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

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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.