TY - JOUR
T1 - Cross-sectional analysis of BioBank Japan clinical data
T2 - A large cohort of 200,000 patients with 47 common diseases
AU - BioBank Japan Cooperative Hospital Group
AU - Hirata, Makoto
AU - Kamatani, Yoichiro
AU - Nagai, Akiko
AU - Kiyohara, Yutaka
AU - Ninomiya, Toshiharu
AU - Tamakoshi, Akiko
AU - Yamagata, Zentaro
AU - Kubo, Michiaki
AU - Muto, Kaori
AU - Mushiroda, Taisei
AU - Murakami, Yoshinori
AU - Yuji, Koichiro
AU - Furukawa, Yoichi
AU - Zembutsu, Hitoshi
AU - Tanaka, Toshihiro
AU - Ohnishi, Yozo
AU - Nakamura, Yusuke
AU - Matsuda, Koichi
AU - Shiono, Masaki
AU - Misumi, Kazuo
AU - Kaieda, Reiji
AU - Harada, Hiromasa
AU - Minami, Shiro
AU - Emi, Mitsuru
AU - Emoto, Naoya
AU - Arai, Hajime
AU - Yamaji, Ken
AU - Hiratsuka, Yoshimune
AU - Asai, Satoshi
AU - Moriyama, Mitsuhiko
AU - Takahashi, Yasuo
AU - Fujioka, Tomoaki
AU - Obara, Wataru
AU - Mori, Seijiro
AU - Ito, Hideki
AU - Nagayama, Satoshi
AU - Miki, Yoshio
AU - Masumoto, Akihide
AU - Yamada, Akira
AU - Nishizawa, Yasuko
AU - Kodama, Ken
AU - Kutsumi, Hiromu
AU - Sugimoto, Yoshihisa
AU - Koretsune, Yukihiro
AU - Kusuoka, Hideo
AU - Yoshiyama, Takashi
N1 - Publisher Copyright:
© 2017 The Authors.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - BioBank Japan Project
KW - Biobank Common disease
KW - Clinical information
KW - Family history
UR - http://www.scopus.com/inward/record.url?scp=85016420191&partnerID=8YFLogxK
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U2 - 10.1016/j.je.2016.12.003
DO - 10.1016/j.je.2016.12.003
M3 - Article
C2 - 28190657
AN - SCOPUS:85016420191
SN - 0917-5040
VL - 27
SP - S9-S21
JO - Journal of epidemiology
JF - Journal of epidemiology
IS - 3
ER -