Dissecting the Genomic Etiology of non-Mendelian Early-Onset Alzheimer Disease and Related Phenotypes

项目总结 阿尔茨海默病(AD)的基因组研究主要集中在非西班牙裔白人(NHW)参与者 受晚发性疾病(负荷；发病年龄：&gt；65)或早发性AD(Eoad； 发病年龄=65岁)来自表现孟德尔遗传模式的家庭的病例与 APP、PSEN1和PSEN2基因。然而，这三个基因的突变可以解释约10%的Eoad病例。那里 没有大规模的努力来收集和研究没有这些基因解释的Eoad病例，尽管事实是 这种无法解释的Eoad类别约占案件的90%。已经进行的为数不多的较小规模的研究 提示EoAD的遗传结构与晚发型只有部分重叠。因此，学习 在没有APP、PSEN1和PSEN2突变的受试者中，Eoad是一个关键的缺口，提供了一个独特的机会 用于发现新的治疗靶点和分子途径。 为了解决这个问题，我们的目标是通过大规模的整体- 不明原因Eoad的基因组测序研究。我们将包括几个著名的案例 AD队列，包括早发性阿尔茨海默病研究资源(READR)，Knight-ADRC，网址： 华盛顿大学、阿尔茨海默病遗传学联合会(ADGC)和其他机构。生成和 协调200个非西班牙裔白人(NHW)和加勒比拉美裔(CH)多个Eoad家庭的数据集， 超过4,000个Eoad单人和超过13,000个不相关的认知控制，都有WGS，这个项目将产生 迄今为止最大的Eoad基因组数据集，提高了变异识别的统计能力，并使我们能够 评估特定因素的影响，如载脂蛋白E基因、血管危险因素和神经精神疾病 合并症。纳入一大组CH家庭和单身人士将允许对Eoad风险进行检查 在一个严重缺乏研究但快速增长的少数族裔人口中。分析将包括链接和 基于关联的方法，多基因和祖先效应的分析，以及对 神经认知、神经精神和心血管内表型。我们希望在成功的情况下 完成后，这项研究将指出Eoad的新基因贡献者，揭示AD的机制和 促进新疗法的发展。 采样、表型和测序分析协议将补充和兼容 现有的负荷基因组学资源，如阿尔茨海默病测序项目(ADSP)和相关 学习。这种表型和基因组的一致性，以及现有AD基础设施的使用 (NIAGADS)，允许立即与加载方面的领先工作集成，从而实现快速大规模 研究各种附加的AD基因组学关键假说。

PROJECT SUMMARY Genomic studies of Alzheimer's disease (AD) have primarily focused on non-Hispanic White (NHW) participants affected by the late-onset form of the disease (LOAD; onset age: >65), or the study of early onset AD (EOAD; onset age <=65) cases from families showing Mendelian inheritance patterns associated with mutations in the APP, PSEN1 and PSEN2 genes. However, mutations in these three genes explain ~10% of EOAD cases. There are no large-scale efforts to collect and study EOAD cases not explained by these genes, despite the fact that this unexplained EOAD category accounts for ~90% of cases. The few smaller studies that have been conducted suggest that the genetic architecture of EOAD overlaps with the late-onset form only partially. Thus, studying EOAD in subjects without APP, PSEN1 and PSEN2 mutations is a critical gap that provides a unique opportunity for discovering novel therapeutic targets and molecular pathways. To address this issue we aim to identify additional EOAD-associated variants through a large-scale whole- genome sequencing (WGS) study of unexplained EOAD. We will include cases from several well-established AD cohorts including the Resource for Early-onset Alzheimer Disease Research (READR), the Knight-ADRC at Washington University, the Alzheimer's Disease Genetics Consortium (ADGC), and others. Generating and harmonizing a dataset of 200 non-Hispanic White (NHW) and Caribbean Hispanic (CH) multiplex EOAD families, over 4,000 EOAD singletons and over 13,000 unrelated, cognitive controls, all with WGS, this project will yield the largest EOAD genomics dataset to-date, improving statistical power for variant identification and allowing us to assess the impact of specific factors such as APOE genotype, vascular risk factors, and neuropsychiatric comorbidities. The inclusion of a large set of CH families and singletons will allow the examination of EOAD risk in a significantly understudied but fast-growing minority population. Analyses will comprise both linkage and association-based approaches, analyses of polygenic and ancestry effects, and a thorough examination of neurocognitive, neuropsychiatric and cardiovascular endophenotypes. We expect that when successfully completed, this study will point to novel genetic contributors to EOAD, shed light on the mechanisms of AD and facilitate the development of novel therapeutics. Sampling, phenotyping and sequencing analysis protocols will be complementary to and compatible with the existing LOAD genomics resources, such as the Alzheimer Disease Sequencing Project (ADSP) and related studies. This phenotypic and genomic consistency, together with the use of existing AD infrastructure (NIAGADS), allows for immediate integration with the leading efforts on LOAD, enabling rapid large-scale investigation of a variety of additional critical AD genomics hypotheses.