Atherosclerosis, the furring of the arteries, leads to peripheral arterial disease, coronary heart disease, stroke and heart attacks thus making it the leading cause of death.

Dr Feng Cheng and the team were able to reduce this initial set to 56 genes by focusing on genes directly involved in inflammation, lipid, carbohydrate and protein metabolism, and genes known to be responsible for the maintenance of blood cells. Genome-wide expression profiling, gene functional inference and multivariate statistical techniques were further used to 'fine tune' the test. This 'prediction array' was able to spot the people with high cholesterol, separating the patients with familial hypercholesterolemia from the control group.
Dr Jae Lee, who led the study, explained "By splitting our 56 genes into three sets, and using the COXEN algorithm, which was originally developed to identify genes involved in cancer with potentially diagnostic or therapeutic properties, we found that we could further refine our test and separate out the very high risk group." Dr Ellen Keeley continued, "This biomarker test, which only requires a blood sample, could be further developed to predict the risk of silent atherosclerosis in clinical practice."
Source-Eurekalert