TY - JOUR
T1 - Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques
AU - Langley, Sarah R
AU - Willeit, Karin
AU - Didangelos, Athanasios
AU - Matic, Ljubica Perisic
AU - Skroblin, Philipp
AU - Barallobre-Barreiro, Javier
AU - Lengquist, Mariette
AU - Rungger, Gregor
AU - Kapustin, Alexander
AU - Kedenko, Ludmilla
AU - Molenaar, Chris
AU - Lu, Ruifang
AU - Barwari, Temo
AU - Suna, Gonca
AU - Yin, Xiaoke
AU - Iglseder, Bernhard
AU - Paulweber, Bernhard
AU - Willeit, Peter
AU - Shalhoub, Joseph
AU - Pasterkamp, Gerard
AU - Davies, Alun H
AU - Monaco, Claudia
AU - Hedin, Ulf
AU - Shanahan, Catherine M
AU - Willeit, Johann
AU - Kiechl, Stefan
AU - Mayr, Manuel
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
U2 - 10.1172/JCI86924
DO - 10.1172/JCI86924
M3 - Article
C2 - 28319050
SN - 0021-9738
VL - 127
SP - 1546
EP - 1560
JO - Journal of Clinical Investigation
JF - Journal of Clinical Investigation
IS - 4
ER -