Identify and study the roles of key genes and proteins in subpopulations of Alzheimer's disease patients with uncoupled neurofibrillary tangles
识别和研究关键基因和蛋白质在具有解偶联神经原纤维缠结的阿尔茨海默病患者亚群中的作用
基本信息
- 批准号:10525012
- 负责人:
- 金额:$ 42.6万
- 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:2022-08-01 至 2024-07-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAgeAlzheimer disease preventionAlzheimer&aposs DiseaseAlzheimer&aposs disease patientApplications GrantsAxonAxonal TransportBehavioralBiochemicalBioinformaticsBiologicalBrainCandidate Disease GeneCharacteristicsClinicalCognitiveDataData SetDementiaDependovirusDepositionDeteriorationDiseaseDisease ProgressionDisease susceptibilityDrosophila genusDrosophila melanogasterElderlyEtiologyEyeGene ProteinsGenesGenetic ModelsGenetic ScreeningGenomicsGoalsHumanImpaired cognitionImpairmentInjectionsMAPT geneMeasuresMicrotubule BundleMiningMitochondriaModelingMouse StrainsMusNeonatalNeurodegenerative DisordersNeurofibrillary TanglesNeuronsPathogenesisPathologicPathologyPathway interactionsPersonsPlayPopulationPredispositionProteinsProteomicsResearchRoleSamplingScreening procedureSeveritiesStressSubgroupSynapsesTauopathiesTestingToxic effectTransgenic Organismsasymptomatic Alzheimer&aposs diseasecausal variantcurative treatmentsdifferential expressiondisorder subtypedrug developmentexperimental studyflyhuman modelimprovedin vivomouse modeloverexpressionpatient subsetsprecision medicinepreventresiliencetau Proteinstau aggregationtherapeutically effectivetranscriptomics
项目摘要
Project Abstract
Alzheimer’s disease (AD) affects about 10% of the US population of age 65 and up, and roughly 40
million people worldwide. Despite decades of studies, the disease etiology of AD still remains unclear,
and till today, there is no curative treatment for AD. Typically, AD patient brains show characteristic
neurofibrillary tangles (NFTs), which are composed of aggregated bundles of microtubule-associated
protein tau in its truncated or hyperphosphorylated state, and the degree of NFTs in the brain usually
positively correlates with the disease progression and cognitive decline. However, there also exists
subpopulations of patients whose disease trajectories do not follow the typical NFT accumulation way. A
subgroup of patients’ brain samples showed AD-like high NFTs but with no or low cognitive deterioration,
while another subgroup of patients presents severe cognitive impairment but low NFT pathology.
Studying these atypical AD subtypes and identifying key factors in such uncoupling between NFT
pathology and cognitive impairment will not only improve precision medicine in AD, but also provide
valuable information on how to prevent and slow down cognitive deterioration during the long disease
progression.
In this project, our overarching hypothesis is that the transcriptomic, proteomic, and network-level
differences identified for the atypical NFTs-dementia uncoupled human brains can contribute to the
mechanisms of rapid cognitive deterioration in low-NFT AD groups and the dementia resilience in
Asymptomatic AD groups. We plan to apply data-driven approaches with integrative genomic analyses
on multiple AD proteomic and transcriptomic datasets to identify candidate genes, proteins, and
coexpression networks that play important roles in the NFTs-dementia uncoupling in the atypical AD
patients. The identified gene candidates will be further screened in the Drosophila strains expressing
human pathological tau for causal genes and proteins that are key factors for either NTF-dementia
uncoupling or rendering neuron protection/susceptibility to AD. Promising candidates obtained from
Drosophila experiments will be further tested in the mouse strains which can express human tau as early
as four months old to understand their roles in terms of neuron-protection or AD-susceptibility. Our long-
term goal is to generate experimental evidence for further grant applications to elucidate the NFT-AD
uncoupling mechanisms behind the two subgroups, which can open new research directions for AD
prevention as well as AD drug development.
