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2 确定晚发性阿尔茨海默病起源和进展中的早期分子和细胞事件 疾病（LOAD）将需要一种分析方法，该方法整合了遗传、分子、体内成像和 行为数据目前正在进行许多以此为目标的临床研究， 基因数据，包括来自生物流体和死后组织的基因组规模的分子数据， 结构和神经病理学，以及随着疾病进展收集的详细认知数据。转变 这些研究的结果，以有针对性的治疗策略，需要翻译的动物模型系统， 了解疾病结局的生物学基础和候选药物的临床前疗效测试 治疗。 绒猴可能是最有前途的非人灵长类动物模型的负载，提供了一个分析 人类研究与高容量细胞和啮齿动物模型系统之间的桥梁。实验室绒猴， 远交遗传学可以潜在地在相关临床表现中提供一系列基因型和表型变异。 结果。这种持续的变异可以通过在特定风险位点的基因工程变异来增强， 我们已经用PSEN 1演示过了。多组学、成像、认知和细胞学的表型变化 结果可以在寿命中等的老龄灵长类动物中进行严格研究。然而，到目前为止， 还没有对大规模的衰老绒猴进行系统的研究。 在这个项目中，我们将通过遗传学和负荷相关的综合分析来启动这些系统的研究。 衰老绒猴的表型。然后我们将严格测试人类和绒猴之间的对应关系 在所有生物水平上，从遗传到多尺度模型。我们的目标是把绒猴培育成一个成熟的 平台的临床前研究，我们将追求以下三个目标：（1）评估自然遗传 远交绒猴的变异作为人类阿尔茨海默病风险的模型;（2）整合遗传，基因组， 和表型数据，以建立稳健的疾病统计模型;（3）评估疾病 通过将绒猴中阿尔茨海默病的分子标记与人类研究进行比对， 同伙通过这项工作，我们希望为LOAD相关的功能基因组学奠定基础， 绒猴，提供了实验室绒猴中自然遗传变异的影响的扩展视图， 优先考虑在绒猴中进行遗传变异工程，并创建与LOAD相关的绒猴的第一个模型 多尺度的病理学。