Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques

Sarah R. Langley(King's College London), Karin Willeit(Innsbruck Medical University), Athanasios Didangelos(King's College London), Ljubica Matic(Karolinska Institutet), Philipp Skroblin(King's College London), Javier Barallobre‐Barreiro(King's College London), Mariette Lengquist(Karolinska Institutet), Gregor Rungger(Krankenhaus Bruneck), Alexander Kapustin(King's College London), Ludmilla Kedenko(Paracelsus Medical University), Chris Molenaar(King's College London), Ruifang Lu(King's College London), Temo Barwari(King's College London), Gonca Suna(King's College London), Xiaoke Yin(King's College London), Bernhard Iglseder(Paracelsus Medical University), Bernhard Paulweber(Paracelsus Medical University), Peter Willeit(Innsbruck Medical University), Joseph Shalhoub(Imperial College London), Gerard Pasterkamp(Utrecht University), Alun H. Davies(Imperial College London), Claudia Monaco(University of Oxford), Ulf Hedin(Karolinska Institutet), Catherine M. Shanahan(King's College London), Johann Willeit(Innsbruck Medical University), Stefan Kiechl(Innsbruck Medical University), Manuel Mayr(King's College London)
Journal of Clinical Investigation
March 19, 2017
Cited by 180Open Access
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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.


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