Novel Integration of Multidimensional Data from an Emerging Model of Aging

描述（由申请人提供）：推进我们对老龄化中社会和行为影响的理解将越来越需要整合复杂且通常不同的数据集。为了测量这些影响，研究人员必须管理关于死亡率和生育率的人口统计数据，关于社会关系的行为或调查数据，以及越来越多的捕获遗传和生理变异的生物标志物数据。目前，现存的数据库旨在促进复杂的人口和社会行为数据或复杂的遗传和基因组数据的分析：满足整合所有这些数据类型的挑战的数据库还不存在。因此，研究界并没有充分利用这些数据集来了解衰老。此外，我们缺乏如何将这些数据类型以内聚和可访问的方式容纳在一起的模型。我们建议通过建立现有的野生灵长类动物数据库来开发这样一个模型，该数据库包含基于个体的多维纵向表型数据，这些数据已经被证明对研究社会和行为对衰老的影响很有价值。我们还拥有越来越多的关于同一个体的互补遗传和基因组数据，包括候选基因和全基因组重测序、基因表达和表观遗传数据集，这些数据集有望捕捉整个生命过程中的生理变化。在拟议的工作中，我们将为这些多维数据集提供集中的，集成的档案存储，在个人层面上创建遗传和表型信息的无缝集成，并提供一个急需的，有据可查的模型。我们还将与国家老龄化计算机数据档案馆（NACDA）合作，建立与该领域其他研究人员共享这些数据的机制。具体来说，我们建议（1）建立数据库模块，以容纳我们不断扩大的多维遗传和基因组数据集，（2）将这些新的遗传学和基因组学模块与我们现有的数据库（BABASE）以及相互链接，以整合我们的遗传和表型信息，以及（3）创建一个BABASE的公共门户网站，允许开放访问数据库遗传学/基因组学模块的所有组件，以及对表型数据中与衰老相关的关键组成部分的开放访问; 2该门户将通过NACDA访问。我们的新遗传模块将借鉴Chado（通用模式生物数据库项目（GMOD）的一个分支）开创的数据库模块设计。总之，这些努力将为这些有价值的数据集提供重要的档案存储，提高数据分析的效率，并促进新的协同研究方向，包括与外部研究人员的合作，使我们能够更深入地了解自然哺乳动物种群的衰老。此外，由于BABASE及其新扩展的所有代码都将是开源的，因此拟议的工作将为其他专注于老龄化的人口研究如何实现类似目标提供模型。

DESCRIPTION (provided by applicant): Advancing our understanding of social and behavioral effects in aging will increasingly require the integration of complex and often disparate data sets To measure such effects, investigators must manage demographic data on mortality and fertility, behavioral or survey data on social relationships, and, increasingly, biomarker data tha capture genetic and physiological variation. Currently, extant databases are designed to facilitate analysis of complex demographic and sociobehavioral data or complex genetic and genomic data: databases that meet the challenge of integrating all of these data types do not yet exist. Consequently, the research community is not reaping the full benefits of these data sets for understanding aging. Further, we lack models for how to house these data types together in a cohesive and accessible fashion. We propose to develop such a model by building on an existing database on wild primates that houses individual-based multidimensional, longitudinal phenotypic data that have already proved valuable for studies of social and behavioral effects on aging. We also have a growing set of complementary genetic and genomic data on the same individuals, including candidate gene and whole genome resequencing, gene expression, and epigenetic data sets that promise to capture physiological changes across the life course. In the proposed work, we will provide centralized, integrated archival storage for these multidimensional data sets, create a seamless integration of genetic and phenotypic information at the individual level, and provide a much needed, well documented model of such an integration. We will also work with the National Archive of Computerized Data on Aging (NACDA) to build mechanisms for sharing these data with other researchers in the field. Specifically, we propose to (1) build database modules to house our expanding multi-dimensional genetic and genomic data sets, (2) link these new genetics and genomics modules to our existing database (BABASE) and to each other, to integrate our genetic and phenotypic information, and (3) create a public portal to BABASE that will allow open access to all components of the genetics/genomics modules of the database, as well as open access to key aging- related components of the phenotypic data; this portal will be accessible through NACDA. Our new genetic modules will draw on database module designs pioneered by Chado, a branch of the Generic Model Organism Database project (GMOD). Together, these efforts will provide important archival storage for these valuable data sets, increase the efficiency of data analysis, and promote new, synergistic research directions, including collaborations with outside investigators that will allow us to gain deeper insights into aging in natural mammal populations. In addition, because all the code underlying BABASE and its new extensions will be open source, the proposed work will produce models for how other population studies focused on aging can achieve similar goals.