Research published in the open access journal Genome Medicine could help to personalize treatments based on a patient's individual risk in conjunction with other risk factors such as smoking or family history.
Each year 7.5 million deaths can be attributed to coronary heart disease globally. It is caused by narrowing of the coronary arteries, reducing blood flow to the heart.
Blood gene expression has already been proposed as a way of identifying healthy individuals at the highest risk of heart disease and heart attack. Here, researchers from Georgia Institute of Technology and Emory University describe a genomic signature to predict outcomes for people with coronary heart disease or who have recently had a heart attack.
Greg Gibson from Georgia Institute of Technology, one of the lead authors, and colleagues were researching wellness when they decided to expand their research in the area of gene expression in the clinical cardiology field. They examined gene expression in blood samples of 338 people with heart disease. They found specific gene expression patterns suggestive of down-regulated T-cell signaling and up-regulated inflammation in association with heart attack, and a subset of 200 or so of these genes that are also elevated in 31 people who subsequently died of an acute cardiovascular event.
The researchers say the next steps are for other groups to independently validate their results. If validated, looking at gene expression of circulating blood as well other measures such as, cholesterol and blood pressure, could act as significant predictors of having a heart attack or death as a result of coronary heart disease. To become useful in clinical practice further work also needs to be done to identify the mechanism between the association of gene expression and risk of death.
Greg Gibson says: "We would like to establish how to combine this type of measure with traditional risk factors, and other newly developed markers including genotypes to provide actionable advice for patients. We envisage a tiered approach to genomic medicine for coronary heart disease risk assessment that incorporates traditional risk factors, biochemical biomarkers, genotypic risk scores, and gene expression."