Association of matrix metalloproteinases and adhesive molecules with important aspects of carotid artery stenosis.

基质金属蛋白酶和粘附分子与颈动脉狭窄的重要方面相关

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作者:Ružanović Ana, Sarić-Matutinović Marija, Milinković Neda, Jovičić Snežana, Dimić Andreja, Matejević David, Kostić Ognjen, Gaković Branko, Končar Igor, Ignjatović Svetlana
BACKGROUND: Symptom risk assessment in carotid artery stenosis (CAS) could be improved by parameters that reflect additional risk aspects such as chronic inflammation rate, and atherosclerotic activity on a systemic level. In light of that, we investigated the association of serum matrix metalloproteinases-2,7,9 (MMP-2,7,9), vascular cell adhesion molecule-1 (VCAM-1) and selectins-P and E with symptomatic status, stenosis degree and plaque morphology in CAS patients in order to select parameters that associate to important clinical determinants of the symptom development risk. METHODS: The study included 119 CAS patients and 46 healthy subjects. Carotid arteries were examined by color flow Doppler and B-mode Duplex ultrasound. Serum parameters were assessed using commercially available enzyme-linked immunosorbent assays (ELISA). Difference was tested by Mann-Whitney U, Kruskal-Wallis and Chi-square tests, and Spearman's correlation was tested. RESULTS: MMP-7 and selectin-P levels were higher in CAS than in controls (p<0.001). Positive correlation with stenosis degree was found for MMP-7 (r=0.155, p=0.007), VCAM-1 (r=0.127, p=0.029) and selectin-P (r=0.269, p<0.001). MMP-7 and selectin-P were higher in subjects with Grey-Weale 2, comparing to subjects with Grey-Weale 3 plaques (p=0.036, p=0.009). Selectin-P was lower in the presence of Grey-Weale 4 than in Grey-Weale 2 (p=0.045). CONCLUSIONS: Concurrent association of MMP-7 and selectin-P with both stenosis degree and carotid plaque morphology shows the joint influence of these important determinants of symptom risk that is reflected in serum parameters. This indicates that they can supply additional information outside ultrasound CAS assessment only, and their integration in a future multiscale approach for CAS risk prediction could be beneficial.

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