Analysis Core Rio Grande Valley AD-RCMAR

项目摘要-分析核心 预计到2050年，阿尔茨海默病(AD)患者的数量将增加近两倍。理解 恢复认知功能是改善患者生活和将灾难性的压力降至最低的关键 医疗保健系统、家庭和联邦预算。对阿尔茨海默病决定因素的认识 疾病风险和疾病后果构成了一个复杂的问题。的分析核心(ANC) 得克萨斯大学少数族裔老龄化研究资源中心(AD-RCMAR) (UTRGV)旨在支持项目，以检查这些大问题并增加我们的知识库 通过在多个层次上结合几种科学方法，对与年龄相关的认知能力下降进行研究。 拟议的AD-RCMAR将鼓励精神病学、神经学、行为科学、神经科学、 流行病学、遗传学、分子生物学、生物统计学、生物信息学等领域的研究重点 西班牙裔和其他少数族裔人群中AD的脆弱性。AD-RCMAR研究将通过以下方式进行 以人群为基础的流行病学、临床研究、动物模型和体外细胞系统。这个 可能的AD-RCMAR项目的广度和深度将产生对最先进分析的特殊需求 解决数据的纵向、高维和综合处理的方法， 和环境(即非遗传)水平，以及考虑因果关系域之间的相互作用。 拟议的非国大旨在通过向专家提供广泛的 能够与AD-RCMAR调查人员协作进行任何 需要特定的分析。计划所要求的拟议核心职能的总体重点 宣布，是关于跨多个广泛领域的数据集的综合分析，包括社交、 经济、行为、心理、生物和遗传因素。我们将通过以下途径实现目标： 具体目标如下：1)在AD-RCMAR项目中最大限度地进行交叉研究和跨模式分析， 我们将把老化的拉美裔/少数族裔的现有数据集整理并提供给一个中央存储库 托管在我们位于南得克萨斯糖尿病和肥胖研究所的高性能计算集群中，包括 2000名墨西哥人参与的脑结构和功能遗传学研究 美国家庭，由居住在委内瑞拉的约4500名拉美裔人组成的lMaracaibo老龄化研究， 以及Kolla人口研究，重点是阿根廷与世隔绝的安第斯人口，由约250人组成 个人；2)非国大将提供相关统计、统计遗传和统计方面的分析专门知识和培训 适用于复杂、多系统和高维数据的生物信息学方法 各种大型数据集的综合分析框架；3)非国大将传播科学信息 关于计量工具、新的方法学发展和由和/或产生的新数据资源 可用于AD-RCMAR。

Project Summary – Analysis Core The number of people living with Alzheimer's disease (AD) is expected to almost triple by 2050. Understanding and restoring cognitive function is critical to improving patients´ lives and minimize the catastrophic strains on the health care system, families, and the federal budget. The understanding of the determinants of Alzheimer’s disease risk and the consequences of disease constitutes a complex problem. The Analysis Core (AnC) of the AD Resource Center for Minority Aging Research (AD-RCMAR) at the University of Texas Rio Grande Valley (UTRGV) aims to support projects in order to examine these large problems and to add to our knowledge base about age-related cognitive decline by combining several scientific methodologies at multiple levels of analysis. The proposed AD-RCMAR will encourage faculty from psychiatry, neurology, behavioral science, neuroscience, epidemiology, genetics, molecular biology, biostatistics, bioinformatics and other areas to focus on the specific vulnerabilities of AD in Hispanic and other minority populations. AD-RCMAR research will be conducted through population-based epidemiology, clinical studies, and work with animal models, and in vitro cell systems. The breadth and depth of likely AD-RCMAR projects will generate particular needs for state-of-the-art analytic approaches that address longitudinal, high-dimensional, and integrative treatment of data at phenotypic, genetic, and environmental (i.e., non-genetic) levels as well as the consideration of interactions between causal domains. The proposed AnC is designed to meet these needs by providing access to experts with a broad range of complementary expertise who will be able to work collaboratively with AD-RCMAR investigators to conduct any needed specified analyses. The overall function of the proposed core focuses, as required by the program announcement, is on the integrative analysis of data sets across multiple broad domains including social, economic, behavioral, psychological, biological and genetic factors. We will achieve our objectives through the following Specific Aims: 1) to maximize cross-study and cross-modality analysis among AD-RCMAR projects, we will organize and make available existing data sets of aging Hispanics/minorities into a central repository hosted in our high performance compute cluster at the South Texas Diabetes and Obesity Institute including the Genetics of Brain Structure and Function Study with 2,000 participants who are members of large Mexican American families, the lMaracaibo Aging Study consisting of ~4,500 Hispanic individuals living in Venezuela, and the Kolla Population Study which focuses on an isolated Andean population in Argentina comprised of ~250 individuals; 2) the AnC will provide analytical expertise and training in relevant statistical, statistical genetic and bioinformatics methods appropriate for complex, multisystem and high dimensional data including a novel integrative analytical framework for diverse large data sets; 3) the AnC will disseminate scientific information regarding measurement tools, novel methodological developments and new data resources produced by and/or available to the AD-RCMAR.