Genomic Approaches to Common Chronic Disease

描述（由申请人提供）：该中心计划旨在评估基因组序列信息在预测健康和疾病方面的表现，超越传统的风险因素。为了实现这一目标，我们将开发统计策略，以1）确定哪些DMA序列变异联合收割机以改善疾病预测，超出特定群体的子集的传统风险因素，2）验证推断群体中所得模型的多样性，以及3）测试独立群体中验证模型的可推广性。拟议的研究包括：1）在一个基因网络中捕获全面的DNA序列变异，这些基因被假设为有助于心血管疾病的风险，并确定它们的组织如何传播对常见慢性多因素疾病遗传研究的限制，（2）发展非传统的统计方法用于将遗传和环境因子的高维网络减少到足以预测遗传和环境因子的子集，连接基因组与疾病终点的中间性状网络，（3）发展非- 传统的统计方法，用于将遗传和环境因子的高维网络减少为足以估计DNA序列变异网络对预测总体中疾病终点的贡献超过中间生化和生理性状网络的贡献的子集，以及建立的危险因素和4）估计罕见的DNA序列变异，常见的DNA序列变异和常见变异的罕见组合在解释冠心病的事件在广大人口的情况下的相对作用。参与该中心项目的共同研究人员为这项研究奋进带来了遗传学，统计学，分子生物学和医学方面的专业知识，这是20多年来对人类复杂常见疾病进行合作研究的结果。每个共同研究者都有数十年的本科和研究生教学经验。我们更新申请的目标之一是向更广泛的学术界传播有关最先进的测量技术和计算/统计方法的专业知识，这些技术和方法用于对常见慢性疾病的遗传研究进行系统方法。为此，我们将实施一个题为“常见慢性病研究的基因组方法”的短期课程，向高年级本科生和研究生水平的学生介绍系统生物学研究，并在参与合作研究者之一的实验室提供为期10周的实习。

DESCRIPTION (provided by applicant): This center program seeks to evaluate the performance of genomic sequence information for predicting health and disease above and beyond traditional risk factors. To accomplish this objective we will develop statistical strategies to 1) determine which DMA sequence variations combine to improve the prediction of disease beyond the traditional risk factors in which subsets of a particular population, 2) validate the resultant multiplicity of models in the population of inference and 3) test the generalizability of the validated models in an independent population. The proposed study includes 1) capturing comprehensive DNA sequence variation in a network of genes that have been hypothesized to contribute to risk of cardiovascular disease and establish how their organization propagates constraints on genetic studies of a common chronic multifactorial disease, 2) developing non-traditional statistical methods for reducing the high dimensional network of genetic and environmental agents into subsets sufficient for predicting the network of intermediate traits that connect the genome with disease endpoints, 3) developing non-traditional statistical methods for reducing the high dimensional network of genetic and environmental agents into subsets sufficient for estimating the contribution of the network of DNA sequence variations to the prediction of disease endpoints in the population at large beyond the contribution of the network of intermediate biochemical and physiological traits and established risk factors and 4) estimating the relative roles of rare DNA sequence variations, common DNA sequence variations and rare combinations of common variations in explaining incident cases of CHD in the population at large. Co-investigators involved in this center program bring to this research endeavor expertise in genetics, statistics, molecular biology and medicine that is a consequence of 20+ years of collaborative research on complex common diseases of humans. Each of the co-investigators has decades of experience in teaching at the undergraduate and graduate level. One of the objectives of our renewal application will be to disseminate expert knowledge to the wider academic community about the most advanced measurement technologies and computation/statistical methods being used in carrying out a systems approach to genetic studies of common chronic diseases. To this end, we will implement a short course entitled "Genomic Approaches to Common Chronic Disease Research" to introduce systems biology research to advanced undergraduate and beginning graduate level students and offer a 10 week internship in the laboratory of one of the participating co-investigators.