Genetic Contributors to White Matter Microstructure in Aging and Alzheimers Disease

衰老和阿尔茨海默病中白质微结构的遗传因素

• 批准号: 10459610
• 负责人: Derek B Archer
• 金额: $ 12.02万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10459610
• 关键词: Academic Medical Centers; Accounting; Aging; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease risk; Architecture; Area; Atrophic; Automobile Driving; Award; Axonal Transport; Baltimore; Big Data Methods; Biological; Brain; Candidate Disease Gene; Career Mobility; Clinical; Cognitive; Complex; Data; Data Analyses; Data Set; Diffusion Magnetic Resonance Imaging; Ensure; Environment; Evaluation; Extracellular Space; Foundations; Functional disorder; Funding; Future; Gene Expression; Genes; Genetic; Genetic Diseases; Genetic Techniques; Genetic study; Genomics; Goals; Image; Impaired cognition; Intracellular Space; Laboratories; Lead; Longevity; Longitudinal Studies; Longitudinal cohort; Measurement; Medial; Mediating; Memory; Mentors; Minority; Modeling; Molecular; Nerve Degeneration; Neurodegenerative Disorders; Oligodendroglia; Participant; Pathway Analysis; Pathway interactions; Positioning Attribute; Process; Registries; Research; Resolution; Resources; Role; Senile Plaques; Signal Transduction; Techniques; Temporal Lobe; Testing; Tissues; Training; Validation; Variant; Water; Wisconsin; Work; base; biobank; career; career development; catalyst; cohort; data harmonization; genetic analysis; genetic architecture; genetic variant; genome wide association study; genome-wide; genome-wide analysis; gray matter; hippocampal atrophy; imaging genetics; in vivo; large scale data; multidisciplinary; myelination; neuroimaging; neuroinflammation; new therapeutic target; novel; polygenic risk score; pre-clinical; professor; religious order study; research and development; research study; risk variant; skills; tau aggregation; tractography; trait; white matter; white matter damage

PROJECT SUMMARY While reductions in medial temporal lobe (MTL) white matter tract microstructure have been suggested to have a central role in longitudinal cognitive decline in aging and Alzheimer’s disease (AD), it is unknown what genetic factors drive these reductions. The objective of this proposal is to use MTL white matter tract templates in conjunction with genome-wide analyses to identify the genetic drivers of white matter tract microstructure. This proposal will leverage several aging datasets, including the Alzheimer’s Disease Neuroimaging Initiative (n=525), Baltimore Longitudinal Study of Aging (n=295), Religious Orders Study/Memory and Aging Project/Minority Aging Research Study (n=414), Vanderbilt Memory & Aging Project (n=319), Wisconsin Alzheimer’s Disease Research Center (n=488), and Wisconsin Registry for Alzheimer’s Prevention (n=468) to conduct all analyses, totaling in 2,509 participants. Moreover, validation of all results will be conducted using data from a well-established lifespan study (UK Biobank (n=14,701)) and data from the AD Genetics Consortium. The central hypothesis is that MTL white matter tract microstructure is driven by genes and pathways related to myelination, axonal transport, and neuroinflammation in aging and AD. Based on this hypothesis, the primary aims of this proposal will take a multi-level approach to understand which genes and pathways lead to MTL white matter microstructure by using: (1) a candidate gene approach to determine with AD-risk genes are associated with MTL white matter microstructure, (2) a genome-wide approach to identify novel variants which contribute to MTL white matter microstructure and quantify genetic overlap with other traits, and (3) a genome-wide approach to identify how gene expression is associated with MTL white matter tract microstructure and localize signals to relevant biologic pathways. The complementary training plan will equip me with the skills necessary to transition to an independent career focused on imaging genetics by emphasizing the following training objectives: (a) expand expertise in computational genetics, (b) acquire a practical understanding of the pathophysiology and clinical manifestation of AD, and (c) enhance my skillset in data harmonization and big data analytical techniques. The mentoring team is made up of experts in each of these areas, and their training will be augmented through formal coursework, interdisciplinary training at the Vanderbilt Memory & Alzheimer’s Center, and cutting-edge computational and genomic resources available at the Vanderbilt University Medical Center. Together, these practical and intellectual resources provide the ideal training environment, and my primary mentor, Dr. Timothy Hohman, has a well-funded laboratory which will provide all the necessary resources for career transition. These resources will allow me to dedicate 100% protected effort as an Assistant Professor to focus on research and career development. This will ensure that I can competitively compete for independent funding (R01) over the course of the proposed award period.

项目总结 而内侧颞叶(MTL)白质束微结构的减少被认为是 在衰老和阿尔茨海默病(AD)中纵向认知能力下降的核心作用，尚不清楚是什么 遗传因素推动了这些减少。该提案的目标是使用MTL白质束模板 结合全基因组分析，以确定白质束微结构的遗传驱动因素。 这项提议将利用几个老化数据集，包括阿尔茨海默病神经成像倡议 (n=525)，巴尔的摩老龄化纵向研究(n=295)，宗教秩序研究/记忆与老龄化 项目/少数民族老龄化研究(n=414)，范德比尔特记忆和老龄化项目(n=319)，威斯康星州 阿尔茨海默病研究中心(n=488)和威斯康星州阿尔茨海默氏症预防登记处(n=468) 进行所有分析，总计2,509名参与者。此外，将使用以下工具对所有结果进行验证 来自一项公认的寿命研究(英国生物库(n=14,701))的数据和来自AD遗传学的数据 财团。中心假说是MTL白质束微结构是由基因和 衰老和阿尔茨海默病中与髓鞘形成、轴突运输和神经炎症相关的通路。在此基础上 假设，这项建议的主要目标将采取多层次的方法来理解哪些基因和 导致MTL白质微结构的途径使用：(1)候选基因方法确定与 AD风险基因与MTL白质微结构有关，(2)全基因组方法识别 有助于MTL白质微结构并量化与其他基因重叠的新变体 特征，以及(3)全基因组方法，以确定基因表达如何与MTL白质相关 追踪微结构并将信号定位到相关的生物途径。补充性培训计划将 让我具备必要的技能，通过以下方式过渡到专注于成像遗传学的独立职业 强调以下培训目标：(A)扩大计算遗传学方面的专门知识；(B)获得 对阿尔茨海默病的病理生理和临床表现有实际的了解，以及(C)提高我在 数据协调和大数据分析技术。指导团队由以下各方面的专家组成 这些领域，他们的培训将通过正式课程作业、在 Vanderbilt Memory&阿尔茨海默氏症中心，以及尖端计算和基因组资源，请访问 范德比尔特大学医学中心。这些实用的和智力的资源共同提供了理想的 培训环境，我的主要导师Timothy Hohman博士有一个资金充足的实验室，它将 为职业过渡提供所有必要的资源。这些资源将让我100%地致力于 受保护的努力，作为助理教授，专注于研究和职业发展。这将确保我 可以在建议的授权期内竞争性地竞争独立资金(R01)。