Despite an increasing negative attitude towards smoking, and intensified public campaigns and legislation against smoking, virtually no further reduction in smoking has occurred in this country during the 1990's. Based on the 1996 National Household Survey on drug abuse, an estimated 68.8 million Americans used tobacco products. Therefore, tobacco represents one of the most widely abused substances. Nicotine is believed to be the primary addictive constituent in tobacco. A long history of epidemiological and neurochemical studies provides strong evidence that certain aspects of nicotine administration are influenced by genetic factors. Research has shown that nicotine can increase dopamine release in the nucleus accumbens and the ventral tegmental area, regions implicated in the rewarding properties of other addictive drugs. To date there has been no reported systematic study on gene expression during acute and chronic exposure to nicotine. In this application, we propose to employ cDNA microarray technology to assess expression profiles during acute and chronic exposure to nicotine in the nucleus accumbens, ventral tegmental area, amygdale and prefrontal cortex, which are known to be involved in drug addiction. Both neural-focused and high-density cDNA microarrays will be developed and employed in this study. The first approach (neural-focused array) is focused on understanding the biological pathways underlying the pharmacological effects of nicotine, per se, while the second approach (high-density array) is focused on the identification of novel gene(s) associated with nicotine acquisition, maintenance and withdrawal in a self-administration paradigm. To gain a biologically relevant insight into such massive neural expression data sets associated with nicotine dependence/withdrawal, various clustering algorithms such as hierarchical, k-means, self-organizing maps, quality clustering, and discriminate function analysis will be applied. Newly developed Jackknifed Reliability Index in our laboratory will be used for data filtering, a key step in data mining and analysis in microarray research. We expect that the completion of the proposed studies will advance our understanding of complex gene expression patterns altered by nicotine administration. Such a global perspective may provide new directions to develop preventative and treatment strategies to nicotine dependence.
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