Statistical tests for association with X-linked genes

描述（由申请人提供）：基于家庭的关联测试被广泛用于寻找导致复杂疾病的基因，如帕金森病和自闭症。然而，这些方法主要集中在常染色体位点的分析上，通常不适用于x连锁基因的分析。建议用于分析X染色体上标记的基于家庭的测试是作为连锁测试而设计的，并不一定是对连锁区域中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定位连锁区域是没有用的，而且我们知道没有基于家族的关联测试可用于分析x连锁标记。显然，有必要开发统计方法，以确定复杂疾病和数量性状变异背后的X染色体上的重要遗传因素。通过这个项目，我们建议为基于家族的x连锁位点关联测试开发新的方法。这些方法将允许纳入有或没有亲代基因型数据的家庭，并将允许检测疾病风险（受影响/未受影响）或数量性状。这些方法将在模拟数据以及来自帕金森氏病、自闭症和早发性心血管疾病研究的真实数据中进行全面评估。最后，将开发和分发用于实现新x链分析方法的软件。有令人信服的证据表明，X连锁基因参与了许多复杂的疾病，缺乏适当的关联测试来利用家庭数据，阻碍了在X染色体上精确定位疾病基因的进展。因此，通过这笔拨款开发的统计方法和软件将立即应用于基因定位研究，并将帮助研究人员识别和定位这些重要的x连锁基因。

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.