MicroRNAs as Diagnostic and Prognostic Biomarker of Alzheimer's Disease

MicroRNA 作为阿尔茨海默病的诊断和预后生物标志物

• 批准号: 10502333
• 负责人: JAN Krzysztof BLUSZTAJN
• 金额: $ 31.88万
• 依托单位: RHODE ISLAND HOSPITAL
• 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 2023-08-18
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10502333
• 关键词: Adult; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease model; Alzheimer' s disease pathology; Alzheimer' s disease patient; Alzheimer’s disease biomarker; Amyloid beta-Protein; Anatomy; Autopsy; Behavior; Biological Markers; Biological Models; Blood; Brain; Cells; Cerebrospinal Fluid; Clinical; Cognition; Cognitive; Cohort Studies; Cross-Sectional Studies; Data; Data Set; Dementia; Development; Diagnosis; Diagnostic; Disease; Elderly; Environment; Environmental Risk Factor; Epigenetic Process; Experimental Models; Framingham Heart Study; Future; Gene Abnormality; Gene Expression; Genetic Risk; Genome; Germany; Hippocampus (Brain); Human; Immune response; Impaired cognition; In Vitro; Individual; Knowledge; Lasers; Late Onset Alzheimer Disease; Link; Longitudinal Studies; Longitudinal cohort; Longitudinal cohort study; Measures; MicroRNAs; Molecular; Neuroglia; Neurons; Participant; Pathologic; Pathology; Patients; Pattern; Plasma; Prefrontal Cortex; Process; Prognostic Marker; Reporting; Risk; Salvelinus; Sample Size; Sampling; Signal Transduction; Structure; Testing; Therapeutic; Time; Tissue Sample; Work; base; brain tissue; candidate marker; circulating microRNA; cohort; cost; diagnostic biomarker; differential expression; early detection biomarkers; experimental study; in vivo; induced pluripotent stem cell; inhibitor; innovation; insight; meetings; microRNA biomarkers; mild cognitive impairment; minimally invasive; mouse model; nanoparticle; neuroimaging; next generation; prevent; prognostic; proteostasis; relating to nervous system; statistical and machine learning; tau Proteins

ABSTRACT Preventative and therapeutic strategies for late onset Alzheimer’s Disease (AD) depend on access to reliable biomarkers for early detection, ideally minimally invasive and inexpensive with more invasive and costly ones reserved for subsequent diagnostics. Despite the progress in the development of blood biomarkers to detect AD- associated beta-amyloid or Tau pathology, the challenges remain because AD is characterized by dysregulated neural gene expression triggered by combinations of genetic and environmental risk factors. Genome-environment interactions are orchestrated by epigenetic processes that include the function of microRNAs (miRNAs, miRs) which is to regulate gene-expression and proteostasis. While altered microRNA expression is repeatedly observed in AD biospecimens, small sample size and lack of mechanism maintain the gap of knowledge whethermicroRNAs could serve as diagnostic and prognostic AD biomarker. The unprecedented combination of samples from Alzheimer’s Disease Neuroimaging Initiative (ADNI), Framingham Heart Study (FHS), and Germany’s cognitive impairment and dementia study (DELCODE) in this application provides us with the opportunity to bridge that gap. In Aim 1we test the hypothesis that distinct patterns of circulating plasma microRNA levels differentiate among cognitively normal (CN), individuals with mild cognitive impairment (MCI), and dementia patients (AD) meeting clinical criteria for AD. Cross-sectional plasma samples for microRNA-Seq analysis were obtained from 847 participants in ADNI-1/GO/-2 and from 585 participants in DELCODE. We will use complementary computational approaches to compare: AD vs CN, MCI vs CN, and AD vs MCI samples and identify microRNA signatures of MCI and AD. The results will be integrated with the data from the FHS cohort comprising 48 participants with diagnoses confirmed postmortem and 3 longitudinal plasma samples separated by years; the participants who developed AD provided 2 samples before and 1 after their clinical AD diagnosis. We will use statistical and machine learning approaches to generate miRNA-based classifiers. Aim 2 will determine if differential expression of circulating candidate biomarker miRs that discriminate between AD and CN subjects can be observed in vulnerable cells, laser- microdissected from postmortem cortices of Aim 1 FHS participants. In these cells we will quantify the expression of miR-181a-5p, miR-148-3p and miR-146a-5p, a 3-miR plasma signature that uncovered patients at risk for converting from MCI to AD in our exploratory study in press. We will also examine the expression of at least 3 top microRNA AD biomarker candidates validated in Aim 1 analyses. In Aim 3 we will uncover the functions of candidate biomarker microRNAs in vitro and in vivo by manipulating levels of biomarker candidates to establish their functional readouts in human induced pluripotent stem cell- derived cortical neurons and glia and in next generation AD mouse models. Our comprehensive interdisciplinary analyses will integrate observational and experimental data to determine how MCI- and AD-associated microRNA signatures reflect AD-associated pathology and serve as a biomarker for developing AD.

