Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques

Sarah R Langley, Karin Willeit, Athanasios Didangelos, Ljubica Perisic Matic, Philipp Skroblin, Javier Barallobre-Barreiro, Mariette Lengquist, Gregor Rungger, Alexander Kapustin, Ludmilla Kedenko, Chris Molenaar, Ruifang Lu, Temo Barwari, Gonca Suna, Xiaoke Yin, Bernhard Iglseder, Bernhard Paulweber, Peter Willeit, Joseph Shalhoub, Gerard PasterkampAlun H Davies, Claudia Monaco, Ulf Hedin, Catherine M Shanahan, Johann Willeit, Stefan Kiechl, Manuel Mayr

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)1546-1560
Number of pages15
JournalJournal of Clinical Investigation
Volume127
Issue number4
DOIs
Publication statusPublished - 2017

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