Epidemiologic Architecture for Genes Linked to Environment (EAGLE)

描述(申请人提供)：随着人类基因组计划、国际HapMap计划和高通量但成本效益高的基因分型的出现，现在有可能用100万个标记询问人类基因组与常见人类疾病和特征的关联。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众健康关注的表型相关的新的遗传变异。虽然这一系列发现令人兴奋，但这些新发现在一般人群环境中的用处尚不清楚。因此，在最有希望的发现转化为改善对普通人群的干预、预防和/或治疗选择之前，GWA初始研究之外的下一步必须提供关于这些初始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)的基因部分可以提供必要的数据，以超越GWA最初的研究发现。NHANES是由疾病控制和预防中心收集的一项以美国人口为基础的横断面调查。NHANES DNA与参与研究的个人的人口、健康、生活方式、实验室、广泛的临床和体检数据有关。由于参与者被确定与健康状况无关，NHANES是表型(临床终点和数量性状)和环境暴露的丰富资源。有了这个大型数据集，将描述GWA识别的基因变异的流行病学架构，并将进行关联研究，以提供许多常见疾病和特征(如2型糖尿病、肥胖症和冠状动脉疾病)的更准确的效应大小估计和人群归因率。最后，将进行基因-环境和核线粒体基因相互作用的测试，后者的实验室数据将被生成以支持统计关联。 这笔赠款的目的是在基于人口的数据集中提供证据，证明GWA确定的基因变异与大多数人相关。因此，将确定GWA确定的变异的特征，并将迅速发布基于人口的统计数据和这些变异修饰者的数据，以便将最有希望的发现纳入研究界未来的翻译研究。

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.