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Abstract Details

Activity Number: 253
Type: Contributed
Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #306200
Title: Using Genomic Data to Better Characterize Adverse Event Risk
Author(s): Robert Makowsky*+ and Kirk Yancy Williams and Samir Lababidi
Companies: FDA and FDA and FDA
Address: 1401 Rockville Pike, Rockville, MD, 20852, United States
Keywords: genomics ; vaccine ; adverse event

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.

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