The Alzheimer Disease Sequence Analysis Collaborative

阿尔茨海默病测序项目（ADSP）是一项国家测序计划，专注于识别 遗传变异，无论是保护或增加风险，晚发性阿尔茨海默病（负载），与 目标是加速开发有效的治疗方法。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色（NHW）病例（N= 5，606）和对照（N= 4，965）进行测序（WES）， 和578个NHW和西班牙裔（HI）家族样品的全基因组测序（WGS）。Discovery扩展 项目阶段增加了对434个新的家族样本和3，343个NHW、AA和HI病例和对照的WGS （统称ADSP-DEP）。对这些数据的初步分析证实了已知的LOAD基因，并指出 几个新的LOAD相关基因及其与APP加工、神经炎症 内吞作用和胆固醇代谢。当前的随访研究阶段（ADSP-FUS）将产生 超过15，000个额外的WGS侧重于“包含尽可能丰富的种族多样性”的样本， 包括HI和非裔美国人（AA）数据集。这些不同数据集的组合来自于 病例对照、队列和家族研究设计需要密集和全面的分析努力， 发现隐藏在WGS中的大量信息。我们（阿尔茨海默病合作组织） 研究[CADRE]）假设保护性和风险性基因组变异将提供潜在的治疗性 阿尔茨海默病的治疗目标因此，本提案的主要目标是将全面 结合ADSP数据（WGS、WES、SNP阵列）与现存生物学数据的基因组分析， 鉴定最高优先级的变体和基因座作为下游功能分析的候选物。通过 利用来自AA和HI混合人群的数据，我们利用他们增加的多样性， 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LOAD中的基因组变异： 种族多样的数据集。我们将分别为ADSP-DEP和ADSP-FUS提供额外的 资助的WES和WGS数据; 2）在种族上使用混合分析来加强发现和精细映射 多样的数据集; 3）通过整合统计和生物信息来优先考虑变体和基因。为 我们确定的变体，我们将从结构和基因表达数据中产生额外的信息， 将所有数据整合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级 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.