DESIGN AND ANALYSIS OF GENOME-WIDE ASSOCIATION STUDIES

全基因组关联研究的设计和分析

• 批准号: 7280472
• 负责人: Duncan C. Thomas
• 金额: $ 30.95万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7280472
• 关键词: Accounting; Address; Admixture; Adopted; African American; Age; Age related macular degeneration; Appendix; Breast; Candidate Disease Gene; Class; Colon; Complex; Condition; Data; Data Analyses; Data Set; Databases; Disease; Elements; Environmental Risk Factor; Ethnic group; Eye; Face; Family; Family history of; Freedom; Gene Frequency; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genome; Genome Scan; Genomics; Genotype; Genus Cola; Goals; Haplotypes; Hispanics; Hybrids; Influentials; Institution; Investigation; Knowledge; Latino; Lead; Linkage Disequilibrium; Localized; Los Angeles; Malignant neoplasm of prostate; Methods; Minor; Modeling; Nucleotides; Numbers; Paper; Pathway interactions; Penetrance; Performance; Personal Satisfaction; Phase; Phenotype; Population; Procedures; Purpose; Range; Rate; Relative (related person); Research; Research Design; Research Personnel; Risk Estimate; Sampling; Scanning; Scheme; Science; Simulate; Staging; Standards of Weights and Measures; Stratification; Structure; Technology; Testing; Time; U-Series Cooperative Agreements; Uncertainty; Validation; Variant; Work; base; case control; cohort; cost; design; gene environment interaction; genetic association; genome wide association study; improved; positional cloning; programs; simulation

DESCRIPTION (provided by applicant): Nearly a decade ago, Risch and Merikangas suggested the possibility of conducting genome-wide association scans. Although the cost was prohibitive at the time, they predicted that these technological barriers would eventually be overcome. With the advent of 500K chip-based or bead technologies, at a cost of about 0.2 cents per genotype, that prediction has now become a reality. Nevertheless, these will still be expensive studies to conduct and there remain numerous methodological challenges to efficient and valid design of such studies. To address these issues, we convened a panel of 165 investigators from around the world at USC in April 2005. These discussions highlighted a number of study design and statistical analysis problems that we propose to continue working on as part of this Cooperative Agreement. Our team is also involved in conducting and planning several such studies for such conditions as breast, colon, and prostate cancer and age-related macular degeneration. We anticipate that this research will inform the conduct of these studies and be motivated by the needs of these projects (as well as the many others at other institutions). In particular, we propose to focus on the following methodological issues: (1) tag SNP selection and haplotype-based methods incorporating both case-control association and case-case sharing comparisons; (2) multiple testing procedures for multistage sampling designs, including hierarchical models for prioritizing SNPs for further consideration using external genomic data; (3) family- vs. population-based studies and allowance for population stratification and admixture; and (4) gene-gene and gene-environment interactions. To investigate these problems, we will apply the methods to real data from our own studies (the Multiethnic Cohort and the Los Angeles Latino Eye Study of age-related macular degeneration), as well as data available in public databases such as the HapMap Project. Since most genome-wide datasets are limited to relatively small samples and are not connected to any phenotype information, we will develop ways for using these real data to generate large populations that would contain realistic degrees of genetic diversity that would look like those seen in these small samples. We will then sample from these populations to simulate replicate case-control data sets under known phenotype models to investigate the statistical performance of alternative study designs and analysis methods.

描述（由申请人提供）：大约十年前，Risch和Merikangas提出了进行全基因组关联扫描的可能性。尽管当时的成本是过分的，但他们预测这些技术障碍最终将被克服。随着基于500k芯片或珠子技术的出现，每个基因型的成本约为0.2美分，该预测已成为现实。然而，这些研究仍然是昂贵的研究，并且对于此类研究的有效和有效设计仍存在许多方法上的挑战。为了解决这些问题，我们于2005年4月在南加州大学召集了来自世界各地的165名调查员的小组。这些讨论强调了许多研究设计和统计分析问题，我们建议在这项合作协议的一部分中继续工作。我们的团队还参与了有关乳腺癌，结肠和前列腺癌以及与年龄相关的黄斑变性等疾病的几项此类研究。我们预计这项研究将为这些研究的行为提供信息，并受这些项目的需求（以及其他机构的许多其他项目）的动机。特别是，我们建议将重点放在以下方法论问题上：（1）标签SNP选择和基于单倍型的方法，这些方法同时结合了病例对照关联和病例共享共享比较； （2）多阶段采样设计的多个测试程序，包括用于使用外部基因组数据进一步考虑的层次模型； （3）家庭与基于人群的研究以及人口分层和混合的津贴； （4）基因基因和基因环境相互作用。为了调查这些问题，我们将将这些方法应用于我们自己的研究（多民族队列和洛杉矶拉丁裔与年龄相关的黄斑变性研究）的真实数据，以及在HAPMAP项目等公共数据库中可用的数据。由于大多数全基因组数据集都仅限于相对较小的样本，并且与任何表型信息都没有连接，因此我们将开发使用这些真实数据产生大量种群的方法，这些人群包含逼真的遗传多样性程度，这些遗传多样性看起来像这些小样品中看到的遗传多样性。然后，我们将从这些人群中进行采样，以模拟已知表型模型下的复制病例对照数据集，以研究替代研究设计和分析方法的统计性能。