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OBSERVED AND UNDERLYING ASSOCIATIONS
IN NICOTINE DEPENDENCE
by
Won Ho Lee
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(STATISTICAL GENETICS AND GENETIC EPIDEMIOLOGY)
August 2012
Copyright 2012 Won Ho Lee
Object Description
| Title | Observed and underlying associations in nicotine dependence |
| Author | Lee, Won H. |
| Author email | wonho77@gmail.com;wonhlee@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Statistical Genetics and Genetic Epidemiology |
| School | Keck School of Medicine |
| Date defended/completed | 2012-04-20 |
| Date submitted | 2012-08-02 |
| Date approved | 2012-08-02 |
| Restricted until | 2014-08-02 |
| Date published | 2014-08-02 |
| Advisor (committee chair) | Conti, David V. |
| Advisor (committee member) |
Gauderman, William James Knowles, James Leventhal, Adam M. Thomas, Duncan C. |
| Abstract | Tobacco-related morbidity and mortality remain among the costliest worldwide public health issues and the most preventable. Nicotine dependence is the primary factor in the persistence of this problem, leading to ongoing efforts to characterize nicotine dependence. Ongoing efforts have also led to the development of treatments to deal with this addictive drug. Nicotine replacement therapies, such as transdermal and nasal spray treatments, and other drugs, such as bupropion, targeted at neurotransmitters effected by nicotine, have had varying degrees of effectiveness for smoking cessation. Studies investigating genetic variants involved in the dopamine reward pathway, nicotine metabolism, and related mechanisms and pathways have shown that specific genetic profiles have different levels of nicotine dependence and respond differentially to treatments for nicotine dependence. For example, differential treatment effects for bupropion have been observed for variants within genes involved in the dopamine reward pathway on smoking cessation, with bupropion inhibiting the reuptake of dopamine. Bupropion has also been shown to be an antagonist for the nicotinic acetylcholine receptors, which bind nicotine. These two actions in concert highlight the interplay between treatments and genes. The metabolism of nicotine has also been of particular interest. Specifically, CYP2A6 has been shown to be a primary mechanism in the metabolism of nicotine to cotinine and then 3-hydroxycotinine (3HC). The nicotine metabolite ratio (NMR), the ratio of 3HC to cotinine, has subsequently been shown to be a reliable proxy for nicotine metabolism. Moreover, those carrying the CYP2A6 variant have been shown to have lower NMR levels, and be slow metabolizers, and those wildtype for CYP2A6 have been shown to be normal or fast metabolizers. ❧ This intricate web of dependence, genetic variation, cessation treatments, and nicotine metabolism has led us to develop a latent variable framework that attempts to capture an underlying process that characterizes a nicotine profile. Latent variable models have been used in the social sciences as a means of estimating constructs that synthesize indices of behavior. Indices for smoking may not capture the extent or degree of dependence on their own, but a latent variable, in describing relationships between measured variables, may ascertain otherwise unobservable effects. The potential problem then may be the interpretation of a latent variable. A hypothetical construct of “nicotine dependence” or “biological pathway X” may or may not be reliable in capturing desired effects. ❧ We present a framework that incorporates a Dirichlet process that does not constrain this underlying process to a single distribution, but can flexibly cluster individuals into profiles based on observed biomarker levels, genetic variation and other biological and psychological characteristics. This non- or semiparametric model made up of a mixture of parametric distributions is able to allocate observed measurements into k clusters. It is non- or semiparametric in the sense that each cluster comes from a discrete distribution, but each cluster has a parametric (typically normal) distribution. This provides flexibility in the estimation of some unmeasured variable or parameter, yielding a multimodal distribution that shrinks observations towards respective cluster effects rather than a grand mean. In doing so, groups can be distinguished from one another, rather than constraining all observations to a single distribution. The association between this latent variable and a smoking related outcome can be estimated, with the eventual purpose of utilizing these risk profiles to predict the outcome of interest. In order to assess the performance of our framework, we conducted simulations and compared it with conventional regressions on the actual data. Simulations performed as expected. In the real data, latent clusters were similar to the slow, normal and fast nicotine metabolism categories based on NMR levels, regardless of whether we constrained the number of estimated latent clusters to 2 or 3 or allowed the framework to determine the number of latent clusters. This is no surprise given that our latent variable was estimated using NMR. What was of interest was that incorporating CYP2A6, NMR levels had an impact in clustering individuals within those carrying the CYP2A6 variant, but not those wildtype for CYP2A6, suggesting that CYP2A6 and NMR play complementary, but not completely dependent roles in nicotine metabolism. Moreover, while our framework did not outperform conventional regressions in predicting smoking cessation, it was comparable, with our framework having the advantage of more refined characterization of individuals and dimension reduction when including more variables. |
| Keyword | genetic association; nicotine dependence; dopamine reward pathway; nicotine metabolism; Dirichlet process; nonparametric latent variable framework |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Lee, Won H. |
| Physical access | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Archival file | uscthesesreloadpub_Volume4/etd-LeeWonH-1124.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | OBSERVED AND UNDERLYING ASSOCIATIONS IN NICOTINE DEPENDENCE by Won Ho Lee A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (STATISTICAL GENETICS AND GENETIC EPIDEMIOLOGY) August 2012 Copyright 2012 Won Ho Lee |
