Transcriptomic Consensus of Atrial Fibrillation Unveils Mechanism-Based Drug Repurposing Opportunities: A Systematic Review and Meta-analysis

Background and Aims Despite advances in understanding atrial fibrillation (AF) pathophysiology through the lens of transcriptomics, marked differences in the key AF genes between studies remain, while drugs targeting preserved dysregulated pathways are limited. This systematic review and meta-analysis aimed to provide a consensus transcriptional signature of AF and use it to identify potentially repurposable drugs. Methods Bibliographic databases and data repositories were systematically searched for studies reporting gene expression patterns in atrial heart auricle tissue from patients with AF and controls in sinus rhythm. A qualitative synthesis and a transcriptomics meta-analysis were performed. We calculated the pooled differences in individual gene expression to create a consensus signature (CS), from which we identified differentially regulated pathways and estimated transcription factors activity. We also created a protein-protein interaction network to identify drug interactions with highly interconnected genes (hub genes) from the AF-CS. Results Thirty-four observational studies were assessed in the qualitative synthesis, while fourteen, comprising 511 samples (338 AF and 173 SR), were included in the meta-analysis. Despite the heterogeneity observed across individual studies, the AF-CS in both chambers were consistent and robust, showing a better performance in classifying AF status than individual studies. The functional analysis revealed commonality in the dysregulated cellular processes across the atria, including extracellular matrix remodeling, downregulation of cardiac conduction pathways, metabolic derangements, and innate immune system activity processes. Finally, drug-gene analyses highlighted several compounds as repurposing drug candidates for AF, highlighting lipid-lowering agents, antioxidants, and retinoids, among others. Conclusions Despite variability in individual studies, this meta-analysis elucidated conserved molecular pathways involved in AF pathophysiology across its phenotypes, offering robust and potentially generalizable diagnostic biomarkers. From this AF-CS, we identified potential compounds targeting these dysregulated pathways, thereby addressing an extant gap in AF-specific pharmacotherapy. Key Question Can a meta-analytically derived consensus transcriptional signature effectively capture the core molecular mechanisms underlying AF and serve as a basis for identifying novel drug candidates targeting these conserved pathways? Key Findings Extracellular matrix remodeling, downregulation of cardiac conduction pathways, and modulation of innate immune system activity emerged as conserved molecular hallmarks across the AF spectrum. Drug-gene interaction analyses highlighted the repurposing potential of lipid-lowering agents, antioxidants, and retinoids, among other compounds, for targeted intervention in these dysregulated pathways. Take Home Message Despite AF’s complexity, a transcriptional signature derived through a meta-analysis can pinpoint conserved molecular pathways across AF phenotypes. These insights provide a foundation for identifying and repurposing drugs targeting the core dysregulated processes in the disease, offering new avenues for targeted, mechanism-based treatment of AF. ![Figure][1] ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The development of this project was funded by the German Research Foundation (Collaborative Research Centre 1550, grant number #464424253 to SAGO, MVM, RO, FW, MK, CS, MF, and RTL), the Informatics for Life Initiative sponsored by the Klaus-Tschirra foundation (MM and RTL), the German Cardiac Society (Research Clinician-Scientist program to FW), the German Heart Foundation/German Foundation of Heart Research (F/03/19 to CS), and the Else-Kroner Fresenius Foundation (EKFS Fellowship and EKFS Clinician-Scientist professorship to CS). The funders had no role in study design, data collection, analysis, interpretation, or report preparation. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Bibliographic databases (MEDLINE/Ovid, EMBASE/Ovid, CINAHL/EBSCOhost, and Google Scholar) and data repositories (Gene Expression Omnibus database, the European Nucleotide Archive, ArrayExpress, and the European Genome Phenome Archive) I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The study data are available in the supplementary material. The code used to generate the results and the processed data is available in GitHub ([https://github.com/thelevinsonlab/AF\_CS\_MA][2]). [1]: pending:yes [2]: https://github.com/thelevinsonlab/AF_CS_MA