| Project/Area Number |
18KT0017
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Multi-year Fund |
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| Section | 特設分野 |
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| Research Field |
Complex Systems Disease Theory
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| Research Institution | Keio University (2021)
The University of Tokyo (2018-2020) |
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Principal Investigator |
Tanaka Hirotoshi 慶應義塾大学, 医学部(信濃町), 特別招聘教授 (00171794)
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| Co-Investigator(Kenkyū-buntansha) |
井元 清哉 東京大学, 医科学研究所, 教授 (10345027)
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| Project Period (FY) |
2018-07-18 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥18,590,000 (Direct Cost: ¥14,300,000、Indirect Cost: ¥4,290,000)
Fiscal Year 2020: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2019: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥11,310,000 (Direct Cost: ¥8,700,000、Indirect Cost: ¥2,610,000)
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| Keywords | 複雑系 / 代謝 / グルココルチコイド受容体 / 臓器連関 / 肥満 / サルコペニア / 骨格筋 / 性差 / 代謝学 / 内分泌学 / オミクス / 生活習慣病 / 糖尿病 / 数理科学 / エネルギー代謝 / 多臓器連関 / グルココルチコイド / 遺伝子発現 / 体組成 / 情報科学 |
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| Outline of Final Research Achievements |
The systemic energy metabolism and body composition are controlled by many factors and regulatory systems, and the manner varies depending on the individual's condition. We considered that such a complex metabolic system is also important in the pathophysiology of obesity, diabetes, and sarcopenia. In this study, we conducted mathematical analyses and molecular biological verification in multiple metabolic model mice. The first of our findings is that excessive fat accumulation in obesity is partly via glucocorticoid signaling in skeletal muscle and related hyperinsulinemia. Second, age-associated early sarcopenic changes involved muscle weakness, and a nutritional intervention that regulates individual's metabolism effectively prevented it. Third, sex differences are found in such mechanisms in muscle-regulated fat accumulation and age-associated early sarcopenic changes.
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| Academic Significance and Societal Importance of the Research Achievements |
肥満や加齢のマウスモデルの解析を通じて、個体の代謝システムの規則性を創る本質的な因子の同定が進むとともに、代謝システムが状況に応じて変容すること、個体背景によって異なること、についての理解が進んだ。本研究で志向した複雑系解析と分子生物学の融合という手法の有用性も明らかとなった。エネルギー代謝に関わる各種の病態（肥満、加齢、糖尿病、脂肪肝、筋萎縮など）の新しい予防法および治療法の開発、とくに個別化医療の実現にも貢献する知見が得られたと考えられる。
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