The Alzheimer Disease Sequence Analysis Collaborative

阿尔茨海默氏症测序项目(ADSP)是一项全国性的测序计划，重点是确定 保护或增加晚发性阿尔茨海默病(LOAD)风险的基因变异，与 加速发展有效疗法的目标。ADSP发现阶段包括整个外显子组 对10,571例无关的非西班牙裔白人(NHW)病例(N=5,606)和对照(N=4,965)进行了测序(WES)， 以及578个nhw和西班牙裔(HI)家族样本的全基因组测序(WGS)。发现扩展 项目阶段增加了对434个新的家庭样本和3343个nhw、aa和hi病例和对照的WGS (统称为ADSP-DEP)。对这些数据的初步分析证实了已知的负荷基因，并指向 几个新的负荷相关基因及其与APP处理、神经炎症、 内吞作用和胆固醇代谢。目前的后续研究阶段(ADSP-FUS)将产生 &gt；另外15,000个工作组专注于“包含尽可能丰富的种族多样性”的样本，这将 主要包括HI和非裔美国人(AA)数据集。这种不同数据集的组合源自 病例对照、队列和家庭研究设计需要密集和全面的分析工作，以 发现隐藏在WGS中的丰富信息。我们(阿尔茨海默病合作组织) 研究[Cadre])假设保护性和危险的基因组变异将提供潜在的治疗 阿尔茨海默病的靶点。因此，这项建议的首要目标是将全面的 与现有生物学数据相结合的ADSP数据(WGS、WES、SNP阵列)的基因组分析 确定最高优先级的变异体和基因座作为下游功能分析的候选。通过 利用来自AA和HI混合种群的数据，我们利用它们增加的多样性来 加速并确定可能的目标。这一目标将通过以下方式实现：1)使用以下方法表征基因组在负载中的变异 不同种族的数据集。我们将分别对ADSP-DEP和ADSP-FUS进行补充 资助WES和WGS数据；2)利用种族混合分析加强发现和精细绘图 不同的数据集；以及3)通过整合统计和生物信息来确定变异和基因的优先顺序。为 我们识别的变异，我们将从结构和基因表达数据中产生额外的信息，并 将所有数据集成到一个基因组驱动的综合生物网络中，该网络将用于确定基因座的优先顺序 作为治疗靶点进行功能测试。

The Alzheimer's Disease Sequencing Project (ADSP) is a national sequencing initiative focused on identifying genetic variants that either protect from or increase the risk for late onset Alzheimer Disease (LOAD), with the goal of accelerating development of effective therapeutics. The ADSP Discovery phase includes whole exome sequencing (WES) of 10,571 unrelated non-Hispanic White (NHW) cases (N=5,606) and controls (N=4,965), and whole genome sequencing (WGS) of 578 NHW and Hispanic (HI) familial samples. The Discovery Extension Phase of the project added WGS on 434 new familial samples and 3,343 NHW, AA, and HI cases and controls (collectively the ADSP-DEP). Preliminary analyses of these data confirm known LOAD genes and point toward several new LOAD-related genes and their functional relationships to APP processing, neuroinflammation, endocytosis, and cholesterol metabolism. The current Follow-Up Study phase (ADSP-FUS) will generate >15,000 additional WGS focused on samples that `encompass the richest possible ethnic diversity', which will include primarily HI and African-American (AA) datasets. This combination of diverse datasets derived from case-control, cohort, and family study designs requires an intensive and comprehensive analytical effort to uncover the wealth of information sequestered in the WGS. We (the Collaboration on Alzheimer Disease REsearch [CADRE]) hypothesize that protective and risk genomic variants will provide potential therapeutic targets for Alzheimer disease. Thus, the primary goal of this proposal is to integrate comprehensive genomic analysis of the combined ADSP data (WGS, WES, SNP array) with extant biological data to identify the highest priority variants and loci as candidates for downstream functional analysis. By leveraging the data derived from the AA and HI admixed populations, we use their increased diversity to accelerate and define likely targets. This goal will be met by: 1) Characterizing genomic variation in LOAD using ethnically diverse datasets. We will supplement the ADSP-DEP and ADSP-FUS with additional, separately funded WES and WGS data; 2) enhancing discovery and fine-mapping using admixture analyses in ethnically diverse datasets; and 3) Prioritizing variants and genes by integrating statistical and biological information. For the variants we identify, we will generate additional information from structural and gene expression data and integrate all data into a genomically driven comprehensive biological network that will be used to prioritize loci for functional testing as therapeutic targets.