This project dives into the aging of the retina, how its components may age at different rates, and what might keep someone’s eye from aging more slowly than that of someone else. We extract spatial data from retinal imaging of fifty thousand UK Biobank. Combining this data with additional functional and structural measures of the eye, we create a model able to predict a participant’s age. The age of different components of the eye is obtained by using subsets of the data. The retinal age gap is then calculated by comparing the predicted age to the observed age of the participant. We then integrate this information with metabolomics and proteomics data to understand if circulating metabolites and proteins might associate with slow and fast aging of the eye.