New study shows how AI and genetics can predict heart disease
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Introduction
Heart disease remains the world’s leading cause of death, and preventing it depends on knowing who’s at risk. A new study published in Nature Medicine shows how advanced computer models combining genetic data and health records can predict the 10-year risk of coronary artery disease (CAD) with greater accuracy than ever before.
What Did the Study Do?
Researchers looked at data from over 330,000 people in the UK Biobank and developed a new tool called a “meta-prediction” model. This model brings together both modifiable factors (like cholesterol and blood pressure) and unmodifiable ones (like age and genetics) to give a personalized risk score for each person.
The model uses machine learning, a type of artificial intelligence, to find patterns in around 2,000 pieces of health information per person — including lab tests, medications, diagnoses, lifestyle habits, and more.
What Makes This Model Special?
Most current risk calculators, like QRISK3 or PCE, are based on a limited number of health factors. This new model includes:
- 22 genetic risk scores (also called polygenic risk scores, or PRSs)
- 13 measured clinical values (like cholesterol, diabetes markers, and body mass index)
- 15 “meta-features” — predictions based on earlier disease signs or risks, like sleep problems or heart conditions
Combining all these factors allows the model to predict whether someone is likely to develop heart disease over the next 10 years — and by how much.
How Accurate Is It?
The new model predicted future heart disease with an accuracy score (AUROC) of 0.84, which is better than any of the current widely-used tools. For comparison:
- QRISK3 scored 0.75
- PCE scored 0.73
- Most other models scored between 0.72 and 0.79
This means the new model is more precise at identifying high-risk individuals and could help doctors make better decisions about early treatment and prevention.
Why Genetics Matter
One of the key advantages of this approach is how it uses genetic risk. Our DNA can carry hidden risk for heart disease, even if we look healthy today. The study found that people with high genetic risk benefited more from lifestyle changes or medications like statins.
In short: knowing your genes can help personalize your treatment.
Who Benefits the Most?
Interestingly, the model performed especially well for:
- People considered “low-risk” by traditional models
- Women
- Younger individuals
- People with normal cholesterol or blood pressure levels, but hidden genetic risks
This could help catch cases that current tools often miss.
What This Means for the Future
This study shows that combining genetics with everyday health data can create a smarter way to predict — and prevent — heart disease. The model can even suggest which changes (like lowering cholesterol) will have the biggest effect for a specific person.
In the future, your doctor might use tools like this to give you a custom heart health plan based on your unique risk profile — not just your age or test results.
Final Thoughts
This research is a big step toward precision prevention — using data and technology to stop disease before it starts. As health systems begin adopting more AI-driven tools, this type of risk prediction model could help millions of people live longer, healthier lives.