Precision Medicine Core

项目总结：精密医学核心 精准症状自我管理中心（PriSSM）的目标是推进以下科学： 症状自我管理的拉丁美洲人通过社会生态透镜，考虑到变异， 个人、人际、组织和环境因素贯穿整个生命过程。范围内 PriSSM中心的总体具体目标，精准医学核心的目标是： 1.建立、完善和维护精准医学的核心社会技术基础设施， 收集和/或检索、存储、分析、解释和集成多个数据源， 支持中心（a）设计和实施六个症状自我管理试点项目，以及（B） 创建和维护一个通用数据元素注册表，适合与美国国家科学院共享。 健康和其他， 2.扩大和利用现有的机构“组学”数据资源，包括哥伦比亚基因组学 与Ehr（GENIE）虚拟生物库集成， 3.为试点项目研究者和其他中心研究者提供以下方面的专业知识和指导 选择数据源（基因组和其他生物标志物，临床，症状自我报告，自我量化， 环境）和分析方法（生物统计学，统计遗传学，数据科学） 自我管理和 4.支持数据科学组件的实施（例如，网络分析，主题建模） 形成性和总结性评估计划。 为了实现这些目标，精准医学核心整合了与各种 数据源（基因组和其他生物标志物、临床、症状自我报告、自我量化、环境） 和分析方法（生物统计学，统计遗传学，数据科学）。联邦信息体系结构 支持使用多个数据源和工具对社会生态模型进行实例化， 基因型和表型的表征，确定干预目标的精确度， 干预精准医学核心是创新的，其重点是拉丁美洲人谁在遗传差异显着 祖先以及文化背景，并在使用哥伦比亚GENIE虚拟生物库定位 试点项目的现有“组学”数据资源。所提出的精确方法将推动科学 症状自我管理的方式与美国国立卫生研究院 症状管理模式。

PROJECT SUMMARY: PRECISION MEDICINE CORE The goal of the Precision in Symptom Self-Management (PriSSM) Center is to advance the science of symptom self-management for Latinos through a social ecological lens that takes into account variability in individual, interpersonal, organizational, and environmental factors across the life course. Within the context of the overall specific aims of the PriSSM Center, the aims of the Precision Medicine Core are to: 1. Establish, refine, and maintain the Precision Medicine Core sociotechnical infrastructure for the collection and/or retrieval, storage, analysis, interpretation, and integration of multiple data sources to support the Center to (a) design and implement six symptom self-management pilot projects and (b) to create and maintain a common data element registry suitable for sharing with the National Institutes of Health and others, 2. Expand and leverage existing institutional “omics” data resources including the Columbia GENomic Integration with Ehr (GENIE) virtual biobank, 3. Provide expertise and guidance to Pilot Project investigators and other Center investigators on selection of data sources (genomic and other biomarkers, clinical, symptom self-reports, quantified-self, environmental) and analytic approaches (biostatistics, statistical genetics, data science) for symptom self-management, and 4. Support the implementation of the data science components (e.g., network analysis, topic modeling) of the formative and summative evaluation plan. To achieve these aims, the Precision Medicine Core integrates expertise and resources related to variety of data sources (genomic and other biomarkers, clinical, symptom self-reports, quantified-self, environmental) and analytic approaches (biostatistics, statistical genetics, data science). A federated information architecture supports instantiation of the Social Ecological Model with multiple data sources and tools to enable precision in characterization of genotype and phenotype, precision in identification of intervention targets, and precision in intervention. The Precision Medicine Core is innovative in its focus on Latinos who vary significantly in genetic ancestry as well as cultural background and in the use of the Columbia GENIE Virtual Biobank to locate existing “omics” data resources for pilot projects. The proposed precision approaches will advance the science of symptom self-management for Latinos in a manner consistent with the National Institutes of Health Symptom Management Model.