A narrative review of Zika virus cardiotropism and atrial fibrillation from pathogenesis and diagnostic challenges to inflammation aware management

Abstract

Systemic inflammation is a key driver of atrial fibrillation (AF), but the mechanisms linking specific viral triggers to arrhythmogenesis are not fully understood. Zika virus (ZIKV) infection, which can induce a significant inflammatory response, provides a compelling clinical model to explore this link. This review synthesizes the current evidence for ZIKV-associated AF, evaluates the proposed pathophysiological mechanisms, and identifies critical knowledge gaps and limitations in the existing literature. Based on preclinical data and clinical case reports, the arrhythmogenic potential of ZIKV appears to be driven by a dual mechanism. Direct viral effects may include cardiomyocyte cytotoxicity and the downregulation of connexin 43 (Cx43), disrupting electrical coupling. Indirectly, a host immune response characterized by elevated pro-inflammatory cytokines (e.g., TNF-α, IL-6) likely accelerates atrial fibrosis and electrical remodeling, creating a pro-arrhythmic substrate. Diagnosing post-ZIKV AF is challenging due to overlapping symptoms and the arrhythmia’s often paroxysmal nature, necessitating enhanced surveillance with serial ECGs. We propose an “inflammation-aware” management paradigm that considers the virally-induced prothrombotic state when evaluating anticoagulation thresholds and uses advanced imaging like Cardiac MRI to characterize the atrial substrate before interventions such as catheter ablation. While ZIKV serves as an important model for inflammation-driven AF, current evidence remains associative and is derived from limited clinical data. Causality in humans is not yet established. There is an urgent need for methodologically rigorous research, including prospective cohort studies to determine incidence, biomarker validation for risk stratification, and mechanistic studies on human cardiac tissue to confirm the pathways identified in preclinical models and guide the development of targeted therapies.