Pan-Neurotrauma Data Commons

泛神经创伤数据共享

• 批准号: 10478255
• 负责人: ADAM R FERGUSON
• 金额: $ 73.85万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10478255
• 关键词: Adoption; Affect; Anatomy; Animal Model; Behavioral; Big Data; Big Data Methods; Brain; Certification; Collaborations; Common Data Element; Communities; Complex; Controlled Vocabulary; Data; Data Commons; Data Pooling; Data Set; Disease; Ecosystem; Educational workshop; FAIR principles; Feedback; Functional disorder; Future; Generations; Goals; Health; Healthcare; Heterogeneity; Human; Impairment; Individual; Infrastructure; Injury; International; Internet; Knowledge; Laboratories; Lead; Licensing; Medical; Metadata; Monitor; Multiple Trauma; Mus; National Institute of Neurological Disorders and Stroke; Nervous System Trauma; Neuraxis; Neurosciences; Ontology; Oranges; Outcome Assessment; Outcome Measure; Persons; Physiology; Police; Policies; Positioning Attribute; Predictive Value; Prevalence; Process; Publication Bias; Publications; Quality Control; Rattus; Recovery; Reporting; Reproducibility; Reproducibility of Results; Research; Research Personnel; Severities; Site; Spinal Cord; Spinal cord injury; Standardization; Structure; Syndrome; System; Terminology; Testing; Therapeutic; Tissue Expansion; Translations; Trauma; Traumatic Brain Injury; Traumatic CNS injury; Treatment Efficacy; U-Series Cooperative Agreements; United States National Institutes of Health; Visualization; Work; advanced analytics; base; body system; central nervous system injury; clinical implementation; clinically relevant; community engagement; complex data; dashboard; data complexity; data format; data interoperability; data management; data mining; data quality; data repository; data resource; data reuse; data sharing; data standards; data visualization; data wrangling; digital object identifier; diverse data; economic cost; economic impact; experience; experimental study; human data; improved; information framework; insight; interoperability; large scale data; neuroinformatics; new technology; novel; open data; open source; operation; pre-clinical; preservation; productivity loss; prospective; public repository; quality assurance; repaired; repository; skills; spinal cord and brain injury; success; symposium; therapeutic development; therapeutic evaluation; tool; trustworthiness; virtual laboratory; web portal; webinar

PROJECT SUMMARY/ABSTRACT Trauma to the central nervous system (CNS: spinal cord and brain) together affect more than 2.5 million people per year in the US, with economic costs of $80 billion in healthcare and loss-of-productivity. Yet, the precise pathophysiological processes impairing recovery remain poorly understood. This lack of knowledge is exacerbated by poor reproducibility of findings in animal models and limits translation of therapeutics across species and into humans. Part of the problem is that neurotrauma is intrinsically complex, involving heterogeneous damage to the central nervous system (CNS), by far the most complex organ system in the body. This results in a multifaceted CNS syndrome reflected across heterogeneous endpoints and multiple scales of analysis. Multi-scale heterogeneity makes traumatic brain injury (TBI) and spinal cord injury (SCI) difficult to understand using traditional analytical approaches that focus on a single endpoint for testing therapeutic efficacy. Single endpoint-testing provides a narrow window into the complex system of changes that describe SCI and TBI. Understanding these disorders involves managing datasets that include high volume anatomy data, high velocity physiology decision-support data, the high variety functional/behavioral data, and assessing correlations among these endpoints. In this sense, neurotrauma is fundamentally a data management problem that involves the classic ‘3Vs of big data’ (volume, velocity, variety). Of these, variety is perhaps the greatest data challenge in neurotrauma research for reproducibility in basic discovery, cross-species translation, and ultimately clinical implementation. For the proposed Data Repositories Cooperative Agreement (U24) we will build on our prior work managing data variety in the Open Data Commons for SCI (odc-sci.org) and TBI (odc-tbi.org) to make neurotrauma data Findable, Accessible, Interoperable, and Reusable (FAIR). The milestone-driven aims will: 1) further develop and harden our data lifecycle management system with end-to-end data version control and provenance tracking, data certification, and data citation; 2) develop in-cloud data dashboards and visualizations to monitor data quality and to promote data reuse, exploration, and hypothesis generation; 3) establish a pan- neurotrauma (PANORAUMA) data commons that brings together separate data assets currently supported by our multi-PI (MPI) team by aligning a patchwork of governance structures and policies. The goal of the proposed project is to develop a pooled repository for preclinical discovery, reproducibility testing, and translational discovery both within and across neurotrauma types. Our team is well-positioned to execute this project given that we developed some of the largest multicenter, multispecies neurotrauma data repositories of neurotrauma to-date (N>10,000 subjects 20,000 curated variables); the Neuroscience Information Framework (NIF); data terminologies and standards for these fields (MIASCI, NIFSTD); and policy work with the International Neuroinformatics Coordinating Facility (INCF). The PANORAUMA cooperative agreement is highly responsive to PAR-20-089, leveraging early successes in SCI and TBI data sharing to improve quality and sustainability.

