Using Genomic Data to Better Characterize Adverse Event Risk

• Activity Number: 253
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Robert Makowsky*+ and Kirk Yancy Williams and Samir Lababidi
• Companies: FDA and FDA and FDA
• Keywords: genomics ; vaccine ; adverse event

Abstract

While the gains associated from genomic data towards human health outcomes have been minimal to date, new methodologies, increased genomic resolution, and a better understanding of genomic architecture are increasing the utility of genomic data. One area where genomic data may prove very helpful concerns risk profiling of adverse events after vaccination. Idiopathic Thrombocytopenia Purpura (ITP), an adverse event associated with MMR vaccine, is one example where genomics may substantially contribute towards determining individual susceptibility. To better understand how genomic data may increase the accuracy of risk profiles, we conducted realistic simulations designed to mimic ITP. Genomic data was created using FREGENE and the genomic architecture and ITP status were defined based on a meta-analysis of published studies. Genomic variability was characterized using an SNP approach and the SNP "Chip" data were analyzed using standard approaches (subset logistic regression, linear discriminant analysis) and whole genomic methods. We characterize expected genomic information across various conditions and find that genomic data can be useful to better characterize risk profiles.