1. Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases
- Author
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Makoto Hirata, Yoichiro Kamatani, Akiko Nagai, Yutaka Kiyohara, Toshiharu Ninomiya, Akiko Tamakoshi, Zentaro Yamagata, Michiaki Kubo, Kaori Muto, Taisei Mushiroda, Yoshinori Murakami, Koichiro Yuji, Yoichi Furukawa, Hitoshi Zembutsu, Toshihiro Tanaka, Yozo Ohnishi, Yusuke Nakamura, Koichi Matsuda, Masaki Shiono, Kazuo Misumi, Reiji Kaieda, Hiromasa Harada, Shiro Minami, Mitsuru Emi, Naoya Emoto, Hajime Arai, Ken Yamaji, Yoshimune Hiratsuka, Satoshi Asai, Mitsuhiko Moriyama, Yasuo Takahashi, Tomoaki Fujioka, Wataru Obara, Seijiro Mori, Hideki Ito, Satoshi Nagayama, Yoshio Miki, Akihide Masumoto, Akira Yamada, Yasuko Nishizawa, Ken Kodama, Hiromu Kutsumi, Yoshihisa Sugimoto, Yukihiro Koretsune, Hideo Kusuoka, and Takashi Yoshiyama
- Subjects
Male ,0301 basic medicine ,Pathology ,medicine.medical_specialty ,Cross-sectional study ,Epidemiology ,Common disease ,Family history ,Disease ,Logistic regression ,Cohort Studies ,03 medical and health sciences ,0302 clinical medicine ,Japan ,Internal medicine ,Databases, Genetic ,Humans ,Medicine ,Precision Medicine ,Medical History Taking ,Aged ,Biological Specimen Banks ,Biobank ,lcsh:R5-920 ,business.industry ,BioBank Japan Project ,General Medicine ,Odds ratio ,Middle Aged ,Cross-Sectional Studies ,030104 developmental biology ,030220 oncology & carcinogenesis ,Cohort ,Female ,Original Article ,Clinical information ,lcsh:Medicine (General) ,business ,Body mass index - 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., Highlights • The BioBank Japan Project (BBJ) annually collected clinical information. • Analysis of the clinical information at enrollment characterized the BBJ cohort. • Analysis of family history revealed impacts of host genetic factors on the diseases.
- Published
- 2017
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