The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.Describing aspects of biology as "heterogeneous" often has a negative connotation. It is a term that is used when we do not understand a measured or observed aspect of disease or when we need to explain data that are not consistent. However, it is evident that recognizing that there are "different kinds" of cells, genes, types of response, and severity of disease could offer a set of opportunities for therapies to work and biomarkers to be meaningful. Thus, it may be time to exploit heterogeneity rather than curse it and to use the opportunity to carve out endotypes of type 1 diabetes that have traction both in the clinic and in the laboratory.The introduction of the term "endotype" can largely be attributed to developments in the field of asthma (1) when it became apparent in the late 1990s that different pathogenic mechanisms induce a similar symptom cluster and manifest as a

IntroductionThe POInT study, an investigator initiated, randomised, placebo-controlled, double-blind, multicentre primary prevention trial is conducted to determine whether daily administration of oral insulin, from age 4.0 months to 7.0 months until age 36.0 months to children with elevated genetic risk for type 1 diabetes, reduces the incidence of beta-cell autoantibodies and diabetes.Methods and analysisInfants aged 4.0 to 7.0 months from Germany, Poland, Belgium, UK and Sweden are eligible if they have a >10.0% expected risk for developing multiple beta-cell autoantibodies as determined by genetic risk score or family history and human leucocyte antigen genotype. Infants are randomised 1:1 to daily oral insulin (7.5 mg for 2 months, 22.5 mg for 2 months, 67.5 mg until age 36.0 months) or placebo, and followed for a maximum of 7 years. Treatment and follow-up is stopped if a child develops diabetes. The primary outcome is the development of persistent confirmed multiple beta-cell autoantibodies or diabetes. Other outcomes are: (1) Any persistent confirmed beta-cell autoantibody (glutamic acid decarboxylase (GADA), IA-2A, autoantibodies to insulin (IAA) and zinc transporter 8 or tetraspanin 7), or diabetes, (2) Persistent confirmed IAA, (3) Persistent confirmed GADA and (4) Abnormal glucose tolerance or diabetes.Ethics and disseminationThe study is approved by the ethical committees of all participating clinical sites. The results will be disseminated through peer-reviewed journals and conference presentations and will be openly shared after completion of the trial.Trial registration numberNCT03364868.

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Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression amongst multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials, and identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in pre-symptomatic subjects using immunotherapy, and as the field moves towards population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics such as epitope targets and affinity; longitudinal patterns such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject’s age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific pre-clinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease.

The role of diet in type 1 diabetes development is poorly understood. Metabolites, which reflect dietary response, may help elucidate this role. We explored metabolomics and lipidomics differences between 352 cases of islet autoimmunity (IA) and controls in the TEDDY (The Environmental Determinants of Diabetes in the Young) study. We created dietary patterns reflecting pre-IA metabolite differences between groups and examined their association with IA. Secondary outcomes included IA cases positive for multiple autoantibodies (mAb+). The association of 853 plasma metabolites with outcomes was tested at seroconversion to IA, just prior to seroconversion, and during infancy. Key compounds in enriched metabolite sets were used to create dietary patterns reflecting metabolite composition, which were then tested for association with outcomes in the nested case-control subset and the full TEDDY cohort. Unsaturated phosphatidylcholines, sphingomyelins, phosphatidylethanolamines, glucosylceramides, and phospholipid ethers in infancy were inversely associated with mAb+ risk, while dicarboxylic acids were associated with an increased risk. An infancy dietary pattern representing higher levels of unsaturated phosphatidylcholines and phospholipid ethers, and lower sphingomyelins was protective for mAb+ in the nested case-control study only. Characterization of this high-risk infant metabolomics profile may help shape the future of early diagnosis or prevention efforts.

Aims/hypothesis Children participating in longitudinal type 1 diabetes prediction studies were reported to have less severe disease at diabetes diagnosis. Our aim was to investigate children who from birth participated in the Diabetes Prediction in Skåne (DiPiS) study for metabolic status at diagnosis and then continued to be followed for two years of regular clinical care. Methods Children, followed in DiPiS before diagnosis, were compared to children in the same birth cohort who did not participate in follow-up. Metabolic status, symptoms at diagnosis as well as HbA1c and doses of insulin at 3, 6, 12 and 24 months after diagnosis were compared. Results Children, followed in DiPiS and diagnosed at 2–12 years of age, had 0.8% (9 mmol/mol) lower HbA1c at diagnosis than those who were not followed (p=0.006). At diagnosis, fewer DiPiS children had symptoms (p=0.014) and ketoacidosis at diagnosis were reduced (2% compared to 18%, p=0.005). During regular clinical care, HbA1c levels for the DiPiS children remained lower both at 12 (0.4% (4 mmol/mol); p=0.009) and 24 months (0.8% (9 mmol/mol) p <0.001) after diagnosis, despite no difference in total daily insulin between the two groups. Conclusions Participation in prospective follow-up before diagnosis of type 1 diabetes leads to earlier diagnosis with fewer symptoms, decreased incidence of ketoacidosis as well as better metabolic control up to two years after diagnosis. Our data indicate that metabolic control at the time of diabetes diagnosis is important for early metabolic control possibly affecting the risk of long-term complications.

GAD-Alum as a subcutaneous prime and boost injection was safe in prediabetic young children but did not affect progression to type 1 diabetes. The safety of GAD-Alum should prove useful in future prevention studies.

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