A data resource for high resolution neuropathological and omics analysis of Alzheimer's disease

用于阿尔茨海默病高分辨率神经病理学和组学分析的数据资源

• 批准号: 10375359
• 负责人: AMY BERNARD
• 金额: $ 133.24万
• 依托单位: ALLEN INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10375359
• 关键词: Address; Aging; Alzheimer' s Disease; Alzheimer' s disease pathology; Anatomy; Atlases; BRAIN initiative; Biological; Brain; Cells; Censuses; Clinical; Clinical Data; Clinical Research; Cognition Disorders; Communities; Community Developments; Complex; Computer software; Custom; Data; Data Analyses; Data Display; Data Management Resources; Data Reporting; Data Set; Data Storage and Retrieval; Data Store; Databases; Dementia; Dimensions; Epigenetic Process; Equipment and supply inventories; Feedback; Foundations; Funding; Future; Gene Expression; General Population; Generations; Goals; Growth; Histologic; Human; Image; In Vitro; Information Dissemination; Infrastructure; Institutes; Institution; Internet; Knowledge; Laboratories; Machine Learning; Management Information Systems; Maps; Metadata; Methodology; Methods; Modality; Molecular; Molecular Profiling; Mus; Nature; Neurobiology; Neurons; Neurosciences; Ontology; Output; Pathologic; Patients; Preparation; Process; Reference Standards; Research; Research Design; Research Personnel; Research Project Grants; Resolution; Resources; Science; Scientist; Semantics; Services; Structure; Surveys; System; Taxonomy; Techniques; Tissues; Training; Traumatic Brain Injury; United States National Institutes of Health; Visualization; analysis pipeline; arm; base; brain cell; cell type; cohort; computerized data processing; computing resources; data access; data acquisition; data centers; data exchange; data framework; data harmonization; data infrastructure; data ingestion; data integration; data interoperability; data management; data portal; data repository; data resource; data sharing; data standards; data tools; data visualization; design; epigenomics; feature extraction; hackathon; in vivo; large scale data; member; multimodality; neuropathology; nonhuman primate; novel; outreach; research study; scaffold; single cell analysis; synergism; systems research; tool; tool development; transcriptomics; unsupervised learning; usability; web portal; web-accessible; web-based tool; webinar

ABSTRACT (DATA CORE) The Allen Institute has demonstrated a tradition of excellence by creating data frameworks to support the dissemination of biological data and analysis tools for the research community. The Allen Brain Atlas data portal (http://www.brain-map.org) is a comprehensive data navigation platform, containing gene expression, brain connectivity, reference atlases and characterization of in vitro and in vivo neuronal cells from multiple species, including human, mouse and non-human primate. The AD Data Core will build on this foundation, to provide centralized data integration and presentation solutions for large-scale data sets derived from the AD Center consortium. The AD Data Core will also form partnerships with other centers and user groups, to maximize impact of the rich data being generated through the AD cell characterization projects. New tools for detailed molecular and spatial analysis of single cells are revolutionizing our understanding of the brain, but the power of emerging techniques has not yet been applied to characterize neuropathology in Alzheimer’s disease (AD). This proposal aims to address this gap by using transcriptomic, epigenetic and multiplex molecular spatial analysis methods to characterize AD pathology at the level of cell types. A centralized and managed approach to collecting, storing, processing, annotating, analyzing and sharing the data is essential. Successful integration will yield a foundational data set depicting a molecular profile of AD, and the AD Data Core will serve results to the community via a catalytic open web portal. The AD Data Core will also leverage methods being developed by major single cell profiling initiatives, to benefit AD research. The Allen Institute for Brain Science, NIH BRAIN Initiative Cell Census Network (BICCN) and the Human Cell Atlas (HCA) have funded complementary efforts to characterize nonpathological brain at the cellular level, including a Brain Cell Data Center (BCDC), which the AD Data Center proposal is designed to synergize with. The expertise and methodological tools required to build the BCDC have been developed by many members of the team proposed for the AD Data Core. Utilization of an existing, rigorous collaborative effort offers great economy to the process of building out an “arm” of cellular profiling capability for AD. Best practices that have been developed for maximizing data usability can now be brought to AD research with this project. Synergy with these cell profiling initiatives offers opportunity to accelerate AD research progress by leveraging content from other cell-centirc databases and corresponding analysis methods. The proposed AD Data Core will also be an end-to-end platform that can accommodate future scale, such as growth of patient cohorts, new data modalities, and additional clinical dimensions of AD or related cognitive disorders. Finally, the AD Core will engage with clinical and research communities through accessible web-based tools for data navigation, and dissemination of information through outreach approaches such as forums, hackathons and informational narratives.

摘要（数据核心） 艾伦研究所通过创建数据框架来支持 为研究界传播生物数据和分析工具。 （http://www.brain-map.org）是一个综合性数据导航平台，包含基因表达、大脑 来自多个物种的体外和体内神经细胞的连接性、参考图集和表征， AD 数据核心将在此基础上建立，包括人类、小鼠和非人类灵长类动物。 来自AD中心的大规模数据集的集中数据集成和呈现解决方案 AD 数据核心还将与其他中心和用户团体建立合作伙伴关系，以最大限度地发挥作用。 通过 AD 细胞表征项目生成的丰富数据的影响。 用于单细胞详细分子和空间分析的新工具正在彻底改变我们的理解 大脑，但新兴技术的力量尚未应用于表征神经病理学 该提案旨在通过转录组学、表观遗传学和 多重分子空间分析方法在细胞类型水平上表征 AD 病理学。 收集、存储、处理、注释、分析和共享数据的管理方法至关重要。 成功的整合将产生一个描述 AD 分子概况的基础数据集，以及 AD 数据 核心将通过催化开放网络门户向社区提供结果，AD 数据核心也将利用这一点。 主要单细胞分析计划正在开发的方法，有利于艾伦研究所的研究。 脑科学、NIH BRAIN 倡议细胞普查网络 (BICCN) 和人类细胞图谱 (HCA) 已资助 补充以在细胞水平上表征非病理性大脑活动，包括脑细胞数据 中心（BCDC），AD 数据中心提案旨在与之协同。 提议的团队的许多成员已经开发了建立 BCDC 所需的方法工具 利用现有的、严格的协作努力为流程提供了巨大的经济性。 为 AD 开发最佳实践的细胞分析功能“手臂”。 现在可以通过该项目将数据可用性最大化，并与这些细胞分析相结合。 倡议提供了利用其他以细胞为中心的内容来加速 AD 研究进展的机会 所提出的AD数据核心也将是一个端到端的。 可以适应未来规模的平台，例如患者群体的增长、新的数据模式和 AD 或相关认知障碍的其他临床维度最后，AD 核心将涉及临床。 和研究界通过可访问的网络工具进行数据导航和传播 通过论坛、黑客马拉松和信息叙述等外展方式提供信息。