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

项目摘要/摘要： 阿尔茨海默病测序项目 (ADSP) 致力于识别新的基因组变异，从而导致 增加多种族人群患阿尔茨海默病的风险和预防措施，并确定新的治疗方法 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 中获得 将为后续研究（FUS）生成。该提案的研究人员多种多样，但 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 目标和 AD 临床专业知识，自 ADSP 成立以来一直参与其中。此外他们 通过他们在 CHARGE（队列）中的角色，带来内表型和其他 WGS 数据方面的专业知识 用于基因组流行病学中的心脏和衰老研究）和 TOPMed（精准医学跨组学） 财团。我们现在提出以下目标来实现 ADSP 目标。目标 1：全面表征已知的 AD 基因座 并通过利用全方位的遗传变异来识别 AD 的新的保护性和风险变异 通过全基因组测序（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 和内表型的扩展关联分析、新发现的识别 通过精心挑选的“Wellderly”样本以及跨分析结果的整合来发现保护性变异。目标 2：利用种族多样化和混合人群来识别 AD 和 AD 的新变异 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 对混合血统样本进行绘图，并进行种族特异性分析和跨种族元分析 分析。将针对 AD、AD 内表型和 Wellderly 状态进行目标 2 分析。目标 3： 通过生物信息学和组学整合，对基因、基因网络和系统进行功能表征 分析以确定假定的治疗靶点。调查人员将与加速中心密切合作 药品合作伙伴关系 (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 内的 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，利用系统方法来理解 ADSP 测序数据 更大范围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 全面、综合的计划，我们将在现有的 ADSP 基础设施内实施该计划 与 ADSP 调查人员协调。

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.