Cohort Core

项目摘要 射血分数正常的心力衰竭（HF）是一种异质性、多方面的综合征， 是精准医疗应用的理想场所。HFpEF已被证明对传统的 研究其潜在的病理生理学和进行随机临床试验的技术。新 因此，正如最近发表的一篇白色论文所指出的， 总结了NHLBI工作组对HFpEF研究优先事项的审议。国家 科学院精准医学报告提出，"当多个分子指标用于 结合常规的临床、组织学和实验室检查结果，它们提供了更多的机会， 准确和精确的疾病描述和分类"。这一范例也得到了NHLBI的支持， 战略愿景，它认为，一个组合的组学（例如，基因组学、蛋白质组学和代谢组学）， 再加上临床和生理数据，将是必要的，以促进了解的病理生物学 HFpEF等复杂临床综合征的基础，并提供了HeartShare的基本原理。 精准医疗的前景在于数据的多样性。不仅仅是生物医学数据的庞大规模， 多种数据模式的分层，提供互补的视角，这将有助于确定 具有共同病理生理学的患者亚组。HeartShare提供了一个巨大的机会来进行多- HFpEF的分层精准医学研究。HeartShare队列核心将产生持久的影响， 通过完成以下响应于HeartShare请求的特定目标来控制HFpEF字段 用于应用程序。(1)汇集、清理和协调来自多种心血管疾病的所有数据和图像 队列和HF试验，以便为研究界开发全面的，数据丰富的资源， 鉴定新HFpEF亚型。(2)使用假设将联合收割机和多组学分析结合起来- 通过询问先前鉴定的HFpEF亚型来驱动方法，以提高鉴定和 这些HFpEF亚型的分子/病理生理学理解。(3)为了将联合收割机和 多维数据（包括多组学），使用无偏方法识别和验证新型HFpEF 亚型

PROJECT SUMMARY Heart failure (HF) with preserved ejection fraction (HFpEF) is a heterogeneous, multifaceted syndrome that is an ideal setting for the application of precision medicine. HFpEF has proven resistant to conventional techniques for the study of its underlying pathophysiology and conduct of randomized clinical trials. New approaches are therefore desperately needed, as indicated in a recently published white paper which summarized the deliberations of the NHLBI Working Group on Research Priorities in HFpEF. The National Academy of Sciences Precision Medicine Report proposes that “when multiple molecular indicators are used in combination with conventional clinical, histological, and laboratory findings, they offer the opportunity for a more accurate and precise description and classification of disease”. This paradigm is also supported by the NHLBI’s Strategic Vision, which argues that a combination of omics (e.g., genomics, proteomics, and metabolomics), coupled with clinical and physiological data, will be necessary to advance understanding of the pathobiological basis of complex clinical syndromes such as HFpEF, and provides the underlying rationale for HeartShare. The promise of precision medicine lies in data diversity. More than the sheer size of biomedical data, it is the layering of multiple data modalities, offering complementary perspectives, that will enable the identification of patient subgroups with shared pathophysiology. HeartShare provides an immense opportunity to conduct a multi- layered precision medicine investigation of HFpEF. The HeartShare Cohort Core will create a lasting impact on the HFpEF field by accomplishing the following specific aims, which are responsive to the HeartShare request for applications. (1) To pool, clean, and harmonize all data and images from multiple cardiovascular disease cohorts and HF trials in order to develop a comprehensive, data-rich resource for the research community to identify novel HFpEF subtypes. (2) To combine machine learning and multi-omics analyses using a hypothesis- driven approach by interrogating previously identified HFpEF subtypes in order to improve the identification and molecular/pathophysiologic understanding of these HFpEF subtypes. (3) To combine machine learning and multi-dimensional data (including multi-omics) using unbiased approaches to identify and validate novel HFpEF subtypes.