95% CI 2.05–4.16]). Convergence varied depending upon the degree of genetic susceptibility. Risks were similar in the highest genetic susceptibility group for multiple islet autoantibodies (14.3% vs .12.7%) and diabetes (4.8% vs. 4.1%) and were up to 5.8-fold divergent for children in the lowest genetic susceptibility group, decreasing incrementally in GP children but not in FDR children. These findings suggest that additional factors enriched within affected families preferentially increase the risk of autoimmunity and type 1 diabetes in lower genetic susceptibility strata.

Children at increased genetic risk for type 1 diabetes (T1D) after environmental exposures may develop pancreatic islet autoantibodies (IA) at a very young age. Metabolic profile changes over time may imply responses to exposures and signal development of the first IA. Our present research in The Environmental Determinants of Diabetes in the Young (TEDDY) study aimed to identify metabolome-wide signals preceding the first IA against GAD (GADA-first) or against insulin (IAA-first). We profiled metabolomes by mass spectrometry from children’s plasma at 3-month intervals after birth until appearance of the first IA. A trajectory analysis discovered each first IA preceded by reduced amino acid proline and branched-chain amino acids (BCAAs), respectively. With independent time point analysis following birth, we discovered dehydroascorbic acid (DHAA) contributing to the risk of each first IA, and γ-aminobutyric acid (GABAs) associated with the first autoantibody against insulin (IAA-first). Methionine and alanine, compounds produced in BCAA metabolism and fatty acids, also preceded IA at different time points. Unsaturated triglycerides and phosphatidylethanolamines decreased in abundance before appearance of either autoantibody. Our findings suggest that IAA-first and GADA-first are heralded by different patterns of DHAA, GABA, multiple amino acids, and fatty acids, which may be important to primary prevention of T1D.

OBJECTIVE: Cesarean section (C-section) is associated with various immune-mediated diseases in the offspring. We investigated the relationship between mode of delivery and celiac disease (CD) and CD autoimmunity (CDA) in a multinational birth cohort. METHODS: From 2004 to 2010, infants from the general population who tested positive for HLA DR3-DQ2 or DR4-DQ8 were enrolled in The Environmental Determinants for Diabetes in the Young (TEDDY) study. Children were annually screened for transglutaminase autoantibodies, if positive, they are retested after 3 to 6 months and those persistently positive defined as CDA. Associations of C-section with maternal (age, education level, parity, pre-pregnancy weight, diabetes, smoking, weight gain during pregnancy) and child characteristics (gestational age, birth weight) were examined by Fisher exact test or Wilcoxon rank-sum test. Hazard ratios (HRs) for CDA or CD were calculated by Cox proportional hazard regression models. RESULTS: Of 6087 analyzed singletons, 1600 (26%) were born by C-section (Germany 38%, United States 37%, Finland 18%, Sweden 16%), and the remaining were born vaginally without instrumental support; 979 (16%) had developed CDA and 343 (6%) developed CD. C-section was associated with lower risk for CDA (hazard ratio [HR] = 0.85; 95% confidence interval [CI] 0.73, 0.99 P = 0.032) and CD (HR = 0.75; 95% CI 0.58, 0.98; P = 0.034). After adjusting for country, sex, HLA-genotype, CD in family, maternal education, and breast-feeding duration, significance was lost for CDA (HR = 0.91; 95% CI 0.78, 1.06; P = 0.20) and CD (HR = 0.85; 95% CI 0.65, 1.11; P = 0.24). Presurgical ruptured membranes had no influence on CDA or CD development. CONCLUSION: C-section is not associated with increased risk for CDA or CD in the offspring.

OBJECTIVE To examine duration of breastfeeding and timing of complementary foods and risk of islet autoimmunity (IA). RESEARCH DESIGN AND METHODS The Environmental Determinants of Diabetes in the Young (TEDDY) study prospectively follows 8,676 children with increased genetic risk of type 1 diabetes (T1D) in the U.S., Finland, Germany, and Sweden. This study included 7,563 children with at least 9 months of follow-up. Blood samples were collected every 3 months from birth to evaluate IA, defined as persistent, confirmed positive antibodies to insulin (IAAs), GAD, or insulinoma antigen-2. We examined the associations between diet and the risk of IA using Cox regression models adjusted for country, T1D family history, HLA genotype, sex, and early probiotic exposure. Additionally, we investigated martingale residuals and log-rank statistics to determine cut points for ages of dietary exposures. RESULTS Later introduction of gluten was associated with increased risk of any IA and IAA. The hazard ratios (HRs) for every 1-month delay in gluten introduction were 1.05 (95% CI 1.01, 1.10; P = 0.02) and 1.08 (95% CI 1.00, 1.16; P = 0.04), respectively. Martingale residual analysis suggested that the age at gluten introduction could be grouped as 9 months. The risk of IA associated with introducing gluten before 4 months of age was lower (HR 0.68; 95% CI 0.47, 0.99), and the risk of IA associated with introducing it later than the age of 9 months was higher (HR 1.57; 95% CI 1.07, 2.31) than introduction between 4 and 9 months of age. CONCLUSIONS The timing of gluten-containing cereals and IA should be studied further.

