Quantitative Analysis Methods for Complex Trait Genetics

描述：（由申请人提供）：

DESCRIPTION: (Provided by Applicant): Cigarette smoking is a major risk factor for premature death and creates a substantial public health burden. While studies have shown that smoking and nicotine dependence are complex traits influenced by significant genetic components, further research is needed to identify genes that influence susceptibility and resistance. The research goal of this proposal is to develop and evaluate new methods for the genetic analysis of complex traits in the context of career development for the candidate, Dr. Nancy Saccone. Dr. Saccone will use artificial neural networks and logistic regression models as her primary methodological tools, and will develop and apply methods especially suited for studying the complex genetics of nicotine addiction and related phenotypes. Preliminary studies have been promising and indicate that further investigation of genetic methods based on these tools is warranted. The research plan will also extend the scope of these applications to include uses for genetic association analysis, as large-scale disequilibrium and association-based approaches are expected to become increasingly important for complex trait gene mapping. Dr. Saccone has chosen Dr. John Rice as mentor and will work with additional co-mentors and consultants. The training components of this proposal will expand Dr. Saccone?s experience to include: ongoing training in the ethical conduct of research, further training in the clinical and biological aspects of nicotine and other substance addiction, and the development of expertise in the use and analysis of other kinds of genetic data besides genotypic data, such as gene expression array data, which will play increasingly important roles in the study of human complex traits. The candidate has designed a program of coursework and mentoring to accomplish these research and training goals and thereby achieve research independence by the end of the award period.