Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques.

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Title: Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques.
Authors: Langley, SR
Willeit, K
Didangelos, A
Matic, LP
Skroblin, P
Barallobre-Barreiro, J
Lengquist, M
Rungger, G
Kapustin, A
Kedenko, L
Molenaar, C
Lu, R
Barwari, T
Suna, G
Yin, X
Iglseder, B
Paulweber, B
Willeit, P
Shalhoub, J
Pasterkamp, G
Davies, AH
Monaco, C
Hedin, U
Shanahan, CM
Willeit, J
Kiechl, S
Mayr, M
Item Type: Journal 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 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. FUNDING: UK: British Heart Foundation (BHF); King's BHF Center; and the National Institute for Health Research Biomedical Research Center based at Guy's and St Thomas' NHS Foundation Trust and King's College London in partnership with King's College Hospital. Austria: Federal Ministry for Transport, Innovation and Technology (BMVIT); Federal Ministry of Science, Research and Economy (BMWFW); Wirtschaftsagentur Wien; and Standortagentur Tirol.
Issue Date: 3-Apr-2017
Date of Acceptance: 19-Jan-2017
ISSN: 0021-9738
Publisher: American Society for Clinical Investigation
Start Page: 1546
End Page: 1560
Journal / Book Title: Journal of Clinical Investigation
Volume: 127
Issue: 4
Copyright Statement: © 2017 American Society for Clinical Investigation. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit
Keywords: 11 Medical And Health Sciences
Publication Status: Published
Conference Place: United States
Appears in Collections:Division of Surgery

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