The researchers used data from UK Biobank, which contains medical and lifestyle records for 500,000 people, to calculate a measure known as fractal dimension. They combined the measure in a model with other factors, such as age, sex, systolic blood pressure, body mass index and smoking status.
The research team then studied people in the database who had experienced a heart attack, or myocardial infarction, after retinal images had been collected.
“Strikingly, we discovered that our model was able to better classify participants with low or high MI risk in UK Biobank when compared with established models that only include demographic data,” Ana Villaplana-Velasco, the presenting author and a PhD student at the Usher and Roslin institutes at the University of Edinburgh, told The Guardian.
The researchers said their analysis found a shared genetic basis between fractal dimension and myocardial infarction.
“The improvement of our model was even higher if we added a score related to the genetic propensity of developing MI,” she said.
The average age for a heart attack is 60. The research team found that their model had its best predictive performance more than 5 years before a heart attack occurred. In the future, the researchers hope that a simple retinal exam can provide enough information to identify people with high risks.
“The calculation of an individualized MI risk from those over 50 years old would seem to be appropriate,” she said. “This would enable doctors to suggest behaviors that could reduce risk, such as giving up smoking and maintaining normal cholesterol and blood pressure.”
The study will be presented at the European Society of Human Genetics annual conference in Vienna this week.