Literature DB >> 35229564

Biomarkers of endothelial activation and dysfunction in cardiovascular diseases.

Jun Zhang1.   

Abstract

Endothelial activation and dysfunction is an important contributor to atherosclerosis, cardiovascular diseases and cardiorenal syndrome. Endothelial dysfunction is also linked with metabolic syndrome and type II diabetes. The search for specific and sensitive biomarkers of endothelial activation and dysfunction may have important clinical implications. This review pinpoints the differences in biomarkers between endothelial activation and endothelial dysfunction in cardiovascular diseases, and then briefly describes the most relevant biomarkers of endothelial activation. Biomarkers of endothelial activation include endothelial adhesion molecules, cytokines, C-reactive protein, CD62E+/E-selectin activated endothelial microparticles, oxidation of low density lipoproteins, asymmetric dimethylarginine and endocan. This review also presents an update on the novel biomarkers of endothelial dysfunction, such as matrix metalloproteinases (e.g., MMP-7, MMP-9), ANGPTL2, endogdlin, annexin V+ endothelial apoptotic microparticles, and serum homocysteine. Finally, this review emphasizes the limitations of biomarkers of endothelial activation and dysfunction in clinical setting.
© 2022 The Author(s). Published by IMR Press.

Entities:  

Keywords:  biomarkers; cardiovascular diseases; endothelial activation; endothelial dysfunction

Mesh:

Substances:

Year:  2022        PMID: 35229564     DOI: 10.31083/j.rcm2302073

Source DB:  PubMed          Journal:  Rev Cardiovasc Med        ISSN: 1530-6550            Impact factor:   2.930


  2 in total

1.  Clinical, biochemical, and miRNA profile of subjects with positive screening of primary aldosteronism and nonclassic apparent mineralocorticoid excess.

Authors:  Alejandra Tapia-Castillo; Cristian A Carvajal; Jorge A Pérez; Carlos E Fardella
Journal:  Endocrine       Date:  2022-06-08       Impact factor: 3.925

2.  Identifying potential signatures for atherosclerosis in the context of predictive, preventive, and personalized medicine using integrative bioinformatics approaches and machine-learning strategies.

Authors:  Jinling Xu; Hui Zhou; Yangyang Cheng; Guangda Xiang
Journal:  EPMA J       Date:  2022-07-20       Impact factor: 8.836

  2 in total

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