β-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 β-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 β-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 β-cell autoantibodies were included in a Cox regression analysis. IAA predominated as the first appearing β-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 β-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 β-cell autoantibody in early life.

Aims/hypothesis: During the A/H1N1 2009 (A/California/04/2009) pandemic, mass vaccination with a squalene-containing vaccine, Pandemrix®, was performed in Sweden and Finland. The vaccination was found to cause narcolepsy in children and young adults with the HLA-DQ 6.2 haplotype. The aim of this study was to investigate if exposure to Pandemrix® similarly increased the risk of islet autoimmunity or type 1 diabetes. Methods: In The Environmental Determinants of Diabetes in the Young (TEDDY) study, children are followed prospectively for the development of islet autoimmunity and type 1 diabetes. In October 2009, when the mass vaccination began, 3401 children at risk for islet autoimmunity and type 1 diabetes were followed in Sweden and Finland. Vaccinations were recorded and autoantibodies against insulin, GAD65 and insulinoma-associated protein 2 were ascertained quarterly before the age of 4 years and semi-annually thereafter. Results: By 5 August 2010, 2413 of the 3401 (71%) children observed as at risk for an islet autoantibody or type 1 diabetes on 1 October 2009 had been vaccinated with Pandemrix®. By 31 July 2016, 232 children had at least one islet autoantibody before 10 years of age, 148 had multiple islet autoantibodies and 96 had developed type 1 diabetes. The risk of islet autoimmunity was not increased among vaccinated children. The HR (95% CI) for the appearance of at least one islet autoantibody was 0.75 (0.55, 1.03), at least two autoantibodies was 0.85 (0.57, 1.26) and type 1 diabetes was 0.67 (0.42, 1.07). In Finland, but not in Sweden, vaccinated children had a lower risk of islet autoimmunity (0.47 [0.29, 0.75]), multiple autoantibodies (0.50 [0.28, 0.90] ) and type 1 diabetes (0.38 [0.20, 0.72]) compared with those who did not receive Pandemrix®. The analyses were adjusted for confounding factors. Conclusions/interpretation: Children with an increased genetic risk for type 1 diabetes who received the Pandemrix® vaccine during the A/H1N1 2009 pandemic had no increased risk of islet autoimmunity, multiple islet autoantibodies or type 1 diabetes. In Finland, the vaccine was associated with a reduced risk of islet autoimmunity and type 1 diabetes.

We examined the association between plasma 25-hydroxyvitamin D [25(OH)D] concentration and islet autoimmunity (IA) and whether vitamin D gene polymorphisms modify the effect of 25(OH)D on IA risk. We followed 8,676 children at increased genetic risk of type 1 diabetes at six sites in the U.S. and Europe. We defined IA as positivity for at least one autoantibody (GADA, IAA, or IA-2A) on two or more visits. We conducted a risk set sampled nested case-control study of 376 IA case subjects and up to 3 control subjects per case subject. 25(OH)D concentration was measured on all samples prior to, and including, the first IA positive visit. Nine polymorphisms in VDR, CYP24A, CYP27B1, GC, and RXRA were analyzed as effect modifiers of 25(OH)D. Adjusting for HLA-DR-DQ and ancestry, higher childhood 25(OH)D was associated with lower IA risk (odds ratio = 0.93 for a 5 nmol/L difference; 95% CI 0.89, 0.97). Moreover, this association was modified by VDR rs7975232 (interaction P = 0.0072), where increased childhood 25(OH)D was associated with a decreasing IA risk based upon number of minor alleles: 0 (1.00; 0.93, 1.07), 1 (0.92; 0.89, 0.96), and 2 (0.86; 0.80, 0.92). Vitamin D and VDR may have a combined role in IA development in children at increased genetic risk for type 1 diabetes.

Objective: The associations of energy, protein, carbohydrate, and fat intake with weight status up to the age of 5.5 years were prospectively assessed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Methods: Food record data (over 3 days) and BMI measurements between 0.25 and 5.5 years were available from 5,563 children with an increased genetic risk for type 1 diabetes followed from shortly after birth. Odds ratios (ORs) were calculated for overweight and obesity by previous intake of energy, protein, carbohydrate, and fat with adjustment for potential confounders. Results: Having overweight or obesity at the age of 5.5 years was positively associated with mean energy intake in previous age intervals (e.g., adjusted OR [95% CI] for overweight: 1.06 [1.04-1.09] per 100 kcal intake at the age of 4.5-5.0 years) and with protein intake after the age of 3.5 and 4.5 years, respectively (e.g., adjusted OR for overweight: 1.06 [1.03-1.09] per 1% of energy intake at the age of 4.5-5.0 years). The respective associations with carbohydrate and fat intake were less consistent. Conclusions: These findings indicate that energy and protein intake are positively associated with increased risk for overweight in childhood but yield no evidence for potential programming effects of protein intake in infancy.

