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Current Drug Metabolism

Editor-in-Chief

ISSN (Print): 1389-2002
ISSN (Online): 1875-5453

Functional Genomics- and Network-driven Systems Biology Approaches for Pharmacogenomics and Toxicogenomics

Author(s): Xia Yang, Bin Zhang and Jun Zhu

Volume 13, Issue 7, 2012

Page: [952 - 967] Pages: 16

DOI: 10.2174/138920012802138633

Price: $65

Abstract

Recent advances in genomic technologies have enabled the identification of thousands of genetic variations that are associated with hundreds of complex human diseases or traits in genome-wide association studies (GWAS). The large number of genetic loci uncovered for each disease or trait along with the difficulty in pinpointing the underlying genes and mechanisms further testify to the complexity of human pathophysiology. To alleviate the challenges of GWAS, systems biology approaches have been utilized to map the molecular mechanisms underlying complex human diseases/traits via the integration of genetic variation, functional genomics (such as genetics of gene expression), pathways, and molecular networks. Similar approaches have been applied to a spectrum of drug metabolizing enzymes to discover novel functional genetic variations that affect the expression or activities of these enzymes as well as to define the regulatory pathways/networks of genes involved in drug metabolism and toxicology in key human tissues. We envision that the increased coverage of functional genetic polymorphisms, the availability of drug metabolism-centered gene networks, and the maturing methodologies previously developed for understanding complex human diseases can be applied to pharmacogenomic and toxicogenomic studies to further our understanding of inter-individual variability in drug efficacy and toxicity and eventually help direct personalized medicine.

Keywords: Drug response, functional genomics, genome-wide association study, molecular network, pharmacogenomics, single nucleotide polymorphism, systems biology, toxicogenomics, Genomics, genome-wide association studies, pathophysiology, efficacy, Traits, Key human tissues, Genetic loci.


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