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
Artificial Intelligence-Based Retinal Aging as a Predictor in Age-Related Ocular Diseases and Its Association with Chronic Kidney Disease
Author Affiliations & Notes
  • Xiao Guo
    Sun Yat-Sen University Zhongshan Ophthalmic Center, Guangzhou, Guangdong, China
  • Footnotes
    Commercial Relationships   Xiao Guo None
  • Footnotes
    Support  This study was supported by grants from the National Natural Science Foundation of China (82171084; 82371086).
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 5476. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Xiao Guo; Artificial Intelligence-Based Retinal Aging as a Predictor in Age-Related Ocular Diseases and Its Association with Chronic Kidney Disease. Invest. Ophthalmol. Vis. Sci. 2024;65(7):5476.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : Objective: To determine the biological ageing in in identifying individuals at high risk for age-related eye diseases (AREDs) like diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma, and explore the influence of chronic kidney disease (CKD) on aging and ARED risk.

Methods : Design, Setting and Participants: A prospective observational cohort study involved over 500,000 UK Biobank participants, enrolled from 2006 to 2010, with up to 11 years of follow-up.
Method: Kidney function was evaluated using the estimated glomerular filtration rate (eGFR) calculated by the CKD-EPI creatinine-cystatin C equation; Aging degree was using AI-based retinal age gap (RAG) and phenotypic age acceleration (PAA).
Main Outcome Measures: ARED development.

Results : Results: Increased RAG and PAA were linked to higher ARED risk. Each additional year in retinal age gap raised the risk of DR by 7% (HR, 1.07; 95% CI, 1.04–1.09), AMD by 6% (HR, 1.06; 95% CI, 1.04–1.09), and glaucoma by 5% (HR, 1.05; 95% CI, 1.03–1.07). Renal function decline correlated significantly with increased RAG and PAA. Even after adjusting for confounders, the RAG was -0.20 (95% CI, -0.25 to -0.15; P<0.001) in mild-CKD and -0.35 (95% CI -0.51 to -0.20; P<0.001) in moderate-to-severe CKD (MS-CKD) groups. Analysis of genetic risk and renal function's joint effect on ARED revealed that MS-CKD individuals with high polygenic risk score (PRS) had a 48% increased DR risk (HR, 0.48; 95% CI, 0.41–0.57), and 64% in the low-PRS group (HR, 0.64; 95% CI, 0.51–0.81) (all P<0.05).

Conclusions : Conclusions: This study presents the inaugural longitudinal evidence demonstrating the efficacy of the RAG and PAA in identifying the risk of ARED. Additionally, it reveals a significant correlation between impaired kidney function, accelerated aging, and an increased risk of developing DR and glaucoma.

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.

×