Sequence-based Discovery of AD Risk & Protective Alleles

基于序列的 AD 风险发现

• 批准号: 8836770
• 负责人: ELLEN M WIJSMAN
• 金额: $ 71.43万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-15 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8836770
• 关键词: Admixture; African American; Aging; Alleles; Alzheimer' s Disease; Alzheimer' s disease risk; Base Sequence; Bioinformatics; Biometry; Case-Control Studies; Clinical; Collaborations; Communities; Complement 3; Computational algorithm; Data; Dementia; Diagnostic; Disease; Disease Clusterings; Disease susceptibility; Family; Funding; Future; Genes; Genetic; Genome; Genomics; Genotype; Health; Hippocampus (Brain); Hispanics; Human Genetics; Individual; Invertebrates; Lead; Magnetic Resonance Imaging; Maps; Memory; Memory Loss; Methods; Minority; Modeling; Nucleotides; Performance; Phenotype; Population; Population Control; Prevention strategy; Public Domains; Race; Recording of previous events; Research Design; Research Personnel; Resolution; Resources; Risk; Sampling; Science; Sequence Analysis; Serum; Structure; Technology; Testing; Translational Research; Variant; base; case control; clinical Diagnosis; cognitive function; computerized tools; design; endophenotype; epigenomics; exome sequencing; familial Alzheimer disease; gene function; genetic linkage; genome sequencing; high risk; improved; meetings; novel; risk variant

DESCRIPTION (provided by applicant): This Sequence Analysis Consortium (SAC) brings together experts in Alzheimer's disease (AD), human genetics, biostatistics and genome sciences to identify risk and protective single nucleotide and copy number variants (SNVs and CNVs) influencing AD and AD-related endophenotypes. This SAC will harmonize and integrate genomic and phenotype data (generated by Core C) from the AD Sequencing Project (ADSP) and other data resources and use the most informative analytic methods (as determined by Core B) to identify novel risk and protective alleles. This SAC is partially based on the ADSP case-control study design with whole exome sequencing in 6,888 cases who developed AD despite an 'a priori low risk' and are likely enriched for novel risk variants, and 14,400 cognitivly normal older controls, a subset of whom are enriched for protective variants. To allow novel discovery in minority populations that carry a disproportionate burden of AD, we will analyze exome sequence data and well-characterized endophenotypes, including verbal memory and hippocampal volume (harmonized by Core D). Replication will be afforded using targeted sequence and genotype data in 50,000 cases and controls and 40,000 individuals with endophenotype data. We will seek to identify SNVs (Project 1) and CNVs (Project 2) contributing to AD susceptibility and protection. Integrated and annotated (using ENCODE and the Epigenomic Roadmap Projects) SNVs and CNVs data from the ADSP families with whole genome sequencing, as well as other familial AD resources will be used for genetic linkage and IBD analyses (Project 3) to identify AD susceptibility or protective alleles in highly-ascertained, multiplex families. The case-control design (Projects 1 and 2) and the family design (Project 3) complement each other to maximize discovery of AD variants. In order to promote AD translational research and discovery, we will collaborate with other researchers to undertake further replication and functional studies, create public resources with integrated genomic and phenotypic data, and make available computational algorithms through the public domain. Identification of variants in genes leading to risk and protection from AD may ultimately lead to novel treatments and prevention strategies.

描述（由申请人提供）：该序列分析联盟 (SAC) 汇集了阿尔茨海默病 (AD)、人类遗传学、生物统计学和基因组科学领域的专家，旨在识别影响 AD 和 AD 相关内表型的风险和保护性单核苷酸和拷贝数变异（SNV 和 CNV）。该 SAC 将协调和整合来自 AD 测序项目 (ADSP) 和其他数据资源的基因组和表型数据（由核心 C 生成），并使用信息最丰富的分析方法（由核心 B 确定）来识别新的风险和保护性等位基因。该 SAC 部分基于 ADSP 病例对照研究设计，对 6,888 名患有 AD 的病例（尽管“先验低风险”）进行了全外显子组测序，并且可能富含新的风险变异，以及 14,400 名认知正常的老年对照，其中一部分富含保护性变异。为了在 AD 负担过重的少数群体中获得新的发现，我们将分析外显子组序列数据和明确表征的内表型，包括言语记忆和海马体积（由核心 D 协调）。将使用 50,000 个病例和对照以及 40,000 个具有内表型数据的个体的目标序列和基因型数据进行复制。我们将寻求确定有助于 AD 易感性和保护的 SNV（项目 1）和 CNV（项目 2）。来自 ADSP 家族的全基因组测序的 SNV 和 CNV 数据以及其他家族 AD 资源的集成和注释（使用 ENCODE 和表观基因组路线图项目）将用于遗传连锁和 IBD 分析（项目 3），以识别高度确定的多重家族中的 AD 易感性或保护性等位基因。病例对照设计（项目 1 和 2）和家族设计（项目 3）相辅相成，以最大限度地发现 AD 变异。为了促进 AD 转化研究和发现，我们将与其他研究人员合作进行进一步的复制和功能研究，创建具有集成基因组和表型数据的公共资源，并通过公共领域提供可用的计算算法。识别导致 AD 风险的基因变异并提供预防措施可能最终会带来新的治疗和预防策略。