Ex-Vivo Modeling for Heritability Assessment and Genetic Mapping in Pharmacogenomics

• Activity Number: 553
• Type: Invited
• Date/Time: Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
• Sponsor: WNAR
• Author(s): Alison Motsinger-Reif*+ and Chad Brown and Tammy Havener and Nicholas Hardison and Eric Peters and Andrew Beam and Lorri Everrit and Howard McLeod
• Companies: North Carolina State University and North Carolina State University and The University of North Carolina at Chapel Hill and North Carolina State University and The University of North Carolina at Chapel Hill and North Carolina State University and The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
• Keywords: heritability ; pharmacogenomics ; nonlinear models ; association mapping

Abstract

The investigation of genetic factors that determine differential drug response is a key goal of pharmacogenomics (PGX), and relies on the often-untested assumption that differential response is heritable. While limitations in traditional study design often prohibit heritability (h2) estimates in PGX, new approaches may allow such estimates. We demonstrate an ex vivo model system to determine the h2 of drug-induced cell killing and performed genome-wide analysis for gene mapping. The cytotoxic effect of 28 diverse chemotherapeutic agents on lymphoblastoid cell lines (LCLs) derived from family- and population-based cohorts was investigated. We used a high throughput format to determine cytotoxicity of the drugs on LCLs and developed a new evolutionary computation approach to fit response curves for each individual. Variance components analysis determined the h2 for each drug response and a wide range of values was observed across drugs. Genome-wide analysis was performed using new analytical approaches. These results lay the groundwork for future studies to uncover genes influencing chemotherapeutic response and demonstrate a new computational framework for performing such analysis.