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.
Current Drug Metabolism
Title:Functional Genomics- and Network-driven Systems Biology Approaches for Pharmacogenomics and Toxicogenomics
Volume: 13 Issue: 7
Author(s): Xia Yang, Bin Zhang and Jun Zhu
Affiliation:
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.
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.
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Cite this article as:
Yang Xia, Zhang Bin and Zhu Jun, Functional Genomics- and Network-driven Systems Biology Approaches for Pharmacogenomics and Toxicogenomics, Current Drug Metabolism 2012; 13 (7) . https://dx.doi.org/10.2174/138920012802138633
DOI https://dx.doi.org/10.2174/138920012802138633 |
Print ISSN 1389-2002 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5453 |
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