Modeling sequence - Sequence interactions for drug response

Min Lin, Hongying Li, Wei Hou, Julie A. Johnson, Rongling Wu

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Motivation: Genetic interactions or epistasis may play an important role in the genetic etiology of drug response. With the availability of large-scale, high-density single nucleotide polymorphism markers, a great challenge is how to associate haplotype structures and complex drug response through its underlying pharmacodynamic mechanisms. Results: We have derived a general statistical model for detecting an interactive network of DNA sequence variants that encode pharmacodynamic processes based on the haplotype map constructed by single nucleotide polymorphisms. The model was validated by a pharmacogenetic study for two predominant beta-adrenergic receptor (βAR) subtypes expressed in the heart, β1AR and β2AR. Haplotypes from these two receptors trigger significant interaction effects on the response of heart rate to different dose levels of dobutamine. This model will have implications for pharmacogenetic and pharmacogenomic research and drug discovery.

Original languageEnglish (US)
Pages (from-to)1251-1257
Number of pages7
JournalBioinformatics
Volume23
Issue number10
DOIs
StatePublished - May 15 2007

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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