Japanese Type 1 Diabetes Database Study (TIDE-J): rationale and study design
Japanese Type 1 Diabetes Database Study (TIDE-J): rationale and study design
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DOI：
10.1007/s13340-021-00541-2
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发表时间：
2021-09-06
影响因子：
2.2
通讯作者：
Kajio, Hiroshi
中科院分区：
文献类型：
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作者：
Chujo, Daisuke;Imagawa, Akihisa;Kajio, Hiroshi
根据日本临床病程的异质性，1型糖尿病（T1D）可分为急性发作型、缓慢进展型和暴发性T1D三种亚型。虽然已经报道了几个T1D的横断面数据库，但我国缺乏调查临床结果的前瞻性纵向数据库。为此，我们构建了T1D三亚型的多中心前瞻性纵向数据库，并附有遗传信息和生物库，命名为日本1型糖尿病数据库研究（TIDE-J）。本研究的纳入标准为：(1)T1D持续时间小于5年；(2)患者有一种或多种胰岛相关自身抗体和/或空腹血清c肽水平小于1.0 ng/mL;(3)患者能够清楚地理解书面的研究同意。TIDE-J使用电子数据收集系统REDCap每年收集临床数据，包括血糖控制、内源性胰岛素分泌、胰岛相关自身抗体、糖尿病并发症和治疗情况。此外，每位参与者的HLA基因型在进入时进行分析，血液样本被保存以评估探索性标记和每年进一步的遗传分析。TIDE-J确实有助于揭示每种T1D亚型的不同临床病程。此外，该数据库可能有助于识别诊断T1D各亚型的新标志物，并预测患者的临床结果（包括胰腺细胞功能和疾病严重程度）。
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.