ArticleBiomarker insights2008
Proteomic Biomarkers of Atherosclerosis.
Article in Biomarker insights, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 30 citations in OpenAlex.
- Identifying Biomarkers for Atherosclerosis via Gene Expression and Biological Networking.Current cardiology reviews · 2025Review
- Functional pathways associated with human carotid atheroma: a proteomics analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2019Article
- Novel Multiomics Profiling of Human Carotid Atherosclerotic Plaques and Plasma Reveals Biliverdin Reductase B as a Marker of Intraplaque Hemorrhage.JACC. Basic to translational science · 2018Article
- Article
- Pathway analysis and transcriptomics improve protein identification by shotgun proteomics from samples comprising small number of cells--a benchmarking study.BMC genomics · 2014Article
- Perspectives on the value of biomarkers in acute cardiac care and implications for strategic management.Biomarker insights · 2013Article
- Article
- A proteomic focus on the alterations occurring at the human atherosclerotic coronary intima.Molecular & cellular proteomics : MCP · 2011Article
- Evaluation of serum cathepsin D concentrations in coronary artery disease.Indian heart journalArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
summaryBiomarkers provide a powerful approach to understanding the spectrum of cardiovascular diseases. They have application in screening, diagnostic, prognostication, prediction of recurrences and monitoring of therapy. The "omics" tool are becoming very useful in the development of new biomarkers in cardiovascular diseases. Among them, proteomics is especially fitted to look for new proteins in health and disease and is playing a significant role in the development of new diagnostic tools in cardiovascular diagnosis and prognosis. This review provides an overview of progress in applying proteomics to atherosclerosis. First, we describe novel proteins identified analysing atherosclerotic plaques directly. Careful analysis of proteins within the atherosclerotic vascular tissue can provide a repertoire of proteins involved in vascular remodelling and atherogenesis. Second, we discuss recent data concerning proteins secreted by atherosclerotic plaques. The definition of the atheroma plaque secretome resides in that proteins secreted by arteries can be very good candidates of novel biomarkers. Finally we describe proteins that have been differentially expressed (versus controls) by individual cells which constitute atheroma plaques (endothelial cells, vascular smooth muscle cells, macrophages and foam cells) as well as by circulating cells (monocytes, platelets) or novel biomarkers present in plasma.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.