OBJECTIVE We tested the associations between genetic background and selected environmental exposures with respect to islet autoantibodies and type 1 diabetes. RESEARCH DESIGN AND METHODS Infants with HLA-DR high-risk genotypes were prospectively followed for diabetes-related autoantibodies. Single nucleotide polymorphisms (SNPs) came from the Illumina ImmunoChip and environmental exposure data were by parental report. Children were followed to age 6 years. RESULTS Insulin autoantibodies occurred earlier than GAD antibody (GADA) and then declined, while GADA incidence rose and remained constant (significant in HLA-DR4 but not in the DR3/3 children). The presence of SNPs rs2476601 (PTPN22) and rs2292239 (ERBB3) demonstrated increased risk of both autoantibodies to insulin (IAA) only and GADA only. SNP rs689 (INS) was protective of IAA only, but not of GADA only. The rs3757247 (BACH2) SNP demonstrated increased risk of GADA only. Male sex, father or sibling as the diabetic proband, introduction of probiotics under 28 days of age, and weight at age 12 months were associated with IAA only, but only father as the diabetic proband and weight at age 12 months were associated with GADA only. Mother as the diabetic proband was not a significant risk factor. CONCLUSIONS These results show clear differences in the initiation of autoimmunity according to genetic factors and environmental exposures that give rise to IAA or GADA as the first appearing indication of autoimmunity.

The development and application of effective immunotherapies for type 1 diabetes mellitus has lagged behind our ability to identify and stage individuals in pre-clinical stages of disease. This Year in Review addresses advances in immunotherapy aimed towards prevention and our readiness to roll out screening in the broader population.

OBJECTIVE This study investigates two-phase growth patterns in early life and their association with development of islet autoimmunity (IA) and type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS The Environmental Determinants of Diabetes in the Young (TEDDY) study followed 7,522 genetically high-risk children in Sweden, Finland, Germany, and the U.S. from birth for a median of 9.0 years (interquartile range 5.7–10.6) with available growth data. Of these, 761 (10.1%) children developed IA and 290 (3.9%) children were diagnosed with T1D. Bayesian two-phase piecewise linear mixed models with a random change point were used to estimate children’s individual growth trajectories. Cox proportional hazards models were used to assess the effects of associated growth parameters on the risks of IA and progression to T1D. RESULTS A higher rate of weight gain in infancy was associated with increased IA risk (hazard ratio [HR] 1.09 [95% CI 1.02, 1.17] per 1 kg/year). A height growth pattern with a lower rate in infancy (HR 0.79 [95% CI 0.70, 0.90] per 1 cm/year), higher rate in early childhood (HR 1.48 [95% CI 1.22, 1.79] per 1 cm/year), and younger age at the phase transition (HR 0.76 [95% CI 0.58, 0.99] per 1 month) was associated with increased risk of progression from IA to T1D. A higher rate of weight gain in early childhood was associated with increased risk of progression from IA to T1D (HR 2.57 [95% CI 1.34, 4.91] per 1 kg/year) in children with first-appearing GAD autoantibody only. CONCLUSIONS Growth patterns in early life better clarify how specific growth phases are associated with the development of T1D.

Type 1 diabetes (T1D) associated genetic factors affect risk of islet autoantibodies (IA), but non-genetic factors show conflicting associations. Mechanistic interactions may play a role. Under a sufficient-component causal framework, we used a rule-based discovery method to investigate if genetic factors, early environment and first appearing IA (IAA or GADA) act synergistically to mark different disease mechanisms. TEDDY children (n=7512) were followed until age 6 years for IA development (n=518). Rules differentiating IAA-first (n=258) from GADA-first (n=243) were identified by a rule discovery algorithm (RuleFit) and examined in logistic regression models. Rule components were assessed for additive interaction on IAA-first and GADA-first separately using Relative Excess Risk due to Interaction (RERI) calculated from Cox regression models. Here we show 2 of the 5 top rules, the first involving the child having CTLA4-AA (rs231775) and mother with a gestational respiratory but no skin infection (rule1, OR=5.6, 95% CI=2.6-12.0, p Figure 1. Gene-environmental interaction with first appearing IA may mark different mechanisms. Disclosure K.F. Lynch: None. T. Feng: None. X. Qian: None. W. Hagopian: Research Support; Self; Novo Nordisk A/S. Å. Lernmark: None. A. Ziegler: None. J. Toppari: None. M. Rewers: None. J. She: None. D. Schatz: None. B. Akolkar: None. J. Krischer: None. S. Huang: None. K. Vehik: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; Centers for Disease Control and Prevention; JDRF; University of Florida (UL1TR000064); University of Colorado (UL1TR001082)

