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Utilizing gene-level biomarkers of AD to identify pathophysiological mechanisms in human neurons

Utilizing gene-level biomarkers of AD to identify pathophysiological mechanisms in human neurons
利用 AD 的基因水平生物标志物识别人类神经元的病理生理机制
批准号:
10727531
负责人:
Judith Ann Potashkin
金额:
$42.26万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-15 至 2025-07-31
关键词:
AccelerationAffectAgeAgingAlzheimer&aposs DiseaseAlzheimer&aposs disease diagnosisAlzheimer&aposs disease patientAlzheimer&aposs disease riskAlzheimer&aposs disease therapeuticAlzheimer’s disease biomarkerAmyloidAnimal ModelAutomobile DrivingAutophagocytosisBioenergeticsBioinformaticsBiological AssayBiological MarkersBiosensorCell physiologyCellsCoupledData SetDatabasesDementiaDepressed moodDiagnosisDiseaseElectrophysiology (science)EndosomesEpigenetic ProcessFamilyFibroblastsFunctional disorderGene ExpressionGenerationsGenesGlucoseGlutamatesGoalsHumanImpaired cognitionImpairmentIndividualKnowledgeLaboratoriesLightLinkLysosomesMemory LossMemory impairmentMeta-AnalysisMetabolicMetabolic stressMetabolismMitochondriaMutationNeuronsNeurophysiology - biologic functionOrganellesOutcomePathogenesisPathogenicityPathologicPathway interactionsPatientsPharmaceutical PreparationsPhenotypePhysiologicalPlayPopulationPrevalenceProcessProductionPropertyProteinsProteomicsRiskRisk FactorsSignal TransductionSocietiesSynapsesSystemTestingTherapeutic InterventionTimeTissue-Specific Gene ExpressionWorkcell typeclinically relevantcognitive functioncohortdata repositorydifferential expressiondisease phenotypeearly detection biomarkersfamilial Alzheimer diseasefluorescence imaginggene networkgenomic variationglucose metabolismhealthy aginghigh riskhigh risk populationhuman diseaseimprovedinnovationinsightlive cell imagingmemory encodingneurophysiologyneurotransmissionnovel therapeuticsoptimismprotein aggregationsexstem cell biologystem cell technologysynaptic functiontau Proteinstooltranscriptomicstransmission process

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中文摘要
翻译
抽象概括 AD治疗的最新进展增加了识别具有发展风险的个体的紧迫性。 阿尔茨海默病(AD)。这一努力可能会加速使用干细胞生物学方法, 导致能够直接从容易获得的患者细胞(例如, 成纤维细胞这为临床研究衰老和疾病相关过程提供了强有力的工具。 相关细胞类型AD患者和健康人现有转录组数据库的荟萃分析研究 无痴呆症(nonAD)的个体也为潜在的病理生理驱动因素提供了新的见解 有助于AD的诊断。虽然这些基因表达谱已被确定为AD风险, 从个体携带到其直接转化的神经元(人诱导神经元,HiN)。这是一 关键的缺失环节需要捕捉这些基因网络概况的生理结果,以便 确定代谢应激、病理性蛋白质聚集和突触 病理生理学-AD的所有关键特征。因此,我们将应用神经生理学和细胞功能 分析来自诊断为散发性或家族性AD的代表性个体的HiN,以及 年龄/性别匹配的非AD对照,以确定这些基因组变异的功能后果, 人口。 我们的总体目标是确定基于基因通路的AD生物标志物或风险因素,并确定AD的发病机制。 与这些基因通路相关的神经元病理生理表型。我们将检验这个假设 来自AD人群的神经元中的突触信号传导、代谢和蛋白质处理过程 将反映区分健康衰老过程与AD发病机制的基因途径的改变, 因此可以作为重要的生物标志物。在目标1中,我们将确定线粒体功能缺陷 与AD中葡萄糖代谢基因通路的改变相关。在目标2中,我们将识别病理性 AD患者中调节自噬和蛋白质处理不当的基因通路改变的表现。在Aim中 3我们将确定与改变的基因网络相对应的神经生理学和突触信号作用, 导致认知能力下降的AD。结合我们在诱导神经元产生方面的专业知识以及 生物信息学和神经生理学分析使这成为一个强大的和创新的建议,将提供 AD的危险因素和生物标志物的重要见解。这是在广告领域的关键时刻, 必须尽早识别出有风险的个体,以最大限度地提高新疗法的益处, available.
英文摘要
Abstract Summary Recent advances AD therapeutics increases the urgency to identify individuals at risk for developing Alzheimer’s disease (AD). This effort can likely be accelerated using stem cell biology approaches which have led to the ability to generate human induced neurons (HiN) directly from easily obtainable patient cells such as fibroblasts. This serves as a powerful tool for studying aging and disease-related processes in clinically relevant cell types. Meta-analysis studies of existing transcriptomic databanks from AD patients and healthy individuals without dementia (nonAD) have also provided new insight into underlying pathophysiological drivers contributing to a diagnosis of AD. While these gene expression profiles have been identified for AD risk which carryover from the individual to their directly transformed neurons (human induced neuron, HiN). This is a crucial missing link needed to capture the physiological outcomes of these gene network profiles in order to identify associated mechanisms of metabolic stress, pathological protein aggregation and synaptic pathophysiology – all key features of AD. Therefore, we will apply neurophysiological and cellular functional analyses to HiNs derived from representative individuals diagnosed with sporadic or familial AD, as well as age/sex-matched nonAD controls, to identify functional consequences of these genomic variations in the human population. Our overall objective is to identify gene-pathway based biomarkers or risk factors for AD and define the neuronal pathophysiological phenotypes associated with these gene pathways. We will test the hypothesis that synaptic signaling, metabolism and protein handling processes in neurons derived from the AD population will reflect the alterations in gene pathways that distinguish healthy aging processes from AD pathogenesis, and thus can serve as important biomarkers. In Aim 1 we will identify mitochondrial functional deficits associated with alterations in glucose metabolism gene pathways in AD. In Aim 2 we will identify pathological manifestations of altered gene pathways regulating autophagy and protein mishandling in AD patients. In Aim 3 we will identify neurophysiological and synaptic signaling effects corresponding with altered gene networks in AD that underlie cognitive decline. The combination of our expertise in induced neuron production as well as bioinformatics and neurophysiology assays makes this a powerful and innovative proposal that will provide important insights into risk factors and biomarkers of AD. This comes at a crucial time in the AD field where it is imperative to identify at risk individuals early in order to maximize benefits of new therapeutics becoming available.
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