Fig. 1: Overview of the study workflow.

Workflow of the proposed FLEX framework, outlining the development and application of retinal age models in healthy women to explore the relationship between retinal aging and reproductive aging. a The Healthy Cohort Retinal Age Model Weights were trained using transfer learning based on the Healthy Cohort, and these weights were subsequently utilized for fundus feature extraction. b The study involved ophthalmic examinations, questionnaires, and Anti-Müllerian hormone (AMH) testing for the Healthy Female Cohort (middle panel). The cohort was stratified by AMH levels into quartiles, with the middle two quartiles (medium AMH group) being used to train a Female Retinal Age Model using the Healthy Cohort Retinal Age Model Weights (upper left panel). The trained model was then applied to predict retinal age for the highest quartile (high AMH group) and the lowest quartile (low AMH group). The retinal age gap served as a measure of an individual’s reproductive aging level. Further analyses were conducted to explore the relationship between the retinal age gap and AMH levels, as well as between reproductive characteristics and AMH levels (lower left panel). Whole-genome sequencing identified Single Nucleotide Polymorphisms (SNPs), which were analyzed in relation to the predicted retinal age gap (top right panel). Additionally, retinal images were integrated with genetic data to predict AMH levels (bottom right panel).