| Project/Area Number |
25461012
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Gastroenterology
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| Research Institution | The Nippon Dental University (2014-2015)
Showa University (2013) |
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Principal Investigator |
Ohkoshi Shogo 日本歯科大学, 新潟生命歯学部, 教授 (70231199)
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| Co-Investigator(Kenkyū-buntansha) |
MATSUDA Yasunobu 新潟大学, 医歯学系, 准教授 (40334669)
YAMAGIWA Satoshi 新潟大学, 医歯学系, 准教授 (10419327)
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| Co-Investigator(Renkei-kenkyūsha) |
YANO Masahiko 昭和大学, 歯学部, 助教 (70529693)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2014: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2013: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
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| Keywords | HCV / RBP-4 / Peg-IFN / インスリン抵抗性 / IFN / Insulin抵抗性 / C型慢性肝炎 / インターフェロン / リバビリン / RBP4 / 肝脂肪化 |
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| Outline of Final Research Achievements |
We examined whether RBP4(Retinol binding protein 4) was a significant factor which determined the outcome of the CH C patients with genotype 1b who were treated with PEG-IFN plus ribavirin.
Because RBP4 was a marker of insulin resistance, we speculated that this might be the key molecule which determined the association between IFN therapy and insulin resistance. We performed in vitro experiments to examine whether RBP4 suppressed IFN signalling, resulting in the resistance of HCV replication against IFN. As a result, in RBP4-knockdown hepatoma cell, ISG genes were activatied and HCV replication was enhanced when compared to RBP4 (+) cells. Thus we found that RBP4 interfered the action of IFN against HCV and result in IFN resistance.
However, RBP4 was not proved to be a significant factor for the prediction of clinical data from more number of patients. In conclusion, we could not verify the significance of RBP4 levels for the prediction of IFN therapy.
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