Genetic Admixture and Confounding in Association Studies

描述（由申请人提供）：针对非裔美国人或西班牙裔美国人的遗传流行病学设计尤其具有挑战性，因为这两个群体最近都经历过混合。事实上，在存在神秘人口结构的情况下，病例对照关联设计可能会产生假阳性关联结果。然而，病例对照设计具有家族设计无法替代的独特优势。因此，开发分析病例对照研究并免受人口分层危险的方法至关重要。与此同时，最近的混合造成了强烈的连锁不平衡，为新的疾病图谱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的定量方法，使研究人员能够确定影响混合或分层人群疾病风险的因素。该项目旨在开发新方法，提高病例对照关联研究的稳健性和效率，并应用于非裔美国人和墨西哥裔美国人。将开发基于引导程序和重采样的程序，利用连锁和非连锁遗传标记的基因型数据来推断个体祖先的重要方面（目标 1）。目标 2 致力于阐明关于实践中可能发生的混杂范围的长期争议。目标 3 开发了一种基于调整的方法，该方法将估计的个体混合纳入回归模型中，从而明确控制由于群体分层而导致的混杂。最后，目标 4 提出了一种连锁不平衡映射方法。调整方法（目标 3）和连锁不平衡图方法（目标 4）的优点和局限性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中的混合而产生的偏差，并设计新的有效且更有力的研究。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，以测试和完善实际应用的方法。

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.