Tenascin C: A Potential Biomarker for Predicting the Severity of Coronary Atherosclerosis

Aims: Coronary artery disease (CAD) is the leading cause of mortality and morbidity worldwide and one of the greatest threats to public health. Tenascin C (TNC) is an extracellular matrix glycoprotein that is found in low concentrations in normal tissues and is enhanced by a range of cardiovascular pathologies. This study aimed to evaluate the value of TNC in assessing the severity of atherosclerosis measured by the Gensini score. Methods: A total of 157 patients with chest pains who underwent selective coronary angiography for suspected coronary atherosclerosis were enrolled. The patients were divided into the CAD group and non-CAD group according to symptoms and angiography. Demographic data and laboratory analyses were collected. Results: The mean TNC level was significantly higher in the CAD group than in the non-CAD group (p < 0.001). A significant positive correlation between TNC levels and Gensini score (p < 0.01, r = 0.672) was found. ROC curve analysis demonstrated that the cutoff value for TNC at 89.48 ng/mL was well differentiated in the CAD and non-CAD groups. Furthermore, TNC was also a good predictor for a higher Gensini score (the third tertile) in the ROC curve analysis. When the cutoff was accepted as 100.91 ng/mL, the sensitivity and specificity were 82.7% and 79%, respectively. Conclusion: A significant relationship was found between the Gensini score and serum TNC level. TNC levels can be considered in risk assessments for CAD before angiography.