A statistical model for functional mapping of quantitative trait loci regulating drug response

Y. Gong, Z. Wang, T. Liu, W. Zhao, Y. Zhu, J. A. Johnson, R. Wu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Differential drug response, that is, pharmacodynamics, is most often likely to be a complex trait, controlled by the combined influences of multiple genes and environmental influences. Genetic mapping has proven to be a powerful tool for detecting and identifying specific genes affecting complex traits, that is, quantitative trait loci (QTL), based on polymorphic markers. In this article, we present a novel statistical model for genetic mapping of QTL governing pharmacodynamic processes. In principle, this model is a combination of functional mapping proposed to map function-valued traits and linkage disequilibrium mapping designed to provide high-resolution mapping of QTL by making use of recombination events created at a historic time. We A implement a closed-form solution for the Expectation-Maximization algorithm to estimate the population genetic parameters of QTL and the simplex algorithm to estimate the curve parameters describing the pharmacodynamic changes of different QTL genotypes in response to drug dose or concentrations. Extensive simulations are performed to investigate the statistical properties of our model. The implications of our model in pharmacogenetic and pharmacogenomic research are discussed.

Original languageEnglish (US)
Pages (from-to)315-321
Number of pages7
JournalPharmacogenomics Journal
Volume4
Issue number5
DOIs
StatePublished - 2004

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Genetics
  • Pharmacology

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