GWA for Gene-Environment Interaction Effects Influencing CHD

GWA 研究影响先心病的基因-环境相互作用效应

• 批准号: 7479363
• 负责人: ERIC A. BOERWINKLE
• 金额: $ 84.16万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-06 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7479363
• 关键词: Acute myocardial infarction; African American; Algorithms; American; Arts; Atherosclerosis; Bioinformatics; Biological; Blood; Blood Coagulation Factor; Blood Pressure; Body Size; Candidate Disease Gene; Case-Control Studies; Chronic; Chronic Obstructive Airway Disease; Clinic Visits; Cohort Studies; Collaborations; Collection; Communities; Confidentiality; Coronary heart disease; Data; Data Analyses; Data Set; Depth; Developed Countries; Developing Countries; Diet; Disease; Disease Outcome; End Point; Environment; Environmental Risk Factor; European; Family Study; Framingham Heart Study; Funding; Gene Family; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genome; Genotype; Grant; Haplotypes; Health; Heart; Heart Rate; Human Genome; Individual; Light; Linkage Disequilibrium; Lipids; Lung; Measures; Methods; Morbidity - disease rate; Obesity; Participant; Pathway interactions; Phenotype; Physical activity; Play; Polymorphism Analysis; Population; Population Genetics; Prevention program; Privacy; Publications; Research; Research Personnel; Resources; Respiratory physiology; Risk; Risk Factors; Role; Sampling; Scientist; Single Nucleotide Polymorphism; Slide; Smoking; Statistical Methods; United States; Variant; aged; base; cohort; computer science; cost; cost effective; disorder risk; environmental change; follow-up; gene environment interaction; genome wide association study; genotyping technology; heart disease risk; improved; innovation; mortality; novel; programs; success

DESCRIPTION (provided by applicant): We propose to leverage the full scope of the Atherosclerosis Risk in Communities (ARIC) study to investigate the interaction between genetic variation and modifiable environments in the determination of incident CHD. We are currently funded (HL087641) to type 600 incident CHD cases and 1,400 individuals in a cohort random sample (CRS) for 500,000 TagSNPs. For the proposed research, we will add an additional 1,100 incident CHD cases (a total of 1,700 CHD cases) and an additional 1,000 CRS individuals (a total of 2,400 CRS individuals) for the same genome-wide collection of SNPs to identify environment-specific genetic effects influencing incident CHD. The already-funded grant is only powered for main effects; this new opportunity allows the study to be powered for interaction effects. We will perform a combination of computer science and sliding window haplotype analyses which directly incorporate gene-environment interaction effects to identify SNP-environmental combinations that predict incident CHD. Replication of initial findings will be done by investigating the concordance of "statistical significance and direction of effect" between the top 10,000 (~2%) SNPs from ARIC and the top 10,000 SNPs from analyses of gene-environment interaction effects in the Framingham Heart Study. For those SNPs that consistently replicate throughout, we will genotype the remainder of the ARIC cohort (-11,900 individuals) so that the full spectrum of environmental and phenotypic variation is represented in initial follow-up analyses. The CRS provides an ideal cost effective opportunity for initial studies to use GWA methods to investigate gene-environment interactions for other heart, lung and blood phenotypes. We will begin to identify genes influencing other heart, lung and blood phenotypes using the CRS and the 500,000 SNP dataset. Finally, we will support further analysis and discovery by sharing the data and analysis algorithms with other scientists in a timely fashion. This project will bring together appropriate population-based samples, good phenotyping, details on environmental measures and state-of-the art analyses to identify environment-specific genetic effects influencing CHD, along with other heart, lung and blood phenotypes. Identification of these environment-specific genetic effects will improve risk prediction and shed light on novel biological pathways bridging health and disease.

描述（由申请人提供）：我们建议充分利用社区动脉粥样硬化风险（ARIC）研究的全部范围，以调查遗传变异和可改变的环境之间的相互作用，以确定冠心病事件。我们目前获得资助（HL 087641），在队列随机样本（CRS）中对600例CHD病例和1，400例个体进行500，000个TagSNP分型。对于拟议的研究，我们将增加额外的1，100例CHD病例（共1，700例CHD病例）和额外的1，000例CRS个体（共2，400例CRS个体），用于相同的全基因组SNP集合，以确定影响CHD事件的环境特异性遗传效应。已经资助的补助金仅针对主效应;这个新的机会允许研究针对交互效应。我们将结合计算机科学和滑动窗口单倍型分析，直接将基因-环境相互作用的影响，以确定预测冠心病事件的SNP-环境组合。将通过研究ARIC中前10，000个（~2%）SNP与Frachial Heart研究中基因-环境相互作用效应分析中前10，000个SNP之间的“统计学显著性和效应方向”的一致性来复制初始结果。对于那些始终复制的SNP，我们将对ARIC队列的其余部分（约11，900个个体）进行基因分型，以便在初始随访分析中呈现环境和表型变异的全谱。CRS为使用GWA方法研究其他心脏、肺和血液表型的基因-环境相互作用的初始研究提供了理想的成本效益机会。我们将开始使用CRS和500，000 SNP数据集来鉴定影响其他心脏、肺和血液表型的基因。最后，我们将通过及时与其他科学家分享数据和分析算法来支持进一步的分析和发现。该项目将汇集适当的基于人群的样本、良好的表型、环境措施的详细信息和最先进的分析，以确定影响CHD的环境特异性遗传效应，沿着其他心脏、肺和血液表型。识别这些环境特异性遗传效应将改善风险预测，并揭示连接健康和疾病的新生物途径。