Translational atherosclerosis research: from experimental models to coronary artery disease in humans

Atherosclerosis is the leading cause of death worldwide. Research on the pathophysiological mechanisms of atherogenesis has made tremendous progress over the past two decades. However, despite great advances there is still a lack of therapies that reduce adverse cardiovascular events to an acceptabl...

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1. Verfasser: Gleißner, Christian A. (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 14 March 2016
In: Atherosclerosis
Year: 2016, Jahrgang: 248, Pages: 110-116
ISSN:1879-1484
DOI:10.1016/j.atherosclerosis.2016.03.013
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.atherosclerosis.2016.03.013
Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S0021915016300880
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Verfasserangaben:Christian A. Gleissner

MARC

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520 |a Atherosclerosis is the leading cause of death worldwide. Research on the pathophysiological mechanisms of atherogenesis has made tremendous progress over the past two decades. However, despite great advances there is still a lack of therapies that reduce adverse cardiovascular events to an acceptable degree. This review addresses successes, but also questions, challenges, and chances regarding the translation of basic science results into clinical practice, i.e. the capability to apply the results of basic and/or clinical research in order to design therapies suitable to improve patient outcome. Specifically, it discusses problems in translating findings from the most broadly used murine models of atherosclerosis into clinically feasible therapies and strategies potentially improving the results of clinical trials. Most likely, the key to success will be a multimodal approach employing novel imaging methods as well as large scale screening tools-summarized as “omics” approach. Using individually tailored therapies, plaque stabilization and regression could prevent adverse cardiovascular events thereby improving outcome of a large number of patients. 
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