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Harada, Sei; Iida, Miho; Miyagawa, Naoko; Hirata, Aya; Kuwabara, Kazuyo; Matsumoto, Minako; Okamura, Tomonori; Edagawa, Shun; Kawada, Yoko; Miyake, Atsuko; Toki, Ryota; Akiyama, Miki; Kawai, Atsuki; Sugiyama, Daisuke; Sato, Yasunori; Takemura, Ryo; Fukai, Kota; Ishibashi, Yoshiki; Kato, Suzuka; Kurihara, Ayako; Sata, Mizuki; Shibuki, Takuma; Takeuchi, Ayano; Kohsaka, Shun; Sawano, Mitsuaki; Shoji, Satoshi; Izawa, Yoshikane; Katsumata, Masahiro; Oki, Koichi; Takahashi, Shinichi; Takizawa, Tsubasa; Maruya, Hiroshi; Nishiwaki, Yuji; Kawasaki, Ryo; Hirayama, Akiyoshi; Ishikawa, Takamasa; Saito, Rintaro; Sato, Asako; Soga, Tomoyoshi; Sugimoto, Masahiro; Tomita, Masaru; Komaki, Shohei; Ohmomo, Hideki; Ono, Kanako; Otsuka-Yamasaki, Yayoi; Shimizu, Atsushi; Sutoh, Yoichi; Hozawa, Atsushi; Kinoshita, Kengo; Koshiba, Seizo; Kumada, Kazuki; Ogishima, Soichi; Sakurai-Yageta, Mika; Tamiya, Gen; Takebayashi, Toru
Journal of Epidemiology, 2024Journal Article
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.
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