Neuropathology of synapses in AD and ADRD
AD 和 ADRD 突触的神经病理学
基本信息
- 批准号:10590045
- 负责人:
- 金额:$ 215.59万
- 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:2022-12-15 至 2025-11-30
- 项目状态:未结题
- 来源:
- 关键词:3xTg-AD mouseAbbreviationsAgingAlzheimer&aposs DiseaseAlzheimer&aposs disease modelAlzheimer&aposs disease related dementiaAmyloid beta-ProteinAnatomyAreaArea Under CurveAtlasesBrainBrain regionBrodmann&aposs areaCD47 geneCellsClinicalCoupledCryopreservationCytometryDataDevelopmentDiseaseElasticityElderlyEventGeneticHippocampusHumanImpaired cognitionInjuryKnowledgeLewy Body DiseaseLongevityMachine LearningMalignant NeoplasmsMediatingMicrogliaModelingMolecularMolecular AnalysisMolecular ProfilingNeuronsParticipantPathologicPathologic ProcessesPathway interactionsPatternPeptidesPredispositionPreparationProteinsResearchResourcesSamplingSignal TransductionSynapsesTechniquesTechnologyTestingTherapeuticTherapeutic InterventionTimeTransgenic MiceTransgenic Organismsagedautoencodercomorbidityeffective interventiongraph neural networkinnovative technologiesinsightmouse modelneuropathologynew technologynew therapeutic targetnewsnonhuman primatenovelnovel therapeuticsoverexpressionpreservationpresynapticpreventresiliencestressortau Proteinstissue resource
项目摘要
PROJECT SUMMARY / ABSTRACT
Although its molecular mechanisms remain to be clarified, the anatomic basis of cognitive impairment in
Alzheimer's disease (AD) is injury and degeneration of synapses. Subpopulations of neurons in different brain
areas may be more or less susceptible to specific types such insults Yet, molecular characterization of
synapses in AD and AD–related dementias (ADRD) is limited, leaving the factors underlying this selectivity and
the fidelity of widely-used mouse models to the human condition unclear. Here, we propose to fill these
important gaps in selective cell vulnerability in aging and AD by identifying molecular signatures to suggest or
confirm cellular pathways that may mediate vulnerability. The proposed project will accomplish this using a
unique tissue resource and novel technology developed by us, and couple them with cutting-edge machine
learning (ML) techniques to enhance differential signals and achieve deeper insights into the factors underlying
selective neuron vulnerability or resilience. The novel technology that we have developed is called
Synaptometry by Time-of-Flight, or SynTOF, and it provides an unparalleled opportunity for multiplex molecular
analysis of millions of single synaptic events. We will build on our preliminary data, which coupled this new
technology with ML approaches to gain novel insights into synaptic injury in AD, including in a transgenic
mouse model that regionally overexpresses amyloid (A) β peptides in neurons, and which highlight the value of
SynTOF in discovering the molecular patterns of injury in human synaptic subtypes, as well as assessing the
fidelity of mouse models at the single synaptic level. Drawing on our unique tissue resource of cryopreserved
synaptic preparations from participants with extensive clinical, genetic, and neuropathologic annotation, novel
and powerful technology, and robust computational approaches, we propose to test the hypothesis that
synapse injury in AD and ADRD is disease-, brain region-, and synapse subtype-specific, thereby highlighting
new targets for therapeutic intervention and determining the extent to which three commonly used transgenic
mouse lines model the synaptic injury of humans. When successfully completed, our novel resources and
approach will provide unique insights into pre- and postsynapse subtype-specific mechanisms of injury at
unprecedented scale, and further highlight new therapeutic targets for AD and ADRD.
项目总结/摘要
虽然其分子机制仍有待阐明,但认知障碍的解剖学基础,
阿尔茨海默病(Alzheimer's disease,AD)是一种神经突触损伤和变性的疾病。不同脑内神经元亚群
区域可能或多或少地对特定类型的损伤敏感。
AD和AD相关性痴呆(ADRD)中的突触是有限的,留下了这种选择性的潜在因素,
广泛使用的小鼠模型对人类状况的真实性尚不清楚。在这里,我们建议填补这些
通过识别分子特征来提示或提示衰老和AD中选择性细胞脆弱性的重要差距
确认可能介导脆弱性的细胞通路。拟议的项目将使用
独特的组织资源和我们开发的新技术,并将其与尖端机器相结合
学习(ML)技术,以增强差分信号,并实现对潜在因素的更深入了解
选择性神经元脆弱性或弹性。我们开发的新技术叫做
通过飞行时间的突触,或SynTOF,它提供了一个无与伦比的机会,多分子
数百万个单个突触事件的分析。我们将建立在我们的初步数据,其中结合这一新的
技术与ML方法,以获得新的见解突触损伤的AD,包括在转基因
在神经元中局部过表达淀粉样蛋白(A)β肽的小鼠模型,
SynTOF在发现人类突触亚型损伤的分子模式,以及评估
小鼠模型在单突触水平的保真度。利用我们独特的冷冻保存组织资源
来自参与者的突触制备物具有广泛的临床、遗传和神经病理学注释,
强大的技术和强大的计算方法,我们建议测试假设,
AD和ADRD中的突触损伤是疾病特异性、脑区域特异性和突触亚型特异性的,从而突出了
治疗干预的新靶点,并确定三种常用的转基因
小鼠品系模拟人类的突触损伤。成功完成后,我们的新资源和
方法将提供独特的见解前和突触后亚型特异性损伤机制,
这是前所未有的规模,并进一步突出了AD和ADRD的新治疗靶点。
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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Nima Aghaeepour其他文献
Nima Aghaeepour的其他文献
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{{ truncateString('Nima Aghaeepour', 18)}}的其他基金
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
临床环境中免疫系统综合建模的机器学习
- 批准号:
10703364 - 财政年份:2020
- 资助金额:
$ 215.59万 - 项目类别:
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
临床环境中免疫系统综合建模的机器学习
- 批准号:
10251069 - 财政年份:2020
- 资助金额:
$ 215.59万 - 项目类别:
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
临床环境中免疫系统综合建模的机器学习
- 批准号:
10028766 - 财政年份:2020
- 资助金额:
$ 215.59万 - 项目类别:
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
临床环境中免疫系统综合建模的机器学习
- 批准号:
10461194 - 财政年份:2020
- 资助金额:
$ 215.59万 - 项目类别:
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
临床环境中免疫系统综合建模的机器学习
- 批准号:
10682328 - 财政年份:2020
- 资助金额:
$ 215.59万 - 项目类别:
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
临床环境中免疫系统综合建模的机器学习
- 批准号:
10727034 - 财政年份:2020
- 资助金额:
$ 215.59万 - 项目类别:
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
临床环境中免疫系统综合建模的机器学习
- 批准号:
10433729 - 财政年份:2020
- 资助金额:
$ 215.59万 - 项目类别:
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