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: 10646374
• 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/10646374
• 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); Environment; Environmental Impact; 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; Positioning Attribute; Prevention; Process; Prognosis; Proteins; Proteomics; Recurrence; Regulator Genes; Stress; Systems Biology; Testing; Therapeutic; Time; Tissue Model; Tissues; Validation; auricular appendage; biobank; candidate validation; 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; single nucleus RNA-sequencing; 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 -基因到OMIC-知情药物：药物重新定位和功能测试，以防止 AF进展 项目摘要 心房颤动（AF）的一个重要临床问题是防止AF进展为更持久的房颤。 forms.首次发作后，AF复发，约50%的患者负担增加，并进展至 25%的患者在诊断后5年内发生持续性或永久性房颤。与阵发性房颤相比， 预后较差，药物或消融治疗后的结果更差， 虽然许多过程和途径已经涉及AF的发展，但对AF的影响较小。 程度进展，精确的分子驱动因素，它们的相互作用和它们作用的背景并不完全 明白AF发生的遗传风险因素可能与促进AF进展的遗传风险因素不同， 其也可能受到环境、共病或细胞应激源的影响。我们假设 可以鉴定AF进展与基因调控和相互作用组网络之间的相互作用， 了解这些机制对于发现房颤进展的治疗方法至关重要。我们的目标 是识别AF进展基因、途径和模块，从而能够识别并验证 预防AF和AF进展的可重复利用药物。为了找到针对AF进展的药物，我们 必须首先更好地了解AF进展的分子组成部分。这个项目建立在我们以前的 人左心房（LA）附件（LAA）组织中的RNA测序（RNASeq）数据显示， 对细胞应激途径的不充分或过度的转录组学反应发生于 我们提出在人LA组织中整合单核转录组学（snRNASeq）， 鉴定主转录因子（TF）和相互作用体介导基因调控网络和细胞类型 基础AF疾病进展，克服了无法解决变化的批量RNASeq数据的局限性 来自不同的细胞组成，例如成纤维细胞，其可能随着AF进展而增加。snRNASeq将 进一步了解AF进展和与进展相关的特定细胞类型。我们还将使用人类 相互作用组网络方法用于识别随AF变化的新风险基因和疾病模块 进展然后，我们将整合相互作用组，遗传和AF进展的基因组，蛋白质组和 使用人工智能（AI）方法确定AF进展的治疗靶点的代谢组学数据 以及靶向AF进展的可再利用药物和药物组合。“来自其他项目的OMIC数据， 还将整合可能产生潜在基因或途径特异性候选药物的计划。候选 然后将在人类工程心脏组织（EHT）中对药物和组合进行功能测试， 自发性AF和AF进展的小鼠模型。我们对识别可重复利用药物的关注将 缩短房颤检测时间。本项目的成功完成将为深入了解 AF进展的机制;用于AF的药物鉴定、功能测试和验证的管道， 房颤进展;重要的是，药物已准备好进行临床测试。