Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases.
Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases.
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DOI：
10.1016/j.je.2016.12.003
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发表时间：
2017-03
影响因子：
4.7
通讯作者：
Matsuda K
中科院分区：
文献类型：
--
作者：
Hirata M;Kamatani Y;Nagai A;Kiyohara Y;Ninomiya T;Tamakoshi A;Yamagata Z;Kubo M;Muto K;Mushiroda T;Murakami Y;Yuji K;Furukawa Y;Zembutsu H;Tanaka T;Ohnishi Y;Nakamura Y;BioBank Japan Cooperative Hospital Group;Matsuda K
为了实施个性化医疗，我们在2003年建立了一个大规模的患者队列--日本生物库。日本生物库包含来自47种疾病的大约200,000名患者的DNA、血清和临床信息。血清和临床信息每年收集一次，直到2012年。我们分析了注册参与者的临床信息，包括年龄、性别、体重指数、高血压、吸烟和饮酒状况，涉及47种疾病，并将结果与日本患者调查数据库和国家健康与营养调查数据库进行比较。我们进行了多变量Logistic回归分析，调整了性别和年龄，以评估家族史和疾病发展之间的联系。登记时的年龄分布反映了典型的疾病发病年龄。对临床信息的分析显示，吸烟与慢性阻塞性肺疾病、饮酒与食道癌、高体重指数与代谢性疾病、高血压与心血管疾病之间存在很强的相关性。Logistic回归分析显示，有瘢痕疙瘩家族史的个体比无家族史者的优势比高，突出了宿主遗传因素(S)对发病的强烈影响。对登记时参与者的临床信息的横断面分析揭示了当前队列的特征。家族史分析揭示了宿主遗传因素对每种疾病的影响。通过公开分发DNA、血清和临床信息，Biobank Japan可以成为实施个性化医疗的基础设施。生物库日本项目(BBJ)每年收集临床信息。对BBJ队列入选时的临床信息进行分析。家族史分析揭示了宿主遗传因素对疾病的影响。
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. 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. 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. 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. 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.