Genetic Studies of Alzheimer's Disease in Jewish and Arab Populations

犹太人和阿拉伯人群阿尔茨海默病的遗传学研究

• 批准号: 10639024
• 负责人: Lindsay A. Farrer
• 金额: $ 238.97万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10639024
• 关键词: Admixture; Affect; Age; Alzheimer' s Disease; Alzheimer' s disease risk; Alzheimer’s disease biomarker; Amyloid beta-Protein; Arabs; Ashkenazim; Bioinformatics; Biological Markers; Blood; Blood specimen; Brain; Caucasians; Clinical; Clinical Trials; Cognitive; Coupled; DNA; Data; Data Set; Development; Drug Targeting; Environmental Exposure; Environmental Risk Factor; Ethnic Origin; Ethnic Population; European ancestry; Evaluation; Funding; Gene Expression; Gene Targeting; Genes; Genetic; Genetic Diseases; Genetic Drift; Genetic Transcription; Genetic study; Genotype; Goals; Haplotypes; Human; Individual; Israel; Jews; Joints; Lead; Life Style; Light; Location; Measures; Medical History; Mendelian randomization; Methods; Middle East; Modeling; Modification; Mutation; Northern Africa; Nucleotides; Outcome; Participant; Pathogenicity; Pathway Analysis; Pathway interactions; Pharmaceutical Preparations; Phenotype; Population; Process; Proteins; Quantitative Trait Loci; Risk; Risk Assessment; Role; Sampling; Satellite Viruses; Sequence Alignment; Site; Spain; Specimen; Tissues; United States National Institutes of Health; Variant; Virus; admixture mapping; analytical method; ancestry analysis; apolipoprotein E-4; brain magnetic resonance imaging; clinical examination; cognitive testing; cohort; drug development; follower of religion Jewish; gene network; genetic analysis; genetic architecture; genetic testing; genome sequencing; genome wide association study; genome-wide; insertion/deletion mutation; machine learning method; neurofilament; next generation sequencing; novel; patient registry; phenotypic data; pleiotropism; positional cloning; prospective; protein structure; recruit; risk variant; tau Proteins; tau-1; trait; viral DNA; viral detection; whole genome

Most discoveries of the genetic basis of Alzheimer disease (AD) were made in Caucasians of European ancestry (EAs) and required samples between 10,000 and 150,000 subjects to detect them. We and others have demonstrated that discovery of AD risk variants can be accomplished in more genetically homogeneous cohorts comprising several thousand or fewer subjects. Studies of non-EA populations also afford the opportunity to discover variants that are relatively rare or absent in EAs and that display a smaller effect size in EAs due to modification by other genes and environmental factors. We will focus on Jews and Arabs currently living in Israel who are descended from the Middle East and North Africa (MENA). Although MENA Jews assimilated to some extent with their non-Jewish neighbors, they have maintained a distinctive genetic profile that reflects some admixture with non-Jews, ancient Jewish background, and a unique component reflecting genetic drift and new mutations during the last two millennia. Our previous studies of Arabs living in the Israeli village called Wadi Ara revealed a genome-wide significant association for AD with ACE, were central to the establishment of SORL1 as an AD gene, and contributed to a trans-ethnic GWAS leading to the discovery of several novel AD genes. In this project, we will leverage the genetic architecture of MENA Jews and Israeli-Arabs, as well as their distinctive environmental exposures and lifestyles, to promote discovery of AD-related genes and variants. Specifically, we will recruit 3,000 MENA Jews at three sites in Israel, as well as 1,000 Israeli-Arabs located in multiple villages (equal numbers of AD cases and controls in the total sample). We will obtain from each participant a blood specimen for DNA and biomarker studies, and phenotypic data including clinical, cognitive test, medical history and lifestyle information, as well as brain MRI data for a portion of the sample. DNA specimens will be whole genome sequenced (WGS). WGS data will be processed using pipelines established by the Alzheimer Disease Sequencing Project (ADSP). We will conduct a GWAS for AD using admixture mapping and methods for single variant and gene-based tests. Top-findings will be replicated in Ashkenazi Jewish and non-Jewish datasets assembled by the Alzheimer Disease Genetics Consortium and ADSP using trans-ethnic analysis and approaches that focus on variants affecting protein structure, transcription, and gene expression. We will also conduct GWAS for age at onset and AD biomarkers using single outcome and pleiotropy models. Next, we will identify gene targets of the top-ranked SNPs by performing expression quantitative trait locus analysis using locally derived and publicly available data containing genotype and gene expression data in brain and other tissues, and establish functional connections among the top-ranked SNPs and genes using pathway, co- expression network, and Mendelian randomization analysis. Finally, we will evaluate the association of viruses detected in WGS data with AD using machine learning methods and regression models. We expect that this project will identify novel targets for development of effective drugs to treat or retard processes leading to AD.

大多数关于阿尔茨海默氏病遗传基础（AD）的发现是在欧洲血统的高加索人 （EAS）和需要10,000至150,000名受试者的样本来检测它们。我们和其他人有 证明可以在更具遗传均匀的人群中实现AD风险变体的发现 包括几千或更少的主题。对非AEA人群的研究也有机会 发现EAS中相对较少或不存在的变体，并且由于EAS在EAS中显示较小的效果大小 其他基因和环境因素的修饰。我们将专注于目前居住在以色列的犹太人和阿拉伯人 从中东和北非（MENA）下来的人。虽然中东犹太人融入了一些 与他们的非犹太人邻居的程度，他们保持着独特的遗传特征，反映了某些 与非犹太人，古老的犹太背景以及反映遗传漂移和新的独特组成部分的混合 过去两千年中的突变。我们以前关于居住在以色列村庄的阿拉伯人的研究称为Wadi Ara 揭示了广告与ACE的全基因组显着关联，这对于建立SORL1是至关重要的 作为AD基因，并为跨种族的GWA做出了贡献，导致发现了几种新型的AD基因。在 这个项目，我们将利用MENA犹太人和以色列阿拉伯的遗传建筑及其独特的 环境暴露和生活方式，以促进与广告相关的基因和变体发现。具体来说，我们 将在以色列的三个地点以及位于多个村庄 （总样本中的AD病例和对照的数量相等）。我们将从每个参与者那里获得血液 DNA和生物标志物研究的标本以及表型数据，包括临床，认知测试，病史 和生活方式信息，以及部分样本的大脑MRI数据。 DNA标本将是完整的 基因组测序（WGS）。 WGS数据将使用阿尔茨海默氏病确立的管道处理 测序项目（ADSP）。我们将使用混合映射和单个方法进行AD的GWA 变体和基因测试。顶级调查将在Ashkenazi犹太人和非犹太数据集中复制 由阿尔茨海默氏病遗传学联盟和ADSP组装，使用跨种族分析和 侧重于影响蛋白质结构，转录和基因表达的变体的方法。我们也会 使用单一结果和多效模型在发病时期和AD生物标志物进行GWAS进行GWAS。接下来，我们会的 使用使用表达定量性状基因座分析来确定排名最高的SNP的基因靶标 本地得出的且公开可用的数据，其中包含大脑和其他中的基因型和基因表达数据 组织，并使用途径共同建立排名最高的SNP和基因之间的功能连接 表达网络和孟德尔随机分析。最后，我们将评估病毒的关联 使用机器学习方法和回归模型在WGS数据中检测到WGS数据。我们期望这 项目将确定开发有效药物以治疗或延迟导致AD的新目标。