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on November 2, 2006

Arteriosclerosis, Thrombosis, and Vascular Biology. 2006
Published online before print November 2, 2006, doi: 10.1161/01.ATV.0000251503.35795.4f
A more recent version of this article appeared on January 1, 2007
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*Substance via MeSH

Submitted on August 30, 2006
Accepted on October 16, 2006

Biomarkers of Atherosclerotic Plaque Instability and Rupture

Wolfgang Koenig * and Natalie Khuseyinova

From the Department of Internal Medicine II-Cardiology, University of Ulm Medical Center, Germany.

* To whom correspondence should be addressed. E-mail: wolfgang.koenig{at}uniklinik-ulm.de.

Abstract--Basic research over the last two decades has identified a large number of molecules pertinent to the atherosclerotic process, which have clearly improved our understanding of the underlying pathology. It is now well established that inflammation represents a major feature which is present in the vessel wall throughout all stages of the disease until the final pathophysiologic steps, representing plaque destabilization and eventually plaque rupture. Several cells typical for the atherosclerotic plaque, like monocyte-derived macrophages and T-lymphocytes are able to produce and secrete such mediator molecules, like cytokines, chemokines, growth-factors, enzymes, and disintegrins, which lead to activation of endothelial cells, proliferation of smooth muscle cells, lesion progression, and finally to the weakening of a vulnerable plaque by matrix degradation of its fibrous cap. Today, many of these molecules involved can be measured systemically by sensitive assays, and elevated concentrations in the circulation have been shown to be associated with future cardiovascular events. Determination of several of these molecules carries important prognostic information, independent of traditional risk factors, and may turn out to be useful in improving risk stratification. However, for most of these biomarkers the clinical utility has not yet been established.


Key words: biomarkers • atherosclerosis • pathophysiology • risk prediction




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