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Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children |
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| Author: | Jacobsen, Laura M.1; Larsson, Helena E.2; Tamura, Roy N.3; |
| Organizations: |
1Department of Pediatrics, University of Florida, Gainesville, Florida 2Department of Clinical Sciences Malmö, Lund University, Skåne University Hospital SUS, Malmö, Sweden 3Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida
4Division of Endocrinology, University of Miami, Miami, Florida
5Pacific Northwest Diabetes Research Institute, Seattle, Washington 6Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, Georgia 7Barbara Davis Center for Childhood Diabetes, University of Colorado, Denver, Colorado 8Department of Pediatrics, Turku University Hospital, Turku, Finland 9Department of Physiology, Institute of Biomedicine, University of Turku, Turku, Finland 10Department of Pediatrics, Medical Research Center, PEDEGO Research Unit, Oulu University Hospital and University of Oulu, Oulu, Finland 11Institute of Diabetes Research, Helmholtz Zentrum München and Forschergruppe Diabetes e.V. Neuherberg, Neuherberg, Germany 12Division of Diabetes, Endocrinology, and Metabolism, National Institute of Diabetes, Digestive, and Kidney Diseases, National Institutes of Health, Bethesda, Maryland |
| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 0.8 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2019042613357 |
| Language: | English |
| Published: |
John Wiley & Sons,
2019
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| Publish Date: | 2020-01-10 |
| Description: |
AbstractObjective: 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. see all
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| Series: |
Pediatric diabetes |
| ISSN: | 1399-543X |
| ISSN-E: | 1399-5448 |
| ISSN-L: | 1399-543X |
| Volume: | 20 |
| Issue: | 3 |
| Pages: | 263 - 270 |
| DOI: | 10.1111/pedi.12812 |
| OADOI: | https://oadoi.org/10.1111/pedi.12812 |
| Type of Publication: |
A1 Journal article – refereed |
| Field of Science: |
3121 General medicine, internal medicine and other clinical medicine 3123 Gynaecology and paediatrics |
| Subjects: | |
| Funding: |
NIH/NCATS Clinical and Translational Science Award University of Colorado, Grant/Award Number: UL1 TR001082; NIH/NCATS Clinical and Translational Science Award University of Florida, Grant/Award Number: UL1 TR000064; TEDDY Study group funding grants, Grant/Award Number: U01 DK63863, U01 DK63836, U01 DK63790 UC4 DK106955, UC4 DK112243, UC4 DK117483 Contract No. HHSN267200700014CU01 DK63829, U01 DK63861, U01 DK63821, U01 DK63865UC4 DK106955, UC4 DK112243, UC4 DK117483UC4 DK63829, UC4 DK63861, UC4 DK63821, UC4 DK63865UC4 DK63863, UC4 DK95300, UC4 DK100238; University of Florida; Florida State University; Columbia University; University of Virginia; University of Bristol; Davis Center; University of South Florida; Clinical Center; Lunds Universitet; Clinical Center; TU Dresden; Technische Universität München; Clinical Center; University of Florida; Augusta University; Clinical Center; Tampere University Hospital; Turku University Hospital; University of Tampere; Clinical Center; Davis Center; University of Colorado; Clinical Center; University of Colorado; University of Florida; Centers for Disease Control and Prevention; National Institute of Environmental Health Sciences; National Institute of Child Health and Human Development; National Institute of Allergy and Infectious Diseases; National Institute of Diabetes and Digestive and Kidney Diseases |
| Copyright information: |
© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. This is the peer reviewed version of the following article: Jacobsen, LM, Larsson, HE, Tamura, RN, et al. Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children. Pediatr Diabetes. 2019; 20: 263– 270, which has been published in final form at https://doi.org/10.1111/pedi.12812. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. |