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Identifying critical age and gender-based metabolomic shifts in a Japanese population of the Tohoku Medical Megabank cohort.
Sakurai, Miyuki; Motoike, Ikuko N; Hishinuma, Eiji; Aoki, Yuichi; Tadaka, Shu; Kogure, Mana; Orui, Masatsugu; Ishikuro, Mami; Obara, Taku; Nakaya, Naoki; Kumada, Kazuki; Hozawa, Atsushi; Kuriyama, Shinichi; Yamamoto, Masayuki; Koshiba, Seizo; Kinoshita, Kengo.
Affiliation
  • Sakurai M; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Motoike IN; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Hishinuma E; Graduate School of Information Sciences, Tohoku University, Sendai, Japan.
  • Aoki Y; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Tadaka S; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, Sendai, Japan.
  • Kogure M; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Orui M; Graduate School of Information Sciences, Tohoku University, Sendai, Japan.
  • Ishikuro M; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Obara T; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Nakaya N; Graduate School of Medicine, Tohoku University, Sendai, Japan.
  • Kumada K; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Hozawa A; Graduate School of Medicine, Tohoku University, Sendai, Japan.
  • Kuriyama S; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Yamamoto M; Graduate School of Medicine, Tohoku University, Sendai, Japan.
  • Koshiba S; Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Kinoshita K; Graduate School of Medicine, Tohoku University, Sendai, Japan.
Sci Rep ; 14(1): 15681, 2024 07 08.
Article in En | MEDLINE | ID: mdl-38977808
ABSTRACT
Understanding the physiological changes associated with aging and the associated disease risks is essential to establish biomarkers as indicators of biological aging. This study used the NMR-measured plasma metabolome to calculate age-specific metabolite indices. In doing so, the scope of the study was deliberately simplified to capture general trends and insights into age-related changes in metabolic patterns. In addition, changes in metabolite concentrations with age were examined in detail, with the period from 55-59 to 60-64 years being a period of significant metabolic change, particularly in men, and from 45-49 to 50-54 years in females. These results illustrate the different variations in metabolite concentrations by sex and provide new insights into the relationship between age and metabolic diseases.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Aging / Metabolome / Metabolomics Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: Japan Publication country: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Aging / Metabolome / Metabolomics Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: Japan Publication country: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM