Genomic Approaches to Common Chronic Disease

在传统风险因素之外预测健康和疾病。为了实现这一目标，我们将 制定统计策略以1)确定哪些DMA序列变化相结合以提高 对特定人群亚群中传统风险因素之外的疾病的预测，2)验证 推理总体中模型的结果的多重性以及3)测试 独立人群中经过验证的型号。建议的研究包括1)全面捕获 基因网络中的DNA序列变异被认为是导致癌症风险的因素 心血管疾病，并确定他们的组织如何传播对 常见的慢性多因素疾病，2)发展非传统统计方法，以降低高 遗传和环境因素的维度网络分成足以预测 将基因组与疾病终点联系起来的中间特征，3)发展非传统统计学 用于将遗传和环境因素的高维网络缩减为子集的方法 足以估计DNA序列变异网络对预测 疾病终点在普通人群中的作用超出了中间体网络的贡献 生化和生理特性和已确定的危险因素；4)评估稀土的相对作用 DNA序列变异、常见DNA序列变异和常见变异的罕见组合 解释普通人群中发生的冠心病病例。 参与该中心项目的合作研究人员为这项研究努力带来了遗传学方面的专业知识， 统计学、分子生物学和医学，这是20多年来合作研究的成果 人类的复杂常见病。每个联合调查员都有几十年的教学经验。 在本科生和研究生阶段。我们续签申请的目标之一将是 向更广泛的学术界传播有关最先进测量的专业知识 正在使用的技术和计算/统计方法，用于对遗传 对常见慢性病的研究。为此，我们将实施一门名为《基因组学》的短期课程 《常见慢性病研究方法》将系统生物学研究引入高等 本科生和初级研究生，提供为期10周的实验室实习机会。 参与调查的联合调查员的名单。

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.