Genetic Admixture and Confounding in Association Studies

描述（由申请人提供）：针对非洲裔美国人或西班牙裔美国人的遗传流行病学设计特别具有挑战性，因为这两个群体最近都经历了混合。事实上，在存在隐型群体结构的情况下，病例对照关联设计可能产生假阳性关联结果。然而，病例对照设计具有基于家庭的设计无法替代的独特优势。因此，制定分析病例对照研究的方法并避免人口分层的危险是至关重要的。同时，最近的混合产生了强烈的连锁不平衡，为新的疾病制图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。该项目旨在开发新的方法，以提高病例对照关联研究的稳健性和效率，并应用于非洲裔美国人和墨西哥裔美国人。将开发基于Bootstrap和重采样的程序，使用关联和非关联遗传标记的基因型数据来推断个人祖先的重要方面（目标1）。目标2努力阐明一个长期存在的争议，即在实践中可能发生的混淆范围。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，从而明确控制由于人口分层引起的混淆。最后，Aim 4提出了一种链接-不平衡映射方法。调整方法（目标3）和联动不平衡映射方法（目标4）的优势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者能够更好地识别和控制基于人群的病例对照研究中由于混合而产生的偏倚，并设计新的有效和更有力的研究。来自各种多民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.