Therapeutic target discovery in ADSP data via comprehensive whole-genome analysis incorporating ethnic diversity and systems approaches

项目概要/摘要： 阿尔茨海默病测序项目（ADSP）旨在确定新的基因组变异， 在多种族人群中增加阿尔茨海默病的风险和保护，并确定新的 疾病治疗和预防的途径。全基因组和全外显子组测序数据（WGS和 WES）可从ADSP发现和发现-扩展阶段以及不同种族群体的WGS获得 将为随访研究（FUS）生成。这项提案的调查人员各不相同， 生物信息学、应用统计学和方法学领域的互补专业知识 开发、混合和种族多样性、罕见变异关联、网络建模、临床前验证 的目标，并在AD的临床专业知识，并已参与了ADSP自成立以来。越远 通过他们在CHARGE（队列）中的作用，带来关于内源性表型和其他WGS数据的专业知识 基因组流行病学中的心脏和衰老研究）和TOPMed（精准医学的Trans-Omics） 财团。我们现在提出以下目标，以实现非洲发展战略文件的目标。目的1：充分表征已知的AD基因座 并通过利用全范围的遗传变异性来鉴定AD的新的保护性和风险变体 通过WGS揭示，包括单核苷酸多态性，小插入/缺失和结构变异。 分析将包括AD和内源性表型的扩展关联分析， 通过精心挑选的“Wellderly”样本，以及分析结果的整合，获得保护性变体。目的 2：利用种族多样性和混合人群来识别AD的新变体， 内表型这将通过估计和核算全球规模的人口结构来实现， ADSP三个阶段的关联分析。我们还建议进行混合 在混合血统的样本中绘图，并进行种族特异性分析和跨种族Meta分析， 分析。将对AD、AD内在表型和健康状态进行目的2分析。目标3： 通过生物信息学和组学整合功能表征基因、基因网络和系统 分析以确定推定的治疗靶点。调查人员将与加速 药品伙伴关系（AMP）项目。我们建议结合使用生物信息学工具和分析 “组学”数据，包括AMP中的DNA甲基化、基因表达、miRNA和代谢组学数据， 在CHARGE队列中预测特定变体或变体组的功能，应用网络 跨基因组的方法，以利用系统方法来了解ADSP测序数据， 更大的人类生物学背景，并确定假定的治疗靶点。我们的建议提供了一个 我们将在现有的ADSP基础设施内实施全面的综合计划， 与ADSP调查员协调。

Project Summary/Abstract: The Alzheimer Disease Sequencing Project (ADSP) seeks to identify new genomic variants contributing to increased risk for and protection from Alzheimer's Disease in multi-ethnic populations, and to identify new pathways for disease treatment and prevention. Whole genome and whole exome sequencing data (WGS and WES) are available from ADSP Discovery and Discovery-Extension Phases and WGS in diverse ethnic groups will be generated for the Follow-up Study (FUS). The investigators of this proposal have diverse but complementary expertise across the range of bioinformatics, applied statistics and methodological development, admixture and ethnic diversity, rare variant association, network modeling, preclinical validation of targets, and clinical expertise in AD and have been involved in the ADSP since its inception. Further they bring expertise on endophenotypes and additional WGS data through their role within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) and TOPMed (Trans-Omics for Precision Medicine) consortia. We now propose the following aims to meet ADSP goals. Aim 1: To fully characterize known AD loci and to identify novel protective and risk variants for AD by exploiting the full range of genetic variability revealed by WGS including single nucleotide polymorphisms, small insertion/deletions, and structural variants. Analyses will include expanded association analyses of AD and endophenotypes, identification of novel protective variants via carefully selected “Wellderly” samples, and integration of findings across analyses. Aim 2: To leverage ethnically-diverse and admixed populations to identify novel variants for AD and endophenotypes. This will be achieved by estimating and accounting for global-scale population structure in association analyses across the three phases of ADSP. We additionally propose to perform admixture mapping in samples of admixed ancestry and to perform ethnic-specific analyses and trans-ethnic meta- analyses. Aim 2 analyses will be performed for AD, AD endophenotypes, and Wellderly status. Aim 3: To functionally characterize genes, gene networks, and systems, via bioinformatics and omics integrative analyses to identify putative therapeutic targets. The investigators will work closely with the Accelerating Medicines Partnership (AMP) projects. We propose to use a combination of bioinformatics tools and analysis of “omics” data, including DNA methylation, gene expression, miRNA and metabolomics data within AMP and in the CHARGE cohorts to predict function of specific variants or groups of variants, to apply network approaches across gene sets, to utilize a systems approach to understand the ADSP sequencing data in the larger context of human biology and to identify putative therapeutic targets. Our proposal provides a comprehensive, integrated plan, which we will implement within the existing ADSP infrastructure and in coordination with ADSP investigators.