| Literature DB >> 35059265 |
Daisuke Chujo1,2,3, Akihisa Imagawa4, Kazuki Yasuda5, Norio Abiru6, Takuya Awata7, Tomoyasu Fukui8, Hiroshi Ikegami9, Eiji Kawasaki10, Takeshi Katsuki11, Tetsuro Kobayashi12, Junji Kozawa13, Kan Nagasawa14, Hiroshi Ohtsu15, Yoichi Oikawa16, Haruhiko Osawa17, Akira Shimada16, Masayuki Shimoda3, Kazuma Takahashi18, Kyoichiro Tsuchiya19, Tetsuro Tsujimoto20, Hisafumi Yasuda21, Toshiaki Hanafusa4,22, Hiroshi Kajio1.
Abstract
Type 1 diabetes (T1D) is classified into three subtypes: acute-onset, slowly progressive, and fulminant T1D, according to the heterogeneity of clinical course in Japan. Although several cross-sectional databases of T1D have been reported, prospective longitudinal databases to investigate clinical outcomes are lacking in our country. Therefore, we herein construct multi-center prospective longitudinal database of the three subtypes of T1D, accompanied with genetic information and biobanking, which is named Japanese Type 1 Diabetes Database Study (TIDE-J). Inclusion criteria of this study are as follows: (1) the duration of T1D was less than 5 years, (2) the patients had one or more islet-related autoantibodies and/or fasting serum C-peptide levels were less than 1.0 ng/mL, (3) the patients could clearly understand the study consent in writing. In the TIDE-J, clinical data, including glycemic control, endogenous insulin secretion, islet-related autoantibodies, diabetic complications, and treatment, are collected annually using electric data collection system, which is named REDCap. Furthermore, HLA genotypes of each participant were analyzed at entry and the blood samples were stored for assessing exploratory markers and further genetic analysis annually. The TIDE-J certainly helps in revealing distinct clinical course of each T1D subtype. Moreover, this database may help in identifying novel markers for diagnosing each subtype of T1D and predicting clinical outcomes (including pancreatic beta cell function and disease severity) in patients. © The Japan Diabetes Society 2021.Entities:
Keywords: Database; Electric data collection; Multi-center; Type 1 diabetes
Year: 2021 PMID: 35059265 PMCID: PMC8733142 DOI: 10.1007/s13340-021-00541-2
Source DB: PubMed Journal: Diabetol Int ISSN: 2190-1678