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Activity Number: 106
Type: Invited
Date/Time: Monday, August 4, 2014 : 8:30 AM to 10:20 AM
Sponsor: Committee on Privacy and Confidentiality
Abstract #310617 View Presentation
Title: On Sharing Quantitative Trait GWAS Results in an Era of Multiple-Omics Data and the Limits of Genomic Privacy
Author(s): Hae Kyung Im*+ and Eric R. Gamazon and Dan Nicolae and Nancy J. Cox
Companies: University of Chicago and University of Chicago and University of Chicago and University of Chicago
Keywords: genomic privacy ; quantitative traits ; confidentiality
Abstract:

Recent advances in genome-scale, system-level measurements of quantitative phenotypes (transcriptome, metabolome, and proteome) promise to yield unprecedented biological insights. In this environment, broad dissemination of results from genome-wide association studies (GWASs) or deep-sequencing efforts is highly desirable. However, summary results from case-control studies (allele frequencies) have been withdrawn from public access because it has been shown that they can be used for inferring participation in a study if the individual's genotype is available. A natural question that follows is how much private information is contained in summary results from quantitative trait GWAS such as regression coefficients or p values. We show that regression coefficients for many SNPs can reveal the person's participation and for participants his or her phenotype with high accuracy. Our power calculations show that regression coefficients contain as much information on individuals as allele frequencies do, if the person's phenotype is rather extreme or if multiple phenotypes are available as has been increasingly facilitated by the use of multiple-omics data sets. These findings emphasize t


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