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的防治研究 所需的知识和信息因领域、规模和时间而异。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 统计核心将继续满足这些关键需求，同时监督数据和统计分析 对于MADRC。数据类型包括临床/神经心理学指标、参与者招募/参与 指标、遗传学、神经病理学测量、神经成像和生物标志物数据，这些数据将由 DMSC。DMSC将继续确保数据符合增强的健康保险便携性， 符合《健康保险责任法案》（HIPAA）和国家标准与技术研究所（NIST）的保障措施， IRB合规性和数据安全性。DMSC与研究教育部分（REC）密切合作 协助，培训和支持初级教师成为独立的调查人员，提供一个 丰富的学习环境，以提高他们的统计和研究技能。的总体目标 DMSC将通过可复制的管道集成，共享和扩展数据，指导数据分析和培训 调查人员在这些过程中。与这些重要领域相对应，灾害管理安全理事会提出了五项建议， 具体目标：目标1：提供自动化、用户友好、集成和安全的数据收集， 目标2：提供可访问的、集成的、信息丰富的大数据和汇总分数， 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：在研究过程的每个阶段提供数据分析支持和咨询;目标5：提供 为MADRC调查人员提供丰富的环境，以扩展其数据可视化，分析和统计 知识DMSC将增强MADRC生成的全面和最先进的数据 通过通知简化的数据收集和数据集成的核心，我们的三个机构， 在NACC。在最初的融资期，我们成功地建立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（生物标志物和神经成像），我们将支持新的和正在进行的研究 运营DMSC的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的装备非常精良，以确保 MADRC为整个地区的创新研究、拓展和培训做出了开创性的贡献， 全国范围内。