Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases

• Hirata Makoto

  Laboratory of Genome Technology, Institute of Medical Science, The University of Tokyo

• Kamatani Yoichiro

  Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences

• Nagai Akiko

  Department of Public Policy, Institute of Medical Science, The University of Tokyo

• Kiyohara Yutaka

  Hisayama Research Institute for Lifestyle Diseases

• Ninomiya Toshiharu

  Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University

• Tamakoshi Akiko

  Department of Public Health, Hokkaido University Graduate School of Medicine

• Yamagata Zentaro

  Department of Health Sciences, University of Yamanashi

• Kubo Michiaki

  RIKEN Center for Integrative Medical Sciences

• Muto Kaori

  Department of Public Policy, Institute of Medical Science, The University of Tokyo

• Mushiroda Taisei

  Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences

• Murakami Yoshinori

  Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo

• Yuji Koichiro

  Project Division of International Advanced Medical Research, Institute of Medical Science, The University of Tokyo

• Furukawa Yoichi

  Division of Clinical Genome Research, Institute of Medical Science, The University of Tokyo

• Zembutsu Hitoshi

  Laboratory of Molecular Medicine, Institute of Medical Science, The University of Tokyo Division of Genetics, National Cancer Center Research Institute

• Tanaka Toshihiro

  SNP Research Center, RIKEN Yokohama Institute Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University Bioresource Research Center, Tokyo Medical and Dental University

• Ohnishi Yozo

  SNP Research Center, RIKEN Yokohama Institute Shinko Clinic, Medical Corporation Shinkokai

• Nakamura Yusuke

  Laboratory of Molecular Medicine, Institute of Medical Science, The University of Tokyo Section of Hematology/Oncology, Department of Medicine, The University of Chicago

• BioBank Japan Cooperative Hospital Group

• Matsuda Koichi

  Laboratory of Molecular Medicine, Institute of Medical Science, The University of Tokyo Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo

Abstract

Background: To implement personalized medicine, we established a large-scale patient cohort, BioBank Japan, in 2003. BioBank Japan contains DNA, serum, and clinical information derived from approximately 200,000 patients with 47 diseases. Serum and clinical information were collected annually until 2012. Methods: We analyzed clinical information of participants at enrollment, including age, sex, body mass index, hypertension, and smoking and drinking status, across 47 diseases, and compared the results with the Japanese database on Patient Survey and National Health and Nutrition Survey. We conducted multivariate logistic regression analysis, adjusting for sex and age, to assess the association between family history and disease development. Results: Distribution of age at enrollment reflected the typical age of disease onset. Analysis of the clinical information revealed strong associations between smoking and chronic obstructive pulmonary disease, drinking and esophageal cancer, high body mass index and metabolic disease, and hypertension and cardiovascular disease. Logistic regression analysis showed that individuals with a family history of keloid exhibited a higher odds ratio than those without a family history, highlighting the strong impact of host genetic factor(s) on disease onset. Conclusions: Cross-sectional analysis of the clinical information of participants at enrollment revealed characteristics of the present cohort. Analysis of family history revealed the impact of host genetic factors on each disease. BioBank Japan, by publicly distributing DNA, serum, and clinical information, could be a fundamental infrastructure for the implementation of personalized medicine.

Journal

• Journal of Epidemiology

  Journal of Epidemiology 27 (Supplement_III), S9-S21, 2017

  Japan Epidemiological Association

Keywords

• BioBank Japan Project
• Biobank
• Common disease
• Clinical information
• Family history

Details

• CRID: 1390001204476322048
• NII Article ID: 130006832556
• DOI: 10.1016/j.je.2016.12.003
• ISSN: 13499092
• ISSN: 09175040
• Web Site: http://api.elsevier.com/content/article/PII:S0917504016301186?httpAccept=text/xml
• Web Site: http://api.elsevier.com/content/article/PII:S0917504016301186?httpAccept=text/plain
• Web Site: https://search.jamas.or.jp/link/ui/2018049259
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed