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 为了进一步解开阿尔茨海默病（AD）的分子机制， 为了定位治疗靶点，我们提出了一种极端的表型设计：全基因组测序 (WGS)在一组多发病、表型良好加勒比西班牙裔人群中进行早发性AD（EOAD）研究 (CH)和非西班牙裔白色（NHW）家庭。极端表型设计（例如，早发性AAO vs.缓慢进展者、非常高对非常低生物标志物水平等）通过产生更多的 同质和遗传负载的人群，并有可能揭示遗传风险因素， 在更异构的数据集中难以识别的机制。这对于澄清AD至关重要 病因学和开发更有效的治疗靶点。 AD的早期研究集中在EOAD，并确定了有限数量的高渗透风险变体： APP、PSEN 1和PSEN 2。这些基因增加淀粉样蛋白β肽的产生和/或聚集， 这是当前治疗策略的基础。然而，这些已知的突变占较少 超过一半的遗传基础。许多EOAD家族不携带已知的突变， 已知的突变携带者AAO通常是高度可变的。这种无法解释的EOAD遗传成分 代表了我们对AD病因学理解的一个关键空白-一个未被正在进行的AD测序填补的空白 研究，主要集中在更异质的晚发型AD（LOAD）。而且这个 提案包括西班牙裔和非西班牙裔白色样本。少数民族人口的加入， 我们在研究不足但快速增长的人群中检查EOAD风险，并绘制AD风险位点， 这是这个种族群体所独有的，进一步深入了解了这种疾病的病因机制。 为了实现这些目标，我们提出了以下目标：（SA 1）识别新的遗传风险因素 通过全基因组和靶向测序来检测EOAD。我们将在87个多重EOAD家庭中进行WGS， 随后是基于分离和功能的生物信息学注释和优先级排序。最高优先级 基因/区域将在家族中得到验证，然后将成为一组定制测序的目标。 EOAD单例，以最大限度地识别变异。(SA2)SA 1产生的推定功能基因座将是 使用定制基因分型阵列在独立EOAD样本中进行验证，并评价（SA 3） 使用现有LOAD资源（如ADSP、ADGC和WHICAP）对迟发性AD进行推广 数据集。最后（4），最有趣的变异将受到快速，生物筛选程序， 确定它们的分子效应。