In American journal of kidney diseases : the official journal of the National Kidney Foundation
RATIONALE & OBJECTIVE : The incidence of end stage kidney disease (ESKD) is known to increase with age. We have previously developed and validated retinal age based on fundus images used as a biomarker of ageing. However, the association of retinal age with ESKD is not clear. We investigated the association of the difference between retinal age and chronological age, the retinal age gap, and the future risk of ESKD.
STUDY DESIGN : Prospective cohort study.
SETTING & PARTICIPANTS : 11,052 UK Biobank study participants without any reported disease for characterizing retinal age in a deep learning algorithm. 35,864 other participants with retinal images and no ESKD were followed to assess the association between retinal age gap and the risk of ESKD.
EXPOSURE : Retinal age gap defined as the difference between model-based retinal age and chronological age.
OUTCOME : Incident ESKD.
ANALYTICAL APPROACH : A deep learning prediction model used to characterize retinal age based on retinal images and chronological age. Cox proportional hazards regression models to investigate the association of retinal age gap with incident ESKD.
RESULTS : After a median follow-up of 11 years (interquartile range [IQR]:10·89-11·14), 115 (0·32%) participants were diagnosed with ESKD. Each one-year increase in retinal age gap was independently associated with a 10% increase in the risk of incident ESKD (hazard ratio [HR] = 1·10, 95% confidence interval [CI]: 1·03-1·17, P = 0·003). Participants with retinal age gaps in the fourth quartile had a significantly higher risk of incident ESKD compared to those in the first quartile (HR = 2·77, 95% CI:1·29-5·93, P = 0·009).
LIMITATIONS : Limited generalizability because of the composition of paticipants in the UK Biobank study.
CONCLUSION : Retinal age gap was significantly associated with incident ESKD and may be a promising non-invasive biomarker for of incident ESKD.
Zhang Shiran, Chen Ruiye, Wang Yan, Hu Wenyi, Kiburg Katerina V, Zhang Junyao, Yang Xiaohong, Yu Honghua, He Mingguang, Wang Wei, Zhu Zhuoting
2022-Dec-01
ageing, biomarker, end stage kidney disease, kidney, retinal age
