| Project/Area Number |
17H04349
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Ophthalmology
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| Research Institution | Tohoku University |
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Principal Investigator |
Nakazawa Toru 東北大学, 医学系研究科, 教授 (30361075)
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| Co-Investigator(Kenkyū-buntansha) |
三枝 大輔 東北大学, 東北メディカル・メガバンク機構, 講師 (90545237)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2019: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2018: ¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2017: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
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| Keywords | 緑内障 / メタボロミクス / バイオマーカー / メタボローム解析 |
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| Outline of Final Research Achievements |
Human samples were analyzed for the purpose of primary selection of powerful biomarker candidates by metabolomics. Comprehensive metabolomics were performed using samples of anterior chamber fluid, peripheral blood, and urine of patients from open-angle glaucoma. As a control group, samples from patients with cataract, preretinal membrane and macular hole were used. The anterior chamber fluid, blood, and urine samples were collected from the same patient. As a result of analyzing 34 cases in the glaucoma group and 37 in the control group, the metabolites varying in the glaucoma group was extracted by the principal component analysis and the discriminant analysis. Furthermore, correlation between the amount of metabolites in the anterior chamber fluid and clinical parameters such as MD value and axial length was investigated, and several metabolites that correlated with each parameter were found.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究により、眼局所のイベントを反映すると考えられる前房水内の代謝物に加え、緑内障患者の体質を反映すると考えられる血液中ならびに尿中の代謝物群を同定した。緑内障は不可逆な視野欠損を示す本邦の中途失明原因の第一位の疾患であり、早期診断は失明対策において重要である。本研究により同定された代謝物はバイオマーカー候補として緑内障の診断補助への応用に加え、緑内障病態の理解ならびに個別化医療の実現に向けた基盤研究となることが期待される。
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