Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults
Publication: Journal of the American College of Cardiology
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8 October 2018
Summary:
Genetic factors have long been known to be major contributors of someone’s risk of developing coronary heart disease – the leading cause of heart attacks. Currently to identify those at risk doctors use scores based on lifestyle and clinical conditions associated with coronary heart disease such as cholesterol level, blood pressure, diabetes and smoking. But these scores are imprecise, age-dependent and miss a large proportion of people who appear ‘healthy’, but will still develop the disease.
The ‘big-data’ GRS technique takes into account 1.7 million genetic variants in a person’s DNA to calculate their underlying genetic risk for coronary heart disease.
The team analysed genomic data of nearly half a million people from the UK Biobank research project aged between 40-69 years. This included over 22,000 people who had coronary heart disease.
The GRS was better at predicting someone’s risk of developing heart disease than each of the classic risk factors for coronary heart disease alone. The ability of the GRS to predict coronary heart disease was also largely independent of these known risk factors. This showed that the genes which increase the risk of coronary heart disease don’t simply work by elevating blood pressure or cholesterol, for example.
People with a genomic risk score in the top 20 per cent of the population were over four-times more likely to develop coronary heart disease than someone with a genomic risk score in the bottom 20 per cent. Read the full press release