Journal
PHARMACOGENETICS AND GENOMICS
Volume 18, Issue 6, Pages 545-549Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/FPC.0b013e3282fe1745
Keywords
exon array; expression quantitative trait loci; gene expression; glutathione-S-transferase; pharmacogenes
Funding
- NIGMS NIH HHS [U01 GM061393-090005, U01 GM061393, U01 GM061393-090010, U01 GM061393-070005, U01GM61393, U01GM61374, U01 GM061393-080005, U01 GM061393-070010, U01 GM061393-060005, U01 GM061393-080010, U01 GM061374, U01 GM061393-060010] Funding Source: Medline
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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 17000 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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