Investigating Identity Matching in GWAS: Potholes in the Path to Personalized Medicine

• Activity Number: 485
• Type: Invited
• Date/Time: Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Statistics in Biopharmaceutical Research Journal
• Author(s): J. Richard Landis*+
• Companies: University of Pennsylvania
• Keywords: forensic biostatistics ; category-specific intraclass correlation ; identity misalignment ; categorical data ; agreement statistics

Abstract

This talk will illustrate the use of forensic biostatistics methods to investigate identity mis-alignment of genotype to phenotype data. Within a multicenter clinical research network, n=3,668 participants with genetic testing consent were selected for genotyping. Alerted by PID mismatches of duplicate SNP data, category-specific intraclass correlation coefficients (Landis et al 2010) comparing self-reported and genetically-inferred race were implemented within subsets of PIDs known to have been processed separately, and the presence of non-random clustering of race disagreement patterns was discovered on selected genotyping plates. Well established associations between HDL-C and CETP gene SNPs were shown to be seriously attenuated (approx. 20%) within race subgroups. A subsequent GWAS fingerprinting sub-study, focusing on 24 identity SNPs common to both studies, permitted realignment of these identities, so that discovery and validation research could proceed. Because of the confounding of race in HDL-C and SNP associations, these results illustrate the major impact that identity mis-alignment can have on biomarker discovery and/or validation.