Genetic Admixture and Confounding in Association Studies

关联研究中的基因混合和混杂

• 批准号: 7018490
• 负责人: Hua Tang
• 金额: $ 24.98万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7018490
• 关键词: African American; Hispanic Americans; case history; computer simulation; data collection methodology /evaluation; data quality /integrity; genetic markers; genetic susceptibility; human data; human population genetics; linkage disequilibriums; linkage mapping; mathematical model; matrix assisted laser desorption ionization; method development; statistics /biometry

DESCRIPTION (provided by applicant): Genetic epidemiologic design focusing on African Americans or Hispanics is particularly challenging because both groups have experienced recent admixture. Indeed, in the presence of cryptic population structure, case-control association designs can produce false-positive association findings. However, case-control designs have unique advantages that family-based designs cannot replace. Therefore, it is crucial to develop approaches that analyze case-control studies and are immune to the perils of population stratification. At the same time, recent admixture creates strong linkage disequilibrium, providing exciting opportunities for novel disease-mapping approaches. The long-term goal of this research is to develop novel quantitative methods which enable researchers to identify the factors that influence disease risk in admixed or stratified populations. This project aims to develop new methods that improve the robustness and efficiency of casecontrol association studies, with applications to African Americans and Mexican Americans. Bootstrap- and resampling-based procedures will be developed to infer important aspects of an individual's ancestry, using genotype data at linked and unlinked genetic markers (Aim 1). Aim 2 strives to shed light on a long-standing controversy regarding the scope of confounding that is likely to occur in practice. Aim 3 develops an adjustment-based approach which incorporates the estimated individual admixture in a regression model and thereby explicitly controls for confounding due to population stratification. Finally, Aim 4 proposes a linkage-disequilibrium mapping approach. The strengths and limitations of the adjustment approach (Aim 3) and the linkage disequilibrium mapping approach (Aim 4) will be assessed analytically and through simulations. Results from this research will enable investigators to better identify and control for bias due to admixture in population-based case-control studies, and to design new valid and more powerful studies. Genotypic data from various multiethnic studies will be used together with extensive simulation experiments to test and refine the methodology for real-world applications.

描述（由申请人提供）：关注非裔美国人或西班牙裔的遗传流行病学设计尤其具有挑战性，因为这两个群体都经历了最近的混合。实际上，在存在神秘人群结构的情况下，病例对照关联设计可以产生假阳性关联发现。但是，案例对照设计具有独特的优势，基于家庭的设计无法替代。因此，开发方法来分析病例对照研究并免疫人口分层的危险至关重要。同时，最近的混合物创造了强烈的连锁不平衡，为新型疾病映射方法提供了令人兴奋的机会。这项研究的长期目标是开发新颖的定量方法，使研究人员能够确定影响混合或分层种群中疾病风险的因素。该项目旨在开发新的方法，以提高Casecontrol协会研究的鲁棒性和效率，并应用于非洲裔美国人和墨西哥裔美国人。将开发基于引导和重新采样的程序，以使用链接和未链接遗传标记的基因型数据来推断个人血统的重要方面（AIM 1）。 AIM 2努力阐明有关在实践中可能发生的混杂范围的长期争议。 AIM 3开发了一种基于调整的方法，该方法将估计的单个混合物纳入回归模型中，从而明确控制由于人口分层而混淆。最后，AIM 4提出了一种链接区的映射方法。调整方法的优势和局限性（AIM 3）和连锁不平衡映射方法（AIM 4）将通过分析和模拟进行评估。这项研究的结果将使研究人员能够更好地识别和控制由于基于人群的病例对照研究的混合而导致的偏见，并设计新的有效和更有力的研究。来自各种多种族研究的基因型数据将与广泛的模拟实验一起使用，以测试和完善现实世界应用的方法。