Imaging Genetics of Brain Structure and Cognitive Aging in Murine Models of Alzheimer's Disease

阿尔茨海默病小鼠模型中大脑结构和认知衰老的影像遗传学

基本信息

批准号：
10549753
负责人：
George ALLAN JOHNSON
金额：
$ 123.13万
依托单位：
UNIVERSITY OF TENNESSEE HEALTH SCI CTR
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-02-01 至 2026-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10549753
关键词：
Age Age Months Age-associated memory impairment Aging Alzheimer&apos s Disease Alzheimer&apos s disease model Behavioral Brain Candidate Disease Gene Cells Cognition Cognitive Cognitive aging Collaborations Communities Complex DNA Data Data Set Databases Error Sources Etiology Exposure to FAIR principles Family Female Functional Magnetic Resonance Imaging Functional disorder Future Genes Genetic Genetic Variation Genome Genomics Genotype-Tissue Expression Project Grain Heritability Hippocampus Human Hybrids Image Immunohistochemistry Impaired cognition Inflammation Informatics Internet Intervention Knowledge Portal Late Onset Alzheimer Disease Left Light Link Magnetic Resonance Imaging Maps Measures Memory Memory Loss Methods Microscopy Mitochondria Modality Modeling Molecular Mus Neocortex Neuroanatomy Neurocognitive Deficit Noise Pathology Pharmacotherapy Phenotype Population Pre-Clinical Model Preclinical Testing Predisposition Prevention Process Proteome Protocols documentation Research Resolution Rest Services Severities Severity of illness Stress Structure Synapses System Techniques Testing Time Transgenes Transgenic Mice Transgenic Organisms Translating Variant Work age related aging brain biobank brain magnetic resonance imaging cell type cohort conditioned fear connectome data integration design empowerment endophenotype familial Alzheimer disease fear memory functional decline gene network genetic testing genetic variant genome wide association study high throughput analysis imaging genetics imaging program improved insight male memory process mouse model neocortical neurogenetics neuron loss normal aging phenome protein aggregation resilience sex success therapeutic target tool transcriptome sequencing web services whole genome

项目摘要

Age-related cognitive decline (ARCD), Alzheimer disease (AD), and late-onset AD-related pathologies are linked to changes in brain structure, cell populations, synapse densities and connections, inflammation, protein aggregation and mitochondrial stress. However, we do not understand the complex causal networks and mechanisms of ARCD and AD. In this neurogenetics imaging program we quantify the impact of human familial AD (FAD) gene variants on brain structure and function using a highly diverse cohort of aging mouse hybrids that combine human genes variants with the BXD family. In Aims 1 and 2 we generate high resolution whole brain MRI DTI data and connectomes for each of 40 sex-matched sets of transgenic and aging control hybrids at ~6 and ~14 months using state-of-the art analysis workflows. We generate matched behavioral data, as well as light-sheet immunohistochemistry for entire brains taken from subsets of cases with the most outstanding phenotypes—lines that are highly susceptible to cognitive loss and those that are most resilient. Light-sheet, MRI-DTI and fMRI connectomes is merged with MI-DTI in Aim 3. All work exploits systems genetics and mapping methods we have developed and embedded in the GeneNetwork web service. A crucial facet of Aim 3 is integrating extensive behavioral data on age-related cognitive and other behavioral and CNS changes generated from AD-BXD and many other models. This allows us to define loci, candidate genes, and mechanisms modulating ARCD and AD, and to systematically test for associations with age, sex, and linked changes in structure, connectivity, and cell types. Finally, we integrate omics data we have for BXD and other genomes (e.g., hippocampal RNA-seq and proteomes) with comprehensive human AD GWAS, imaging, and omics data. All results are shared openly using robust internet services—GeneWeaver, CIVM server, NIF, Mouse Phenome Database, and the AMP-AD Knowledge Portal. Data and workflows will be FAIR-compliant. Key deliverables are (1) far more quantitative, unbiased, global, and replicable data on genetic, molecular, cellular, and system-wide processes linked to cognitive loss and AD. We also deliver causal molecular and mechanistic models of that incorporate realistically high levels of genetic diversity—6 million DNA variants. This work empowers in-depth unbiased analyses of age-related functional decline in ARCD and AD that translate to human populations. Success will enable faster and more robust preclinical testing of interventions and drug treatments for ARCD and AD.

与年龄相关的认知下降（ARCD），阿尔茨海默氏病（AD）和迟发性广告相关的病理要改变大脑结构，细胞种群，突触密度和连接，炎症，蛋白质聚集和线粒体应力。但是，我们不了解复杂的因果网络和 ARCD和AD的机制。在这个神经遗传学成像计划中，我们量化了人类家庭的影响 AD（FAD）基因变体在大脑结构和功能上使用高度多样的老化小鼠杂种将人类基因变体与BXD家族相结合。在目标1和2中，我们产生高分辨率的整体 40种性别匹配的转基因和衰老控制杂种的大脑MRI DTI数据和连接组使用最先进的分析工作流程〜6和〜14个月。我们也生成匹配的行为数据作为所有大脑的灯页免疫组织化学，从最杰出的案例中表型 - 极易受到认知损失的线和最有弹性的线。灯书， MRI-DTI和FMRI连接组与MI-DTI合并在AIM 3中。所有工作都利用了系统遗传学和映射我们已经开发并嵌入了GenEnetwork Web服务中的方法。 AIM 3的关键方面是在与年龄相关的认知和其他行为和中枢神经系统变化上整合广泛的行为数据来自AD-BXD和许多其他模型。这使我们能够定义局部，候选基因和机制调节ARCD和AD，并系统地测试与年龄，性别和链接变化的关联结构，连通性和细胞类型。最后，我们集成了BXD和其他基因组的OMICS数据（例如，海马RNA-seq和蛋白质组织）具有全面的人类AD GWA，成像和OMICS数据。所有结果均使用强大的Internet服务公开共享 - Geneweaver，Civm Server，NIF，鼠标现象数据库和AMP-AD知识门户。数据和工作流程将是合理的。关键可交付成果（1）关于遗传，分子，细胞和系统范围的更定量，公正，全局和可复制数据与认知损失和AD相关的过程。我们还提供了因果分子和机械模型结合现实水平的遗传多样性 - 600万个DNA变体。这项工作能够深入影响对ARCD和AD的年龄相关功能下降的无偏分析，这些分析转化为人类人群。成功将使ARCD的干预措施和药物治疗更快，更强大的临床前测试和广告。