Project 2: Identify and enhance LOAD-related signatures in outbred and genetically-engineered marmosets

项目 2：识别并增强近交系和基因工程狨猴中与 LOAD 相关的特征

• 批准号: 10494776
• 负责人: Gregory W Carter
• 金额: $ 39.66万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10494776
• 关键词: Aging; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease risk; Animal Model; Autopsy; Behavioral; Bioinformatics; Biological; Biological Markers; Biological Models; Callithrix; Cell model; Clinical; Clinical Research; Cognitive; Cohort Studies; Communities; Complement; Data; Data Aggregation; Dementia; Dimensions; Disease; Disease Outcome; Disease Progression; Disease model; Drug Targeting; Engineering; Evaluation; Event; Foundations; Future; Generations; Genetic; Genetic Engineering; Genetic Variation; Genome; Genomics; Genotype; Goals; Human; Human Genetics; Image; Impaired cognition; Knowledge Portal; Laboratories; Late Onset Alzheimer Disease; Link; Longevity; Methods; Modeling; Molecular; Outcome; Outcome Study; Pathology; Pathway interactions; Phenotype; Population; Primates; Process; Proteins; Research; Rodent Model; Serum; Statistical Models; Structure; Study models; Testing; Tissues; Validation; Variant; Work; analytical method; clinically relevant; data integration; data modeling; data-driven model; efficacy testing; functional genomics; genetic analysis; genetic association; genetic variant; genome-wide; genomic data; human data; human study; in vivo imaging; molecular marker; molecular scale; mouse model; multi-scale modeling; multimodality; multiple data types; multiple omics; neuropathology; nonhuman primate; phenotypic data; pre-clinical research; preclinical efficacy; preclinical study; presenilin-1; risk variant; targeted treatment; whole genome

PROJECT SUMMARY PROJECT 2 Determining the early molecular and cellular events in the origins and progression of late-onset Alzheimer’s disease (LOAD) will require an analytical approach that integrates genetic, molecular, in vivo imaging, and behavioral data. Many clinical studies with this goal are currently underway, which increasingly complement genetic data with genome-scale molecular data from biofluids and post-mortem tissues, in vivo imaging data of structure and neuropathology, and detailed cognitive data collected over disease progression. Transforming the outcomes of these studies into targeted therapeutic strategies requires translatable animal model systems, both for understanding the biological underpinnings of disease outcomes and preclinical efficacy testing of candidate treatments. The marmoset is potentially the most promising non-human primate model of LOAD, providing an analytical bridge between human studies and high-capacity cell and rodent model systems. Laboratory marmosets with outbred genetics can potentially provide a range of genotypic and phenotypic variation in relevant clinical outcomes. This standing variation can be augmented by genetically engineering variants at specific risk loci, as we have demonstrated with PSEN1. Phenotypic changes in multi-omic, imaging, cognitive, and cellular outcomes can be rigorously studied in an aging primate with an intermediate lifespan. However, to date there have not been systematic studies of aging marmosets at scale. In this project, we will initiate these systematic studies through integrated analyses of genetics and LOAD-related phenotypes in aging marmosets. We will then rigorously test correspondences between human and marmosets at all biological levels, from genetic to multi-scale models. Our goal is to develop the marmoset into a mature platform for preclinical research, which we will pursue with the following three aims: (1) assess natural genetic variation in outbred marmosets as a model Alzheimer’s disease risk in humans; (2) integrate genetic, genomic, and phenotype data to establish robust statistical models of disease in marmosets; and (3) evaluate disease relevance of models by aligning molecular markers of Alzheimer’s disease in marmosets with human study cohorts. Through this work, we expect to lay the foundations for LOAD-related functional genomics in marmosets, provide an expanded view of the impact of natural genetic variation in laboratory marmosets, prioritize genetic variants to engineer in marmosets, and create the first models of LOAD-related marmoset pathology at multiple scales.

项目概要 项目 2 确定迟发性阿尔茨海默氏症起源和进展的早期分子和细胞事件 疾病（LOAD）需要一种整合遗传、分子、体内成像和 目前正在进行许多针对这一目标的临床研究，这些研究日益补充。 遗传数据与来自生物体液和死后组织的基因组规模分子数据、体内成像数据 结构和神经病理学，以及在疾病进展过程中收集的详细认知数据。 将这些研究结果转化为靶向治疗策略需要可转化的动物模型系统， 用于了解疾病结果的生物学基础和候选药物的临床前功效测试 治疗。 狨猴可能是最有前途的 LOAD 非人类灵长类动物模型，提供了一种分析方法 人类研究与高容量细胞和啮齿动物模型系统之间的桥梁。 近交遗传学有可能在相关临床中提供一系列基因型和表型变异 这种长期变异可以通过特定风险位点的基因工程变异来增强，例如 我们已经用 PSEN1 证明了多组学、成像、认知和细胞的表型变化。 然而，迄今为止，可以对寿命中等的衰老灵长类动物进行严格研究。 尚未对衰老狨猴进行大规模的系统研究。 在这个项目中，我们将通过对遗传学和LOAD相关的综合分析来启动这些系统研究 然后，我们将严格测试人类和狨猴之间的对应关系。 从遗传到多尺度模型的所有生物学层面，我们的目标是将狨猴发展成成熟的模型。 临床前研究平台，我们将致力于以下三个目标：（1）评估自然遗传 近交狨猴的变异作为人类阿尔茨海默病风险的模型；（2）遗传整合，基因组， (3)评估疾病 通过将狨猴中阿尔茨海默病的分子标记与人类研究相结合来确定模型的相关性 通过这项工作，我们期望为 LOAD 相关的功能基因组学奠定基础。 狨猴，提供了实验室狨猴自然遗传变异影响的扩展视图， 优先考虑狨猴中的遗传变异，并创建第一个 LOAD 相关狨猴模型 多尺度的病理学。