Correcting for Population Structure in Gene-by-Environment Interaction Studies

在过去的几年里，全基因组关联研究（GWAS）已经确定了许多基因 与人类常见疾病有关。在这些研究中，数千个个体的遗传变异 被收集并与这些个体的疾病状态相关联。环境因素往往 与遗传变异相互作用，增加患病风险。识别这些相互作用，称为 基因与环境（GxE）的相互作用，现在是人类研究和 模式生物研究。发现GxE相互作用可以深入了解疾病途径， 了解环境因素对疾病的影响，更好地预测风险， 治疗小鼠等模式生物是研究GxE相互作用的理想环境 因为环境暴露可以被仔细控制。 在这个提议中，我们建议开发一种方法，来确定基因与环境之间的关系 存在相互作用，并且可以量化这些相互作用的总量。我们项目的成果 将是一套方法，然后可以广泛使用的许多研究人员参与的研究， 发现基因与环境的相互作用。 我们将把我们开发的方法应用于明尼苏达州双胞胎和家庭研究中心（MCTFR） 研究基因-环境相互作用如何影响物质滥用（SA）的发展的数据 以及研究影响对高脂肪饮食反应的遗传因素的小鼠遗传研究 和心力衰竭的易感性。我们将通过以下方式向研究界提供我们的方法： 公开可用的软件包和网络服务器资源。

Over the past few years, genome-wide association studies (GWASs) have identified numerous genes associated with common human diseases. In these studies, genetic variation in thousands of individuals is collected and correlated with the disease status in these individuals. Environmental factors often interact with genetic variation to increase risk of disease. Identifying these interactions, referred to as gene-by-environment (GxE) interactions, is now a major focus of research in both human studies and model organism studies. Discovering GxE interactions can provide insight into disease pathways, an understanding of the effect of environmental factors in disease, better risk prediction and personalized therapies. Model organisms such as mouse are ideal environments for studying GxE interactions because environmental exposures can be carefully controlled. In this proposal we propose to develop methodology that determine whether or not gene-by-environment interactions are present and can quantify the total amount of these interactions. The results of our project will be a set of methods that can then be widely used by many researchers involved in studies to discovery gene-by-environment interactions. We will apply our developed methods to the Minnesota Center for Twin and Family Research (MCTFR) data to investigate how gene-environment interplay influences the development of substance abuse (SA) and to mouse genetic studies investigating the genetic factors which influence response to high fat diet and susceptibility to heart failure. We will make our methods available to the research community through publicly available software packages and webserver resources.