New statistical strategies for comprehensive analysis of epigenomewide methylation data

项目摘要 阿尔茨海默病(AD)是最常见的神经退行性疾病，约6%的人 在全世界范围内都是几年或更久。目前，还没有针对这种疾病的有效治疗或预防措施。与 在美国不断增长的老年人口中，阿尔茨海默病已经成为一个主要的公共卫生问题，也是 经济上代价高昂的疾病。尽管最近在识别与阿尔茨海默病相关的遗传变异方面取得了进展，但 阿尔茨海默病的生物学机制仍不清楚。绝大多数AD病例是散发性的(特发性)， 疾病可能是由遗传和环境因素的复杂相互作用引起的，例如 吸烟、不良饮食和缺乏锻炼。 表观遗传学研究探索了在不改变所选基因表达水平的情况下 潜在DNA序列的变化。对这些表观遗传模式的研究为 检测可能易受环境因素影响的新的监管机制， 反过来又增加了患病的风险。在表观遗传修饰中，DNA甲基化是最广泛的 学习。DNA甲基化水平的改变与包括阿尔茨海默病在内的许多疾病有关。 虽然已经开发了一些工具来识别差异甲基化区域(DMR) 表观基因组范围的关联研究，大多数只关注包含高度显著的区域 基因组中差异甲基化的CPGS，即“冰山一角”，但缺乏关于 在基因组的其余部分中包含具有真实但适度关联的CPGS。我们假设在大多数情况下 在阿尔茨海默病等复杂疾病中，多个基因组区域的甲基化是 与疾病的发展和进展有关，其中一些区域可能未被检测到 使用传统的“最重要的点击量”方法。 在目标1中，我们将开发一种有效的分析管道来鉴定具有生物意义的DMR以及 为整个基因组区域提供全面的重要性评估，这将简化 下游综合分析。在目标2中，我们将把新方法应用于两个阿尔茨海默病患者的大脑样本 疾病数据集，以确定AD中最可能受表观遗传机制控制的基因和途径。 目标1的成功完成将为表观基因组范围的关联的综合分析提供关键工具 并将有助于改变目前只关注区域的环境与环境研究的分析范式 包含最显著的差异甲基化的CPGS，并且在很大程度上忽略了 基因组。目标2的成功完成将为理解表观遗传学提供重要的见解 阿尔茨海默氏症的潜在程序。

Project Summary Alzheimer's disease (AD) is the most common neurodegenerative disorder, affecting about 6% of people 65 years and older worldwide. Currently, there is no effective treatment or prevention for the disease. With the rising elderly population in the US, AD has become a major public health problem and one of the most financially costly diseases. Despite recent progress in identifying genetic variants associated with AD, the biological mechanism underlying AD remains elusive. The vast majority of AD cases are sporadic (idiopathic), with disease likely resulting from a complicated interplay of genetic and environmental factors such as smoking, poor diet, and lack of exercise. Epigenetic studies investigate the mechanisms that modify the expression levels of selected genes without changes to the underlying DNA sequence. The study of these epigenetic patterns hold excellent promise for detecting new regulatory mechanisms that may be susceptible to modification by environmental factors, which in turn increase the risk of disease. Among epigenetic modifications, DNA methylation is the most widely studied. Alterations of DNA methylation levels are involved in many diseases including Alzheimer's Disease. Although a number of tools have been developed to identify Differentially Methylated Regions (DMRs) in Epigenome-Wide Association Studies, most of them only focus on the regions that contain highly significantly differentially methylated CpGs in the genome, i.e. the “tip of the iceberg”, but lack information on regions that contain CpGs with real but modest associations in the rest of the genome. We hypothesize that in the majority of complex diseases such as Alzheimer's Disease, methylation at multiple genomic regions are causally implicated in the development and progression of the disease, and some of these regions might be undetected using the conventional “most significant hits” approaches. In Aim 1, we will develop an efficient analytical pipeline for identifying biologically meaningful DMRs as well as providing comprehensive significance assessment to regions across the genome, which will streamline downstream integrative analysis. In Aim 2, we will apply the new method to brain samples in two Alzheimer disease datasets, to identify genes and pathways most likely controlled by epigenetic mechanism in AD. Successful completion of Aim 1 will provide critical tools for integrative analysis of epigenome-wide association studies (EWAS) and will help shift the current analysis paradigm of EWAS, which focuses only on regions contain the most significant differentially methylated CpGs, and largely ignores information in the rest of the genome. Successful completion of Aim 2 will provide important insights into understanding the epigenetic programs underlying Alzheimer's Disease.