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
基本信息
- 批准号:10494776
- 负责人:
- 金额:$ 39.66万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AgingAlzheimer&aposs DiseaseAlzheimer&aposs disease modelAlzheimer&aposs disease riskAnimal ModelAutopsyBehavioralBioinformaticsBiologicalBiological MarkersBiological ModelsCallithrixCell modelClinicalClinical ResearchCognitiveCohort StudiesCommunitiesComplementDataData AggregationDementiaDimensionsDiseaseDisease OutcomeDisease ProgressionDisease modelDrug TargetingEngineeringEvaluationEventFoundationsFutureGenerationsGeneticGenetic EngineeringGenetic VariationGenomeGenomicsGenotypeGoalsHumanHuman GeneticsImageImpaired cognitionKnowledge PortalLaboratoriesLate Onset Alzheimer DiseaseLinkLongevityMethodsModelingMolecularOutcomeOutcome StudyPathologyPathway interactionsPhenotypePopulationPrimatesProcessProteinsResearchRodent ModelSerumStatistical ModelsStructureStudy modelsTestingTissuesValidationVariantWorkanalytical methodclinically relevantdata integrationdata modelingdata-driven modelefficacy testingfunctional genomicsgenetic analysisgenetic associationgenetic variantgenome-widegenomic datahuman datahuman studyin vivo imagingmolecular markermolecular scalemouse modelmulti-scale modelingmultimodalitymultiple data typesmultiple omicsneuropathologynonhuman primatephenotypic datapre-clinical researchpreclinical efficacypreclinical studypresenilin-1risk varianttargeted treatmentwhole genome
项目摘要
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.
项目总结项目2
确定迟发性阿尔茨海默病发生和发展的早期分子和细胞事件
疾病(LOAD)将需要一种分析方法,将遗传、分子、活体成像和
行为数据。许多以此为目标的临床研究目前正在进行中,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的分子数据,活体成像数据
结构和神经病理学,以及关于疾病进展收集的详细认知数据。转变
这些靶向治疗策略的研究结果需要可翻译的动物模型系统,两者
为了了解疾病结局的生物学基础和候选患者的临床前疗效测试
治疗。
绒猴可能是最有希望的非人类灵长类负载模型,提供了一种分析
人类研究与大容量细胞和啮齿动物模型系统之间的桥梁。实验室的绒猴和
近亲交配遗传学可能在相关的临床中提供一系列的基因和表型变异
结果。这种长期的变异可以通过在特定风险基因座上进行基因工程变异来扩大,例如
我们已经用PSEN1进行了演示。多染色体、成像、认知和细胞的表型变化
可以严格研究中等寿命的老化灵长类动物的结局。然而,到目前为止,那里
还没有对大规模老化的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研究
老化绒猴的表型。然后,我们将严格测试人类和绒猴之间的对应关系
在所有生物层面,从基因到多尺度模型。我们的目标是将绒猴培育成成熟的
临床前研究平台,我们将追求以下三个目标:(1)评估自然遗传
作为人类阿尔茨海默病风险模型的近交绒猴的变异;(2)整合遗传、基因组和
和表型数据,以建立可靠的绒猴疾病统计模型;以及(3)评估疾病
通过匹配绒猴阿尔茨海默病分子标志物建立的模型与人类研究的相关性
一群人。通过这项工作,我们希望为与Load相关的功能基因组学奠定基础
绒猴,提供了实验室绒猴自然遗传变异的影响的扩展视图,
优先在绒猴中设计基因变异,并创建与负荷相关的第一个模型
多尺度的病理学。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Gregory W Carter其他文献
Genetic interactions improve models of quantitative traits
遗传相互作用改进数量性状模型
- DOI:
10.1038/ng.3829 - 发表时间:
2017-03-30 - 期刊:
- 影响因子:29.000
- 作者:
Anna L Tyler;Gregory W Carter - 通讯作者:
Gregory W Carter
Gregory W Carter的其他文献
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{{ truncateString('Gregory W Carter', 18)}}的其他基金
An Explainable Unified AI Strategy for Efficient and Robust Integrative Analysis of Multi-omics Data from Highly Heterogeneous Multiple Studies
一种可解释的统一人工智能策略,用于对来自高度异质性多项研究的多组学数据进行高效、稳健的综合分析
- 批准号:
10729965 - 财政年份:2023
- 资助金额:
$ 39.66万 - 项目类别:
Generation, Characterization, and Validation of Marmoset Models of Alzheimer's Disease
阿尔茨海默病狨猴模型的生成、表征和验证
- 批准号:
10494769 - 财政年份:2022
- 资助金额:
$ 39.66万 - 项目类别:
Modeling the Genetic Interaction Between Klotho and APOE Alleles in Alzheimer's Disease
模拟阿尔茨海默病中 Klotho 和 APOE 等位基因之间的遗传相互作用
- 批准号:
10524407 - 财政年份:2022
- 资助金额:
$ 39.66万 - 项目类别:
Generation, Characterization, and Validation of Marmoset Models of Alzheimer's Disease
阿尔茨海默病狨猴模型的生成、表征和验证
- 批准号:
10819807 - 财政年份:2022
- 资助金额:
$ 39.66万 - 项目类别:
Open Drug Discovery Center for Alzheimer's Disease
阿尔茨海默病开放药物发现中心
- 批准号:
10250427 - 财政年份:2019
- 资助金额:
$ 39.66万 - 项目类别:
Open Drug Discovery Center for Alzheimer's Disease
阿尔茨海默病开放药物发现中心
- 批准号:
10017132 - 财政年份:2019
- 资助金额:
$ 39.66万 - 项目类别:
IU/JAX/Pitt MODEL-AD: Deep Phenotyping Proteomics Year 1
IU/JAX/Pitt MODEL-AD:深度表型蛋白质组学第 1 年
- 批准号:
10092243 - 财政年份:2016
- 资助金额:
$ 39.66万 - 项目类别:
The IU/JAX Alzheimer's Disease Precision Models Center: Metabolomics
IU/JAX 阿尔茨海默病精密模型中心:代谢组学
- 批准号:
9537115 - 财政年份:2016
- 资助金额:
$ 39.66万 - 项目类别:
The IU/JAX Alzheimer's Disease Precision Models Center: Aging
IU/JAX 阿尔茨海默病精密模型中心:衰老
- 批准号:
9930786 - 财政年份:2016
- 资助金额:
$ 39.66万 - 项目类别: