Statistical Methods in Genetic Epidemiology

描述（申请人提供）：人类基因组计划和高通量技术的最新进展使研究人员能够全面研究复杂疾病的病因。 产生的大量数据提出了许多有趣的统计问题。 我们建议继续研究家庭研究，从以前的赠款题为“方法在发病年龄数据的遗传流行病学”（AG 14358）。该研究包括开发半参数方法，用于聚集分析和估计携带者和非携带者的边际累积风险，当易感基因仅在家庭成员的一个子集上进行基因分型时，通常是家庭的指标受试者。感兴趣的主要结果是发病年龄的家庭成员，计数过程的现代理论将被应用到处理这种相关的故障时间数据。这项研究的直接动机是在弗雷德哈钦森癌症研究中心进行的早发性乳腺癌的两个病例对照家庭研究。在这些研究中，乳腺癌易感基因BRCA 1/BRCA 2在病例和对照组的子集上进行基因分型，同时收集了所有研究参与者及其女性亲属的病史和口服避孕药使用情况等综合信息。我们将分析这些数据作为所提出的方法的说明。 我们还建议开发用于分析杂合性缺失（洛）或等位基因缺失的统计方法，其定义为匹配肿瘤DNA中两个相应等位基因之一的完全或部分信号降低。洛缺失是目前评价基因组不稳定性和定位抑癌基因最常用的方法之一。信息标记处的洛合性缺失状态的数学表示是杂合性保留或缺失的0/1。我们建议应用生存分析技术来处理越来越多的遗传标记，在染色体可以被认为是一个“时间”轴从着丝粒到端粒和染色体上的标记作为“检查时间”。我们将开发半参数和非参数方法，用于比较两个样本（如两种类型的乳腺癌）之间的洛缺失谱，并对杂合缺失的边缘和局部依赖性分析进行协变量（如p53基因表达）的回归分析。我们将应用所提出的方法对乳腺小叶癌和导管癌进行全基因组洛缺失分析。

DESCRIPTION (provided by applicant): Recent advances in the Human Genome Project and high throughput technologies have enabled researchers to study the etiology of complex diseases comprehensively. A large amount of data that have been generated have posed many interesting statistical issues. We propose to continue research on family studies from the previous grant entitled "Methods for Age at Onset Data in Genetic Epidemiology" (AG 14358). The research includes the development of semi-parametric methods for aggregation analysis and for the estimation of marginal cumulative risk for carriers and non-carriers when the susceptible genes are genotyped only on a subset of family members, usually the index subjects of the family. The primary outcomes of interest are the ages at onset for the family members, for which the modem theory of counting processes will be applied to deal with such correlated failure time data. This research is directly motivated by the two-case-control family studies of early onset breast cancer conducted at the Fred Hutchinson Cancer Research Center. In these studies, breast cancer susceptible genes BRCA1/BRCA2 were genotyped on a subset of cases and controls while comprehensive information such as medical history and oral contraceptive usage have been collected on all study participants and their female relatives. We will analyze these data as an illustration for the proposed methods. We also propose to develop statistical methods for the analysis of loss of heterozygosity (LOH) or allelic loss, which is defined as a complete or partial signal reduction of one of the two corresponding alleles in the matching tumor DNA. LOH is one of the most widely used methods for assessing the genomic instability and localizing the tumor suppressor genes. The mathematical representation of the LOH status at an informative marker is 0/1 for retention or loss of heterozygosity. We propose to apply the survival analysis techniques to deal with the increasingly large number of genetic markers, in that the chromosome can be considered as a "time" axis starting from the centromere to the telomere and the markers on the chromosome as the "inspection times". We will develop semi- and non-parametric methods for comparing the LOH profiles between two samples such as two types of breast cancer and for regression analysis of covariates such as expression of p53 gene on the marginal and local dependency analysis of LOHs. We will apply proposed methods to the genome-wide LOH analysis for the lobular and ductal breast cancers.