Background: There is an unmet need for accurate cost-effective estimation of future T1D risk. Methods: We derived a combined T1D prediction model using 7883 children followed closely from birth for a median of 9 yr, considering T1D genetic risk score (GRS), family T1D history (FH), standard islet autoantibodies (IA), race, birth circumstances, early growth and nutrient status. T1D developed in 326. Results: Machine learning and traditional methods (Cox models) performed equivalently as measured by time-dependent AUC ROC. Future T1D was accurately predicted by combining only 3 variables: GRS, FH and IA status. Accuracy of combined scores increased with age at scoring. By age 2, they were highly predictive for T1D in the next 5 years (AUC >0.91, 95% CI 0.88-0.95) (see X on Figure). A 2-yr-old with 2 IA, positive FH and high GRS (>12) would have T1D risk over the next 1, 3 and 5 years of 14% (8-19%), 36% (25-45%) and 51% (39%-61%) respectively. A 2-yr-old with 1 IA, no FH and moderate GRS (10-11) has T1D risk of 0.8% (0.6-1.2%), 2.6% (1.9-3.2%) and 4.3% (3.4%-5.2%) respectively. After newborn genetic screening, only simple venous sampling in routine healthcare settings is required. Conclusion: This approach allows updated individual risk estimates by age, and in the future may enable release of low risk individuals from surveillance long after initial newborn screening for more cost-efficient population based pediatric T1D prediction. Disclosure L.A. Ferrat: None. K. Vehik: None. S.A. Sharp: None. Å. Lernmark: None. A. Ziegler: None. M. Rewers: None. J. She: None. J. Toppari: None. B. Akolkar: None. J. Krischer: None. M.N. Weedon: None. S.S. Rich: None. R.A. Oram: Other Relationship; Self; Randox Laboratories Ltd. W. Hagopian: Research Support; Self; Novo Nordisk A/S. Funding National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; JDRF; Centers for Disease Control and Prevention

This study investigates two-phase growth patterns in early life and their associations with development of islet autoimmunity (IA) and type 1 diabetes (T1D). There were 7521 genetically high-risk children from Sweden, Finland, U.S. and Germany followed from birth for a median of 9.0 (IQR 5.7-10.6) years with available growth data. Of these, 761 children developed IA and 290 children progressed to T1D. Bayesian two-phase piecewise linear mixed models with a random change point were used to evaluate distinct growth phases in early life (Figure 1). Cox proportional hazard models were used to assess growth phase effects on risk of IA and progression to T1D. A higher rate of weight gain (kg/year) in the first phase was associated with an increased IA risk (HR =1.10, 95% CI 1.02, 1.18). A height growth pattern with a slower growth rate (cm/year) in the first phase, a higher growth rate in the second phase and younger age (months) at the phase transition was associated with an increased risk of progression from IA to T1D (HR=0.80, 95% CI 0.70, 0.91; HR=1.47, 95% CI 1.21, 1.78; HR=0.69, 95% CI 0.52, 0.93, respectively). A higher rate of weight gain in the second phase was associated with an increased risk of progression from IA to T1D (HR=2.54, 95% CI 1.36, 4.74) in children with first appearing GADA-only. Considering growth by phases in early life better clarified how specific growth phases contribute to the risk of IA and T1D. Disclosure X. Liu: None. K. Vehik: None. Y. Huang: None. H. Elding Larsson: None. J. Toppari: None. A. Ziegler: None. J. She: None. M. Rewers: None. W. Hagopian: Research Support; Self; Novo Nordisk A/S. B. Akolkar: None. J. Krischer: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; Centers for Disease Control and Prevention; JDRF; University of Florida (UL1TR000064); University of Colorado (UL1TR001082)

OBJECTIVE Assessment of the predictive power of The Environmental Determinants of Diabetes in the Young (TEDDY)-identified risk factors for islet autoimmunity (IA), the type of autoantibody appearing first, and type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS A total of 7,777 children were followed from birth to a median of 9.1 years of age for the development of islet autoantibodies and progression to T1D. Time-dependent sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated to provide estimates of their individual and collective ability to predict IA and T1D. RESULTS HLA genotype (DR3/4 vs. others) was the best predictor for IA (Youden’s index J = 0.117) and single nucleotide polymorphism rs2476601, in PTPN22, was the best predictor for insulin autoantibodies (IAA) appearing first (IAA-first) (J = 0.123). For GAD autoantibodies (GADA)-first, weight at 1 year was the best predictor (J = 0.114). In a multivariate model, the area under the ROC curve (AUC) was 0.678 (95% CI 0.655, 0.701), 0.707 (95% CI 0.676, 0.739), and 0.686 (95% CI 0.651, 0.722) for IA, IAA-first, and GADA-first, respectively, at 6 years. The AUC of the prediction model for T1D at 3 years after the appearance of multiple autoantibodies reached 0.706 (95% CI 0.649, 0.762). CONCLUSIONS Prediction modeling statistics are valuable tools, when applied in a time-until-event setting, to evaluate the ability of risk factors to discriminate between those who will and those who will not get disease. Although significantly associated with IA and T1D, the TEDDY risk factors individually contribute little to prediction. However, in combination, these factors increased IA and T1D prediction substantially.

Testing for beta cell autoantibodies is used for wide-scale identification of early stages of type 1 diabetes. This requires suitable screening assays. We aimed to establish screening that utilized a first step assay (3 Screen) able to detect autoantibodies to the target antigens glutamic acid decarboxylase-65 (GAD), insulinoma-associated antigen 2 (IA-2), and zinc transporter 8 (ZnT8) to identify children positive for multiple beta cell autoantibodies.An ELISA format was used where plates were coated with a mixture of recombinant GAD, IA-2, and ZnT8The 3 Screen assay sensitivity for detecting autoantibody-positive patients at onset of type 1 diabetes was similar to that achieved by separate radiobinding assays (RBAs) for antibodies to GAD, IA-2, and ZnT8. Results in venous and capillary serum were correlated (R = 0.987). At a threshold corresponding to the 98th centile (29.1 U/mL) of all 33,639 capillary samples, the 3 Screen was positive in 123 samples with two or more RBA-positive antibodies to insulin, GAD, IA-2, or ZnT8, 146 with one antibody, and 479 that were RBA negative for beta cell autoantibodies.A 3 Screen ELISA was developed that was suitable for first step screening of multiple beta cell autoantibodies in capillary blood.

