Omics Phenotyping for Identifying Molecular Signatures of the Healthy and Failing Heart: An Integrated Data Science Platform

项目摘要/摘要 R35机制的建立证明了NHLBI领导层的远见和远见。显然， 这将为推动发现和增进人类健康提供无与伦比的机会。利用一种 22年的科学创新、培训和服务社会的记录，以及在 利用加州大学洛杉矶分校NIH BD2K卓越中心建立的技术基础，该应用程序 提出了一种多管齐下的策略，以确定驱动心脏表型的分子签名。这 应用程序解决了两个关键的生物医学挑战。首先，在我们如何处理这些问题上存在知识鸿沟 概念化蛋白质，包括它们如何与其他基因组相互作用，以及它们的动态如何有助于 功能表型。其次，缺乏用于系统联系的计算工具 表型和分子数据，心血管领域缺乏共享的信息管理 数据集和资源均可访问并可互操作以进行综合分析的环境。 因此，这款R35提出了两个突破新领域的重点领域。第一个重点领域将是 揭示心肌线粒体时空蛋白质组及其与代谢组和基因组的相互作用 信息驱动心脏表型。这涉及到技术平台的进步，以表征 心肌蛋白质、代谢物和通路的全球时空动力学，产生有价值的 来自模型系统和人类队列的分子数据集和优化的动力学模型，使全球 动态分析。第二个重点领域将是建立分析工具，以整合分子和 表型数据，并构建支持按需的原型心血管数据共享空间 数据、工具、资源和用户之间的交互。这些努力将使澄清 来自蛋白质组、代谢组、遗传变异和临床数据类型的相互关联的生物网络 通过一种新颖的混合模型回归算法。此外，这将产生新的组件 支持心血管医学领域的专业数据共享，包括新的API、图形用户 接口、云计算基础设施和数据管理管道。 综上所述，这款R35提出构建无缝数据采集和转换的数据生态系统 支持数据驱动的知识生产新模式的信息学平台。新发现将推动 NHLBI的任务向前推进，包括在模型系统和人类中揭示疾病的分子签名， 促进培养未来的生物医学专业人员，并将进展传播给科学 社区和公众通过一个专门的心血管公地，都在实现精准医疗。

PROJECT SUMMARY/ABSTRACT The inception of the R35 mechanism is a testament to the foresight and vision of NHLBI leadership. Clearly, this will provide unparalleled opportunities for driving discovery and enhancing human health. Capitalizing on a 22-year track record of scientific innovation, training and service to the community, as well as unique abilities in leveraging the technical foundation built by the NIH BD2K Center of Excellence at UCLA, this application presents a multi-pronged strategy for identifying molecular signatures that drive cardiac phenotypes. This application addresses two critical biomedical challenges. Firstly, there is a knowledge gap in how we conceptualize proteins, including how they interplay with other omes, and how their dynamics contribute to functional phenotypes. Secondly, there is an inadequacy of computational tools for systematically linking phenotypic and molecular data, and the cardiovascular community lacks a shared informatics management environment where both datasets and resources are accessible and interoperable for integrative analyses. Accordingly, this R35 proposes two areas of focus for breaking new ground. The first focus area will be to unveil how cardiac mitochondrial spatio-temporal proteomes and their interplay with metabolomic and genomic information drive cardiac phenotypes. This involves the advancement of technological platforms to characterize global spatio-temporal dynamics of cardiac proteins, metabolites, and pathways, producing both valuable molecular datasets from model systems and human cohorts and optimized kinetic models for enabling global dynamic analyses. The second focus area will be to build analytical tools for integrating molecular and phenotypic data, and to construct a prototypic cardiovascular data commons for supporting on-demand interactions among data, tools, resources, and users. These efforts will enable the elucidation of interconnected biological networks from proteomic, metabolomic, genetic variation, and clinical data types through a novel mixed model regression algorithm. Moreover, this will result in novel components for supporting a specialized data commons in cardiovascular medicine, including new APIs, graphical user interface, cloud-computing infrastructure, and data management pipeline. In summary, this R35 proposes to build a translational data ecosystem of seamless data acquisition and informatics platforms for enabling a new model of data-driven knowledge production. Discoveries will propel the NHLBI mission forward, including unveiling molecular signatures of disease in model systems and humans, fostering the training of future biomedical professionals, and disseminating advances to the scientific community and public via a specialized cardiovascular commons, all in the realization of precision medicine.