Network and Systems Biology Scientific Core 3

网络与系统生物学科学核心 3

• 批准号: 10646354
• 负责人: John Barnard
• 金额: $ 23.79万
• 依托单位: CLEVELAND CLINIC LERNER COM-CWRU
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10646354
• 关键词: Age; Arrhythmia; Atrial Fibrillation; Biological Assay; Cell Nucleus; Clinical; Data; Detection; Diagnosis; Disease; Doctor of Philosophy; Gene Expression; Genes; Genetic; Genomics; Goals; Heart Atrium; Human Resources; Incidence; Kinetics; Knowledge; Lead; Metabolic; Modeling; Molecular; Obesity; Outcome; Population; Process; Proteins; Proteomics; RNA; RNA Processing; Reproducibility; Research Institute; Research Personnel; Risk; Sample Size; Sampling; Services; Stroke; Study models; Systems Biology; Therapeutic; Visualization; Work; cardiovascular risk factor; cell type; clinical application; differential expression; drug discovery; experience; flexibility; genome wide association study; metabolomics; mortality; network models; power analysis; single nucleus RNA-sequencing; skills; success; therapeutically effective; trait; transcriptome sequencing; transcriptomics

SC3 PROJECT SUMMARY Atrial fibrillation (AF) is the most common arrhythmia and a major risk factor for cardiovascular mortality and stroke. Incidence of AF is further increasing due to the rise in obesity and age of the population, factors closely related to AF risk and progression. Despite significant advances in AF diagnosis and management, treatment and clinical outcomes remain poor and more than a decade has passed since the last AF drug discovery. The overall goal of this PPG application is to use genomic and transcriptomic findings to identify preventative and therapeutic strategies for AF and develop them towards clinical application. Our central hypothesis is that increasing our knowledge about molecular mechanisms involved in genetic, transcriptomic, metabolic and structural changes in the atria will allow us to pinpoint possible targets for safer and more effective therapeutic strategies. To help the projects advance towards these goals, the Network and Systems Biology Core (SC3) will be responsible for the processing, analysis, integration and network modeling of all RNA sequencing data, including bulk and single nuclei, proteomic, metabolomics, and functional assay data used and generated in the four projects. All Projects have proposed extensive use of RNA sequencing studies, making SC3 integral to their success. Functional assay data will be generated primarily in SC1 and SC2 under direction of the Projects and then sent to SC3 for analysis and integration with RNASeq. SC3 will work closely with the project leads and personnel to help interpret and visualize the results including those from traditional differential analyses as well as from more advanced network and systems biology approaches. SC3 has a unique blend of expertise and experience, combining personnel with RNA processing and modeling skills and those with a network and systems biology focus, which together with a rigorous and reproducible pipeline implementation will help enable the four projects in this PPG to fill knowledge gaps and make advances towards understanding and treating atrial fibrillation. SC3 will provide two major groups of services to the PPG organized around the type of data being analyzed. Aim 1 will focus on services for RNA sequencing data, including advanced network and systems biology approaches, while Aim 2 will focus on services for functional assay data as well as integrations with the RNA data.

SC3 项目概要 心房颤动（AF）是最常见的心律失常，也是心血管死亡和死亡的主要危险因素。 中风。由于肥胖和人口老龄化的增加，房颤的发病率进一步增加，这些因素密切相关 与 AF 风险和进展有关。尽管 AF 诊断和管理取得了重大进展，但治疗方法 临床结果仍然很差，距离上次发现 AF 药物已经过去十多年了。这 该 PPG 应用程序的总体目标是利用基因组和转录组学发现来识别预防性和 AF 的治疗策略并将其开发为临床应用。我们的中心假设是 增加我们对涉及遗传、转录组、代谢和代谢的分子机制的了解 心房的结构变化将使我们能够确定可能的目标，以实现更安全、更有效的治疗 策略。为了帮助项目实现这些目标，网络和系统生物学核心 (SC3) 将负责所有RNA测序数据的处理、分析、整合和网络建模， 包括使用和生成的大量和单核、蛋白质组学、代谢组学和功能分析数据 四个项目。所有项目都提议广泛使用 RNA 测序研究，使 SC3 成为不可或缺的一部分 他们的成功。功能分析数据将主要在 SC1 和 SC2 的指导下生成 项目然后发送到 SC3 进行分析并与 RNASeq 集成。 SC3将与该项目密切合作 领导和人员帮助解释和可视化结果，包括传统差分结果 分析以及更先进的网络和系统生物学方法。 SC3 具有独特的混合 专业知识和经验，将具有 RNA 处理和建模技能的人员与具有 网络和系统生物学重点，以及严格且可重复的管道实施 将有助于使本 PPG 中的四个项目能够填补知识空白并促进理解 和治疗心房颤动。 SC3 将为 PPG 提供两大类服务： 正在分析的数据类型。目标 1 将重点关注 RNA 测序数据服务，包括先进的 网络和系统生物学方法，而 Aim 2 也将重点关注功能分析数据服务 与 RNA 数据的整合。