Analysis Core

分析核心

• 批准号: 10730147
• 负责人: John Blangero
• 金额: $ 6.57万
• 依托单位: UNIVERSITY OF TEXAS RIO GRANDE VALLEY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10730147
• 关键词: Address; Advisory Committees; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Area; Behavior Therapy; Behavioral; Behavioral Sciences; Bioinformatics; Biological; Biological Markers; Biometry; Brain; Budgets; Caregivers; Caring; Collaborations; Communities; Complex; Data; Data Analyses; Data Set; Dementia; Development; Diabetes Mellitus; Discipline of Nursing; Disease; Doctor of Philosophy; Early Onset Alzheimer Disease; Environment; Epidemiology; Faculty; Family; Fostering; Funding; Genetic; Goals; Healthcare Systems; High Performance Computing; Hispanic Americans; Human Genetics; Infrastructure; Instruction; Integrative Therapy; Intervention; Intervention Studies; Ions; Leadership; Longitudinal cohort; Measurement; Mentors; Methodology; Methods; Mexican Americans; Mexico; Minority; Minority Groups; Modality; Molecular Biology; NIH Program Announcements; Neurology; Neurosciences; Obesity; Observational Study; Participant; Patients; Persons; Pharmacotherapy; Phenotype; Pilot Projects; Population; Poverty; Psychiatry; Research; Research Design; Research Personnel; Research Project Grants; Resources; Risk; Scientist; Social Work; Sociology; South Texas; Structure; System; Texas; Thinking; Training; Training Activity; Underrepresented Populations; Universities; base; behavioral and social science; career; cluster computing; cognitive function; data resource; design; education research; experience; high dimensionality; high risk; improved; interest; large datasets; medical schools; member; method development; minority investigator; multidimensional data; non-genetic; novel; pharmacologic; professor; programs; recruit; repository; research study; risk stratification; skills; social; social interventions; social science research; therapy development; tool

Project Summary – Analysis Core The number of people living with Alzheimer's disease (AD) and AD-related dementias (AD/ADRD) is expected to almost triple by 2050. In the US, Hispanic Americans will comprise an ever-larger fraction of this population, as their numbers are increasing, and they have higher risk for and earlier onset of AD/ADRD. Despite much effort and funding to focused on developing effective drug therapies, breakthroughs remain challenging. An urgent need persists to develop efficient social and behavioral interventions to support people living with dementia and their caregivers. Also, there is a need to refine AD/ADRD risk stratification and responsiveness to treatments. A key barrier to understanding how complex social/behavioral structures impact aging of Hispanic Americans is that they are vastly underrepresented both in the research workforce and as participants in research studies. To overcome these challenges, the Analysis Core (AnC) of the Rio Grande Valley (RGV) AD/ADRD Resource Center for Minority Aging Research (AD/ADRD-RCMAR) at the University of Texas Rio Grande Valley (UTRGV) will support high-quality, cutting-edge research in priority areas of behavioral and social science research on AD/ADRD by RCMAR scientists, focusing on Hispanic Americans, and particularly Mexican Americans of the impoverished US-Mexico border region in Texas. The breadth and depth of AD/ADRD-RCMAR projects require state-of-the-art analytic approaches that enable longitudinal, high- dimensional, and integrative analyses of data at the phenotypic, genetic, and environmental levels to exploit relevant biomarkers and biological risk determinants that can point to interacting factors that may be targets for interventions. The AnC will conduct such analyses for AD/ADRD-RCMAR scientists and further meet the field’s needs by providing instructional higher-order analytical skill-building and technical training to fully prepare a cadre of diverse minority early career stage investigators. The AnC, led by experts with a broad range of complementary expertise, will serve as a critical mechanism for maximizing rigor and impact of the research conducted by AD/ADRD RCMAR scientists. For the new funding cycle, we will achieve our objectives via the following Specific Aims: 1) Provide analytical expertise and training in relevant statistical and bioinformatics methods appropriate for complex, multisystem, and high dimensional data, including a novel integrative analytical framework for diverse large data sets. 2) Maximize cross-study and cross-modality analyses among all AD/ADRD-RCMARs’ projects by organizing and make available existing data sets on aging Mexican Americans residing in South Texas into a central repository hosted in our high-performance computing cluster. 3) Disseminate scientific information on measurement tools, novel methodological developments, and new data resources produced by and/or available to the AD/ADRD-RCMAR. Unique strengths of the RGV AnC include experienced core leaders, a rich training and mentoring environment, the ability to foster careers of minority investigators, and access to longitudinal cohorts of Mexican Americans.

项目摘要-分析核心 预计阿尔茨海默病（AD）和AD相关痴呆（AD/ADRD）患者人数 到2050年几乎翻三倍。在美国，西班牙裔美国人将在这一人口中占据越来越大的比例， 随着其数量的增加，他们患AD/ADRD的风险更高，发病更早。尽管有许多 尽管我们的努力和资金都集中在开发有效的药物疗法上，但取得突破仍然具有挑战性。一个 迫切需要持续发展有效的社会和行为干预措施，以支持患有 痴呆症及其护理人员。此外，还需要完善AD/ADRD风险分层和反应性 到治疗。理解复杂的社会/行为结构如何影响老龄化的一个关键障碍是， 西班牙裔美国人的问题是，他们在研究人员和参与者中的代表性都大大不足 在研究中。为了克服这些挑战，格兰德河流域（RGV）的分析核心（AnC） AD/ADRD少数民族老龄化研究资源中心（AD/ADRD-RCMAR）在得克萨斯州里约大学 格兰德谷（UTRGV）将支持高质量，尖端的研究在行为和行为的优先领域， RCMAR科学家对AD/ADRD的社会科学研究，重点是西班牙裔美国人，特别是 墨西哥裔美国人生活在德克萨斯州的贫困的美墨边境地区。的广度和深度 AD/ADRD-RCMAR项目需要采用最先进的分析方法， 在表型、遗传和环境水平上对数据进行多维和综合分析， 相关的生物标志物和生物风险决定因素，可以指向相互作用的因素，可能是目标， 干预措施。AnC将为AD/ADRD-RCMAR科学家进行此类分析，并进一步满足该领域的需求。 通过提供指导性的高阶分析技能建设和技术培训， 不同少数民族早期职业生涯阶段的调查人员骨干。AnC由专家领导，拥有广泛的 互补的专业知识，将作为一个关键机制，最大限度地提高研究的严谨性和影响力 由AD/ADRD RCMAR科学家进行。在新一轮拨款中，我们会透过 1）提供相关统计和生物信息学方面的分析专业知识和培训 方法适用于复杂的，多系统的，高维数据，包括一个新的综合 为不同的大型数据集提供分析框架。2)最大限度地提高跨研究和跨模态分析， 所有AD/ADRD-RCMARs的项目，组织和提供现有的数据集， 美国人居住在南德克萨斯州到一个中央存储库托管在我们的高性能计算集群。 3)传播关于测量工具、新方法发展和新数据的科学信息 由AD/ADRD-RCMAR制作和/或可供AD/ADRD-RCMAR使用的资源。RGV AnC的独特优势包括 经验丰富的核心领导者，丰富的培训和指导环境，培养少数民族职业的能力 调查人员，并获得纵向队列的墨西哥裔美国人。