NHS launches polygenic scores pilot to calculate heart disease risk

The NHS is to trial a new approach in personalised medicine that aims to help calculate patients' individual risk for heart disease.

The approach will be evaluated in a pilot study of around 1000 patients in the North East of England. During regular GP check-ups blood samples will be taken and the DNA will be analysed for risk factors associated with cardiac diseases.

'By using genetics, we can improve risk prediction for cardiovascular disease so that therapies like statins as well as lifestyle changes, can be better targeted to the right individuals,' said Professor Sir Peter Donnelly, founder of Genomics PLC which is partnering with the NHS for the trial.

The test delivers a so-called polygenic risk score. Many common diseases are not caused by a single genetic mutation but by a large number of different risk variants spread throughout the genome. Individually these variants have very small effects on risk, but cumulatively the effect can be significant, and this is what polygenic risk scores attempt to quantify.

The new test will analyse more than a million points in the patient's genome and combine the results into an overall score. Together with non-genetic factors such as cholesterol levels and body mass index (BMI), this score will be used to decide which patients are classified as 'high risk' – those who have a ten percent chance of developing heart disease in the next ten years.

These individuals could then be closely monitored for heart disease symptoms and given lifestyle advice or drug interventions such as statins.

Polygenic risk scores can be very accurate at a population level, but their usefulness for individuals is hotly debated among genetics professionals. They are very different from other genetic tests currently used in medical contexts, both in the methods involved and in the fact that they are not predictive or diagnostic of disease. This was the source of a high-profile misunderstanding by health secretary Matt Hancock in 2019 (see BioNews 992).

If the trial is a success, the same approach could also be used to evaluate the risk for other diseases such as type 2 diabetes, bipolar disorder and several types of cancer.