Genetic Epidemiology of Early-Onset Alzheimers disease in Caribbean Hispanics and non-Hispanic Whites

加勒比西班牙裔和非西班牙裔白人早发性阿尔茨海默病的遗传流行病学

• 批准号: 9194817
• 负责人: Gary Wayne Beecham
• 金额: $ 357.86万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9194817
• 关键词: Accounting; Affect; Age; Aged, 80 and over; Alzheimer' s Disease; Alzheimer' s disease risk; Amyloid; Amyloid beta-Protein; Bioinformatics; Biological; Biological Markers; Caribbean Hispanic; Custom; Data; Data Set; Disease; Elderly; Elements; Ensure; Ethnic group; Etiology; Family; Fostering; Frequencies; Generations; Genes; Genetic; Genomics; Genotype; Goals; Hispanics; Individual; Late Onset Alzheimer Disease; Maps; Minority; Molecular; Mutation; Not Hispanic or Latino; Peptides; Phenotype; Pilot Projects; Population; Presenile Alzheimer Dementia; Proteins; Protocols documentation; RNA; Race; Resources; Risk; Sampling; Screening procedure; Series; Technology; Testing; Therapeutic; Validation; Variant; base; case control; cohort; design; early onset; genetic epidemiology; genetic risk factor; genetic variant; genome sequencing; genome wide association study; genome-wide; insight; interest; member; mutation carrier; novel; presenilin-1; presenilin-2; risk variant; screening; segregation; sex; targeted sequencing; tau Proteins; therapeutic target; tool; whole genome

Project Summary To further disentangle the molecular mechanisms underlying Alzheimer's disease (AD) and to foster the mapping of therapeutic targets, we propose an extreme phenotype design: a whole-genome sequencing (WGS) study of early-onset AD (EOAD) in a large set of multiply affected, well-phenotyped Caribbean Hispanic (CH) and non-Hispanic White (NHW) families. Extreme phenotype designs (e.g., early age-at-onset--AAO, fast vs. slow progressors, very high vs. very low biomarker levels, etc) increase statistical power by creating more homogeneous and genetically loaded populations, and have the potential to reveal genetic risk factors and mechanisms that are difficult to identify in more heterogeneous datasets. This is critical for clarifying AD etiology and developing more effective therapeutic targets. Early studies in AD focused on EOAD and identified a limited number of highly penetrant risk variants: APP, PSEN1, and PSEN2. These genes increase the generation and/or aggregation of the amyloid ß peptide, an observation that underlies current therapeutic strategies. However, these known mutations account for less than half of the genetic basis of EOAD. Many of the EOAD families do not carry known mutations, and among known mutation carriers AAO is often highly variable. This unexplained genetic component to EOAD represents a critical gap in our understanding of AD etiology—a gap not filled by the ongoing AD sequencing studies, which largely focus on the more heterogeneous late-onset form of AD (LOAD). Additionally, this proposal includes both Hispanic and non-Hispanic white samples. The inclusion of minority populations allows us to examine EOAD risk in an understudied but fast-growing population and to map AD risk loci that are unique to this ethnic group, giving further insight into the etiologic mechanisms underlying the disease. To accomplish these goals, we propose the following Aims: (SA1) Identification of novel genetic risk factors for EOAD by whole genome and targeted sequencing. We will perform WGS in 87 multiplex EOAD families, followed by bioinformatics annotation and prioritization based on segregation and function. Highest priority genes/regions will be validated in the family and then will become targets for custom sequencing in a set of EOAD singletons to maximize variant identification. (SA2) Putative functional loci resulting from SA1 will be validated in independent EOAD samples using custom genotyping arrays and (SA3) evaluated for generalizability to late-onset AD using existing LOAD resources such as the ADSP, ADGC, and WHICAP datasets. Finally (4), the most interesting variants will be subject to rapid, biological screening procedures to determine their molecular effects.

项目摘要 为了进一步解散阿尔茨海默氏病（AD）的分子机制，并促进 映射治疗靶标，我们提出了一种极端的表型设计：全基因组测序 （WGS）在一系列倍数受影响的，良好的加勒比海西班牙 （CH）和非西班牙裔白人（NHW）家庭。极端表型设计（例如，早年时代 - aao，快速 与缓慢的进步者，非常高与非常低的生物标志物水平等）通过创建更多 同质和遗传载荷人群，并有可能揭示遗传危险因素和 在更异质的数据集中难以识别的机制。这对于澄清广告至关重要 病因和发展更有效的治疗靶标。 AD的早期研究集中在EOAD上，并确定了有限数量的高度渗透风险变体： 应用，PSEN1和PSEN2。这些基因增加了淀粉样蛋白ßpepperide的产生和/或聚集， 当前理论策略是基础的观察。但是，这些已知突变较少 EOAD遗传基础的一半。许多EOAD家庭都没有携带已知突变， 已知的突变载体AAO通常是高度可变的。 EOAD的意外遗传成分 在我们对AD病因的理解中代表了一个关键的差距，这一差距并非由正在进行的广告测序填补 研究很大程度上集中在AD（负载）的更异质的后期形式。另外，这个 提案包括西班牙裔和非西班牙裔白色样品。包括少数族裔允许 我们要检查一个可理解但增长快速的人口中的EOAD风险，并绘制AD风险基因座 这个族裔独有，进一步了解了该疾病的病因机制。 为了实现这些目标，我们提出以下目的：（SA1）识别新型遗传风险因素 用于整个基因组和靶向测序的EOAD。我们将在87个多重EOAD系列中执行WGS， 然后基于隔离和功能进行生物信息学注释和优先次序。最高优先级 基因/区域将在家庭中进行验证，然后成为一组定制测序的目标 EOAD单例最大化变体识别。 （SA2）SA1产生的假定功能基因座将是 使用自定义基因分型阵列和（SA3）评估的独立EOAD样品验证 使用现有的负载资源（例如ADSP，ADGC和WHICAP）进行迟到广告的概括性 数据集。最后（4），最有趣的变体将受到快速的生物学筛查程序的约束 确定它们的分子效应。