The Transcriptional Landscape of Atrial Fibrillation: A Systematic Review and Meta-analysis

SUMMARY Background Despite advances in understanding atrial fibrillation (AF) pathophysiology, there is limited agreement on the key genes driving its pathophysiology. To understand the genome-wide transcriptomic landscape, we performed a meta-analysis from studies reporting gene expression patterns in atrial heart tissue from patients with AF and controls in sinus rhythm (SR). 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. We calculated the pooled differences in individual gene expression from fourteen studies comprising 534 samples (353 AF and 181 SR) to create a consensus signature (CS), from which we identified differentially regulated pathways, estimated transcription factor activity, and evaluated its performance in classifying validation samples as AF or SR. Results Despite heterogeneity in the top differentially expressed genes across studies, the AF-CS in both chambers were robust, showing a better performance in classifying AF status than individual study signatures. Functional analysis revealed commonality in the dysregulated cellular processes between chambers, including extracellular matrix remodeling, cardiac conduction, metabolic derangements, and innate immune system activity. Finally, the AF-CS showed a good performance differentiating AF from controls in three validation datasets (two from peripheral blood and one from left ventricle samples). Conclusions Despite variability in individual studies, this meta-analysis elucidated conserved molecular pathways involved in AF pathophysiology across its phenotypes and the potential of a transcriptomic signature in identifying AF from peripheral blood samples. Our work highlights the value of integrating published transcriptomics data in AF and the need for better data deposition practices. Abstract Figure Graphical abstract Clinical Perspective What Is New? This meta-analysis of 534 atrial tissue samples reveals a robust consensus transcriptional signature for atrial fibrillation (AF), identifying consistently dysregulated genes and pathways across heterogeneous patient populations and study designs. What Are the Clinical Implications? The identified consensus signature provides a molecular framework for developing targeted diagnostic biomarkers and mechanism-based treatment strategies for AF, potentially leading to more personalized and effective management approaches. The study’s findings of conserved gene expression patterns across different AF types and the signature’s performance in classifying AF from peripheral blood samples suggest potential for non-invasive diagnostic and prognostic applications in clinical practice. Research Perspective What New Question Does This Study Raise? Given the identified conserved molecular pathways in atrial fibrillation (AF), how do these transcriptional signatures evolve across different AF types (paroxysmal, persistent, and permanent) and in response to various therapeutic interventions? What Question Should be Addressed Next? Can the consensus transcriptional signature be validated in large-scale, prospective studies to develop and evaluate blood-based biomarkers for early AF detection, risk stratification, and treatment response prediction? How do the identified dysregulated pathways, particularly those related to structural remodeling and metabolic reprogramming, interact with genetic predisposition and environmental factors to influence AF onset and progression?