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Genomic Predictive Modeling
of Nicotine Dependence
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description |
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| Tobacco use, primarily cigarette smoking, is
the greatest source of preventable mortality in the world
and costs over $160 million in health-related economic losses
in the U.S. alone. Nicotine dependence is the primary reason
that smokers continue smoking and that most unassisted quit
attempts fail within a single week. It is known that nicotine
dependence has a genetic component, but that it is a complex
trait, i.e., no single gene is responsible for nicotine dependence.
Thus, researchers and funding agencies have devoted considerable
effort and support to identifying the genetic underpinnings
of the trait through whole genome scans, putting us in a unique
position to identify global genetic predictors of nicotine
dependence. In collaboration with the Collaborative Genetic
Study of Nicotine Dependence (COGEND),
this project proposes to identify the set of genetic variations
predicting the complex trait of nicotine dependence . |
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people |
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publications |
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| Ramoni RB, Saccone NL, Hatsukami
DK, Bierut LJ, Ramoni MF, Genomic Prognostic Modeling of Nicotine
Dependence Using Bayesian Networks. [article] [www] |
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support |
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external links |
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| Website of the Collaborative Genetic
Study of Nicotine Dependence (COGEND) [here] |
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