AD Gene Discovery: Exome Chip, New Endophenotypes & Functional Studies in CHARGE

AD 基因发现：外显子组芯片、新内表型

• 批准号: 8579953
• 负责人: Sudha Seshadri
• 金额: $ 61.84万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-02-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8579953
• 关键词: Age; Aging; Alzheimer' s Disease; Alzheimer' s disease risk; Amyloid; Anisotropy; Applications Grants; Atherosclerosis; Autopsy; Bioinformatics; Biological; Biological Aging; Biological Markers; Biology; Body mass index; Brain; Cardiovascular system; Cholesterol; Clinical; Code; Cognition; Cognitive; Cohort Studies; Collaborations; Communities; Computer Simulation; Coronary artery; Data; Databases; Dementia; Development; Disease; Drosophila genus; EPHA1 gene; Environment; Epidemiology; Exposure to; Framingham Heart Study; Frequencies; Funding; Generations; Genes; Genetic; Genomics; Genotype; Grant; Health; Healthcare; Heart; Heritability; Hippocampus (Brain); Human; Image; International; Intervention; Laboratories; Late Onset Alzheimer Disease; Lead; Magnetic Resonance Imaging; Measures; Memory; Messenger RNA; Meta-Analysis; Methylation; MicroRNAs; Modeling; Neurology; Neurons; Pathological Staging; Pathway interactions; Pattern; Persons; Phenotype; Plasma; Positioning Attribute; Predisposition; Prevention; Public Health; Publications; Research; Research Personnel; Resources; Risk; Risk Factors; Sampling; Serum; Staging; Testing; Translating; Variant; aged; aging brain; aging gene; brain volume; cerebral atrophy; cognitive function; cohort; cost; endophenotype; epidemiology study; exome; exome sequencing; gene discovery; gene environment interaction; gene interaction; genetic variant; genome wide association study; genome-wide; interest; middle age; novel; pre-clinical; prospective; public health relevance; sulfated glycoprotein 2; tau Proteins; working group; young adult

DESCRIPTION (provided by applicant): This competitive renewal grant application seeks to continue a collaboration that used genome-wide association data in large, prospective epidemiological cohorts, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), with >2-6 decades of risk factor, dementia, AD, MRI and cognitive endophenotype data in >30,000 persons to identify new genes/loci underlying the risk of Alzheimer's disease (AD). It produced >50 publications, helped identify 9 novel loci for AD (BIN1 & EPHA1 first reached genome-wide significance in a CHARGE-lead publication), and 8 for AD endophenotypes. CHARGE helped found the International Genomics of Alzheimer Project (IGAP) and established collaborations with >25 cohorts/ consortia such as the Enhancing Neuro Imaging through Meta-Analysis (ENIGMA) consortium. However, genes identified to date collectively explain <35% of the observed AD heritability of 60-80%. The missing heritability could be partly explained by multiple low-frequency or rare genetic variants that can be detected cost-effectively via analysis of exome chip (EC) data now available in the original CHARGE and in 4 additional cohorts (the CHARGE-Plus sample: n=45,910, ~4058 with AD). In this application we propose the following: Aim 1: To use EC data to search for rare genetic variants related to incident clinical AD, and to AD endophenotypes. We have shown that GWAS of AD endophenotypes, e.g. hippocampal & total brain volumes, verbal memory can identify novel loci implicated in brain aging, and biological pathways underlying AD. We propose to use EC data to search for rare variants related to these established AD endophenotypes. Aim 2: To understand preclinical AD, the stage of early pathological changes 1-2 decades before clinical AD, during which AD is likely most amenable to intervention, we propose GWAS and EC analyses of emerging novel, sensitive MRI endophenotypes, cognitive and circulating biomarker (plasma ¿-amyloid and clusterin) data in the entire CHARGE-Plus and in younger cohorts aged 30-65 years. Aim 3: To better understand the biology, epidemiological and public health significance of the identified genes we will study gene-gene interactions between known and novel loci, and gene-environment interactions both targeted (interaction of loci from Aims 1&2 with midlife cholesterol and BMI), and genome-wide. The CHARGE cohorts, with premorbid data on mid-life exposure to a wide-range of environmental covariates, are uniquely positioned to study such interactions and permit analyses of other covariates when indicated. Aim 4: Finally, we will explore the biology of the identified variants using bio-informatics annotation databases created in CHARGE, available systemic and brain mRNA, miRNA, methylation data (n~8000 & 750, respectively), hippocampal neuronal expression in autopsy brains and in Drosophila tau & ¿-amyloid models. We seek modest analytic resources to leverage existing phenotypic and genotypic data worth millions, to discover new AD genes and potentially novel prevention and treatment approaches for AD.

DESCRIPTION (provided by application): This competitive renewal grant application seeks to continue a collaboration that used genome-wide association data in large, prospective epidemiological cohorts, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), with >2-6 decades of risk factor, dementia, AD, MRI and cognitive endophenotype data in >30,000 people to identify new genes/loci underlying the risk of阿尔茨海默氏病（AD）。它产生了> 50个出版物，帮助确定了9个新颖的AD环境（BIN1和EPHA1首次在电荷铅出版物中达到了全基因组的重要性），而AD内表型的8个。 Charge帮助建立了阿尔茨海默氏症项目（IGAP）的国际基因组学，并与> 25个同类/财团（例如通过荟萃分析（Enigma）联盟增强神经成像，建立了合作。但是，迄今为止确定的基因共同解释了观察到的60-80％的AD遗传力的35％。缺失的遗传力可以通过多种低频或罕见的遗传变异来解释，这些变异可以通过分析现已在原始电荷中可用的外显质芯片（EC）数据进行成本效率地检测到，并在4个其他同类群体中（电荷加上样本：n = 45,910，〜4058 the AD）。在此应用程序中，我们提出以下内容：目标1：使用EC数据搜索与事件临床AD相关的稀有遗传变异和AD内表型。我们已经表明，AD内表型的GWA，例如海马和总脑体积，言语记忆可以鉴定植入大脑衰老的新基因座以及AD下的生物学途径。我们建议使用EC数据来搜索与这些已建立的AD内型型相关的稀有变体。目的2：为了了解临床前AD，临床AD前1-2年的早期病理变化的阶段，在此期间，AD可能最适合干预，我们建议对新兴的，敏感的MRI内表型的GWAS和EC分析，认知和循环生物标志物（等化性生物标志）（血浆amyloid和Cluse）30年的cohlus-30-Plus-Plus-inter-Plus-inter-Plus-inter-col-Plus-Plus-inter-Plus-Plus-inter-Plus-目的3：为了更好地了解已鉴定基因的生物学，流行病学和公共健康意义，我们将研究已知基因座和新颖基因座之间的基因 - 基因相互作用，以及基因环境相互作用均针对性（AIMS 1和2与中年胆固醇和BMI的AIM 2与基因座的相互作用），以及全基因组。电荷队列具有有关中期暴露于广泛环境协变量的中期的细胞数据，在指示时可以独特地研究此类相互作用并允许对其他协变量进行分析。 AIM 4：最后，我们将使用由负责，可用的系统和脑mRNA，miRNA，甲基化数据（N〜8000＆750），尸检大脑中的海马神经元表达创建的生物信息学注释数据库探索已鉴定的变体的生物学。我们寻求适度的分析资源来利用价值数百万人的现有表型和基因型数据，以发现新的AD基因以及潜在的新型AD预防和治疗方法。