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 预防和治疗异质性阿尔茨海默氏病和相关痴呆症（ADRD）的研究 需要随着域，规模和时间而变化的知识和信息。那是满足的挑战 ADRD有必要的大数据跨学科，共享数据和整个密歇根州的协作 阿尔茨海默氏病研究中心（MADRC）和整个ADRC网络，部署适当 静态模型，以及对数据方法和统计的科学家的培训。 MADRC数据管理和 统计核心（DMSC）将继续满足这些关键需求，因为IT海外数据和统计分析 对于马德克。数据类型包括临床/神经心理学措施，参与者招募/参与 指标，遗传学，神经病理学措施，神经影像学和生物标志物数据将由该数据集成 DMSC。 DMSC将继续确保数据符合增强的健康保险可移植性和 责任法（HIPAA）合规性和国家研究所标准与技术（NIST）保障措施， IRB合规性和数据安全性。 DMSC与研究教育部分紧密合作（REC） 通过提供，培训和支持初级教职员工成为独立调查员 丰富的学习环境以提高其统计和研究技能。总体目标 DMSC将通过可重复的管道，指导数据分析和培训整合，共享和扩展数据 这些过程中的研究人员。与这些重要性相对应，DMSC提案五 具体目的：目标1：提供自动化，用户友好，集成和安全的数据收集，以及 管理平台；目标2：提供可访问，集成和信息丰富的大数据和摘要分数 MADRC研究需求； AIM 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 MADRC调查人员的丰富环境扩展其数据可视化，分析和统计 知识。 DMSC将增强MADRC生成的全面和最新数据 核心通过跨核心，我们的三个机构以及 与NACC。在最初的资金期间，我们成功地构建了一个可重复的数据库平台 将历史人群信息与新的纵向参与信息相结合。我们将扩大我们的活动 支持两个新的核心（生物标志物和神经影像学），我们将支持新的和正在进行的研究 运营。 DMSC活动将增强整个社区的研究合作和分析培训 ADRD研究人员。在我们经验丰富的团队的情况下，DMSC的设备齐全，以确保 Madrc为整个地区的创新研究，外展和培训做出了第二贡献 全国。