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Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques

Overview of attention for article published in Journal of Clinical Investigation, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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18 tweeters
facebook
1 Facebook page

Citations

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26 Dimensions

Readers on

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67 Mendeley
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Title
Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques
Published in
Journal of Clinical Investigation, March 2017
DOI 10.1172/jci86924
Pubmed ID
Authors

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 Pasterkamp, Alun H. Davies, Claudia Monaco, Ulf Hedin, Catherine M. Shanahan, Johann Willeit, Stefan Kiechl, Manuel Mayr

Abstract

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. 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. 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. 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. 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.

Twitter Demographics

The data shown below were collected from the profiles of 18 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
United Kingdom 1 1%
Unknown 65 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 25%
Researcher 17 25%
Unspecified 13 19%
Professor 4 6%
Student > Master 3 4%
Other 13 19%
Readers by discipline Count As %
Unspecified 22 33%
Medicine and Dentistry 15 22%
Biochemistry, Genetics and Molecular Biology 14 21%
Agricultural and Biological Sciences 13 19%
Chemistry 2 3%
Other 1 1%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 March 2017.
All research outputs
#881,402
of 9,247,714 outputs
Outputs from Journal of Clinical Investigation
#1,730
of 6,885 outputs
Outputs of similar age
#39,207
of 260,338 outputs
Outputs of similar age from Journal of Clinical Investigation
#57
of 136 outputs
Altmetric has tracked 9,247,714 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,885 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 260,338 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.