Extraction of molecular signature of HFpEF via a machine learning-empowered proteomic characterization: A study of the BCAA pathway

通过机器学习支持的蛋白质组表征提取 HFpEF 的分子特征：BCAA 途径的研究

• 批准号: 10183311
• 负责人: Chun Ming Dominic Ng
• 金额: $ 64.97万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10183311
• 关键词: Address; Affect; Age; Aging; Atlases; Biology; Branched-Chain Amino Acids; Cardiac; Catabolism; Cell physiology; Cells; Clinical; Complex; Data Analyses; Data Science; Defect; Diabetes Mellitus; Diagnostic; Disease; Disease Progression; Disease model; EFRAC; Enzymes; Exposure to; Failure; Functional disorder; Genetic Predisposition to Disease; Glucose; Heart; Heart Atrium; Heart Diseases; Heart failure; Homeostasis; Hypertension; Knowledge; Lead; Link; Machine Learning; Mechanical Stress; Mediating; Metabolic; Metabolic Diseases; Metabolic Pathway; Metabolic stress; Metabolism; Methodology; Methods; Mitochondria; Modeling; Molecular; Molecular Genetics; Molecular Profiling; Molecular Target; Mus; Myocardium; Nature; Obese Mice; Obesity; Organ; Oxidation-Reduction; Oxidative Stress; Pathogenesis; Pathogenicity; Pathologic; Pathway interactions; Patients; Phenotype; Post-Translational Protein Processing; Procedures; Process; Production; Proteins; Proteome; Proteomics; Reactive Oxygen Species; Regulation; Research; Research Personnel; Risk Factors; Role; Stress; Symptoms; System; Technology; Thinness; Treatment Failure; Uncertainty; Woman; antioxidant enzyme; base; computational platform; constriction; effective therapy; empowered; exhaustion; fatty acid metabolism; heart function; in vivo; insight; knowledge graph; men; molecular phenotype; mouse model; new therapeutic target; novel; novel diagnostics; preservation; pressure; protein function; therapeutic target; tool

PROJECT SUMMARY Heart failure with preserved ejection fraction (HFpEF), characterized by heart failure symptoms with normal ejection fraction, is highly prevalent. However, most HFpEF patients do not respond to standard therapy for heart failure with reduced ejection fraction (HFrEF), and there are no clear and uniform diagnostic criteria to stratify and differentiate HFpEF from HFrEF. Therefore, there is a pressing unmet need for us to better understand HFpEF at the molecular and system levels. Unbiased approaches such as machine learning (ML) offer a powerful means to tease out the molecular signatures of HFpEF in relevant disease models. The emerging evidence implicates that metabolism and redox homeostasis are two significant disruptions in cellular processes evidenced by clinical symptoms of HFpEF. Previous studies have identified branched-chain amino acid (BCAA) catabolic defect as another major metabolic hallmark in heart failure as well as in metabolic disorders. Moreover, BCAA catabolic defects have been demonstrated to directly impact mitochondrial function and elevate reactive oxygen species (ROS) production, resulting in oxidative stress-sensitive post-translational modifications (O-PTMs) that govern protein function and pathways. These exciting discoveries lead to our new hypothesis that O-PTM-mediated proteome remodeling is a dynamic and pervasive molecular change in diseased hearts, affecting proteins with central function in cardiac homeostasis and pathophysiology. To investigate the unique molecular features and pathogenic mechanisms of HFpEF, we highlight a novel HFpEF mouse model that incorporates both genetic predisposition for obesity/diabetes and pressure-overload, the two major risk factors for HFpEF, by performing trans-aortic constriction (TAC) in the ob/ob mice. We have also perfected the experimental tools and data analysis platform to provide O-PTM profiling at the whole-proteome level in hearts. Accordingly, we have strategically formulated the following aims according to three phenotypic levels: At the systemic level, Aim 1 will establish and characterize in vivo mouse models of HFpEF vs. HFrEF by cardiac and mitochondrial function as well as redox status. At the organellar level, Aim 2 will conduct targeted proteomics profiling of the cardiac mitochondria and extract O-PTM signatures using ML-based methods to achieve deep phenotyping of HFpEF and HFrEF. This information will then be integrated and enriched in an O- PTM molecular atlas and knowledge graph. At the molecular level, Aim 3 will target the BCAA catabolic pathway to exhaustively scrutinize its role in HFpEF and HFrEF. A multilevel understanding of the HFpEF phenotype, from its global profiling to molecular targets, will provide valuable new insights into the disease process that can lead to potential novel diagnostic and therapeutic targets.

项目摘要 射血分数正常的心力衰竭（HFpEF），特征为心力衰竭症状， 射血分数是非常普遍的。然而，大多数HFpEF患者对心脏标准治疗无反应， 射血分数降低（HFrEF）失败，并且没有明确和统一的诊断标准进行分层 并区分HFpEF和HFrEF。因此，我们迫切需要更好地了解 HFpEF在分子和系统水平。无偏见的方法，如机器学习（ML），提供了强大的 这意味着在相关疾病模型中梳理出HFpEF的分子特征。 新出现的证据表明，代谢和氧化还原稳态是两个重要的破坏， HFpEF的临床症状证明了细胞过程。以前的研究已经确定了支链 氨基酸（BCAA）分解代谢缺陷是心力衰竭以及代谢性心力衰竭的另一个主要代谢标志， 紊乱此外，BCAA分解代谢缺陷已被证明直接影响线粒体功能 并提高活性氧（ROS）的产生，导致氧化应激敏感的翻译后 修饰（O-PTM）控制蛋白质功能和途径。这些令人兴奋的发现导致我们的新 假设O-PTM介导的蛋白质组重构是一种动态的和普遍的分子变化， 病变心脏，影响心脏稳态和病理生理学中具有中心功能的蛋白质。 为了研究HFpEF独特的分子特征和致病机制，我们重点介绍了一种新的HFpEF， 一种小鼠模型，该模型结合了肥胖/糖尿病和压力超负荷的遗传易感性， HFpEF的主要危险因素，通过在ob/ob小鼠中进行经主动脉缩窄（TAC）。我们还 完善实验工具和数据分析平台，提供全蛋白质组的O-PTM图谱 水平在心中。因此，我们根据三个表型，战略性地制定了以下目标： 水平：在全身水平，目标1将建立和表征HFpEF与HFrEF的体内小鼠模型 心脏和线粒体功能以及氧化还原状态。在细胞器水平，目标2将进行有针对性的 心肌线粒体的蛋白质组学分析，并使用基于ML的方法提取O-PTM特征， 实现HFpEF和HFrEF的深度表型分型。然后，这些信息将被整合和丰富在一个O- PTM分子图谱和知识图谱。在分子水平上，Aim 3将针对BCAA分解代谢途径 详尽地审查其在HFpEF和HFrEF中的作用。对HFpEF表型的多层次理解， 从其全球概况到分子靶点，将为疾病过程提供有价值的新见解， 导致潜在新的诊断和治疗靶点。