Classification Method for Predicting the Development of Myocardial Infarction by Using the Interaction between Genetic and Environmental Factors

• Item type: Trans(1)
• 公開日: 2006-11-15
• タイトル: Classification Method for Predicting the Development of Myocardial Infarction by Using the Interaction between Genetic and Environmental Factors
• タイトル / 言語: en
• タイトル: Classification Method for Predicting the Development of Myocardial Infarction by Using the Interaction between Genetic and Environmental Factors
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: Original Papers
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Department of Biotechnology School of Engineering Nagoya University
• 著者所属: Department of Cardiology Graduate School of Medicine Nagoya University
• 著者所属: Department of Cardiology Graduate School of Medicine Nagoya University
• 著者所属: Department of Cardiovascular Genome Science School of Medicine Nagoya University
• 著者所属: School of Bioscience and Biotechnology Chubu University Presently with Department of Genome Science School of Dentistry Aichi-Gakuin University
• 著者所属: Department of Biotechnology School of Engineering Nagoya University
• 著者所属(英): en
• 著者所属(英): Department of Biotechnology, School of Engineering, Nagoya University
• 著者所属(英): en
• 著者所属(英): Department of Cardiology, Graduate School of Medicine, Nagoya University
• 著者所属(英): en
• 著者所属(英): Department of Cardiology, Graduate School of Medicine, Nagoya University
• 著者所属(英): en
• 著者所属(英): Department of Cardiovascular Genome Science, School of Medicine, Nagoya University
• 著者所属(英): en
• 著者所属(英): School of Bioscience and Biotechnology, Chubu University , Presently with Department of Genome Science, School of Dentistry, Aichi-Gakuin University
• 著者所属(英): en
• 著者所属(英): Department of Biotechnology, School of Engineering, Nagoya University
• 著者名: Yasuyuki, Tomita; Hiroyuki, Asano; Hideo, Izawa; Mitsuhiro, Yokota; Takeshi, Kobayashi; Hiroyuki, Honda
• 著者名(英): Yasuyuki, Tomita; Hiroyuki, Asano; Hideo, Izawa; Mitsuhiro, Yokota; Takeshi, Kobayashi; Hiroyuki, Honda
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Multifactorial diseases such as lifestyle-related diseases for example cancer diabetes mellitus and myocardial infarction are believed to be caused by the complex interactions between various environmental factors on a polygenic basis. In addition it is believed that genetic risk factors for the same disease differ on an individual basis according to their susceptible environmental factors. In the present study to predict the development of myocardial infarction (MI) and classify the subjects into personally optimum development patterns we have extracted risk factor candidates (RFCs) that comprised a state that is a derivative form of polymorphisms and environmental factors using a statistical test. We then selected the risk factors using a criterion for detecting personal group (CDPG) which is defined in the present study. By using CDPG we could predict the development of MI in blinded subjects with an accuracy greater than 75% In addition the risk percentage for MI was higher with an increase in the number of selected risk factors in the blinded data. Since sensitivity using the CDPG was high it can be an effective and useful tool in preventive medicine and its use may provide a high quality of life and reduce medical costs.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Multifactorial diseases, such as lifestyle-related diseases, for example, cancer, diabetes mellitus, and myocardial infarction, are believed to be caused by the complex interactions between various environmental factors on a polygenic basis. In addition, it is believed that genetic risk factors for the same disease differ on an individual basis according to their susceptible environmental factors. In the present study, to predict the development of myocardial infarction (MI) and classify the subjects into personally optimum development patterns, we have extracted risk factor candidates (RFCs) that comprised a state that is a derivative form of polymorphisms and environmental factors using a statistical test. We then selected the risk factors using a criterion for detecting personal group (CDPG), which is defined in the present study. By using CDPG, we could predict the development of MI in blinded subjects with an accuracy greater than 75% In addition, the risk percentage for MI was higher with an increase in the number of selected risk factors in the blinded data. Since sensitivity using the CDPG was high, it can be an effective and useful tool in preventive medicine and its use may provide a high quality of life and reduce medical costs.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA12177013
• 書誌情報: IPSJ Transactions on Bioinformatics （TBIO）; 巻 47, 号 SIG17(TBIO1), p. 48-66, 発行日 2006-11-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-6679
• 出版者 / 言語: ja
• 出版者: 情報処理学会