| Project/Area Number |
26253041
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Epidemiology and preventive medicine
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| Research Institution | Aichi Cancer Center Research Institute (2015-2016)
Kyushu University (2014) |
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Principal Investigator |
Matsuo Keitaro 愛知県がんセンター(研究所), 遺伝子医療研究部, 部長 (80393122)
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| Co-Investigator(Kenkyū-buntansha) |
大中 佳三 九州大学, 医学(系)研究科(研究院), 講師 (30325518)
山本 健 久留米大学, 医学部, 教授 (60274528)
細野 覚代 愛知県がんセンター(研究所), 疫学・予防部, 主任研究員 (80402600)
高柳 涼一 九州大学, 医学(系)研究科(研究院), 教授 (30154917)
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| Co-Investigator(Renkei-kenkyūsha) |
ITO Hidemi 愛知県がんセンター(研究所), 遺伝子医療研究部, 室長 (90393123)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥42,120,000 (Direct Cost: ¥32,400,000、Indirect Cost: ¥9,720,000)
Fiscal Year 2016: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2015: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2014: ¥32,240,000 (Direct Cost: ¥24,800,000、Indirect Cost: ¥7,440,000)
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| Keywords | ALDH2 / GWAS / 飲酒 / polymorphism / alcohol drinking / 遺伝子多型 / 飲酒習慣 / 全ゲノム関連解析 / 遺伝子環境要因交互作用 / 飲酒行動 / 日本人 |
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| Outline of Final Research Achievements |
We tried to identify new genetic loci for alcohol drinking behaviour among Japanese population. We first tried to examine a cross-sectional study at Aichi Cancer Center and identified previously reported ALDH2 rs671 as a single significant locus. We extended analysis using other epidemiological study with genome-scan data, but failed to identify new locus. Therefore, we changed research focus to identify new diseases which may modified or influence by ALDH2 rs671 polymorphism. We firstly discovered that bladder cancer, formerly regarded as non-alcohol related cancer as acetaldehyde related cancer when we consider ALDH2 genotype. This association was replicated in an independent study. Moreover, association between smoking initiation/quitting and ALDH2 genotype was discovered. For possible application in cancer prevention, we developed risk prediction model and estimated cumulative risk.
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