Type 1 diabetes, a disease defined by absolute insulin deficiency, is considered a chronic autoimmune disorder resulting from the destruction of insulin-producing pancreatic β-cells. The incidence of childhood-onset type 1 diabetes has been increasing at a rate of 3%–5% per year globally. Despite the introduction of an impressive array of therapies aimed at improving disease management, no means for a practical “cure” exist. This said, hope remains high that any of a number of emerging technologies (e.g., continuous glucose monitoring, insulin pumps, smart algorithms), alongside advances in stem cell biology, cell encapsulation methodologies, and immunotherapy, will eventually impact the lives of those with recently diagnosed or established type 1 diabetes. However, efforts aimed at reversing insulin dependence do not address the obvious benefits of disease prevention. Hence, key “stretch goals” for type 1 diabetes research include identifying improved and increasingly practical means for diagnosing the disease at earlier stages in its natural history (i.e., early, presymptomatic diagnosis), undertaking such efforts in the population at large to optimally identify those with presymptomatic type 1 diabetes, and introducing safe and effective therapeutic options for prevention.

Progression to type 1 diabetes in children and adolescents is not uniform. Based on individual genetic background and environment, islet autoimmunity may develop at variable age, exhibit different autoantibody profiles and progress to clinical diabetes at variable rates. Here, we aimed to quantify the qualitative dynamics of sequential islet autoantibody profiles in order to identify longitudinal patterns that stratify progression rates to type 1 diabetes in multiple-autoantibody-positive children. Qualitative changes in antibody status on follow-up and progression rate to diabetes were analysed in 88 children followed from birth in the prospective BABYDIAB study who developed multiple autoantibodies against insulin (IAA), GAD (GADA), insulinoma-associated antigen-2 (IA-2A) and/or zinc transporter 8 (ZnT8A). An algorithm was developed to define similarities in sequential autoantibody profiles and hierarchical clustering was performed to group children with similar profiles. We defined nine clusters that distinguished children with respect to their sequential profiles of IAA, GADA, IA-2A and ZnT8A. Progression from first autoantibody appearance to clinical diabetes between clusters ranged from 6% (95% CI [0, 16.4]) to 73% (28.4, 89.6) within 5 years. Delayed progression was observed in children who were positive for only two autoantibodies, and for a cluster of 12 children who developed three or four autoantibodies but were IAA-negative in their last samples, nine of whom lost IAA positivity during follow-up. Among all children who first seroconverted to IAA positivity and developed at least two other autoantibodies (n = 57), the 10 year risk of diabetes was 23% (0, 42.9) in those who became IAA-negative during follow-up compared with 76% (58.7, 85.6) in those who remained IAA-positive (p = 0.004). The novel clustering approach provides a tool for stratification of islet autoantibody-positive individuals that has prognostic relevance, and new opportunities in elucidating disease mechanisms. Our data suggest that losing IAA reactivity is associated with delayed progression to type 1 diabetes in multiple-islet-autoantibody-positive children.

Autoantibodies to pancreatic beta cell proteins are markers of asymptomatic type 1 diabetes. The aim was to determine whether autoantibodies to the beta cell protein tetraspanin 7 would improve the ability to identify autoimmunity against pancreatic beta cells.Full length and external domain fragments of tetraspanin 7 were expressed as luciferase-tagged fusion proteins and used in immunoprecipitation assays to measure autoantibodies in samples from 363 patients with type 1 diabetes at onset of disease, 503 beta cell autoantibody negative first-degree relatives of patients, and 212 relatives with autoantibodies to insulin, glutamic acid decarboxylase, insulinoma antigen 2 or zinc transporter 8.Antibody binding was observed against the full length and external domains of tetraspanin 7, and was strongest against the full length protein. Autoantibodies that could be inhibited by untagged tetraspanin 7 were detected in 5 (1%) of 503 autoantibody negative relatives, 3 (3.2%) of 94 autoantibody negative patients, 95 (35.3%) of 269 autoantibody positive patients, 1 (1%) of 98 single autoantibody positive relatives and 25 (21.9%) of 114 multiple autoantibody positive relatives. Progression to diabetes did not differ between multiple autoantibody positive relatives with and without tetraspanin 7 autoantibodies.Tetraspanin 7 is an autoantigen in type 1 diabetes. Tetraspanin 7 autoantibodies are a marker of type 1 diabetes, but provide minor additional value to existing autoantibodies in identifying beta cell autoimmunity.

