PMID- 35468213 OWN - NLM STAT- MEDLINE DCOM- 20220718 LR - 20230701 IS - 1945-7197 (Electronic) IS - 0021-972X (Print) IS - 0021-972X (Linking) VI - 107 IP - 8 DP - 2022 Jul 14 TI - Integration of Infant Metabolite, Genetic, and Islet Autoimmunity Signatures to Predict Type 1 Diabetes by Age 6 Years. PG - 2329-2338 LID - 10.1210/clinem/dgac225 [doi] AB - 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. CI - (c) The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. FAU - Webb-Robertson, Bobbie-Jo M AU - Webb-Robertson BM AUID- ORCID: 0000-0002-4744-2397 AD - Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352,USA. AD - Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA. FAU - Nakayasu, Ernesto S AU - Nakayasu ES AUID- ORCID: 0000-0002-4056-2695 AD - Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352,USA. FAU - Frohnert, Brigitte I AU - Frohnert BI AUID- ORCID: 0000-0002-6636-4048 AD - Barbara Davis Center for Childhood Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA. FAU - Bramer, Lisa M AU - Bramer LM AUID- ORCID: 0000-0002-8384-1926 AD - Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352,USA. FAU - Akers, Sarah M AU - Akers SM AUID- ORCID: 0000-0003-3727-5801 AD - Computing & Analytics Division, Pacific Northwest National Laboratory, Richland, Washington 99352, USA. FAU - Norris, Jill M AU - Norris JM AUID- ORCID: 0000-0001-8674-2598 AD - Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA. FAU - Vehik, Kendra AU - Vehik K AUID- ORCID: 0000-0001-6243-6772 AD - Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida 33612, USA. FAU - Ziegler, Anette-G AU - Ziegler AG AUID- ORCID: 0000-0002-6290-5548 AD - Institute of Diabetes Research, Helmholtz Zentrum Munchen, 85764 Neuherberg, Germany. AD - Kilinikum rechts der Isar, Technische Universitat Munchen, 80333 Munich, Germany. AD - Forschergruppe Diabetes e.V., 85764 Neuherberg, Germany. FAU - Metz, Thomas O AU - Metz TO AUID- ORCID: 0000-0001-6049-3968 AD - Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352,USA. FAU - Rich, Stephen S AU - Rich SS AUID- ORCID: 0000-0003-3872-7793 AD - Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908,USA. FAU - Rewers, Marian J AU - Rewers MJ AUID- ORCID: 0000-0003-3829-9207 AD - Barbara Davis Center for Childhood Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, USA. LA - eng GR - U01 DK063821/DK/NIDDK NIH HHS/United States GR - UC4 DK063863/DK/NIDDK NIH HHS/United States GR - UL1 TR002535/TR/NCATS NIH HHS/United States GR - UC4 DK063836/DK/NIDDK NIH HHS/United States GR - U01 DK063790/DK/NIDDK NIH HHS/United States GR - U01 DK063836/DK/NIDDK NIH HHS/United States GR - U01 DK63829/CC/CDC HHS/United States GR - U01 DK063829/DK/NIDDK NIH HHS/United States GR - U01 DK063865/DK/NIDDK NIH HHS/United States GR - UC4 DK095300/DK/NIDDK NIH HHS/United States GR - UC4 DK063861/DK/NIDDK NIH HHS/United States GR - UC4 DK063829/DK/NIDDK NIH HHS/United States GR - ES/NIEHS NIH HHS/United States GR - UC4 DK063821/DK/NIDDK NIH HHS/United States GR - UC4 DK117483/DK/NIDDK NIH HHS/United States GR - U01 DK124166/DK/NIDDK NIH HHS/United States GR - U01 DK063861/DK/NIDDK NIH HHS/United States GR - UC4 DK063865/DK/NIDDK NIH HHS/United States GR - U01 DK063863/DK/NIDDK NIH HHS/United States PT - Journal Article PT - Research Support, N.I.H., Extramural PT - Research Support, U.S. Gov't, P.H.S. PL - United States TA - J Clin Endocrinol Metab JT - The Journal of clinical endocrinology and metabolism JID - 0375362 RN - 0 (Autoantibodies) SB - IM CIN - J Clin Endocrinol Metab. 2022 May 27;:. PMID: 35639990 MH - Autoantibodies/genetics MH - Autoimmunity/genetics MH - Child MH - Child, Preschool MH - Cohort Studies MH - *Diabetes Mellitus, Type 1/diagnosis/epidemiology/genetics MH - Genetic Predisposition to Disease MH - Humans MH - Infant MH - Infant, Newborn MH - *Islets of Langerhans MH - Prospective Studies MH - United States PMC - PMC9282254 OTO - NOTNLM OT - integration OT - machine learning OT - prediction OT - type 1 diabetes EDAT- 2022/04/26 06:00 MHDA- 2022/07/19 06:00 PMCR- 2023/04/25 CRDT- 2022/04/25 17:25 PHST- 2021/06/04 00:00 [received] PHST- 2022/04/26 06:00 [pubmed] PHST- 2022/07/19 06:00 [medline] PHST- 2022/04/25 17:25 [entrez] PHST- 2023/04/25 00:00 [pmc-release] AID - 6573923 [pii] AID - dgac225 [pii] AID - 10.1210/clinem/dgac225 [doi] PST - ppublish SO - J Clin Endocrinol Metab. 2022 Jul 14;107(8):2329-2338. doi: 10.1210/clinem/dgac225.