Published 3 Mar 2021
• Genomics plc’s method outperforms current tools and could help save more than 2,000 lives annually in the US alone
• Opportunity to identify individuals who are at risk of heart disease and target immediate prevention
Credit: Jennie Lin and Circulation: Genomic and Precision Medicine
03 March 2021, OXFORD, UK – Genomics plc, a pioneering healthcare company that uses large-scale genetic information to develop innovative precision healthcare tools is pleased to announce the successful results of a study in predicting coronary artery disease (CAD).
Using an integrated risk tool (IRT) which combines polygenic risk scores (PRS) with external factors such as age, sex and BMI, Genomics can more accurately predict CAD. This presents a particular opportunity for identifying high-risk individuals much earlier to target lifestyle changes and potentially interventions.
The study, published in the journal Circulation: Genomic and Precision Medicine, demonstrates that the risk of developing CAD is more accurately predicted if existing risk prediction tools used by clinicians are adjusted to include PRS. The study involved a collaboration with researchers from Stanford, the University of Oxford and University College London.
The Genomics tool was shown to be particularly effective for use on 40-54-year-old men where the PRS was in fact the most powerful individual risk factor for heart disease – more powerful for example than cholesterol, blood pressure, BMI, or smoking history. The research estimates that use of the IRT could help prevent up to 12,000 deaths in the US over a 5-year period.
Prevention is a key part of the future of healthcare provision and as we shift from reactive to preventative treatment, this study demonstrates the viability of using precision healthcare to identify risks and reduce pressure on the healthcare system.
Professor Sir Peter Donnelly, CEO of Genomics plc, said: “We have known for a long time that genetics is a major contributor to risk for heart disease. Polygenic risk scores now give us a robust way of capturing that risk for individual patients. These exciting results confirm that combining polygenic risk scores with traditional risk assessments improves their accuracy. The combined approach not only identifies more of the high-risk individuals, but it can help healthcare professionals focus better on the correct individuals, enabling earlier intervention, and in turn, the potential to save lives through more targeted introduction of statins.”