Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques
Langley, Sarah R; Willeit, Karin; Didangelos, Athanasios; Matic, Ljubica Perisic; Skroblin, Philipp; Barallobre-Barreiro, Javier; Lengquist, Mariette; Rungger, Gregor; Kapustin, Alexander; Kedenko, Ludmilla; Molenaar, Chris; Lu, Ruifang; Barwari, Temo; Suna, Gonca; Yin, Xiaoke; Iglseder, Bernhard; Paulweber, Bernhard; Willeit, Peter; Shalhoub, Joseph; Pasterkamp, Gerard; Davies, Alun H; Monaco, Claudia; Hedin, Ulf; Shanahan, Catherine M; Willeit, Johann; Kiechl, Stefan; Mayr, Manuel
(2017) Journal of Clinical Investigation, volume 127, issue 4, pp. 1546 - 1560
(Article)
Abstract
BACKGROUND. The identification of patients with high-risk atherosclerotic plaques prior to the manifestation of clinical events remains challenging. Recent findings question histology-and imaging-based definitions of the vulnerable plaque, necessitating an improved approach for predicting onset of symptoms. METHODS. We performed a proteomics comparison of the vascular extracellular matrix and associated
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molecules in human carotid endarterectomy specimens from 6 symptomatic versus 6 asymptomatic patients to identify a protein signature for high-risk atherosclerotic plaques. Proteomics data were integrated with gene expression profiling of 121 carotid endarterectomies and an analysis of protein secretion by lipid-loaded human vascular smooth muscle cells. Finally, epidemiological validation of candidate biomarkers was performed in two community-based studies. RESULTS. Proteomics and at least one of the other two approaches identified a molecular signature of plaques from symptomatic patients that comprised matrix metalloproteinase 9, chitinase 3-like-1, S100 calcium binding protein A8 (S100A8), S100A9, cathepsin B, fibronectin, and galectin-3-binding protein. Biomarker candidates measured in 685 subjects in the Bruneck study were associated with progression to advanced atherosclerosis and incidence of cardiovascular disease over a 10-year follow-up period. A 4-biomarker signature (matrix metalloproteinase 9, S100A8/S100A9, cathepsin D, and galectin-3-binding protein) improved risk prediction and was successfully replicated in an independent cohort, the SAPHIR study. CONCLUSION. The identified 4-biomarker signature may improve risk prediction and diagnostics for the management of cardiovascular disease. Further, our study highlights the strength of tissue-based proteomics for biomarker discovery.
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Keywords: Journal Article
ISSN: 0021-9738
Publisher: The American Society for Clinical Investigation
Note: Copyright: Copyright 2017 Elsevier B.V., All rights reserved.
(Peer reviewed)