著者
Kazuharu Arakawa Masaru Tomita
出版者
Pesticide Science Society of Japan
雑誌
Journal of Pesticide Science (ISSN:1348589X)
巻号頁・発行日
vol.31, no.3, pp.282-288, 2006 (Released:2006-08-24)
参考文献数
52
被引用文献数
14 28

The advent of high-throughput measurement technologies has resulted in the rapid accumulation of “omics” information including genome, transcriptome, proteome, and metabolome data. This increase in data acquisition has lead to a demand for an efficient computational platform for in silico analysis. The G-language software suite provides a comprehensive workbench for large-scale omics research and systems biology. The suite includes a bioinformatics research framework G-language Genome Analysis Environment, which contains a Gene Prediction Accuracy Classification benchmarking tool for the quantification of the sensitivity of genome informatics analysis methods to genome annotation completeness. Omics data processed in this environment can be visualized with KEGG-based pathway mapping web service, and Genome-based Modeling System enables automatic prototyping of metabolic pathway models from the genome. The software suite covers various domains of omics, with the goal of integrating all of these data for research into systems biology.
著者
Sei Harada Hideki Ohmomo Minako Matsumoto Mizuki Sata Miho Iida Aya Hirata Naoko Miyagawa Kazuyo Kuwabara Suzuka Kato Ryota Toki Shun Edagawa Daisuke Sugiyama Asako Sato Akiyoshi Hirayama Masahiro Sugimoto Tomoyoshi Soga Masaru Tomita Atsushi Shimizu Tomonori Okamura Toru Takebayashi
出版者
Japan Epidemiological Association
雑誌
Journal of Epidemiology (ISSN:09175040)
巻号頁・発行日
pp.JE20230170, (Released:2023-11-04)
参考文献数
33
被引用文献数
1

Background: Heated tobacco products (HTPs) have gained global popularity, but their health risks remain unclear. Therefore, the current study aimed to identify plasma metabolites associated with smoking and HTP use in a large Japanese population to improve health risk assessment.Methods: Metabolomics data from 9,922 baseline participants of the Tsuruoka Metabolomics Cohort Study (TMCS) were analyzed to determine the association between smoking habits and plasma metabolites. Moreover, alterations in smoking-related metabolites among HTP users were examined based on data obtained from 3,334 participants involved from April 2018 to June 2019 in a follow-up survey.Results: Our study revealed that cigarette smokers had metabolomics profiles distinct from never smokers, with 22 polar metabolites identified as candidate biomarkers for smoking. These biomarker profiles of HTP users were closer to those of cigarette smokers than those of never smokers. The concentration of glutamate was higher in cigarette smokers, and biomarkers involved in glutamate metabolism were also associated with cigarette smoking and HTP use. Network pathway analysis showed that smoking was associated with the glutamate pathway, which could lead to endothelial dysfunction and atherosclerosis of the vessels.Conclusions: Our study showed that the glutamate pathway is affected by habitual smoking. These changes in the glutamate pathway may partly explain the mechanism by which cigarette smoking causes cardiovascular disease. HTP use was also associated with glutamate metabolism, indicating that HTP use may contribute to the development of cardiovascular disease through mechanisms similar to those in cigarette use.
著者
Sei Harada Miho Iida Naoko Miyagawa Aya Hirata Kazuyo Kuwabara Minako Matsumoto Tomonori Okamura Shun Edagawa Yoko Kawada Atsuko Miyake Ryota Toki Miki Akiyama Atsuki Kawai Daisuke Sugiyama Yasunori Sato Ryo Takemura Kota Fukai Yoshiki Ishibashi Suzuka Kato Ayako Kurihara Mizuki Sata Takuma Shibuki Ayano Takeuchi Shun Kohsaka Mitsuaki Sawano Satoshi Shoji Yoshikane Izawa Masahiro Katsumata Koichi Oki Shinichi Takahashi Tsubasa Takizawa Hiroshi Maruya Yuji Nishiwaki Ryo Kawasaki Akiyoshi Hirayama Takamasa Ishikawa Rintaro Saito Asako Sato Tomoyoshi Soga Masahiro Sugimoto Masaru Tomita Shohei Komaki Hideki Ohmomo Kanako Ono Yayoi Otsuka-Yamasaki Atsushi Shimizu Yoichi Sutoh Atsushi Hozawa Kengo Kinoshita Seizo Koshiba Kazuki Kumada Soichi Ogishima Mika Sakurai-Yageta Gen Tamiya Toru Takebayashi
出版者
Japan Epidemiological Association
雑誌
Journal of Epidemiology (ISSN:09175040)
巻号頁・発行日
pp.JE20230192, (Released:2024-01-06)
参考文献数
40
被引用文献数
1

The Tsuruoka Metabolomics Cohort Study (TMCS) is an ongoing population-based cohort study being conducted in the rural area of Yamagata Prefecture, Japan. This study aimed to enhance the precision prevention of multi-factorial, complex diseases, including non-communicable and aging-associated diseases, by improving risk stratification and prediction measures. At baseline, 11,002 participants aged 35–74 years were recruited in Tsuruoka City, Yamagata Prefecture, Japan, between 2012 and 2015, with an ongoing follow-up survey. Participants underwent various measurements, examinations, tests, and questionnaires on their health, lifestyle, and social factors. This study used an integrative approach with deep molecular profiling to identify potential biomarkers linked to phenotypes that underpin disease pathophysiology and provide better mechanistic insights into social health determinants. The TMCS incorporates multi-omics data, including genetic and metabolomic analyses of 10,933 participants and comprehensive data collection ranging from physical, psychological, behavioral, and social to biological data. The metabolome is used as a phenotypic probe because it is sensitive to changes in physiological and external conditions. The TMCS focuses on collecting outcomes for cardiovascular disease, cancer incidence and mortality, disability, functional decline due to aging and disease sequelae, and the variation in health status within the body represented by omics analysis that lies between exposure and disease. It contains several sub-studies on aging, heated tobacco products, and women's health. This study is notable for its robust design, high participation rate (89%), and long-term repeated surveys. Moreover, it contributes to precision prevention in Japan and East Asia as a well-established multi-omics platform.