UC Irvine MODEL-AD

摘要 加州大学欧文分校模型-AD U54中心的目标是开发新的小鼠模型- 发病阿尔茨海默病(LOAD)，以深入表型这些并提供所有数据和小鼠品系 为了使研究人员能够选择最佳的小鼠模型和时间点进行治疗和干预测试， 以及对有关载荷机制的假设进行测试。在过去的五年里，我们创造了 和带有我们基础遗传平台的一个组件的深度表型小鼠，在该平台中，App的A？区域 基因从啮齿类动物转变为人类序列，我们最近引入了第二个 成分，一个人源化的MAPT(TAU)基因座，通过基因替换产生。我们还使用了CRISPR和 基因组替换以建模和验证GWA9个确定的负载风险基因座并确定了小鼠的特征 在野生型和5xFAD背景下，确定它们对斑块生成的影响 以及对大脑造成的损害作为对病理的反应。在本系列中，我们将使用这些结果 分析以确定最有可能发生表型复制负载的负载风险变量组合并引入它们 在两个互补的hab-ki、hTAU、hAPOE4平台线上，旨在模拟具有 是最近定义的。为了确保可翻译性，我们扩展了对生物标志物和比对的关注 具有人类的表型。为此，我们建立了一个新的核心--神经成像和神经血管 核心(NIVC)，它将提供目前在人类AD受试者中使用的脑成像模式，以匹配 人类疾病进展过程中小鼠的表型。我们还扩展了我们的流体生物标志物分析 努力纳入脑脊液，以及血浆脂质组学和代谢组学，以与人类AD血浆进行比较 签名。同样，我们的生物信息学和数据管理工作已经扩展到包括单细胞 和核rna-seq和atac-seq，以及空间转录组学，以使来自我们的数据比对 具有人类AD签名的模型，但也理解疾病进展的机制 我们的老鼠。我们正在利用一种全面的方法来评估我们的小鼠的整个寿命，其中包括 行为/认知评估，电生理分析，超分辨率突触成像， 神经成像，散装和单细胞rna-seq，单细胞水平空间转录分析，无偏倚 蛋白质组学，以及微生物组和代谢组研究。UCI模型-AD中心将利用 NIA资助的阿尔茨海默病研究中心与AMP-AD和其他人类 AD数据集，便于与人类条件进行比较，以确定最佳的老鼠模型进行评估 再远一点。所有数据和模型都将通过杰克逊实验室不受限制地提供，数据将 可通过modadexplorer.org网站浏览，原始数据可通过AD免费下载 知识门户。

ABSTRACT The goal of the University of California, Irvine MODEL-AD U54 Center is to develop novel mouse models of late- onset Alzheimer’s disease (LOAD), to deeply phenotype these and to make all data and mouse strains available to enable researchers to select the optimal mouse model and timepoints for therapeutic and intervention testing, as well as testing of hypotheses concerning mechanisms of LOAD. During the past five years, we have generated and deeply phenotyped mice with one component of our base genetic platform in which the Aß region of the App gene was converted from the rodent to the human sequence, and we have recently introduced the second component, a humanized MAPT (TAU) locus produced via gene-replacement. We have also used CRISPR and genome replacement to model and validate nine GWAS identified LOAD risk loci and have characterized mice with each of these both on a wild-type and 5xFAD background to determine their effects on plaque generation and damage exerted on the brain in response to pathology. In this continuation, we will use the results of these analyses to identify the combinations of LOAD risk variants most likely to phenocopy LOAD and introduce them on two complementary hAb-KI, hTAU, hAPOE4 platform lines, designed to mimic sub-types of AD that have been recently defined. To ensure translationability, we have an expanded focus on biomarkers and alignment with human phenotypes. To that end we have established a new Core – the Neuroimaging and neurovascular core (NIVC), which will provide brain imaging modalities currently employed in human AD subjects to align phenotypes in our mice with human disease progression. We have also expanded our fluid biomarker analysis efforts to include CSF, as well as plasma lipidomics and metabolomics to be compared to human AD plasma signatures. Similarly, our bioinformatics and data management efforts have been expanded to include single cell and nucleus RNA-seq and ATAC-seq, as well as spatial transcriptomics to enable alignment of data from our models with human AD signatures, but also to understand the mechanisms underlying disease progression in our mice. We are utilizing a comprehensive approach to evaluate our mice across their lifespans, which includes behavioral/cognitive assessment, electrophysiological analysis, super-resolution synaptic imaging, neuroimaging, bulk and single-cell RNA-seq, single cell level spatial transcriptomic analysis, unbiased proteomics, and microbiome and metabolome investigations. The UCI MODEL-AD Center will leverage the resources of our NIA-funded Alzheimer’s Disease Research Center combined with AMP-AD and other human AD datasets to facilitate comparisons to the human condition to identify the best mouse models to evaluate further. All data and models will be made available without restrictions, via The Jackson Labs, and data will be explorable via the modeladexplorer.org website, and raw data freely available for download via the AD Knowledge Portal.