Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report
Author:
Krischer Jeffrey P.1ORCID, Liu Xiang1, Vehik Kendra1, Akolkar Beena2, Hagopian William A.3, Rewers Marian J.4, She Jin-Xiong5, Toppari Jorma67, Ziegler Anette-G.8ORCID, Lernmark Åke9, Rewers Marian, Bautista Kimberly, Baxter Judith, Felipe-Morales Daniel, Driscoll Kimberly, Frohnert Brigitte I., Gallant Marisa, Gesualdo Patricia, Hoffman Michelle, Karban Rachel, Liu Edwin, Norris Jill, Steck Andrea, Waugh Kathleen, Toppari Jorma, Simell Olli G., Adamsson Annika, Ahonen Suvi, Hekkala Mari Åkerlund Anne, Holappa Henna, Hyöty Heikki, Ikonen Anni, Ilonen Jorma, Jäminki Sinikka, Jokipuu Sanna, Karlsson Leena, Kähönen Miia, Knip Mikael, Koivikko Minna-Liisa, Koreasalo Mirva, Kurppa Kalle, Kytölä Jarita, Latva-aho Tiina, Lindfors Katri, Lönnrot Maria, Mäntymäki Elina, Mattila Markus, Multasuo Katja, Mykkänen Teija, Niininen Tiina, Niinistö Sari, Nyblom Mia, Oikarinen Sami, Ollikainen Paula, Pohjola Sirpa, Rajala Petra, Rautanen Jenna, Riikonen Anne, Romo Minna, Ruohonen Suvi, Simell Satu, Sjöberg Maija, Stenius Aino, Tossavainen Päivi, Vähä-Mäkilä Mari, Vainionpää Sini, Varjonen Eeva, Veijola Riitta, Viinikangas Irene, Virtanen Suvi M., She Jin-Xiong, Schatz Desmond, Hopkins Diane, Steed Leigh, Bryant Jennifer, Silvis Katherine, Haller Michael, Gardiner Melissa, McIndoe Richard, Sharma Ashok, Anderson Stephen W., Jacobsen Laura, Marks John, Towe P.D., Ziegler Anette G., Bonifacio Ezio, D'Angelo Miryam, Gavrisan Anita, Gezginci Cigdem, Heublein Anja, Hoffmann Verena, Hummel Sandra, Keimer Andrea, Knopff Annette, Koch Charlotte, Koletzko Sibylle, Ramminger Claudia, Roth Roswith, Scholz Marlon, Stock Joanna, Warncke Katharina, Wendel Lorena, Winkler Christiane, Lernmark Åke, Agardh Daniel, Aronsson Carin Andrén, Ask Maria, Bremer Jenny, Cilio Corrado, Ericson-Hallström Emelie, Fors Annika, Fransson Lina, Gard Thomas, Bennet Rasmus, Hansen Monika, Hyberg Susanne, Jisser Hanna, Johansen Fredrik, Jonsdottir Berglind, Jovic Silvija, Larsson Helena Elding, Lindström Marielle, Lundgren Markus, Månsson-Martinez Maria, Markan Maria, Melin Jessica, Mestan Zeliha, Nilsson Caroline, Ottosson Karin, Rahmati Kobra, Ramelius Anita, Salami Falastin, Sjöberg Anette, Sjöberg Birgitta, Törn Carina, Wallin Anne, Wimar Åsa, Åberg Sofie, Hagopian William A., Killian Michael, Crouch Claire Cowen, Skidmore Jennifer, Akramoff Ashley, Chavoshi Masumeh, Dunson Kayleen, Hervey Rachel, Lyons Rachel, Meyer Arlene, Mulenga Denise, Radtke Jared, Romancik Matei, Schmitt Davey, Schwabe Julie, Zink Sarah, Becker Dorothy, Franciscus Margaret, Smith MaryEllen Dalmagro-Elias, Daftary Ashi, Klein Mary Beth, Yates Chrystal, Krischer Jeffrey P., Austin-Gonzalez Sarah, Avendano Maryouri, Baethke Sandra, Brown Rasheedah, Burkhardt Brant, Butterworth Martha, Clasen Joanna, Cuthbertson David, Eberhard Christopher, Fiske Steven, Garmeson Jennifer, Gowda Veena, Heyman Kathleen, Hsiao Belinda, Karges Christina, Laras Francisco Perez, Lee Hye-Seung, Li Qian, Liu Shu, Liu Xiang, Lynch Kristian, Maguire Colleen, Malloy Jamie, McCarthy Cristina, Merrell Aubrie, Meulemans Steven, Parikh Hemang, Quigley Ryan, Remedios Cassandra, Shaffer Chris, Smith Laura, Smith Susan, Sulman Noah, Tamura Roy, Tewey Dena, Toth Michael, Uusitalo Ulla, Vehik Kendra, Vijayakandipan Ponni, Wood Keith, Yang Jimin, Yu Liping, Miao Dongmei, Bingley Polly, Williams Alistair, Chandler Kyla, Ball Olivia, Kelland Ilana, Grace Sian, Gillard Ben, Hagopian William, Chavoshi Masumeh, Radtke Jared, Schwabe Julie, Erlich Henry, Mack Steven J., Fear Anna Lisa, Ke Sandra, Mulholland Niveen, Rich Stephen S., Chen Wei-Min, Onengut-Gumuscu Suna, Farber Emily, Pickin Rebecca Roche, Davis Jonathan, Davis Jordan, Gallo Dan, Bonnie Jessica, Campolieto Paul, Akolkar Beena, Bourcier Kasia, Briese Thomas, Johnson Suzanne Bennett, Triplett Eric,
Affiliation:
1. Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 2. National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 3. Pacific Northwest Research Institute, Seattle, WA 4. Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, CO 5. Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 6. Research Centre for Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku, Turku, Finland 7. Department of Pediatrics, Turku University Hospital, Turku, Finland 8. Klinikum rechts der Isar, Technische Universität München, and Forschergruppe Diabetes e.V., Helmholtz Zentrum München, Neuherberg, Germany 9. Department of Clinical Sciences, Clinical Research Centre, Lund University, Skane University Hospital, Malmö, Sweden
Abstract
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.
Funder
National Institute of Diabetes and Digestive and Kidney Diseases National Center for Advancing Translational Sciences
Publisher
American Diabetes Association
Subject
Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine
Cited by
70 articles.
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