Epidemiologic Architecture for Genes Linked to Environment (EAGLE)

环境相关基因的流行病学结构 (EAGLE)

• 批准号: 7533567
• 负责人: DANA C CRAWFORD
• 金额: $ 168.39万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-17 至 2012-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7533567
• 关键词: Accounting; African; Age related macular degeneration; Alleles; American; Architecture; Cardiovascular Diseases; Centers for Disease Control and Prevention (U.S.); Chemicals; Clinical; Clinical Data; Collection; Communities; Complex; Contracts; Coronary Arteriosclerosis; Cotinine; Cross-Sectional Studies; DNA; Data; Data Set; Databases; Development; Diet; Disease; Disease regression; Elderly; Electron Transport; End Point; Ensure; Environment; Environmental Exposure; Equipment; European; Family; Female; Frequencies; Funding; Future; General Population; Genes; Genetic; Genetic Research; Genetic Variation; Genome; Genotype; Glucose; Grant; Haplotypes; Health; Health Status; Human; Human Genome; Human Genome Project; Individual; Inflammation; International; Investments; Laboratories; Life Style; Link; Literature; Maps; Measurement; Measures; Metabolic; Methods; Mexican Americans; Minority; Mitochondria; Modeling; National Health and Nutrition Examination Survey; Non-Insulin-Dependent Diabetes Mellitus; Not Hispanic or Latino; Nuclear; Obesity; Outcome; Participant; Pharmaceutical Preparations; Phase; Phenotype; Physical Examination; Physical activity; Physicians; Population; Population Attributable Risks; Population Heterogeneity; Positioning Attribute; Predisposition; Prevention intervention; Proteins; Public Health; Purpose; Questionnaires; Reporting; Request for Applications; Research; Research Personnel; Resources; Rheumatoid Arthritis; Risk; SNP genotyping; Sampling; Staging; Standardization; Standards of Weights and Measures; Statistical Methods; Surveys; System; Testing; Translating; United States National Center for Health Statistics; Universities; Variant; Visit; base; case control; cigarette smoking; cigarette smoking; clinical phenotype; cohort; cost; demographics; disease phenotype; gene environment interaction; gene interaction; genetic association; genome wide association study; human disease; interest; lipid metabolism; novel; pesticide exposure; research study; sex; size; statistics; trait; translational study

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.

描述（由申请人提供）：随着人类基因组计划、国际人类基因组单体型图计划和高通量但成本有效的基因分型的出现，现在可以用> 100万个标记来询问人类基因组与常见人类疾病和性状的关联。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，这些研究确定了与公共健康相关的表型相关的新遗传变异。虽然这一系列的发现令人兴奋，但这些新发现在一般人群中的有用性仍不清楚。因此，除了最初的GWA研究之外，接下来的步骤必须在最有希望的发现转化为一般人群的干预，预防和/或治疗选择的改善之前提供基于人群的数据。国家健康和营养检查调查（NHANES; n~ 20，000）的遗传组成部分可以提供必要的数据，以超越最初的GWA研究发现。NHANES是美国疾病控制和预防中心收集的基于人口的横断面调查。NHANES DNA与参与个体的人口统计学，健康，生活方式，实验室，广泛的临床和体检数据相关。由于参与者无论健康状况如何都是确定的，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。通过这个大数据集，将描述GWA鉴定的遗传变异的流行病学结构，并进行关联研究，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检测，后者将生成实验室数据以支持统计学关联。 这项资助的目的是在基于人群的数据集中提供证据，证明GWA确定的遗传变异与大多数人相关。因此，GWA确定的变异将得到表征，基于人口的统计数据和这些变异修饰符的数据将迅速发布，以便最有前途的发现可以被研究界纳入未来的转化研究。