Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Retinal age gap and the risk of age-related diseases
Author Affiliations & Notes
  • Zhuoting Zhu
    Centre for Eye Research Australia Ltd, East Melbourne, Victoria, Australia
  • Ruiye Chen
    Centre for Eye Research Australia Ltd, East Melbourne, Victoria, Australia
  • Zhen Yu
    Monash University, Clayton, Victoria, Australia
  • Zongyuan Ge
    Monash University, Clayton, Victoria, Australia
  • Mingguang He
    Centre for Eye Research Australia Ltd, East Melbourne, Victoria, Australia
  • Footnotes
    Commercial Relationships   Zhuoting Zhu None; Ruiye Chen None; Zhen Yu None; Zongyuan Ge None; Mingguang He None
  • Footnotes
    Support  NHMRC Investigator Grant
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 3769. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Zhuoting Zhu, Ruiye Chen, Zhen Yu, Zongyuan Ge, Mingguang He; Retinal age gap and the risk of age-related diseases. Invest. Ophthalmol. Vis. Sci. 2024;65(7):3769.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose : To further refine the deep learning technology for retinal age (biological age based on retinal images) and comprehensively explore the clinical values of retinal age gap (retina-predicted age minus chronological age) in terms of the risk of multiple age-related diseases.

Methods : Retinal age prediction was refined using Temporal Fundus Images Enhanced Progressive Label Distribution Learning. Retinal age gaps were determined for patients who had no history of corresponding diseases at baseline. Diseases events were determined by data linkage to hospital records on admissions and diagnoses. Cox proportional hazards regression models were performed to evaluate the association between retinal age gaps and incident diseases.

Results : The mean absolute error (MAE) reduced from 3.5 to 2.8 years after refinement. During the follow-up time, a total of 849 cases of mortality, 640 cases of cardiovascular diseases (CVD), 75 cases of end-stage renal diseases (ESRD), 1252 cases of chronic obstructive pulmonary disease(COPD), 514 of dementia and 4460 of cancers were identified among the participants without the corresponding diseases at the baseline. Table 1 shows that after adjusting for multiple confounding factors each 1-year increase in retinal age gaps was associated with a 5% increase in the risk of mortality, 6% increase in CVD, 11% increase in ESRD, 3% increase in COPD, 7% in dementia and 1% in cancers (HR=1.05, 95% CI: 1.03–1.07, P<0.001; HR = 1.06, 95% CI = 1.04-1.09, P = 0.011; HR = 1.11, 95% CI = 1.02-1.19, P = 0.002; HR = 1.03, 95% CI = 1.01-1.05, P < 0.001; HR = 1.07, 95% CI = 1.04-1.11, P = 0.007; HR = 1.01, 95% CI = 1.00-1.02, P < 0.001, respectively).

Conclusions : We found the retinal age gap was associated with an increased risk of multiple incident age-related diseases highlighting the value of retinal age as a reliable ageing biomarker. It may serve as an informative tool to facilitate the risk assessment and personalized screening pattern of ageing.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×