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.

摘要 晚发性阿尔茨海默病（AD）的预防和治疗策略依赖于可靠的 用于早期检测的生物标志物，理想情况下是微创和廉价的，而更具侵入性和昂贵的生物标志物 用于后续诊断。尽管在开发血液生物标志物以检测AD方面取得了进展， 尽管AD与β-淀粉样蛋白或Tau病理学相关，但挑战仍然存在，因为AD的特征在于调节异常 神经基因表达由遗传和环境风险因素的组合触发。基因组-环境 相互作用由表观遗传过程协调，包括microRNA（miRNAs，miRs）的功能 即调节基因表达和蛋白质稳定。虽然反复观察到改变的microRNA表达， 在AD生物标本中，小样本量和缺乏机制维持了对microRNA是否 可作为AD诊断和预后的生物标志物。前所未有的样本组合， 阿尔茨海默病神经影像学倡议（ADNI），心脏病研究（FHS）和德国的认知 本应用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。 在目的1中，我们检验了以下假设：循环血浆microRNA水平的不同模式可区分以下患者： 认知正常（CN）、轻度认知障碍（MCI）和痴呆患者（AD） AD的临床标准。用于microRNA-Seq分析的横截面血浆样品从847名受试者中获得。 ADNI-1/GO/-2中的参与者和DELCODE中的585名参与者。我们将使用互补计算 比较方法：AD与CN、MCI与CN以及AD与MCI样本并识别MCI的microRNA特征 的AD。结果将与来自FHS队列的数据整合，该队列包括48名诊断为 确认死后和3个纵向血浆样本分开多年;参与者谁开发AD 提供了2份临床AD诊断前和1份临床AD诊断后的样本。我们将使用统计和机器学习 方法来生成基于miRNA的分类器。目的2将确定是否差异表达的循环 可以在易损细胞中观察到区分AD和CN受试者的候选生物标志物miR，激光- 从Aim 1 FHS参与者的死后皮质显微解剖。在这些细胞中，我们将定量表达 miR-181 a-5 p、miR-148- 3 p和miR-146 a-5 p的表达，这是一种3-miR血浆特征， 在我们的探索性研究中从MCI转化为AD。我们还将检查至少3个top的表达式 在Aim 1分析中验证的microRNA AD生物标志物候选物。在目标3中，我们将揭示 通过操纵生物标志物候选物的水平，在体外和体内检测候选生物标志物微RNA， 它们在人类诱导多能干细胞衍生的皮层神经元和神经胶质细胞中的功能读数， AD小鼠模型。我们全面的跨学科分析将整合观测和 实验数据，以确定MCI和AD相关的microRNA特征如何反映AD相关的 病理学，并作为发展AD的生物标志物。