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学。已经产生的大量数据提出了许多有趣的统计问题。 我们建议继续研究前一项题为“遗传流行病学中发病年龄数据的方法”(AG 14358)的家庭研究。这项研究包括发展聚合分析的半参数方法，以及当易感基因只在家庭成员的子集上进行基因分型时，估计携带者和非携带者的边际累积风险。令人感兴趣的主要结果是家庭成员的发病年龄，对于这些年龄，将应用现代计数过程理论来处理此类相关的故障时间数据。这项研究直接受到弗雷德·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族研究的推动。在这些研究中，乳腺癌易感基因BRCA1/BRCA2在一部分病例和对照组上进行了基因分型，同时收集了所有研究参与者及其女性亲属的综合信息，如病史和口服避孕药使用情况。我们将对这些数据进行分析，以说明所提出的方法。 我们还建议开发统计方法来分析杂合性丢失(LOH)或等位基因丢失，其定义为匹配的肿瘤DNA中两个相应等位基因之一的完全或部分信号减少。杂合性缺失是评估基因组不稳定性和定位抑癌基因最常用的方法之一。在信息性标记上，杂合性缺失状态的数学表示为杂合性保留或丢失的0/1。我们建议应用生存分析技术来处理数量越来越多的遗传标记，因为染色体可以被认为是从着丝粒到端粒的时间轴，染色体上的标记可以被认为是检查时间。我们将开发半参数和非参数方法来比较两个样本(如两种类型的乳腺癌)之间的杂合性缺失情况，并在杂合性缺失的边缘和局部相关性分析中回归分析协变量，如P53基因的表达。我们将把所提出的方法应用于小叶和导管乳腺癌的全基因组杂合性缺失分析。

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.