A conceptual framework for pharmacodynamic genome-wide association studies in pharmacogenomics

Rongling Wu, Chunfa Tong, Zhong Wang, David Mauger, Kelan Tantisira, Stanley J. Szefler, Vernon M. Chinchilli, Elliot Israel

Research output: Contribution to journalReview articlepeer-review

18 Scopus citations

Abstract

Genome-wide association studies (GWAS) have emerged as a powerful tool to identify loci that affect drug response or susceptibility to adverse drug reactions. However, current GWAS based on a simple analysis of associations between genotype and phenotype ignores the biochemical reactions of drug response, thus limiting the scope of inference about its genetic architecture. To facilitate the inference of GWAS in pharmacogenomics, we sought to undertake the mathematical integration of the pharmacodynamic (PD) process of drug reactions through computational models. By estimating and testing the genetic control of PD and pharmacokinetic (PK) parameters, this mechanistic approach does not only enhance the biological and clinical relevance of significant genetic associations, but also improve the statistical power and robustness of gene detection. This report discusses the general principle and development of PDs-based GWAS, highlights the practical use of this approach in addressing various pharmacogenomic problems, and suggests that this approach will be an important method to study the genetic architecture of drug responses or reactions.

Original languageEnglish (US)
Pages (from-to)884-890
Number of pages7
JournalDrug Discovery Today
Volume16
Issue number19-20
DOIs
StatePublished - Oct 2011

All Science Journal Classification (ASJC) codes

  • Pharmacology
  • Drug Discovery

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