Gene Expression Profiling of Human Atherosclerosis

• Atherosclerosis is the main underlying cause of coronary artery disease (CAD) and stroke. These two diseases are leading causes of death in the developed world. The socio-economical cost for treatments and absence of work is enormous. Recent numbers from the US show no tendency of decline in the spread of atherosclerosis.Common risk factors for premature atherosclerosis are obesity, diabetes, smoking, physical inactivity and high blood pressure. Medications have been developed for treatment of risk factors and a breakthrough was the release of statins, an effective lipid-lowering drug. Nevertheless, atherosclerosis is multi-factorial and all the different players in the pathological process are not yet identified. New large-scale studies, such as gene expression profiling, are needed to understand the interplay between risk factors and pathways in atherosclerosis and with that reveal new therapeutic targets.In this thesis two studies are presented where gene expression profiling in well-characterized patients suffering from severe atherosclerosis have been performed. In study number one, five types of tissues (atherosclerotic aortic root, unatherosclerotic mammary artery, mediastinal fat, skeletal muscle and liver) were collected from a total of 66 patients undergoing coronary by-pass surgery. Subjects were also screened for cardiovascular risk factors. RNA was isolated from the biopsies and gene expression analysis using Affymetrix GeneChip system was performed. The main result showed that mediastinal fat appears to be central in CAD.In study number two, gene expression analysis of plaques from patients undergoing carotid endorectomy was performed. Again, all patients were screened for conventional risk factors and RNA was isolated and expression profiles were obtained using Affymetrix technology. Cluster analyses identified genes associated to intima-media thickness in these patients.Taken together, expression analyses of clinical whole-genome expression datasets can be used to identify novel pathways and individual genes with possible importance for atherosclerosis development.

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