Smartwatch Photoplethysmography-Derived Heart Age via ECG-Guided Cross-Modal Pretraining as a Digital Biomarker of Vascular Aging

Digital biomarkers of cardiovascular aging derived from physiological signals, commonly referred to as heart age or vascular age, have been extensively studied and shown to associate with a range of diseases and cardiovascular outcomes. However, most existing work relies on resting electrocardiography (ECG), imaging, or specialized clinical vascular function measurements, and studies that link wearable photoplethysmography (PPG) to clinically relevant phenotypes such as arterial stiffness and hypertension remain scarce, particularly in the low-burden, repeatable setting of smartwatches. To address this gap, we developed an ECG-guided cross-modal pretraining framework that leverages synchronized smartwatch ECG during training to enhance PPG representation learning, while relying solely on PPG at inference to match the intended smartwatch deployment scenario, and systematically evaluated the resulting model-derived heart age gap in relation to arterial stiffness and prevalent hypertension. The study included three cohorts sourced from OPPO across China, comprising 581,804 participants and 7,452,131 recordings. The Vascular Health Study (VHS) cohort was used for synchronized ECG--PPG self-supervised pretraining, supervised fine-tuning, and internal validation; two external cohorts, pulse wave velocity (PWV) and home blood pressure monitoring (HBPM), were used for the corresponding arterial stiffness and hypertension prevalence association analyses. The model combined subject-aware self-supervised learning with ECG-PPG contrastive alignment and was deployed using PPG-only inference. The SA-CLIP-pretrained PPG-only model achieved subject-level MAE values of 5.895 years with Pearson's r=0.819 in the external PWV cohort and 4.344 years with r=0.800 in the HBPM cohort. Short-term aggregation of repeated recordings further improved subject-level stability. Heart age gap remained significantly associated with PWV after controlling for chronological age, with a partial correlation of 0.2627 (P < 0.001); multivariable OLS showed that each 1-year higher heart age gap was associated with 0.062 m/s higher PWV. Participants with accelerated heart aging had 0.91 m/s higher adjusted PWV than those with decelerated heart aging. In the HBPM cohort, each 1-SD higher adjusted heart age gap was associated with higher odds of prevalent hypertension (OR 1.72, 95% CI 1.49-1.99), and the highest quartile had an OR of 4.25 compared with the lowest quartile. These findings suggest that ECG-guided pretraining enhances PPG heart-age representations and that smartwatch PPG-derived heart age gap may serve as a scalable digital biomarker for stratifying arterial stiffness and prevalent hypertension.