Project 3 Genes to Omics-Informed Drugs: Drug Repositioning and Testing to Prevent AF Progressions

项目 3 基因组学药物：药物重新定位和测试以预防 AF 进展

• 批准号: 10410650
• 负责人: Mina Kay Chung
• 金额: $ 62.14万
• 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/10410650
• 关键词: Ablation; Algorithms; Artificial Intelligence; Atrial Fibrillation; Bass; Cell Nucleus; Cell model; Cells; Cellular Stress; Cessation of life; Clinical; Data; Databases; Development; Diagnosis; Disease; Disease Progression; Doctor of Philosophy; Drug Combinations; Drug Targeting; Electrophysiology (science); Fibroblasts; Gene Expression; Genes; Genetic; Genomics; Goals; Heart Atrium; Human; Human Engineering; Lead; Left; Measures; Mediating; Medical; Metabolic; Methodology; Modeling; Molecular; Molecular Disease; Multiomic Data; Mus; Network-based; Outcome; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacotherapy; Population; Prevention; Process; Prognosis; Proteins; Proteomics; Recurrence; Regulator Genes; Stress; Systems Biology; Testing; Therapeutic; Time; Tissue Model; Tissues; Validation; appendage; auricular appendage; base; biobank; cardiac tissue engineering; cell type; comorbidity; drug candidate; drug development; drug testing; gene regulatory network; genetic risk factor; genome wide association study; human interactome; insight; metabolomics; mouse model; multimodality; novel; personalized medicine; precision medicine; preclinical efficacy; prevent; programs; research clinical testing; response; risk variant; side effect; stressor; success; therapeutic target; transcription factor; transcriptome sequencing; transcriptomics; trial design

PROJECT 3 - Genes to Omics-Informed Drugs: Drug Repositioning and Functional Testing to Prevent AF Progression PROJECT SUMMARY An important clinical problem in atrial fibrillation (AF) is preventing AF from progressing to more persistent forms. After an initial episode, AF recurs with increase in burden occurring in ~50% and progression to persistent or permanent AF occurring in 25% within 5 years of diagnosis. Compared to paroxysmal AF, prognosis is poorer and outcomes after medical or ablation therapy are worse for patients with persistent or permanent AF. While many processes and pathways have been implicated in AF development and to a lesser extent progression, the precise molecular drivers, their interactions and context in which they act are not fully understood. Genetic risk factors for development of AF may differ from those promoting progression of AF, which may also be impacted by environmental, comorbid or cellular stressors. We hypothesize that an interplay between AF progression and gene regulatory and interactome networks can be identified and that understanding these mechanisms is essential to informing therapeutic discovery for AF progression. Our goal is to identify AF progression genes, pathways and modules that will enable identification and then validation of repurposable drugs for the prevention of AF and AF progression. To find drugs to target progression of AF, we must first better understand the molecular components of AF progression. This project builds upon our prior RNA sequencing (RNASeq) data in human left atrial (LA) appendage (LAA) tissues that showed altered, inadequate or overwhelmed transcriptomic responses to cell stress pathways occur with progression to persistent AF. We propose to integrate single-nucleus transcriptomics (snRNASeq) in human LA tissue to identify master transcription factor (TF)- and interactome-mediated gene regulatory networks and cell types underlying AF disease progression, overcoming a limitation of bulk RNASeq data that cannot resolve changes from differing cell composition, such as fibroblasts, which may increase with AF progression. snRNASeq will yield further insights into AF progression and specific cell types related to progression. We will also use human interactome network approaches to identify novel risk genes and disease modules that change with AF progression. We will then integrate interactome, genetic, and AF progression genomic, proteomic and metabolomics data using artificial intelligence (AI) approaches to identify therapeutic targets for AF progression and repurposable drugs and drug combinations targeting AF progression. ‘Omic data from other projects in the Program will also be integrated that may yield potential gene or pathway specific candidate drugs. Candidate drugs and combinations will then be functionally tested in human engineered heart tissues (EHTs) and relevant mouse models of spontaneous AF and AF progression. Our focus on identifying repurposable drugs will shorten the time to testing for AF. Successful completion of this Project will provide insights into the molecular mechanisms of AF progression; a pipeline for drug identification, functional testing and validation for AF and AF progression; and importantly, drugs ready for clinical testing.

项目3-从基因到OMICS知情药物：药物重新定位和功能测试以预防 房颤进展 项目总结 心房颤动(房颤)的一个重要临床问题是阻止房颤进展到更持久。 表格。在最初的发作后，房颤复发，负荷增加约50%，并进展到 持续性或永久性房颤在诊断后5年内发生的比例为25%。与阵发性房颤相比， 对于持续性或非持续性的患者，预后更差，药物或消融治疗后的结果更差 永久自动对焦。虽然许多过程和途径都与房颤的发展有关，但到了较小的程度 程度进展，确切的分子驱动因素，它们的相互作用和它们发挥作用的背景还不完全 明白了。房颤发生的遗传危险因素可能不同于那些促进房颤进展的因素， 这也可能受到环境、共病或细胞应激源的影响。我们假设一个 可以确定房颤进展与基因调控和相互作用组网络之间的相互作用，并且 了解这些机制对于房颤进展的治疗发现至关重要。我们的目标 是确定房颤进展基因、通路和模块，从而能够识别并验证 用于预防房颤和房颤进展的可再利用药物。为了找到针对房颤进展的药物，我们 必须首先更好地了解房颤进展的分子成分。这个项目建立在我们以前的基础上 人左心房(LA)附件(LAA)组织中的RNA测序(RNAseq)数据显示， 对细胞应激途径的转录反应不足或不堪重负，随着进展到 持续性房颤。我们建议在人类LA组织中整合单核转录组学(SnRNASeq)以 确定主转录因子(TF)和交互作用组介导的基因调控网络和细胞类型 房颤疾病进展的基础，克服了无法解决变化的批量RNAseq数据的限制 来自不同的细胞成分，如成纤维细胞，可能会随着房颤的进展而增加。SnRNASeq将 对房颤进展和与进展相关的特定细胞类型有进一步的了解。我们还将使用人类 识别与房颤相关的新危险基因和疾病模式的互动组网络方法 进步。然后，我们将整合交互作用组、遗传和AF进展基因组、蛋白质组和 使用人工智能(AI)方法识别房颤进展的治疗靶点的代谢组学数据 以及针对房颤进展的可再利用药物和药物组合。‘来自中国其他项目的OMIC数据 计划也将被整合，可能产生潜在的基因或途径特定的候选药物。侯选人 然后，药物和组合物将在人类工程心脏组织(EHTS)中进行功能测试，并与 自发性房颤和房颤进展的小鼠模型。我们将重点放在识别可再利用药物上 缩短房颤检测的时间。该项目的成功完成将为深入了解分子 房颤进展的机制；房颤的药物识别、功能测试和验证的流水线 房颤进展；重要的是，药物准备好进行临床试验。