Autor(es): Ferreira, Mónica ; V, Geraldes ; Felix, Ana Clara ; Oliveira, Mario ; Laranjo, Sergio ; Rocha, Isabel
Data: 2025
Identificador Persistente: http://hdl.handle.net/10362/182065
Origem: Repositório Institucional da UNL
Assunto(s): animal models; atrial fibrillation (AF); pathophysiology; remodelling mechanisms; translational research; Medicine (miscellaneous); Biochemistry, Genetics and Molecular Biology(all); SDG 3 - Good Health and Well-being
Funding Information: This paper was funded by Funda\u00E7\u00E3o para a Ci\u00EAncia e a Tecnologia, reference number UIDB/00306/2020. Publisher Copyright: © 2025 by the authors.
Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, presenting a significant global healthcare challenge due to its rising incidence, association with increased morbidity and mortality, and economic burden. This arrhythmia is driven by a complex interplay of electrical, structural, and autonomic remodelling, compounded by genetic predisposition, systemic inflammation, and oxidative stress. Despite advances in understanding its pathophysiology, AF management remains suboptimal, with ongoing debates surrounding rhythm control, rate control, and anticoagulation strategies. Animal models have been instrumental in elucidating AF mechanisms, facilitating preclinical research, and advancing therapeutic development. This review critically evaluates the role of animal models in studying AF, emphasizing their utility in exploring electrical, structural, and autonomic remodelling. It highlights the strengths and limitations of various models, from rodents to large animals, in replicating human AF pathophysiology and advancing translational research. Emerging approaches, including optogenetics, advanced imaging, computational modelling, and tissue engineering, are reshaping AF research, bridging the gap between preclinical and clinical applications. We also briefly discuss ethical considerations, the translational challenges of animal studies and future directions, including integrative multi-species approaches, omics technologies and personalized computational models. By addressing these challenges and addressing emerging methodologies, this review underscores the importance of refining experimental models and integrating innovative technologies to improve AF management and outcomes.
