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Background ageing is an important risk factor for a variety of human pathologies. Biological age (BA) may better capture ageing-related physiological changes compared with chronological age (CA). Objective we developed a deep learning (DL) algorithm to predict BA based on retinal photographs and evaluated the performance of our new ageing marker in the risk stratification of mortality and major morbidity in general populations. Methods we first trained a DL algorithm using 129,236 retinal photographs from 40,480 participants in the Korean Health Screening study to predict the probability of age being ≥65 years ('RetiAGE') and then evaluated the ability of RetiAGE to stratify the risk of mortality and major morbidity among 56,301 participants in the UK Biobank. Cox proportional hazards model was used to estimate the hazard ratios (HRs). Results in the UK Biobank, over a 10-year follow up, 2,236 (4.0%) died; of them, 636 (28.4%) were due to cardiovascular diseases (CVDs) and 1,276 (57.1%) due to cancers. Compared with the participants in the RetiAGE first quartile, those in the RetiAGE fourth quartile had a 67% higher risk of 10-year all-cause mortality (HR = 1.67 [1.42–1.95]), a 142% higher risk of CVD mortality (HR = 2.42 [1.69–3.48]) and a 60% higher risk of cancer mortality (HR = 1.60 [1.31–1.96]), independent of CA and established ageing phenotypic biomarkers. Likewise, compared with the first quartile group, the risk of CVD and cancer events in the fourth quartile group increased by 39% (HR = 1.39 [1.14–1.69]) and 18% (HR = 1.18 [1.10–1.26]), respectively. The best discrimination ability for RetiAGE alone was found for CVD mortality (c-index = 0.70, sensitivity = 0.76, specificity = 0.55). Furthermore, adding RetiAGE increased the discrimination ability of the model beyond CA and phenotypic biomarkers (increment in c-index between 1 and 2%). Conclusions the DL-derived RetiAGE provides a novel, alternative approach to measure ageing. [ABSTRACT FROM AUTHOR]

To evaluate ethnic variations, ocular and systemic determinants of retinal nerve fiber layer (RNFL) thickness, and neuroretinal rim area among Asians using a large consortium of population-based eye studies. Cross-sectional pooled analysis. Twenty-two thousand four hundred thirty-six participants (22 436 eyes) from 10 population-based studies (in China, Hong Kong, India, Japan, Russia, and Singapore) of the Asian Eye Epidemiology Consortium. Participants 40 years of age or older without glaucoma were included. All participants underwent spectral-domain OCT imaging and systemic and ocular examinations. Data were pooled from each study. Multivariable regression was performed to evaluate interethnic differences, intermachine variations, and ocular and systemic factors associated with RNFL thickness and rim area, adjusting for age, gender, diabetes, intraocular pressure (IOP), spherical equivalent (SE), ethnicity, OCT model, and study group. When evaluating body mass index, smoking, and hypertension as exposures, these factors were additionally adjusted for in the model. Average RNFL thickness (in micrometers) and rim area (in square millimeters). Indian and Japanese eyes have thinner RNFLs than those of other Asian ethnicities (β values range, 7.31–12.76 μm; P < 0.001 for all pairwise comparisons). Compared with measurements by Cirrus HD-OCT (Carl Zeiss Meditec, Inc), RNFL on average was 7.29 μm thicker when measured by Spectralis (Heidelberg Engineering), 12.85 μm thicker when measured by RS-3000 (NIDEK Co, Ltd), and 17.48 μm thicker when measured by iVue/RTVue (Optovue, Inc) devices (all P < 0.001). Additionally, older age (per decade, β = –2.70), diabetes (β = –0.72), higher IOP (per 1 mmHg, β = –0.07), more myopic SE (per diopter, β = –1.13), cardiovascular disease (β = –0.94), and hypertension (β = –0.68) were associated with thinner RNFL (all P ≤ 0.003). Similarly, older age (β = –0.019), higher IOP (β = –0.010), and more myopic SE (β = –0.025) were associated with smaller rim area (all P < 0.001). In this large pooled analysis of Asian population studies, Indian and Japanese eyes were observed to have thinner RNFL profiles. These findings suggest the need for an ethnic-specific normative database to improve glaucoma detection. [ABSTRACT FROM AUTHOR]