OBJECTIVE Autoimmune diseases can be diagnosed early through the detection of autoantibodies. The aim of this study was to determine the risk of organ-specific autoimmunity in individuals with a family history of type 1 diabetes. RESEARCH DESIGN AND METHODS The study cohort included 2,441 first-degree relatives of patients with type 1 diabetes who were prospectively followed from birth to a maximum of 29.4 years (median 13.2 years). All were tested regularly for the development of autoantibodies associated with type 1 diabetes (islet), celiac disease (transglutaminase), or thyroid autoimmunity (thyroid peroxidase). The outcome was defined as an autoantibody-positive status on two consecutive samples. RESULTS In total, 394 relatives developed one (n = 353) or more (n = 41) of the three disease-associated autoantibodies during follow-up. The risk by age 20 years was 8.0% (95% CI 6.8–9.2%) for islet autoantibodies, 6.3% (5.1–7.5%) for transglutaminase autoantibodies, 10.7% (8.9–12.5%) for thyroid peroxidase autoantibodies, and 21.5% (19.5–23.5%) for any of these autoantibodies. Each of the three disease-associated autoantibodies was defined by distinct HLA, sex, genetic, and age profiles. The risk of developing any of these autoantibodies was 56.5% (40.8–72.2%) in relatives with HLA DR3/DR3 and 44.4% (36.6–52.2%) in relatives with HLA DR3/DR4-DQ8. CONCLUSIONS Relatives of patients with type 1 diabetes have a very high risk of organ-specific autoimmunity. Appropriate counseling and genetic and autoantibody testing for multiple autoimmune diseases may be warranted for relatives of patients with type 1 diabetes.

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.

Progression to clinical type 1 diabetes varies among children who develop β-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5 years). Children who developed multiple autoantibody types (n = 370) were clustered, and progression from seroconversion to clinical diabetes within 5 years ranged between clusters from 6% (95% CI 0, 17.4) to 84% (59.2, 93.6). Children who seroconverted early in life (median age

Objective: This study aimed to determine the relationship between different forms of, and potential pathways between, maternal diabetes and childhood obesity at different ages. Methods: Prospective cohort data from The Environmental Determinants of Diabetes in the Young (TEDDY) study, which was composed of 5,324 children examined from 0.25 to 6 years of age, were analyzed. Cross-sectional and longitudinal analyses taking into account potential confounders and effect modifiers such as maternal prepregnancy BMI and birth weight z scores were performed. Results: Offspring of mothers with gestational diabetes mellitus (GDM) or type 1 diabetes mellitus (T1DM) showed a higher BMI standard deviation score and increased risk for overweight and obesity at 5.5 years of age than offspring of mothers without diabetes. While these associations could be substantially explained by maternal prepregnancy BMI in offspring of mothers with GDM, significant associations disappeared after adjustment for birth weight z scores in offspring of T1DM mothers. Furthermore, overweight risk became stronger with increasing age in offspring of mothers with diabetes compared with offspring of mothers without diabetes. Conclusions: Maternal diabetes is associated with increased risk of offspring overweight, and the association appears to get stronger as children grow older. Indeed, intrauterine exposure to maternal T1DM may predispose children to later obesity through increased birth weight, while maternal BMI is more important in children exposed to GDM. (Less)

Aims/hypothesis Adult-onset type 1 diabetes, in which the 65 kDa isoform of GAD (GAD65) is a major autoantigen, has a broad clinical phenotype encompassing variable need for insulin therapy. This study aimed to evaluate whether autoantibodies against N-terminally truncated GAD65 more closely defined a type 1 diabetes phenotype associated with insulin therapy. Methods Of 1114 participants with adult-onset diabetes from the Action LADA (latent autoimmune diabetes in adults) study with sufficient sera, we selected those designated type 1 (n = 511) or type 2 diabetes (n = 603) and retested the samples in radiobinding assays for human full-length GAD65 autoantibodies (f-GADA) and N-terminally truncated (amino acids 96–585) GAD65 autoantibodies (t-GADA). Individuals’ clinical phenotypes were analysed according to antibody binding patterns. Results Overall, 478 individuals were f-GADA-positive, 431 were t-GADA-positive and 628 were negative in both assays. Risk of insulin treatment was augmented in t-GADA-positive individuals (OR 4.69 [95% CI 3.57, 6.17]) compared with f-GADA-positive individuals (OR 3.86 [95% CI 2.95, 5.06]), irrespective of diabetes duration. Of 55 individuals who were f-GADA-positive but t-GADA-negative, i.e. with antibody binding restricted to the N-terminus of GAD65, the phenotype was similar to type 2 diabetes with low risk of progression to insulin treatment. Compared with these individuals with N-terminal GAD65-restricted GADA, t-GADA-positive individuals were younger at diagnosis (p = 0.005), leaner (p

