RT Journal Article SR Electronic T1 Retinal age gap as a predictive biomarker for mortality risk JF British Journal of Ophthalmology JO Br J Ophthalmol FD BMJ Publishing Group Ltd. SP bjophthalmol-2021-319807 DO 10.1136/bjophthalmol-2021-319807 A1 Zhuoting Zhu A1 Danli Shi A1 Peng Guankai A1 Zachary Tan A1 Xianwen Shang A1 Wenyi Hu A1 Huan Liao A1 Xueli Zhang A1 Yu Huang A1 Honghua Yu A1 Wei Meng A1 Wei Wang A1 Zongyuan Ge A1 Xiaohong Yang A1 Mingguang He YR 2022 UL http://bjo.bmj.com/content/early/2021/11/17/bjophthalmol-2021-319807.abstract AB Aim To develop a deep learning (DL) model that predicts age from fundus images (retinal age) and to investigate the association between retinal age gap (retinal age predicted by DL model minus chronological age) and mortality risk.Methods A total of 80 169 fundus images taken from 46 969 participants in the UK Biobank with reasonable quality were included in this study. Of these, 19 200 fundus images from 11 052 participants without prior medical history at the baseline examination were used to train and validate the DL model for age prediction using fivefold cross-validation. A total of 35 913 of the remaining 35 917 participants had available mortality data and were used to investigate the association between retinal age gap and mortality.Results The DL model achieved a strong correlation of 0.81 (p<0·001) between retinal age and chronological age, and an overall mean absolute error of 3.55 years. Cox regression models showed that each 1 year increase in the retinal age gap was associated with a 2% increase in risk of all-cause mortality (hazard ratio (HR)=1.02, 95% CI 1.00 to 1.03, p=0.020) and a 3% increase in risk of cause-specific mortality attributable to non-cardiovascular and non-cancer disease (HR=1.03, 95% CI 1.00 to 1.05, p=0.041) after multivariable adjustments. No significant association was identified between retinal age gap and cardiovascular- or cancer-related mortality.Conclusions Our findings indicate that retinal age gap might be a potential biomarker of ageing that is closely related to risk of mortality, implying the potential of retinal image as a screening tool for risk stratification and delivery of tailored interventions.Data are available in a public, open access repository.