抽象的 迟发性阿尔茨海默病 (AD) 的预防和治疗策略取决于能否获得可靠的信息 用于早期检测的生物标志物，最好是微创且便宜的，也有更具侵入性且昂贵的生物标志物 保留用于后续诊断。尽管检测 AD 的血液生物标志物的开发取得了进展， 相关的 β-淀粉样蛋白或 Tau 病理学，挑战仍然存在，因为 AD 的特点是失调 由遗传和环境风险因素的组合触发的神经基因表达。基因组环境 相互作用是由表观遗传过程精心安排的，其中包括 microRNA（miRNA、miR）的功能 这是调节基因表达和蛋白质稳态。虽然反复观察到 microRNA 表达发生改变 在 AD 生物样本中，小样本量和缺乏机制维持了关于 microRNA 是否存在的知识差距 可以作为 AD 的诊断和预后生物标志物。前所未有的样本组合 阿尔茨海默病神经影像倡议 (ADNI)、弗雷明汉心脏研究 (FHS) 和德国认知 此应用程序中的损伤和痴呆研究 (DELCODE) 为我们提供了弥合这一差距的机会。 在目标 1 中，我们测试了以下假设：循环血浆 microRNA 水平的不同模式可区分不同人群 认知正常（CN）、轻度认知障碍（MCI）和痴呆患者（AD）的个体 AD 的临床标准。 [第 847 章] ADNI-1/GO/-2 的参与者和 DELCODE 的 585 名参与者。我们将使用互补计算 比较方法：AD 与 CN、MCI 与 CN、AD 与 MCI 样本并识别 MCI 的 microRNA 特征 和广告。结果将与 FHS 队列的数据进行整合，该队列由 48 名患有诊断的参与者组成 经确认的尸检样本和 3 个相隔数年的纵向血浆样本；开发 AD 的参与者 提供了临床 AD 诊断之前的 2 个样本和之后的 1 个样本。我们将使用统计和机器学习 生成基于 miRNA 的分类器的方法。目标 2 将确定循环的差异表达是否 可以在脆弱细胞中观察到区分 AD 和 CN 受试者的候选生物标志物 miR，激光- 从 Aim 1 FHS 参与者死后皮质中进行显微解剖。在这些细胞中，我们将量化表达 miR-181a-5p、miR-148-3p 和 miR-146a-5p 的 3-miR 血浆特征发现了有风险的患者 在我们发表的探索性研究中，从 MCI 转换为 AD。我们还将检查至少 3 个顶级的表达 microRNA AD 候选生物标志物在 Aim 1 分析中得到验证。在目标 3 中，我们将揭示以下功能 通过操纵候选生物标志物的水平来建立体外和体内候选生物标志物 microRNA 他们在人类诱导多能干细胞衍生的皮质神经元和神经胶质细胞中的功能读数以及接下来的研究 一代 AD 小鼠模型。我们全面的跨学科分析将整合观察和 实验数据以确定 MCI 和 AD 相关 microRNA 特征如何反映 AD 相关 病理学并作为 AD 发展的生物标志物。