Epidemiologic Architecture for Genes Linked to Environment (EAGLE)

描述（由申请人提供）：随着人类基因组计划、国际单体型图计划和高通量且具有成本效益的基因分型的出现，现在有可能用100万个标记来询问人类基因组，以寻找与人类常见疾病和特征的关联。在过去的几个月里，文献中充斥着全基因组关联（GWA）研究的报告，这些研究发现了与公共卫生利益相关的表型相关的新遗传变异。虽然这些发现令人兴奋，但这些新发现对一般人群的有用性仍不清楚。因此，在将最有希望的发现转化为改善普通人群的干预、预防和/或治疗方案之前，GWA初步研究的下一步必须提供这些初步关联的基于人群的数据。国家健康和营养检查调查（NHANES; n~20,000）的遗传成分可以提供必要的数据，以超越最初的GWA研究发现。NHANES是一项以美国人口为基础的横断面调查，由疾病控制和预防中心收集。NHANES dna与参与个人的人口统计、健康、生活方式、实验室、广泛的临床和体检数据相关联。由于参与者的健康状况不受影响，因此NHANES是表型（临床终点和数量性状）和环境暴露的丰富资源。有了这个庞大的数据集，gwa鉴定的遗传变异的流行病学结构将被描述，关联研究将被进行，以提供更准确的效应大小估计和许多常见疾病和特征（如2型糖尿病、肥胖和冠状动脉疾病）的人群归因分数。最后，将进行基因-环境和核线粒体基因相互作用的测试，后者将生成实验室数据以支持统计关联。

DESCRIPTION (provided by applicant): With the advent of the Human Genome Project, the International HapMap Project, and high-throughput yet cost-effective genotyping, it is now possible to interrogate the human genome with >1 million markers for associations with common human diseases and traits. Within the last few months, the literature has become inundated with reports of genome-wide association (GWA) studies identifying new genetic variations associated with phenotypes of public health interest. While the flurry of discovery is exciting, the usefulness of these new findings in a general population setting remains unclear. Therefore, the next steps beyond the initial GWA studies must provide population-based data on these initial associations before the most promising findings can be translated into improvements in intervention, prevention, and/or treatment options for the general population. The genetic component of the National Health and Nutrition Examination Surveys (NHANES; n~20,000) can provide the data necessary to move beyond the initial GWA study discoveries. NHANES is a U.S. population-based, cross-sectional survey collected by the Centers for Disease Control and Prevention. NHANES DNAs are linked to demographic, health, lifestyle, laboratory, extensive clinical, and physical examination data for participating individuals. Because participants are ascertained regardless of health status, NHANES is a rich resource for phenotypes (clinical endpoints and quantitative traits) and environmental exposures. With this large dataset, the epidemiologic architecture of GWA-identified genetic variations will be described, and association studies will be conducted to provide more accurate effect size estimates and population attributable fractions for many common diseases and traits such as type 2 diabetes, obesity, and coronary artery disease. Finally, tests for gene-environment and nuclear mitochondrial gene interactions will be performed, the latter of which laboratory data will be generated to support the statistical association. The purpose of this grant is to provide evidence in population-based datasets that GWA-identified genetic variations are relevant to most people. As such, GWA-identified variations will be characterized and population-based statistics and data for modifiers of these variations will be released rapidly so that the most promising findings can be incorporated into future translational studies by the research community.