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Journal of epidemiology · Mar 2017
ReviewOverview of the BioBank Japan Project: Study design and profile.
- Akiko Nagai, Makoto Hirata, Yoichiro Kamatani, Kaori Muto, Koichi Matsuda, Yutaka Kiyohara, Toshiharu Ninomiya, Akiko Tamakoshi, Zentaro Yamagata, Taisei Mushiroda, Yoshinori Murakami, Koichiro Yuji, Yoichi Furukawa, Hitoshi Zembutsu, Toshihiro Tanaka, Yozo Ohnishi, Yusuke Nakamura, BioBank Japan Cooperative Hospital Group, and Michiaki Kubo.
- Department of Public Policy, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
- J Epidemiol. 2017 Mar 1; 27 (3S): S2-S8.
BackgroundThe BioBank Japan (BBJ) Project was launched in 2003 with the aim of providing evidence for the implementation of personalized medicine by constructing a large, patient-based biobank (BBJ). This report describes the study design and profile of BBJ participants who were registered during the first 5-year period of the project.MethodsThe BBJ is a registry of patients diagnosed with any of 47 target common diseases. Patients were enrolled at 12 cooperative medical institutes all over Japan from June 2003 to March 2008. Clinical information was collected annually via interviews and medical record reviews until 2013. We collected DNA from all participants at baseline and collected annual serum samples until 2013. In addition, we followed patients who reported a history of 32 of the 47 target diseases to collect survival data, including cause of death.ResultsDuring the 5-year period, 200,000 participants were registered in the study. The total number of cases was 291,274 at baseline. Baseline data for 199,982 participants (53.1% male) were available for analysis. The average age at entry was 62.7 years for men and 61.5 years for women. Follow-up surveys were performed for participants with any of 32 diseases, and survival time data for 141,612 participants were available for analysis.ConclusionsThe BBJ Project has constructed the infrastructure for genomic research for various common diseases. This clinical information, coupled with genomic data, will provide important clues for the implementation of personalized medicine.Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.
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