Beyond vision: leveraging retinal biomarkers to predict cardiovascular disease

Project Summary

One in three deaths are caused by cardiovascular disease (CVD). To avoid untimely deaths, those at risk must be identified early to allow targeted preventative strategies. Using a combination of photographs of the inner lining of the eye (known as retinal photographs) and genetic information, we expect we can accurately identify who is at risk. Retinal photographs reveal the health of the blood vessels and nerves and genetic information can reveal inherited risk of disease. Using artificial intelligence, we will predict CVD based on both retinal photographs alone and in combination with genetic information. We will compare our risk calculators to existing tools recommended by the health service, and use genetic analysis to explore the relationships between retinal photograph findings and disease beyond the eye. This work will represent progress toward cheap, accessible, accurate, opportunistic screening to identify those at risk of future CVD.