Statistical tests for association with X-linked genes

与 X 连锁基因关联的统计检验

• 批准号: 6904155
• 负责人: Eden R. Martin
• 金额: $ 24.42万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2008-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6904155
• 关键词: Parkinson' s disease; autism; bioinformatics; cardiovascular disorder; computational biology; computer program /software; computer simulation; computer system design /evaluation; disease /disorder onset; family genetics; genetic susceptibility; genotype; human data; linkage mapping; method development; molecular biology information system; sex linked trait; statistics /biometry

DESCRIPTION (provided by applicant): Family-based tests of association are widely used in the search for genes contributing to complex diseases such as Parkinson's disease and autism. However, these methods have focused on the analysis of autosomal loci and are not generally useful for analysis of X-linked genes. Family-based tests that have been suggested for analysis of markers on the X chromosome are designed as tests of linkage, and are not necessarily valid tests of allelic association in linked regions. Therefore these methods are not useful for fine-mapping regions of linkage through association analysis, and we are aware of no family-based tests of association that are valid for analysis of X-linked markers. Clearly, there is a need to develop statistical methods designed for identifying important genetic factors on the X chromosome underlying complex diseases and quantitative trait variation. Through this project, we propose to develop new methodology for family-based association tests of X-linked loci. These methods will allow for inclusion of families with or without parental genotype data and will allow testing of disease risk (affected/unaffected) or quantitative traits. These methods will be thoroughly evaluated in simulated data, as well as real data from studies of Parkinson's disease, autism and early-onset cardiovascular disease. Finally software to implement the novel methods for X-linked analysis will be developed and distributed. There is compelling evidence of involvement of X-linked genes in many complex diseases, and the lack of appropriate association tests to make use of family-data hinders progress in fine-mapping disease genes on the X chromosome. Thus, the statistical methods and software developed through this grant will have an immediate application in gene mapping studies, and will help researchers identify and localize these important X-linked genes.

描述（由申请人提供）：基于家庭的关联测试广泛用于寻找导致帕金森病和自闭症等复杂疾病的基因。然而，这些方法集中于常染色体位点的分析，通常不适用于 X 连锁基因的分析。已建议用于分析 X 染色体标记的基于家族的测试被设计为连锁测试，并且不一定是连锁区域等位基因关联的有效测试。因此，这些方法对于通过关联分析精细绘制连锁区域是没有用的，并且我们知道没有基于家族的关联测试对于 X 连锁标记的分析有效。显然，需要开发统计方法来识别 X 染色体上潜在的复杂疾病和数量性状变异的重要遗传因素。通过这个项目，我们建议开发新的方法用于 X 连锁基因座的基于家族的关联测试。这些方法将允许纳入有或没有父母基因型数据的家庭，并允许测试疾病风险（受影响/未受影响）或数量性状。这些方法将在模拟数据以及帕金森病、自闭症和早发性心血管疾病研究的真实数据中得到彻底评估。最后，将开发并分发用于实施 X 连锁分析新方法的软件。有令人信服的证据表明 X 连锁基因参与许多复杂疾病，并且缺乏利用家族数据的适当关联测试阻碍了 X 染色体上疾病基因精细定位的进展。因此，通过这笔资助开发的统计方法和软件将立即应用于基因图谱研究，并将帮助研究人员识别和定位这些重要的X连锁基因。