التفاصيل البيبلوغرافية
| العنوان: |
Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories |
| المؤلفون: |
Kwon, B. C. (Bum Chul), Anand, V. (Vibha), Achenbach, P. (Peter), Dunne, J. L. (Jessica L.), Hagopian, W. (William), Hu, J. (Jianying), Koski, E. (Eileen), Lernmark, Å. (Åke), Lundgren, M. (Markus), Ng, K. (Kenney), Toppari, J. (Jorma), Veijola, R. (Riitta), Frohnert, B. I. (Brigitte I.), the T1DI Study Group |
| بيانات النشر: |
Springer Nature |
| سنة النشر: |
2022 |
| المجموعة: |
Jultika - University of Oulu repository / Oulun yliopiston julkaisuarkisto |
| مصطلحات موضوعية: |
Autoimmunity, Predictive medicine, Type 1 diabetes |
| الوصف: |
Development of islet autoimmunity precedes the onset of type 1 diabetes in children, however, the presence of autoantibodies does not necessarily lead to manifest disease and the onset of clinical symptoms is hard to predict. Here we show, by longitudinal sampling of islet autoantibodies (IAb) to insulin, glutamic acid decarboxylase and islet antigen-2 that disease progression follows distinct trajectories. Of the combined Type 1 Data Intelligence cohort of 24662 participants, 2172 individuals fulfill the criteria of two or more follow-up visits and IAb positivity at least once, with 652 progressing to type 1 diabetes during the 15 years course of the study. Our Continuous-Time Hidden Markov Models, that are developed to discover and visualize latent states based on the collected data and clinical characteristics of the patients, show that the health state of participants progresses from 11 distinct latent states as per three trajectories (TR1, TR2 and TR3), with associated 5-year cumulative diabetes-free survival of 40% (95% confidence interval [CI], 35% to 47%), 62% (95% CI, 57% to 67%), and 88% (95% CI, 85% to 91%), respectively (p < 0.0001). Age, sex, and HLA-DR status further refine the progression rates within trajectories, enabling clinically useful prediction of disease onset. |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/url/https://github.com/bckwon/dpvis-waterfall |
| الاتاحة: |
http://urn.fi/urn:nbn:fi-fe2022102162736 |
| Rights: |
info:eu-repo/semantics/openAccess ; © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. ; https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: |
edsbas.3103B5D2 |
| قاعدة البيانات: |
BASE |