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., Anette-Gabriele Ziegler and colleagues report their novel genetic risk score for identifying infants with a high risk of developing type 1 diabetes., Author summary Why was this study done? Prevention of childhood diseases such as type 1 diabetes is of medical importance. Prevention of type 1 diabetes might be best achieved by intervention prior to the development of islet autoantibodies, which define a pre-symptomatic disease stage. Early intervention requires tools such as measures of genetic risk that identify future cases. Risk for type 1 diabetes in the absence of a family history is currently identified by HLA genotyping, with maximum identified risk reaching around 5%. Genetic scores derived from multiple risk loci may improve risk stratification for pre-symptomatic type 1 diabetes. What did the researchers do and find? Two previously proposed genetic scores for type 1 diabetes risk were calculated for over 3,000 children without a family history of type 1 diabetes but with 1 of the 2 highest-risk HLA genotypes (heterozygous DR3 and DR4-DQ8 or homozygous DR4-DQ8) participating in the TEDDY cohort study, which prospectively follows children from birth for the development of islet autoantibodies and diabetes. We found that both of the genetic scores, and a merged genetic score that combined the features of both, stratified the risk for islet autoantibodies and diabetes in the children. The upper quartile of the merged genetic score was associated with a >10% risk for the pre-symptomatic stage of multiple islet autoantibodies, and almost half the children who developed pre-symptomatic or symptomatic diabetes were identified by this score. What do these findings mean? Combining genetic information from multiple risk loci can improve the prediction of diseases such as type 1 diabetes. A genetic risk score model is proposed that could be used to recruit infants into early type 1 diabetes primary prevention trials. The model provides a new paradigm for genetic screening and selection of at-risk infants that, together with family history and HLA genotyping, could identify up to 25% of future childhood cases of type 1 diabetes from less than 1% of newborns.

Autoimmune-mediated destruction of pancreatic islet β cells results in type 1 diabetes (T1D). Serum islet autoantibodies usually develop in genetically susceptible individuals in early childhood before T1D onset, with multiple islet autoantibodies predicting diabetes development. However, most at-risk children remain islet-antibody negative, and no test currently identifies those likely to seroconvert. We sought a genomic signature predicting seroconversion risk by integrating longitudinal peripheral blood gene expression profiles collected in high-risk children included in the BABYDIET and DIPP cohorts, of whom 50 seroconverted. Subjects were followed for 10 years to determine time of seroconversion. Any cohort effect and the time of seroconversion were corrected to uncover genes differentially expressed (DE) in seroconverting children. Gene expression signatures associated with seroconversion were evident during the first year of life, with 67 DE genes identified in seroconverting children relative to those remaining antibody negative. These genes contribute to T cell-, DC-, and B cell-related immune responses. Near-birth expression of ADCY9, PTCH1, MEX3B, IL15RA, ZNF714, TENM1, and PLEKHA5, along with HLA risk score predicted seroconversion (AUC 0.85). The ubiquitin-proteasome pathway linked DE genes and T1D susceptibility genes. Therefore, a gene expression signature in infancy predicts risk of seroconversion. Ubiquitination may play a mechanistic role in diabetes progression.

The susceptibility to autoimmune diseases is influenced by genes encoding major histocompatibility complex (MHC) proteins. By examining the epigenetic methylation maps of cord blood samples, we found marked differences in the methylation status of CpG sites within the MHC genes (cis-metQTLs) between carriers of the type 1 diabetes risk haplotypes HLA-DRB1*03-DQA1*0501-DQB1*0201 (DR3-DQ2) and HLA-DRB1*04-DQA1*0301-DQB1*0302 (DR4-DQ8). These differences were found in children and adults, and were accompanied by reduced HLA-DR protein expression in immune cells with the HLA-DR3-DQ2 haplotype. Extensive cis-metQTLs were identified in all 45 immune and non-immune type 1 diabetes susceptibility genes analyzed in this study. We observed and validated a novel association between the methylation status of CpG sites within the LDHC gene and the development of insulin autoantibodies in early childhood in children who are carriers of the highest type 1 diabetes risk genotype. Functionally relevant epigenetic changes in susceptibility genes may represent therapeutic targets for type 1 diabetes.

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

The purpose of this review was to describe the potential for general childhood population-based screening of risk of symptomatic type 1 diabetes (T1D) RECENT FINDINGS: The earliest stages of T1D can be identified and risk and rate of progression to symptomatic disease can be estimated by the presence of multiple islet autoantibodies and glucose intolerance (dysglycemia) in individuals screened for risk. Screening for human leukocyte antigen risk genotypes in neonates with follow-up detection of islet autoantibodies in childhood has been explored. An alternative approach of general childhood population-based detection of autoantibodies at well child visits provides an approach to detect a high proportion of children who will develop T1D. The Fr1da study was launched in Bavaria in 2015 to explore this concept.General childhood population-based screening for risk of T1D will allow detection of an at-risk population that can participate in natural history studies to better understand disease pathogenesis and intervention trials to prevent symptomatic disease and will provide a framework for public health-based prevention of childhood-onset T1D.

