Molecular prediction for atherogenic risks across different cell types of leukocytes

We first discovered 356 expression biomarkers which showed significant differential expression between genome-wide microarray data of monocytes from patients with familial hyperlipidemia and increased risk of atherosclerosis compared to normal controls. These biomarkers were further triaged with 56 biomarkers known to be directly related to atherogenic risks. We also applied a COXEN algorithm to identify concordantly expressed biomarkers between monocytes and each of three different cell types of leukocytes. We then developed a multi-gene predictor using all or three subsets of these 56 biomarkers on the monocyte patient data. These predictors were then applied to multiple independent patient sets from three cell types of leukocytes (macrophages, circulating T cells, or whole white blood cells) to predict patients with atherogenic risks.When the 56 predictor was applied to the three patient sets from different cell types of leukocytes, all significantly stratified patients with atherogenic risks from healthy people in these independent cohorts. Concordantly expressed biomarkers identified by the COXEN algorithm provided slightly better prediction results.These results demonstrated the potential of molecular prediction of atherogenic risks across different cell types of leukocytes.Atherosclerosis is the leading cause of death in most countries [1]. In the United States alone, it is estimated that more than 16 million people have atherosclerotic heart disease resulting in 870, 000 deaths in 2005. Diagnosis of subclinical atherosclerosis is difficult since individuals are still asymptomatic. Early detection of atherosclerosis may help to prevent complications of the disease or slow its progression [2]. Atherosclerosis risk can first be indirectly predicted by clinical disease risk factors such as diabetes, LDL, HDL, or triglyceride. The progression of atherosclerosis, however, is a complex multifactorial process which involves multiple molecular mechanisms such as lipi