M. Grasso, Darshana Dalvi, Soma Das, Matthew Gately, Vlad Korolev, Y. Yesha
{"title":"Genetic information for chronic disease prediction","authors":"M. Grasso, Darshana Dalvi, Soma Das, Matthew Gately, Vlad Korolev, Y. Yesha","doi":"10.1109/BIBMW.2011.6112535","DOIUrl":null,"url":null,"abstract":"Type 2 diabetes and coronary artery disease are commonly occurring polygenic diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. Advances in genetics have raised the hope that genetic testing may aid in disease prediction, treatment, and prevention. Although intuitive, the addition of genetic information to increase the accuracy of disease prediction remains an unproven hypothesis. We present an overview of genetic issues involved in polygenic diseases, and summarize ongoing efforts to use this information for disease prediction.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"53 1","pages":"997-997"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBMW.2011.6112535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Type 2 diabetes and coronary artery disease are commonly occurring polygenic diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. Advances in genetics have raised the hope that genetic testing may aid in disease prediction, treatment, and prevention. Although intuitive, the addition of genetic information to increase the accuracy of disease prediction remains an unproven hypothesis. We present an overview of genetic issues involved in polygenic diseases, and summarize ongoing efforts to use this information for disease prediction.