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Structured Abstract Background AI-enabled electrocardiographic age (AI-ECG age) is a digital biomarker of electrophysiological cardiac health. Although cardiovascular physiology exhibits circadian organization, the circadian behavior of AI-ECG age and its structural correlates have not been defined in AF-naïve individuals. Objectives To determine whether AI-ECG age exhibits reproducible circadian patterns and whether disruption of these patterns is associated with left atrial (LA) remodeling, a marker of atrial myopathy. Methods Continuous single-lead wearable ECGs were analyzed from two independent prospective cohorts (S-Patch [ https://ClinicalTrials.gov : NCT05119725 , registered November 2021]; Memo Patch [ https://ClinicalTrials.gov : NCT05355948 , registered May 2022]). In AF-naïve participants with ≥48 hours of data, AI-ECG age was estimated every 10 minutes. Unsupervised clustering was used to identify intrinsic circadian trajectories. For clinical interpretability, participants were classified using a day–night difference cutoff (ΔAge 0.6 years) as Restorative (ΔAge >0.6) or Disrupted (ΔAge ≤0.6). We assessed phenotype reproducibility and examined associations with left atrial volume index (LAVI) using multivariable regression and meta-analysis. Results Unsupervised learning consistently identified three circadian trajectory patterns across cohorts. Under the simplified binary classification, the Restorative phenotype was observed in approximately half of the participants (47.6–50.2%). Phenotype reproducibility was moderate (Cohen’s κ=0.518; ICC=0.51–0.54) and was not fully explained by conventional heart rate variability measures. Among participants with echocardiography (n=122), the Disrupted phenotype was associated with higher LAVI (adjusted mean difference 6.09 mL/m²; 95% CI 1.46–10.72; p=0.010) and higher odds of severe LA enlargement (adjusted OR 4.17; 95% CI 1.58–10.99; p=0.004), with negligible heterogeneity (I²=0%). Conclusions Wearable-derived AI-ECG age exhibits circadian patterns in AF-naïve individuals, with unsupervised learning identifying distinct trajectories. Attenuation of a nocturnal decline—the Disrupted phenotype—is associated with left atrial enlargement, independent of conventional comorbidities and static AI-ECG age metrics. These findings suggest that circadian electrophysiological aging phenotyping may capture a dimension of atrial structural vulnerability not reflected by point-in-time assessments, and support prospective studies to evaluate its clinical utility. Condensed Abstract Continuous wearable ECGs revealed circadian patterns in AI-ECG age in AF-naïve individuals. A Disrupted phenotype, defined by an attenuated nocturnal decline (day–night AI-ECG age difference ≤0.6 years), was associated with left atrial remodeling, including higher LAVI and severe enlargement, independent of conventional comorbidities and static AI-ECG age metrics. Circadian electrophysiological aging phenotyping may capture a dimension of atrial structural vulnerability not reflected by point-in-time assessments, and motivates prospective validation of its clinical utility.