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Published on: June 22, 2017
Functional characterization of SNPs in CHRNA3/B4 intergenic region associated with drug behaviors
Amber V Flora1, Cristian A Zambrano, Xavier Gallego
1Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30th Street, Boulder, CO 80303, USA. amber.flora@colorado.edu
Abstract:
The cluster of human neuronal nicotinic receptor genes (CHRNA5/A3/B4) (15q25.1) has been associated with a variety of smoking and drug-related behaviors, as well as risk for lung cancer. CHRNA3/B4 intergenic single nucleotide polymorphisms (SNPs) rs1948 and rs8023462 have been associated with early initiation of alcohol and tobacco use, and rs6495309 has been associated with nicotine dependence and risk for lung cancer. An in vitro luciferase expression assay was used to determine whether these SNPs and surrounding sequences contribute to differences in gene expression using cell lines either expressing proteins characteristic of neuronal tissue or derived from lung cancers. Electrophoretic mobility shift assays (EMSAs) were performed to investigate whether nuclear proteins from these cell lines bind SNP alleles differentially. Results from expression assays were dependent on cell culture type and haplotype. EMSAs indicated that rs8023462 and rs6495309 bind nuclear proteins in an allele-specific way. Additionally, GATA transcription factors appeared to bind rs8023462 only when the minor/risk allele was present. Much work has been done to describe the rat Chrnb4/a3 intergenic region, but few studies have examined the human intergenic region effects on expression; therefore, these studies greatly aid human genetic research as it relates to observed nicotine phenotypes, lung cancer risk and potential underlying genetic mechanisms. Data from these experiments support the hypothesis that SNPs associated with human addiction-related phenotypes and lung cancer risk can affect gene expression, and are potential therapeutic targets. Additionally, this is the first evidence that rs8023462 interacts with GATA transcription factors to influence gene expression.
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