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 aging and mortality. Therefore, we aim to investigate associations of retinal age gap with arterial stiffness index and incident cardiovascular disease (CVD).
METHODS:
A deep learning model was trained based on 19 200 fundus images of 11 052 participants without any 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 arterial stiffness index. 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 1-year increase in retinal age gap was associated with increased arterial stiffness index (β=0.002 [95% CI, 0.001–0.003];
P
<0.001). After a median follow-up of 5.83 years (interquartile range: 5.73–5.97), 675 (2.00%) developed CVD. In the fully adjusted model, each 1-year increase in retinal age gap was associated with a 3% increase in the risk of incident CVD (hazard ratio=1.03 [95% CI, 1.01–1.06];
P
=0.014). In the restricted cubic splines analysis, the risk of incident CVD increased significantly when retinal age gap reached 1.21 (hazard ratio=1.05 [95% CI, 1.00–1.10];
P
-overall <0.0001;
P
-nonlinear=0.0681).
CONCLUSIONS:
We found that retinal age gap was significantly associated with arterial stiffness index and incident CVD events, supporting the potential of this novel biomarker in identifying individuals at high risk of future CVD events.
BACKGROUND:
Hypertension might be a modifiable risk factor for neurodegeneration diseases. However, the associations between blood pressure (BP), arterial stiffness index and retinal neurodegeneration remain unclear.
METHODS:
This study used cross-sectional data from the United Kingdom BioBank (UKB) and longitudinal data from the Chinese Ocular Imaging Project (COIP). The macular ganglion cell-inner plexiform layer thickness (mGCIPLT) and macular retinal nerve fiber layer thickness were measured using spectral domain optical coherence tomography imaging. Swept-source optical coherence tomography was performed to obtain the longitudinal trajectory of the mGCIPLT and peripapillary retinal nerve fiber layer thickness in the COIP cohort. Multivariable linear models were used to analyze the associations between BP and retinal measurements.
RESULTS:
In a cross-sectional analysis of 22 801 participants from UKB, thinner mGCIPLT was related to higher systolic BP (β: −0.103 [−0.146 to −0.061];
P
<0.001), and higher diastolic BP (β: −0.191 [−0.265 to −0.117];
P
<0.001), and was significantly associated with higher mean arterial pressure (β: −0.174 [−0.238 to −0.109];
P
<0.001) and higher mean pulse pressure (β: −0.080 [−0.139 to −0.020];
P
=009). In a longitudinal analysis of 2012 eligible COIP participants, higher levels of baseline systolic BP, diastolic BP, mean arterial pressure, and mean pulse pressure were associated with faster thinning in mGCIPLT and peripapillary retinal nerve fiber layer thickness (all
P
<0.001). The strongest association was the effect of mean arterial pressure on mGCIPLT (β: −0.118 [−0.175 to −0.061];
P
<0.001). The results of the analysis of macular retinal nerve fiber layer thickness and peripapillary retinal nerve fiber layer thickness were consistent with those of mGCIPLT.
CONCLUSIONS:
BP levels were independently and consistently associated with various retinal neurodegenerative exacerbations.
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