Islet autoantibodies, in addition to elevated blood glucose, define type 1 diabetes. These autoantibodies are detectable for a variable period of time before diabetes onset. Thus, the occurrence of islet autoantibodies is associated with the beginning of the disease process. The age at, and order in, which autoantibodies appear may be associated with different genetic backgrounds or environmental exposures, or both.Infants with HLA-DR high-risk genotypes (DR3/4, DR4/4, DR4/8 and DR3/3) were enrolled and prospectively followed with standardised autoantibody assessments quarterly throughout the first 4 years of life and then semi-annually thereafter.Autoantibodies appeared in 549/8,503 (6.5%) children during 34,091 person-years of follow-up. Autoantibodies at 3 (0.1%) and 6 (0.2%) months of age were rare. Of the 549, 43.7% had islet autoantibodies to insulin (IAA) only, 37.7% had glutamic acid decarboxylase autoantibodies (GADA) only, 13.8% had both GADA and IAA only, 1.6% had insulinoma antigen-2 only and 3.1% had other combinations. The incidence of IAA only peaked within the first year of life and declined over the following 5 years, but GADA only increased until the second year and remained relatively constant. GADA only were more common than IAA only in HLA-DR3/3 children but less common in HLA-DR4/8 children.Islet autoantibodies can occur very early in life and the order of appearance was related to HLA-DR-DQ genotype.

Typ-1-Diabetes wird bei einem Drittel der betroffenen Kinder und Jugendlichen erst diagnostiziert, wenn eine lebensbedrohliche Ketoazidose auftritt. Dies konnte sich durch ein Screening auf Inselautoantikorper im Blut andern, wie erste Ergebnisse der „Fr1da“-Studie in Bayern zeigen. Daruber hinaus wird getestet, ob die Gabe von oralem Insulin die Manifestation eines Typ-1-Diabetes verhindern kann.

BackgroundProgression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.MethodsIn 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.ResultsIslet 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).ConclusionsGenetic 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.

Background: Although detection of children at high risk of developing type 1 diabetes and diagnosis of early stages is possible, up to now there exists no approved therapy to delay or prevent type 1 diabetes. Thus it is vital to develop evidence-based interventions. For this a sufficient number of trial participants is crucial but difficult to obtain especially in asymptomatic children. Aim: Identifying family characteristics that lead to or impede trial participation and analyze reasons stated by families for non-participation. Methods: Participants for the Fr1da Insulin Intervention study are recruited from the Fr1da study, a population based screening for early stage type 1 diabetes in Bavaria. Families with eligible children were invited to enroll. We analyzed sex and age of the child, distance of the family to the study center in Munich and the existence of a first degree family member with type 1 as possible influential factors for study participation. We also analyzed reasons stated by families who declined study participation in a phone interview. Results: Of 146 eligible children 77 (53%) were enrolled into the trial. None of the tested family characteristics differed significantly between the enrolling and the families not participating, but in general enrolling families lived closer to the study site than families not participating. This is also reflected in the reasons given by non-participating families. The most frequent reason stated were time restrictions. The second most frequent reason was the venous blood draw. Conclusion: The factors for non-participation identified in this project need be taken into account for the design of future trials in young children to ensure proper recruitment and thus to generate valid results for medical treatment of children. More research on the reason of participation and non-participation in clinical trials is needed. Keywords: Type 1 diabetes, Trial recruitment, Trial enrollment, Infants, Children, Asymptomatic

Objective Women with insulin-requiring gestational diabetes mellitus (GDM) are at high risk of developing diabetes within a few years postpartum. We implemented this phase II study to test the hypothesis that vildagliptin, a dipeptidyl peptidase-4 inhibitor, is superior to placebo in terms of reducing the risk of postpartum diabetes. Methods Women with insulin-requiring GDM were randomized to either placebo or 50 mg vildagliptin twice daily for 24 months followed by a 12-month observation period (EudraCT: 2007-000634-39). Both groups received lifestyle counseling. The primary efficacy outcomes were the diagnosis of diabetes (American Diabetes Association (ADA) criteria) or impaired fasting glucose (IFG)/impaired glucose tolerance (IGT). Results Between 2008 and 2015, 113 patients (58 vildagliptin, 55 placebo) were randomized within 2.2–10.4 (median 8.6) months after delivery. At the interim analysis, nine diabetic events and 28 IFG/IGT events had occurred. Fifty-two women withdrew before completing the treatment phase. Because of the low diabetes rate, the study was terminated. Lifestyle adherence was similar in both groups. At 24 months, the cumulative probability of postpartum diabetes was 3% and 5% (hazard ratio: 1.03; 95% confidence interval: 0.15–7.36) and IFG/IGT was 43% and 22% (hazard ratio: 0.55; 95% confidence interval: 0.26–1.19) in the placebo and vildagliptin groups, respectively. Vildagliptin was well tolerated with no unexpected adverse events. Conclusions The study did not show significant superiority of vildagliptin over placebo in terms of reducing the risk of postpartum diabetes. However, treatment was safe and suggested some improvements in glycemic control, insulin resistance, and β-cell function. The study identified critical issues in performing clinical trials in the early postpartum period in women with GDM hampering efficacy assessments. With this knowledge, we have set a basis for which properly powered trials could be performed in women with recent GDM. Trial registration number at ClinicalTrials.gov NCT01018602., Highlights • Treatment with vildagliptin suggested positive effects on β-cell function and HbA1c. • Treatment with vildagliptin was safe. • Contraindication of vildagliptin during lactation led to exclusion of women with early postpartum diabetes. • Slow enrolment and high drop-out rates are major challenges in studies of women with GDM.