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10.1016/j.je.2016.12.003 http://scihub22266oqcxt.onion/10.1016/j.je.2016.12.003 C5363792!5363792!28190657     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28190657&cmd=llinks): Failed to open stream: HTTP request failed! 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Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases |pdf=|usr=}}{{28190657}} gab.com Text Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases JO: J Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=28190657 #FOAvip 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. Twit Text FOAVip Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases ????J Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=28190657 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28190657 #FOAvip English Wikipedia <ref>{{Cite pmid|28190657}}</ref> Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases #MMPMID28190657 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; Matsuda K J Epidemiol 2017[Mar]; 27 (3 Suppl): S9-S21 PMID28190657show ga 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. äCross-sectional analysis of BioBank Japan clinical data: A large cohor(epmc).pdf DeepDyve Pubget Overpricing