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

项目总结 心衰保留射血分数(HFpEF)，以正常的心力衰竭症状为特征 射血分数，是非常普遍的。然而，大多数HFpEF患者对心脏的标准治疗没有反应。 射血分数降低(HFrEF)的衰竭，没有明确和统一的诊断标准来分层 并对HFpEF和HFrEF进行了区分。因此，我们有迫切的未得到满足的需要，需要更好地了解 在分子和系统水平上的HFpEF。不偏不倚的方法，如机器学习(ML)，提供了强大的 在相关疾病模型中梳理出HFpEF的分子特征的方法。 新出现的证据表明，新陈代谢和氧化还原动态平衡是 HFpEF的临床症状证实了细胞过程。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和代谢异常的另一个主要代谢标志 精神错乱。此外，支链氨基酸分解代谢缺陷已被证明直接影响线粒体功能。 并增加活性氧物种(ROS)的产生，导致氧化应激敏感的翻译后 调节蛋白质功能和途径的修饰(O-PTM)。这些令人兴奋的发现为我们带来了新的 假设O-PTM介导的蛋白质组重塑是一种动态和普遍的分子变化。 病变的心脏，影响在心脏动态平衡和病理生理学中具有中心功能的蛋白质。 为了研究HFpEF的独特分子特征和致病机制，我们重点介绍了一种新的HFpEF 结合了肥胖/糖尿病遗传易感性和压力超负荷的小鼠模型，两者 通过对ob/ob小鼠实施经主动脉缩窄(TAC)，导致HFpEF的主要危险因素。我们还有 完善实验工具和数据分析平台，提供全蛋白质组O-PTM图谱 心平气和。因此，我们根据三个表型制定了以下战略目标 水平：在系统水平上，目标1将建立和表征HFpEF与HFrEF的活体小鼠模型 由心脏和线粒体功能以及氧化还原状态决定。在细胞器水平上，目标2将进行有针对性的 使用基于ML的方法对心肌线粒体进行蛋白质组学分析并提取O-PTM特征 实现HFpEF和HFrEF的深度表型。然后，这些信息将被整合并丰富在O- Ptm分子图谱和知识图谱。在分子水平上，目标3将针对支链氨基酸分解代谢途径。 详尽研究其在HFpEF和HFrEF中的作用。对HFpEF表型的多层次了解， 从全球概况到分子靶点，将为疾病过程提供有价值的新见解， 导致潜在的新的诊断和治疗靶点。

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.