Literature DB >> 18496134

Identification of genetic variants and gene expression relationships associated with pharmacogenes in humans.

Rong Stephanie Huang1, Shiwei Duan, Emily O Kistner, Wei Zhang, Wasim K Bleibel, Nancy J Cox, M Eileen Dolan.   

Abstract

OBJECTIVES: The very important pharmacogenes (VIPs) were selected by Pharmacogenetic Research Network (National Institutes of Health-PGRN) owing to their significant effects on drug treatment both at the pharmacokinetic and pharmacodynamic levels. Our objective was to identify single nucleotide polymorphisms (SNPs) that potentially affected the expression of these genes or potential SNP-gene interactions involved to improve our understanding of genetic effects on drug therapy. BASIC
METHODS: Gene expression was evaluated in 176 International HapMap lymphoblastoid cell lines derived from CEU (CEPH, Utah residents with ancestry from northern and western Europe; n=87) and YRI (Yoruba in Ibadan, Nigeria; n=89) using Affymetrix GeneChip Human Exon 1.0 ST arrays (Affymetrix Laboratory, Affymetrix Inc., Santa Clara, California, USA) with interrogation of greater than 17,000 human genes. Genome-wide association was performed between over two million publicly available HapMap SNPs and gene expression. MAIN
RESULTS: The expression of two PGRN-VIPs (GSTT1 and GSTM1) are significantly associated with SNPs within 2.5 Mb of the genes; whereas the expression of three and ten PGRN-VIPs are significantly associated with distant-acting SNPs in CEU and YRI, respectively. In addition, three and four PGRN-VIPs harbor SNPs that are distantly associated with other gene expressions in CEU and YRI, respectively. PRINCIPAL
CONCLUSION: Using this information, one may identify genetic variants that are significantly associated with the expression of any set of genes of interest; or evaluate potential gene-gene interaction through SNP expression relationships.

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Year:  2008        PMID: 18496134      PMCID: PMC2567052          DOI: 10.1097/FPC.0b013e3282fe1745

Source DB:  PubMed          Journal:  Pharmacogenet Genomics        ISSN: 1744-6872            Impact factor:   2.089


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