Challenges in Predicting Risk of Women Diseases Using Genomic Data

• Activity Number: 316
• Type: Invited
• Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Mariza De Andrade*+
• Companies: Mayo Clinic
• Keywords: risk prediction models ; genetic risk ; rare variants

Abstract

Recently several articles have discussed the issues of risk prediction using genomic data. The genomic data come from different genotyping technologies; however only common genetic variants are selected to be part of these chips. It is also known that strong family history and early onset of disease are the major non-genetic risk factors for certain women diseases such as breast cancer. The known genetic variants for breast cancer are rare in the general population, which make difficult to create genetic risk models to predict the disease of interest. These genetic risk factors normally account for very small proportion of the risk. Thus, in this presentation I will introduce several methods used for disease risk prediction, discuss the appropriateness of the predictor models using breast cancer data, and briefly discuss the issue of discloser of incidental findings in genetic studies.