Key result
Each one-year increase in the retinal age gap was associated with a 3% increase in the risk of incident cardiovascular disease (HR 1.03, 95% CI 1.01-1.06, P=0.012).
Why the study?
Retinal parameters reflect systemic vascular changes, but the association of deep learning-predicted retinal age gap with arterial stiffness and incident cardiovascular disease required investigation.
Does a higher retinal age gap predict increased arterial stiffness and incident cardiovascular disease in a general adult population?
Cohort (n=35,917)
Yes
Does a higher retinal age gap predict increased arterial stiffness and incident cardiovascular disease in a general adult population?
Retinal age gap derived from fundus images using deep learning is an independent predictor of arterial stiffness and future incident cardiovascular disease.
Retinal age gap may flag higher CVD risk; leaves open its added value beyond standard predictors in validation studies.
Background Retinal parameters could reflect systemic vascular changes. With the advances of deep learning technology, we have recently developed an algorithm to predict retinal age based on fundus images, which could be a novel biomarker for ageing and mortality. Objective To investigate associations of retinal age gap with arterial stiffness index (ASI) and incident cardiovascular disease (CVD). Methods A deep learning (DL) model was trained based on 19,200 fundus images of 11,052 participants without any past medical history at baseline to predict the retinal age. Retinal age gap (retinal age predicted minus chronological age) was generated for the remaining 35,917 participants. Regression models were used to assess the association between retinal age gap and ASI. Cox proportional hazards regression models and restricted cubic splines were used to explore the association between retinal age gap and incident CVD. Results We found each one-year increase in retinal age gap was associated with increased ASI (β=0.002, 95% confidence interval [CI]: 0.001-0.003, P<0.001). After a median follow-up of 5.83 years (interquartile range [IQR]: 5.73-5.97), 675 (2.00%) developed CVD. In the fully adjusted model, each one-year increase in retinal age gap was associated with a 3% increase in the risk of incident CVD (hazard ratio [HR]=1.03, 95% CI: 1.01-1.06, P=0.012). In the restricted cubic splines analysis, the risk of incident CVD increased significantly when retinal age gap reached 1.21 (HR=1.05; 95% CI, 1.00-1.10; P-overall <0.0001; P-nonlinear=0.0681). Conclusion We found that retinal age gap was significantly associated with ASI and incident CVD events, supporting the potential of this novel biomarker in identifying individuals at high risk of future CVD events.
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Zhu et al. (2022) conducted a cohort in Cardiovascular disease (n=35,917). Retinal age gap vs. Chronological age was evaluated on Incident cardiovascular disease (CVD) (HR 1.03, 95% CI 1.01-1.06, p=0.012). Each one-year increase in the retinal age gap was associated with a 3% increase in the risk of incident cardiovascular disease (HR 1.03, 95% CI 1.01-1.06, P=0.012).
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