The interaction effects of genetic variants, age, diet, sex and mitochondrial copy number on Alzheimer's disease, aging-phenotypes and longevity

随着人口平均年龄的增加，了解长寿的生物学和老年病 变得越来越重要。线粒体在阿尔茨海默病(AD)和病理性衰老中的关键作用 在跨物种的研究中得到证实，并使用基因工程进行了机械验证 模特们。线粒体DNA拷贝数(MtDNAcn)随年龄和饮食而变化，在不同组织中，以及 跨物种。更高的mtDNAcn与衰老时更好的健康结果相关，并与 长寿，而mtDNAcn减少与包括AD在内的衰老障碍有关。然而，我们并没有 了解遗传变异、mtDNAcn、饮食、性别、衰老和AD之间的机械相互作用。这里 我们建议确定将mtDNAcn与AD和衰老相关的基因-环境相互作用(GxE)联系起来 已在重组近交系BXD和转基因AD-BXD小鼠品系中收集的表型包括 长寿、记忆力、学习、运动和神经解剖表型。在目标1和目标2中，我们将测试GxE和 确定三个“外周”(皮肤、血液、肌肉)和三个“中央”(肝脏、 肾脏、海马体)组织。我们将使用之前从45个BXD菌株中收集的组织 24个月龄，分别饲喂标准饲料或高脂饮食，并量化mtDNAcn。在目标3中，我们 将利用组织鉴定mtDNAcn、年龄、性别和家族性AD转基因(5XFAD)之间的关系 已经从AD-BXD收集到了。作为目标2和目标3的一部分，我们将重新产生上述菌株的子集 并对线粒体功能和活性氧产生进行分析，确定其联系 线粒体DNAcn和线粒体跨组织功能之间的关系。在目标4中，我们将集成生成的数据 与年龄相关的认知和其他行为和中枢神经系统变化的广泛行为数据 来自BXD和AD-BXD。这将使我们能够确定AD和AD的基因座、候选基因和机制 并系统地测试与年龄、性别、饮食和线粒体相关变化的相关性 DNAcn或Function。最后，我们将集成之前为BXD和其他公司生成的组学数据 基因组(例如，RNA-seq、meth-seq、代谢组和蛋白质组)与来自大型人类AD和 MtDNAcn GWASs和其他现有组学数据。所有结果将使用强大的互联网公开共享 服务-鼠标表现组数据库、基因网络等。数据和工作流程将是公平合规的。钥匙 可交付成果更加量化、无偏见、全球化和可复制的遗传、分子和 与线粒体共同作用以调节认知丧失、阿尔茨海默病和长寿的环境过程。我们还将 提供包含实际高水平遗传多样性的因果分子和机制模型- 600万个DNA变种。这项工作使得对与年龄相关的功能衰退的深入、公正的分析成为可能 这就转化为人类人口。Success将提供一个测试新干预措施的平台 这种在基因组和环境上可复制的种群被称为“实验精准医学”。

As the average age of the population increases, understanding the biology of longevity and diseases of aging is increasingly important. The key role of mitochondria in Alzheimer’s disease (AD) and pathogenic aging has been established in studies across species and mechanistically validated using genetically engineered models. Mitochondrial DNA copy number (mtDNAcn) changes with age and diet, in various tissues, and across species. Higher mtDNAcn is associated with better health outcomes in aging and with increased longevity, while decreased mtDNAcn is linked to disorders of aging including AD. However, we do not understand the mechanistic interaction between genetic variants, mtDNAcn, diet, sex, aging and AD. Here we propose to identify gene-by-environment interactions (GxE) that link mtDNAcn to AD- and aging- relevant phenotypes already collected in the recombinant inbred BXD and transgenic AD-BXD mouse lines, including longevity, memory, learning, motor, and neuroanatomical phenotypes. In Aims 1 and 2, we will test GxE, and identify loci underlying these interactions in three “peripheral” (skin, blood, muscle) and three “central” (liver, kidney, hippocampus) tissues. We will use previously gathered tissue from 45 BXD strains between 6- and 24-months old that had been fed either standard chow or high-fat diet, and quantify mtDNAcn. In Aim 3, we will identify relationships between mtDNAcn, age, sex and the familial AD transgenes (5XFAD), using tissue already collected from the AD-BXD. As part of Aims 2 and 3, we will re-produce a subset of the above strains and carry out analysis of mitochondrial function and reactive oxygen species generation to determine the link between mtDNAcn and mitochondrial function across tissues. In Aim 4, we will integrate our generated data with extensive behavioral data on age-related cognitive and other behavioral and CNS changes generated from BXD and AD-BXD. This will allow us to define loci, candidate genes, and mechanisms of AD and longevity and to systematically test for associations with age, sex, diet, and linked changes in mitochondrial DNAcn or function. Finally, we will integrate previously generated -omics data that we have for BXD and other genomes (e.g., RNA-seq, meth-seq, metabolomes and proteomes) with data from large human AD and mtDNAcn GWASs, and other existing -omics data. All results will be shared openly using robust internet services—Mouse Phenome Database, GeneNetwork, etc. Data and workflows will be FAIR-compliant. Key deliverables are far more quantitative, unbiased, global, and replicable data on genetic, molecular, and environmental processes that act with mitochondria to mediate cognitive loss, AD and longevity. We will also deliver causal molecular and mechanistic models that incorporate realistically high levels of genetic diversity— 6 million DNA variants. This work empowers in-depth, unbiased analyses of age-related functional decline that translates to human populations. Success will provide a platform in which to test novel interventions in this genomically- and environmentally- replicable population — so called “experimental precision medicine”.