Bayesian Hierarchical Risk Models: Nutrition, Genes, & Environment Interactions

贝叶斯分层风险模型：营养、基因、

基本信息

批准号：
7828080
负责人：
MICHAEL D SWARTZ
金额：
$ 3.09万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-06-01 至 2010-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7828080
关键词：
Accounting Affect Age Agreement Bayesian Method Biological Availability Cancer Biology Cancer Etiology Case-Control Studies Data Data Sources Development Diet Diet Habits Dietary Component Dietary Factors Dietary Practices Discipline Elements Environmental Risk Factor Epidemiologist Epidemiology Ethnic Origin Folate Food Funding Gender Genes Genetic Genetic Models Goals Grant Individual Intake Interdisciplinary Study Intervention Knowledge Literature Lung Malignant Neoplasms Malignant neoplasm of lung Mentors Methodology Modeling Molecular Nutrient Nutritional Odds Ratio Pathway interactions Pattern Physical activity Predisposition Prevention strategy Probability Procedures Process Research Research Personnel Research Project Grants Review Literature Risk Risk Factors Smoker Smoking Smoking Status Source Statistical Methods Statistical Models Suggestion Techniques Training Uncertainty Variant Weight absorption base cancer epidemiology cancer prevention cancer risk career development case control flexibility folic acid metabolism gene environment interaction genetic epidemiology genetic risk factor mathematical model method development nutrition nutritional epidemiology programs skills

项目摘要

DESCRIPTION (provided by applicant): My goal is to become an independent researcher in methodological development across the disciplines of statistical genetics, epidemiology, and nutritional epidemiology. Specifically, I want to focus on using Bayesian hierarchical models to model cancer risk while accounting for the uncertainty surrounding genetic, epidemiological and nutritional data and their interactions. This goal builds upon my previous statistical training, bayesian modeling and statistical genetics, but requires training in nutrition and nutritional epidemiology, cancer biology, and general epidemiology. At the end of this training period, I will be an established researcher in the nutrition and genetics of cancer prevention. To attain these goals, I have developed a comprehensive educational plan, including expert mentors consisting of a statistical geneticist, an epidemiologist specializing in lung cancer, a nutritional epidemiologist and a Bayesian statistician. The research I have proposed both reinforces my training and provides original, cutting edge methodologies to the field of cancer prevention. The research plan focuses on the following specific aims: 1) To perform a literature review of the current information about dietary patterns, environmental and genetic risk factors that influence the folate metabolism pathways as they relate to lung cancer risk. This review will further my knowledge in the field, and provide the field with a concentrated review of risk factors for lung cancer that relate to diet, folate intake and folate metabolism. 2) To develop Bayesian Hierarchical models to simultaneously identify diet and physical activity patterns and dietary components that associate with lung cancer risk. Using sophisticated models to identify dietary patterns consider nutrients as they naturally occur and are ingested as food. Additionally, we will build models that jointly consider genes, nutritional factors and environmental factors. 3) To develop Bayesian hierarchical models to identify genes and gene by diet interactions involved with folate metabolism that affect lung cancer risk. Bayesian hierarchical models provide sophisticated machinery to investigate interactions that may occur with or without related main effects. The Bayesian methodologies proposed consider sources of variation that frequentist models do not, and can provide more comprehensive risk models. The models and techniques developed can be applied to multiple cancers.

描述（由申请人提供）：我的目标是成为跨统计遗传学、流行病学和营养流行病学学科的方法开发的独立研究员。具体来说，我想重点关注使用贝叶斯分层模型来模拟癌症风险，同时考虑遗传、流行病学和营养数据及其相互作用的不确定性。这个目标建立在我之前的统计培训、贝叶斯建模和统计遗传学的基础上，但需要营养和营养流行病学、癌症生物学和一般流行病学方面的培训。培训期结束后，我将成为癌症预防的营养和遗传学领域的一名资深研究员。为了实现这些目标，我制定了一个全面的教育计划，包括由统计遗传学家、肺癌专业流行病学家、营养流行病学家和贝叶斯统计学家组成的专家导师。我提出的研究既强化了我的训练，又为癌症预防领域提供了原创、前沿的方法。该研究计划重点关注以下具体目标： 1) 对影响叶酸代谢途径（与肺癌风险相关）的饮食模式、环境和遗传风险因素的当前信息进行文献综述。这篇综述将进一步加深我在该领域的知识，并为该领域提供与饮食、叶酸摄入和叶酸代谢相关的肺癌危险因素的集中综述。 2) 开发贝叶斯分层模型，以同时识别与肺癌风险相关的饮食和身体活动模式以及饮食成分。使用复杂的模型来识别饮食模式，考虑天然存在并作为食物摄入的营养物质。此外，我们将建立联合考虑基因、营养因素和环境因素的模型。 3) 开发贝叶斯分层模型来识别与影响肺癌风险的叶酸代谢相关的基因和饮食相互作用的基因。贝叶斯分层模型提供了复杂的机制来研究可能发生的有或没有相关主效应的相互作用。提出的贝叶斯方法考虑了频率论模型没有考虑的变异来源，并且可以提供更全面的风险模型。开发的模型和技术可应用于多种癌症。