项目摘要
阿尔茨海默病 (AD) 影响美国 65 岁及以上人口的约 10%,以及大约 40 岁
尽管经过数十年的研究,AD 的病因仍不清楚,
直到今天,AD 还没有治愈的方法。通常,AD 患者的大脑表现出特征。
神经原纤维缠结(NFT),由与微管相关的聚集束组成
处于截短或过度磷酸化状态的 tau 蛋白,以及大脑中 NFT 的程度通常
然而,也存在与疾病进展和认知能力下降呈正相关的情况。
疾病轨迹不遵循典型 NFT 累积方式 A 的患者亚群。
亚组患者的大脑样本显示出类似 AD 的高 NFT,但没有或很少有认知恶化,
而另一组患者则表现出严重的认知障碍,但 NFT 病理学水平较低。
研究这些非典型 AD 亚型并确定 NFT 之间脱钩的关键因素
病理学和认知障碍不仅可以改善 AD 的精准医疗,还可以提供
关于如何预防和减缓长期疾病期间认知能力恶化的宝贵信息
进展。
在这个项目中,我们的总体假设是转录组、蛋白质组和网络水平
非典型 NFT-痴呆症非耦合人类大脑的差异可能有助于
低 NFT AD 群体认知快速恶化的机制以及痴呆恢复力
我们计划应用数据驱动的方法和综合基因组分析。
在多个 AD 蛋白质组和转录组数据集上识别候选基因、蛋白质和
共表达网络在非典型 AD 中 NFT-痴呆解偶联中发挥重要作用
确定的候选基因将在果蝇菌株中进行进一步筛选。
人类病理性 tau 蛋白的致病基因和蛋白质是 NTF-痴呆症的关键因素
解偶联或呈现对 AD 的有希望的候选者的神经保护/易感性。
果蝇实验将在最早可以表达人类 tau 的小鼠品系中进行进一步测试
四个月大时,我们就了解了它们在神经元保护或 AD 易感性方面的作用。
术语目标是为进一步的拨款申请生成实验证据,以阐明 NFT-AD
两个亚组背后的解耦机制,可以为AD开辟新的研究方向
预防以及 AD 药物开发。
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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Cristian Lasagna-Reeves其他文献
Cristian Lasagna-Reeves的其他文献
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{{ truncateString('Cristian Lasagna-Reeves', 18)}}的其他基金
Tau-seed protein interactome and its role in neurodegenerative tauopathies
Tau 种子蛋白相互作用组及其在神经退行性 tau 病中的作用
- 批准号:
10456475 - 财政年份:2021
- 资助金额:
$ 42.6万 - 项目类别:
Tau-seed protein interactome and its role in neurodegenerative tauopathies
Tau 种子蛋白相互作用组及其在神经退行性 tau 病中的作用
- 批准号:
10407715 - 财政年份:2021
- 资助金额:
$ 42.6万 - 项目类别:
Tau-seed protein interactome and its role in neurodegenerative tauopathies
Tau 种子蛋白相互作用组及其在神经退行性 tau 病中的作用
- 批准号:
10480212 - 财政年份:2020
- 资助金额:
$ 42.6万 - 项目类别:
Tau-seed protein interactome and its role in neurodegenerative tauopathies
Tau 种子蛋白相互作用组及其在神经退行性 tau 病中的作用
- 批准号:
10470271 - 财政年份:2020
- 资助金额:
$ 42.6万 - 项目类别:
Tau-seed protein interactome and its role in neurodegenerative tauopathies
Tau 种子蛋白相互作用组及其在神经退行性 tau 病中的作用
- 批准号:
10683165 - 财政年份:2020
- 资助金额:
$ 42.6万 - 项目类别:
Tau-seed protein interactome and its role in neurodegenerative tauopathies
Tau 种子蛋白相互作用组及其在神经退行性 tau 病中的作用
- 批准号:
10268217 - 财政年份:2020
- 资助金额:
$ 42.6万 - 项目类别:
Tau-seed protein interactome and its role in neurodegenerative tauopathies
Tau 种子蛋白相互作用组及其在神经退行性 tau 病中的作用
- 批准号:
10093443 - 财政年份:2020
- 资助金额:
$ 42.6万 - 项目类别:
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