Core C: Data Management and Statistical Core

核心C：数据管理与统计核心

• 批准号: 10261111
• 负责人: Kelly Marie Bakulski
• 金额: $ 36.51万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 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 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10261111
• 关键词: Alzheimer' s Disease; Alzheimer' s disease related dementia; Applications Grants; Area; Big Data; Bioinformatics; Biological Markers; Characteristics; Clinical; Collaborations; Communication; Communities; Complex; Consultations; Custom; Data; Data Analyses; Data Collection; Data Security; Database Management Systems; Databases; Development; Discipline; Ensure; Epidemiology; Exposure to; Faculty; Funding; Generations; Genetic; Genomics; Goals; Grant; Health Insurance Portability and Accountability Act; Institutes; Institution; Institutional Review Boards; International; Knowledge; Link; Machine Learning; Magnetic Resonance Imaging; Measures; Methods; Michigan; Neuropsychology; Operations Research; Participant; Pathologic; Patient Recruitments; Phenotype; Prevention; Procedures; Process; Proteomics; Reproducibility; Research; Research Personnel; Risk Factors; Scientist; Secure; Seminal; Statistical Data Interpretation; Statistical Models; Techniques; Technology; Telemedicine; Time; Training; Training Support; Visit; Work; base; cohort; complex data; data integration; data integrity; data management; data pipeline; data sharing; data visualization; design; education research; educational atmosphere; electronic data; environmental enrichment for laboratory animals; experience; flexibility; imaging biomarker; improved; innovation; investigator training; meetings; member; multiple data sources; multiple omics; neuroimaging; neuroimaging marker; neuropathology; next generation; outreach; polygenic risk score; query tools; skills; statistics; training opportunity; user-friendly

ABSTRACT – CORE C: DATA MANAGEMENT AND STATISTICAL CORE Research on prevention and treatment of heterogeneous Alzheimer’s disease and related dementias (ADRD) requires knowledge and information that varies by domain, scale and time. Thus, meeting the challenge of ADRD necessitates big data integrated across disciplines, shared data and collaboration across the Michigan Alzheimer’s Disease Research Center (MADRC) and the entire ADRC network, deployment of appropriate statistical models, and training of scientists in data methods and statistics. The MADRC Data Management and Statistical Core (DMSC) will continue to meet these critical needs as it oversees data and statistical analyses for the MADRC. Data types include clinical/neuropsychological measures, participant recruitment/engagement metrics, genetics, neuropathologic measures, neuroimaging, and biomarker data that will be integrated by the DMSC. The DMSC will continue to ensure that the data meet enhanced Health Insurance Portability and Accountability Act (HIPAA) compliance and National Institute Standards and Technology (NIST) safeguards, IRB compliance and data security. The DMSC works closely with the Research Education Component (REC) to assist, train and support junior faculty members in becoming independent investigators by providing an enriched learning environment to increase their statistical and research skills. The overarching goals of the DMSC are to integrate, share, and scale data through reproducible pipelines, guide data analyses, and train investigators in these processes. Corresponding to these areas of importance, the DMSC proposes five Specific Aims: Aim 1: Provide an automated, user friendly, integrated, and secure data collection and management platform; Aim 2: Provide accessible, integrated, and informative big data and summary scores for MADRC research needs; Aim 3: Share data, pipelines, and analytic expertise with NACC and related Centers; Aim 4: Provide data analysis support and consultation at every stage of the research process; Aim 5: Provide an enriched environment for MADRC investigators to expand their data visualization, analytical, and statistical knowledge. The DMSC will enhance the comprehensive and state-of-the-art data generated by the MADRC Cores by informing streamlined data collection and data integration across Cores, our three institutions, and with the NACC. In the initial funding period, we succeeded in building a reproducible database platform that combined historic cohort information with new longitudinal participant information. We will expand our activities to support two new Cores (Biomarker and Neuroimaging) and we will support new and ongoing research operations. DMSC activities will enhance research collaboration and analytic training across the community of ADRD researchers. With our highly experienced team, the DMSC is exceptionally well-equipped to ensure that the MADRC makes seminal contributions to innovative research, outreach, and training across the region and nationally.

摘要 – 核心 C：数据管理和统计核心 异质性阿尔茨海默病及相关痴呆（ADRD）的防治研究 需要因领域、规模和时间而异的知识和信息。因此，迎接挑战 ADRD 需要跨学科集成大数据、共享数据和整个密歇根州的协作 阿尔茨海默病研究中心 (MADRC) 和整个 ADRC 网络，部署适当的 统计模型，以及对科学家进行数据方法和统计方面的培训。 MADRC 数据管理和 统计核心 (DMSC) 将继续满足这些关键需求，因为它负责监督数据和统计分析 对于 MADRC。数据类型包括临床/神经心理学测量、参与者招募/参与 指标、遗传学、神经病理学测量、神经影像学和生物标志物数据将由 DMSC。 DMSC 将继续确保数据满足增强的健康保险可移植性和 责任法案 (HIPAA) 合规性和国家标准与技术研究所 (NIST) 保障措施， IRB 合规性和数据安全。 DMSC 与研究教育部门 (REC) 密切合作 通过提供 丰富的学习环境，以提高他们的统计和研究技能。该组织的总体目标 DMSC 将通过可重复的管道集成、共享和扩展数据，指导数据分析并培训 这些过程中的调查员。对应于这些重要领域，DMSC提出了五个 具体目标： 目标 1：提供自动化、用户友好、集成且安全的数据收集和 管理平台；目标 2：提供可访问的、集成的、信息丰富的大数据和总结分数 MADRC 研究需求；目标 3：与 NACC 和相关中心共享数据、管道和分析专业知识； 目标4：在研究过程的各个阶段提供数据分析支持和咨询；目标 5：提供 为 MADRC 研究人员提供丰富的环境，以扩展他们的数据可视化、分析和统计 知识。 DMSC 将增强 MADRC 生成的全面且最先进的数据 通过告知核心、我们的三个机构和核心之间的简化数据收集和数据集成 与 NACC 合作。在最初的资助期间，我们成功地构建了一个可复制的数据库平台， 将历史队列信息与新的纵向参与者信息相结合。我们将扩大我们的活动 支持两个新的核心（生物标记和神经影像），我们将支持新的和正在进行的研究 运营。 DMSC 活动将加强整个社区的研究合作和分析培训 ADRD 研究人员。凭借我们经验丰富的团队，DMSC 装备精良，可确保 MADRC 为整个地区的创新研究、推广和培训做出了开创性贡献 全国范围内。