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

作者：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, Takashi Yoshiyama · 发表于：Journal of Epidemiology · 年份：2017 · DOI：10.1016/j.je.2016.12.003 · 被引用次数：179 · 研究领域：Genetic Associations and Epidemiology、Dermatologic Treatments and Research、Nutrition, Genetics, and Disease

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 impa...