Discovering Centrally Linked Peripheral Molecular Signatures of Alzheimer's Disease

发现阿尔茨海默病的中心连锁外周分子特征

• 批准号: 10555727
• 负责人: NILUFER ERTEKIN-TANER
• 金额: $ 97.58万
• 依托单位: MAYO CLINIC JACKSONVILLE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10555727
• 关键词: African American; Aging; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease pathology; Alzheimer' s disease related dementia; Alzheimer’s disease biomarker; American; Autopsy; Biological; Biological Markers; Blood; Blood Vessels; Blood specimen; Brain; Brain region; Cell Nucleus; Cerebrospinal Fluid; Clinic; Clinical; Cognition; Cognitive; Collaborations; Communities; Complex; Data; Diagnosis; Diagnostic; Disease; Disease Progression; Early Diagnosis; Epigenetic Process; Ethnic Population; Florida; Functional disorder; Future; Gene Expression Profile; Genes; Genetic; Genome; Image; Individual; Knowledge; Latino; Link; Longitudinal cohort; Measures; Molecular; Molecular Profiling; Multiomic Data; Natural Immunity; Outcome; Participant; Pathway Analysis; Pathway interactions; Pattern; Peripheral; Phenotype; Population; Population Heterogeneity; Proteins; Proteome; RNA; Resources; Sampling; Symptoms; Synapses; Testing; Therapeutic; Therapeutic Intervention; Transcript; Translations; advanced analytics; artificial neural network; biomarker discovery; blood-based biomarker; brain cell; cell type; cohort; comparative; cost effective; disease phenotype; disorder subtype; lipidome; metabolome; methylome; multi-ethnic; multiple omics; myelination; neuroimaging; neuropathology; novel; patient stratification; peripheral blood; personalized medicine; precision medicine; preservation; prognostic; random forest; transcriptome; transcriptome sequencing; transcriptomic profiling; translational approach; translational study; validation studies

SUMMARY ABSTRACT Discovering Alzheimer’s disease (AD) biomarkers for early diagnosis, tracking of disease progression and timely therapeutic interventions is a significant need. Despite the utility of existing neuroimaging and cerebrospinal fluid biomarkers, there is an urgent need to develop cost-effective and blood-based biomarkers to apply at the population level. Large-scale multi-omics studies identified a multitude of molecular perturbations in AD. These discoveries support the rationale for discovery of peripheral biomarkers that capture the full spectrum of central changes that occur in this disease. Our proposal aims to leverage combined blood and brain multi-omics data in well-characterized cohorts to identify peripheral molecular signatures which reflect the central molecular perturbations that occur in AD brains. We hypothesize that blood molecular signatures can serve as centrally- linked peripheral biomarkers (CLPBM) since many brain multi-omics changes can also be observed in blood and vice versa. As they are linked with brain molecular perturbations, such CLPBM can provide mechanistic information on potential drivers of disease and its progression. CLPBM can also be expected to aid in patient stratification according to biological subtypes and disease stage, ultimately paving the way for personalized medicine. There are, however, no sizable studies that simultaneously analyze brain and blood samples from the same individuals to discover centrally-linked peripheral molecular signatures (CLPMS) that can serve as future centrally-linked peripheral biomarkers (CLPBM). In Project 1, we leverage three studies with complementary strengths, Mayo Clinic Study of Aging, Alzheimer’s Disease Neuroimaging Initiative and Mayo Clinic Florida post- mortem African American and Latino American cohorts, to accomplish our specific aims to: 1. Discover brain region-specific CLPMS through molecular profiling (transcriptome, genome, methylome, proteome, metabolome/lipidome) in up to 5 brain regions and in matched blood samples. 2. Identify cell-type specific CLPMS through single nucleus transcriptome profiling across 5 brain regions and in matched blood samples. 3. Establish CLPMS in diverse populations by profiling of same -omics measures across the same brain regions from LA and AA participants. 4. Discover CLPMS that reflect biological subtypes and temporal progression of AD through use of advanced analytics approaches of the molecular data. We expect to identify brain region and cell-type specific CLPMS, which reflect the heterogeneous neuropathology in AD; associate with or drive antemortem clinical, neuroimaging and cognitive progression and outcomes of AD; define biological subtypes and predict molecular stage of AD in multi-ethnic populations. Findings from Project 1, together with those from Projects 2 and 3, collectively comprising >20,000 multi-omics and >48,000 AD phenotypes from >3,700 multi- ethnic participants will be analyzed applying our well-defined Roadmap to Translation approach to prioritize CLPMS for translation to precision medicine biomarkers for AD. Further, the data, outcomes and knowledge from this Project will be shared broadly and serve as an unprecedented resource for the research community.

摘要 发现阿尔茨海默病（AD）的生物标志物，用于早期诊断，跟踪疾病进展， 治疗干预是一个重要的需求。尽管现有的神经影像学和脑脊液检查 生物标志物，迫切需要开发具有成本效益的血液生物标志物，以应用于 人口水平。大规模的多组学研究确定了AD中的多种分子扰动。这些 这些发现支持了发现外周生物标志物的基本原理， 这种疾病发生的变化。我们的提案旨在利用血液和大脑多组学数据， 充分表征的队列，以确定反映中心分子的外周分子特征， 发生在AD大脑中的扰动。我们假设血液分子特征可以作为中枢- 连锁外周生物标志物（CLPBM），因为许多脑多组学变化也可以在血液中观察到 且反之亦然。由于它们与脑分子扰动有关，因此这种CLPBM可以提供机制性的 关于疾病及其进展的潜在驱动因素的信息。CLPBM也有望帮助患者 根据生物亚型和疾病阶段进行分层，最终为个性化 药然而，还没有大规模的研究同时分析大脑和血液样本， 相同的个体发现中央连锁的外周分子特征（CLPMS），可以作为未来 中心连锁外周生物标志物（CLPBM）。在项目1中，我们利用三项研究， 优势，马约诊所衰老研究，阿尔茨海默病神经影像学倡议和马约诊所佛罗里达后， 尸检非洲裔美国人和拉丁美洲裔美国人队列，以实现我们的具体目标：1。发现大脑 区域特异性CLPMS通过分子分析（转录组，基因组，甲基化组，蛋白质组， 代谢组/脂质组）中的代谢产物。2.识别细胞类型特异性 CLPMS通过5个脑区和匹配血液样本中的单核转录组分析。3. 通过分析相同脑区的相同组学指标，在不同人群中建立CLPMS 来自LA和AA的参与者。4.发现反映生物学亚型和时间进展的CLPMS AD通过使用分子数据的先进分析方法。我们希望能够识别大脑区域， 细胞类型特异性CLPMS，反映了AD中的异质性神经病理学;与AD相关或驱动 AD的生前临床、神经影像学和认知进展和结局;定义生物学亚型 并预测多种族人群中AD的分子阶段。项目1的结果，以及 项目2和3，共同包括来自> 3，700个多组学的> 20，000个多组学和> 48，000个AD表型。 将应用我们定义良好的翻译路线图方法对少数民族参与者进行分析， CLPMS用于转化为AD的精确医学生物标志物。此外，数据、成果和知识 该项目的成果将被广泛分享，并成为研究界前所未有的资源。