No abstract

Fundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Using a fully automated image processing pipeline, we extracted 17 different morphological vascular phenotypes, including median vessels diameter, diameter variability, main temporal angles, vascular density, central retinal equivalents, the number of bifurcations, and tortuosity, from over 130k fundus images of close to 72k UK BioBank subjects. We performed genome-wide association studies (GWAS) of these parameters. From this, we estimated their individual heritabilities, ranging between 5 and 25%, and genetic cross-trait correlations, which mostly mirrored the corresponding phenotypic correlations, but tended to be slightly larger. Projecting our genetic association signals onto genes and pathways revealed remarkably low overlap suggesting largely decoupled mechanisms modulating the different traits. Our disease trait associations confirmed some previously known findings and revealed many novel connections. Notably, diameter variability, especially for the veins, seems to have many new and interesting associations with multiple disease traits, including age of death, pulmonary embolism, and heart attack. Our analyses provide evidence that large-scale analysis of image-derived vascular traits has sufficient power for obtaining functional, as well as some initial causal insights into the processes modulating the retinal vasculature.