项目概要/摘要 中枢神经系统（CNS：脊髓和大脑）创伤共同影响了超过 250 万人 美国每年在医疗保健和生产力损失方面造成的经济损失高达 800 亿美元。然而，准确的 损害康复的病理生理过程仍然知之甚少。这种知识的缺乏是 动物模型研究结果的重复性差加剧了这一问题，并限制了治疗方法的转化 物种并进入人类。部分问题在于神经创伤本质上很复杂，涉及 对中枢神经系统（CNS）的异质性损害，中枢神经系统是迄今为止体内最复杂的器官系统。 这导致了多方面的中枢神经系统综合症，反映在不同的终点和多个尺度上。 分析。多尺度异质性使得创伤性脑损伤（TBI）和脊髓损伤（SCI）难以识别 了解使用专注于单一终点的传统分析方法来测试治疗效果。 单一终点测试为了解描述 SCI 和 SCI 的复杂变化系统提供了一个狭窄的窗口。 创伤性脑损伤。了解这些疾病涉及管理数据集，其中包括大量解剖数据、高 速度生理学决策支持数据、多种功能/行为数据以及评估相关性 在这些端点之间。从这个意义上说，神经创伤从根本上来说是一个数据管理问题，涉及 经典的“大数据 3V”（容量、速度、多样性）。其中，多样性可能是最大的数据挑战 在神经创伤研究中，确保基础发现、跨物种翻译和最终临床的可重复性 执行。对于拟议的数据存储库合作协议（U24），我们将建立在我们之前的基础上 致力于管理 SCI (odc-sci.org) 和 TBI (odc-tbi.org) 开放数据共享中的数据多样性，以便 神经创伤数据可查找、可访问、可互操作和可重复使用 (FAIR)。里程碑驱动的目标将：1) 通过端到端数据版本控制进一步开发和强化我们的数据生命周期管理系统 溯源、数据认证和数据引用； 2）开发云中数据仪表板和可视化 监控数据质量并促进数据重用、探索和假设生成； 3）建立泛 神经创伤（PANORAUMA）数据共享，汇集了当前支持的单独数据资产 我们的多 PI (MPI) 团队通过调整治理结构和政策的拼凑而成。拟议的目标 该项目的目的是开发一个用于临床前发现、再现性测试和转化的汇集存储库 神经创伤类型内部和跨神经创伤类型的发现。我们的团队有能力执行这个项目 我们开发了一些最大的多中心、多物种神经创伤数据存储库 迄今为止（N>10,000 名受试者，20,000 个策划变量）；神经科学信息框架（NIF）；数据 这些领域的术语和标准（MIASCI、NIFSTD）；与国际组织的政策合作 神经信息学协调设施（INCF）。 PANORAUMA合作协议反应灵敏 PAR-20-089，利用 SCI 和 TBI 数据共享的早期成功来提高质量和可持续性。