Brigitte I Frohnert | PubMed Health

PubMed2026

International consensus guidance for general population screening for islet autoantibodies to diagnose early-stage type 1 diabetes: a nominal group technique process.

Type 1 diabetes is an autoimmune disease that targets and destroys insulin-producing beta cells in the pancreatic islets. The incidence of type 1 diabetes is rising globally. At the clinical diagnosis of type 1 diabetes, between 20% and 67% of children and adolescents present with diabetic ketoacidosis (DKA) requiring hospitalisation, and one-third of these require intensive care. Type 1 diabetes can be detected in early stages, prior to the insulin-requiring clinical diagnosis, through screening for islet autoantibodies (IAbs). Identifying individuals with early-stage type 1 diabetes, combined with monitoring of and education on disease progression, prevents DKA and results in a milder clinical onset. This allows for timely insulin initiation in outpatient settings and improved long-term glucose management. Early diagnosis also enables access to novel disease-modifying therapies that can delay the clinical onset of diabetes. In this international consensus, we provide guidance on the principles and practice of implementing general population screening for IAbs to diagnose early-stage type 1 diabetes. We also outline the minimum requirements for establishing effective population screening programmes to diagnose early-stage type 1 diabetes through IAb detection. This consensus statement has been endorsed by the following professional associations: Advanced Technologies & Treatments for Diabetes (ATTD); Association of Diabetes Care and Education Specialists (ADCES); Association Belge Du Diabète; Associazione Medici Diabetologi (AMD); Australian Diabetes Society (ADS); Belgian Diabetes Liga; Breakthrough T1D; Czech Diabetes Society (ČDS); EASD; Finnish Diabetes Association (FDS); Fondazione Italiana Diabete (FID); International Diabetes Federation (IDF)-Europe; International Society of Paediatric and Adolescent Diabetes (ISPAD); Paediatric Endocrinology Nursing Society (PENS); Polish Diabetes Society; Portuguese Diabetes Association (APDP); Sociedade Portuguesa de Diabetologia (SPD); Società Italiana di Diabetologia (SID); Société Francophone du Diabète (SFD) and Type 1 Diabetes Exchange (T1D Exchange).

Consensus report↗

PubMed2022

Integration of Infant Metabolite, Genetic, and Islet Autoimmunity Signatures to Predict Type 1 Diabetes by Age 6 Years.

CONTEXT: Biomarkers that can accurately predict risk of type 1 diabetes (T1D) in genetically predisposed children can facilitate interventions to delay or prevent the disease. OBJECTIVE: This work aimed to determine if a combination of genetic, immunologic, and metabolic features, measured at infancy, can be used to predict the likelihood that a child will develop T1D by age 6 years. METHODS: Newborns with human leukocyte antigen (HLA) typing were enrolled in the prospective birth cohort of The Environmental Determinants of Diabetes in the Young (TEDDY). TEDDY ascertained children in Finland, Germany, Sweden, and the United States. TEDDY children were either from the general population or from families with T1D with an HLA genotype associated with T1D specific to TEDDY eligibility criteria. From the TEDDY cohort there were 702 children will all data sources measured at ages 3, 6, and 9 months, 11.4% of whom progressed to T1D by age 6 years. The main outcome measure was a diagnosis of T1D as diagnosed by American Diabetes Association criteria. RESULTS: Machine learning-based feature selection yielded classifiers based on disparate demographic, immunologic, genetic, and metabolite features. The accuracy of the model using all available data evaluated by the area under a receiver operating characteristic curve is 0.84. Reducing to only 3- and 9-month measurements did not reduce the area under the curve significantly. Metabolomics had the largest value when evaluating the accuracy at a low false-positive rate. CONCLUSION: The metabolite features identified as important for progression to T1D by age 6 years point to altered sugar metabolism in infancy. Integrating this information with classic risk factors improves prediction of the progression to T1D in early childhood.

Autoantibodies↗