Statistical Methods in Genetic Epidemiology Research

描述（由申请人提供）：本研究的长期目标是开发强大的统计方法，用于分析遗传流行病学研究的数据。由于人类基因组计划和高通量基因分型技术的快速发展，大量数据变得可用，但需要强大的统计方法才能最终成功识别易感遗传变异及其环境修饰剂。该项目的重点是开发用于分析围产期或生命早期疾病的遗传关联研究的统计方法。这些研究通常采用回顾性病例对照设计，但它们有一个明显的特点，即母亲病例/对照（围产期疾病）的后代或后代病例/对照（生命早期疾病）的父母也被招募。因此，这些研究既有不相关的病例对照比较的信息，也有基因型/单倍型家庭内的传播。这些研究的另一个重要特征是，研究人群中的协变量分布是有结构的，因此遗传和环境变量通常在家庭中是独立的。事实上，这种独立性不持有的情况下，人口的备择假设提供了进一步的信息，超出标准的病例对照比较的关联。这些研究通常试图评估母体和后代基因型/单倍型的影响，它们的相互作用，以及基因-环境相互作用。基于目前可用的病例对照关联研究和病例父母三联体分析方法，我们提出了新的有效的估计和检验方法，可以解释回顾性病例对照设计，并将基因型/单体型传播的家族信息和协变量分布的结构。病例对照研究的经典逻辑回归适用于大多数分析，但由于忽略了家庭信息和协变量结构，效率较低。用于分析病例-亲本三联体的传递/不平衡类型检验或基于可能性的方法丢弃对照和/或其亲本，并且不能估计所有感兴趣的参数（例如，环境暴露的主要影响）。我们的方法范围从轮廓似然方法和基于估计函数的方法到基于案例三元组和伪似然的条件似然的混合方法。该项目的动机是并将应用于宾夕法尼亚大学正在进行的科学研究，PI正在合作，表型包括早产、先兆子痫、尿道下裂和哮喘。我们的方法也有广泛的影响，研究表型以外的围产期和生命早期疾病。我们将为所提出的方法发展大样本理论，通过模拟研究评估其有限样本性能，并使用真实的数据证明其实用性。将使用免费提供的统计软件包R提供执行这些方法的完整记录的软件供公众使用。 公共卫生相关性：该项目提出了新的统计方法，用于分析围产期或儿童早期疾病病例对照遗传流行病学研究的数据。数据通常由病例和对照母亲及其各自的后代组成，或者由病例-父母三联体和对照-父母三联体组成。所提出的方法用于估计和检验母体和后代基因型/单体型主效应以及基因型/单体型与环境变量之间的交互作用和交互作用效应。

DESCRIPTION (provided by applicant): The long-term objective of this research is to develop powerful statistical methods for the analysis of data from genetic epidemiology studies. While voluminous data are becoming available owing to the Human Genome Project and rapid advancement of high throughput genotyping technology, powerful statistical methods are needed for ultimate success in identifying predisposing genetic variants and their environmental modifiers. This project focuses on developing statistical methods for analyzing genetic association studies on perinatal or early-life diseases. These studies very often adopt a retrospective case-control design, but they have a distinct feature in that offspring of mother cases/controls (for perinatal diseases) or parents of offspring cases/controls (for early-life diseases) are also recruited. Thus these studies have information on both unrelated case-control comparisons and genotype/haplotype transmissions within families. Another important feature of these studies is that the covariate distribution in the study population is structured so that genetic and environmental variables are usually independent within families. The fact that such independence does not hold in the case population under the alternative hypothesis provides further information on the association beyond standard case-control comparison. These studies usually seek to evaluate effects of both maternal and offspring genotypes/haplotypes, their interactions, and gene-environment interactions. Building on currently available approaches for analysis of case-control association studies and case-parent triads, we propose novel efficient estimation and testing methods that can account for the retrospective case-control design and incorporate the family information on the genotype/haplotype transmission and the structure in the covariate distribution. Classical logistic regression for case-control studies applies for most of the analysis but is less efficient due to the ignorance of family information and covariate structure. The Transmission/Disequilibrium type test or likelihood-based methods for analyzing case-parent triads discard the controls and/or their parents and cannot estimate all parameters of interest (e.g., main effects of environmental exposures). Our methods range from profile-likelihood methods and estimating-function based methods to hybrid methods based on the conditional likelihood for case triads and pseudo-likelihoods. This project is motivated by and will be applied to ongoing scientific studies at the University of Pennsylvania on which the PI is collaborating, and the phenotypes include pre-term birth, preeclampsia, hypospadias, and asthma. Our methods also have broad implications to the study of phenotypes other than perinatal and early-life diseases. We will develop large sample theories for the proposed methods, evaluate their finite sample performance by simulation studies, and demonstrate their usefulness using real data. Fully documented software to implement these methods for public use will be provided using freely available statistical package R. PUBLIC HEALTH RELEVANCE: This project proposes novel statistical methods for the analysis of data arising from case- control genetic epidemiology studies of perinatal or early childhood diseases. Data usually consist of case and control mothers and their respective offspring or consist of both case-parent triads and control-parent triads. The proposed methods are for the estimation and testing of maternal and offspring genotype/haplotype main effects and interactions and interaction effects between genotypes/haplotypes and environment variables.