European review for medical and pharmacological sciences · 2022
MOTS-c as a predictor of coronary lesions and complexity in patients with stable coronary artery disease.
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Yaşar E, Çakmak T, Bayramoğlu A, Karakuş Y, Tekin S, Şekerci G, Türkoğlu C
Аннотация
OBJECTIVE: Atherosclerosis plays a major role in the development of coronary artery disease (CAD). It has been shown that mitochondrial open-reading-frame of the twelve S rRNA-c (MOTS-c), a mitochondrial-derived peptide, has preventive effects on atherosclerosis. The aim of this study was to determine the relationship between MOTS-c levels and CAD presence and severity using SYNTAX score (SS) in patients with stable angina pectoris.
PATIENTS AND METHODS: Ninety-two consecutive patients with stable coronary artery disease (CAD+) and ninety-two consecutive patients with normal coronary artery (CAD-) were included. Presence and severity of coronary artery disease were determined using the SS.
RESULTS: We observed that the MOTS-c levels was lower in the CAD group (111±13 vs. 161±23, p<0.001). The MOTS-c levels were also found to be significant independent predictors for CAD in multiple regression analysis (p<0.001). A MOTS-c levels ≥130.9 had 80.3% sensitivity and 73.2% specificity (area under the curve [AUC]: 0.858, 95% CI: 0.895-0.999, p<0.001) for predicting CAD.
CONCLUSIONS: The authors revealed that there is a strong correlation between MOTS-c levels and CAD. Therefore, MOTS-c may help identify patients with CAD, thus allowing for early preventive treatment.
PATIENTS AND METHODS: Ninety-two consecutive patients with stable coronary artery disease (CAD+) and ninety-two consecutive patients with normal coronary artery (CAD-) were included. Presence and severity of coronary artery disease were determined using the SS.
RESULTS: We observed that the MOTS-c levels was lower in the CAD group (111±13 vs. 161±23, p<0.001). The MOTS-c levels were also found to be significant independent predictors for CAD in multiple regression analysis (p<0.001). A MOTS-c levels ≥130.9 had 80.3% sensitivity and 73.2% specificity (area under the curve [AUC]: 0.858, 95% CI: 0.895-0.999, p<0.001) for predicting CAD.
CONCLUSIONS: The authors revealed that there is a strong correlation between MOTS-c levels and CAD. Therefore, MOTS-c may help identify patients with CAD, thus allowing for early preventive treatment.