Combining information about the pattern of blood vessels in the retina with genetic data can enable accurate prediction of individual risk of coronary heart disease (CAD) and its life-threatening outcome, myocardial infarction (MI), commonly known as heart attack. The discovery could lead to a simple screening process where a risk of myocardial infarction could be calculated when a person undergoes a routine eye test, researchers will tell the European Society of Human Genetics annual conference today ( Monday).
We already knew that variations in retinal vasculature could provide insight into our health. Since retinal imaging is a non-invasive technique, we decided to investigate the health benefits we could get from these images. First, we investigated the branching patterns of the retinal vasculature by calculating a measure called fractal dimension (Df) from data available from the UK Biobank (UKB). UKB includes demographic, epidemiological, clinical, imaging and genotyping data from over 500,000 participants across the UK. We found that lower Df, simplified branching patterns of vessels, is related to CAD and therefore MI.”
Ms Ana Villaplana-Velasco, PhD Candidate at Usher and Roslin Institutes, University of Edinburgh, Edinburgh, UK
The researchers then developed a model capable of predicting the prediction of MI risk by studying UKB participants who had experienced an MI event after their retinal images were collected. The model included Df along with traditional clinical factors, such as age, gender, systolic blood pressure, body mass index, and smoking status to calculate personalized MI risk. “Strikingly, we found that our model was able to better classify participants at low or high risk for MI in the UKB compared to established models that only include demographic data. Improving our model was even higher if we added a score related to the genetic propensity to develop MI,” Ms. Villaplana-Velasco said.
“We wondered if the Df-MI association was influenced by shared biology, so we looked at the genetics of Df and found nine genetic regions that mediate retinal vascular branching patterns. Four of these regions are known to be implicated in the genetics of cardiovascular disease. In particular, we found that these common genetic regions are involved in processes related to MI severity and recovery.”
These results may also be useful in identifying propensity for other diseases. Variations in the retinal vascular pattern also reflect the development of other ocular and systemic diseases, such as diabetic retinopathy and stroke. The researchers think it’s possible that each condition has a unique pattern of retinal variation. “We would like to investigate this further and undertake a gender-specific analysis. We know that women at higher risk of MI or coronary artery disease tend to have pronounced retinal vascular deviations compared to the male population. We would like to repeat our analysis separately in males and females to determine whether a sex-specific model for myocardial infarction complements better risk classification,” says Villaplana-Velasco.
Even though the researchers knew that variations in retinal vasculature were associated with an individual’s health status, their compelling results came as a surprise. “There have been several attempts to improve predictive models of CAD and MI risk by accounting for retinal vascular traits, but these showed no significant improvement over established models. In our case, we found that the MI clinical definition – the diagnostic codes that describe myocardial infarction events in medical records – is critical to the successful development of predictive models, which underlies the need to develop robust disease definitions in large studies such than UKB. Once we validated our MI definition, we found that our model performed extremely well,” said Villaplana-Velasco.
In the future, a simple retinal scan may provide enough information to identify those at risk. The average age of an MI is 60, and the researchers found that their model achieved its best predictive performance more than five years before the MI event. “Thus, calculating an individualized risk of MI from over 50 would seem appropriate,” says Villaplan-Velasco. “This would allow doctors to suggest behaviors that can reduce risk, such as quitting smoking and maintaining normal cholesterol and blood pressure levels. Our work once again shows the importance of ‘a comprehensive analysis of routinely collected data and its value in the further development of personalized medicine.’
Professor Alexandre Reymond, chair of the conference, said: “This study demonstrates the importance of implementing prevention now, and how personalized health provides us with the tools to do so.”
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