It’s about time: modeling circadian regulation of cardiac electrophysiology and arrhythmogenesis

Cardiac electrophysiology models resolve processes ranging from millisecond-scale ion-channel gating to hour-scale protein trafficking; yet, most do not explicitly represent circadian time. Consequently, ion-channel conductance, autonomic input, body temperature, and clock-regulated gene expression are often treated as fixed parameters or time-invariant inputs, causing simulated cardiac cells to correspond to an implicit and potentially arbitrary biological phase. In vivo, however, these factors vary across the ~24-h cycle and jointly shape sinoatrial nodal pacemaking, ventricular repolarization, arrhythmia susceptibility, and drug response. In this mini-review, we examine recent efforts to incorporate circadian regulation into computational models of cardiac electrophysiology, including sinoatrial nodal and ventricular myocyte models of pacemaking, arrhythmogenesis, seizure-induced sinus arrhythmias, and drug-induced proarrhythmic risk. We synthesize these studies using a layered “source–transfer–target” organization in which intrinsic and systemic circadian sources act through source-specific transfer processes—including transcription, translation, channel trafficking, receptor-mediated signaling, and direct thermal modulation—to regulate shared electrophysiological targets. Building on this synthesis, we propose a general current-level formulation for incorporating circadian regulation of maximal conductance, channel gating, and ionic driving force into Hodgkin–Huxley-type models. Finally, we identify the experimental, computational, and clinical advances needed to translate these formulations into human-specific, personalized models of cardiac rhythm and arrhythmogenesis, with the long-term goal of enabling circadian-aware cardiac digital twins for time-resolved risk prediction and chronotherapeutic optimization.