Comparative evaluation of serum TGF-β1 and PDGF-BB levels across patients with normal coronary arteries, stable coronary artery disease, and acute coronary syndrome.

BACKGROUND

To compare serum levels of Transforming Growth Factor-Beta (TGF-β) and Platelet-Derived Growth Factor-BB (PDGF-BB) among patients with normal coronary arteries (NCA) and those with coronary artery disease (CAD) subclasses [stable CAD and acute coronary syndrome (ACS)], and to evaluate their potential diagnostic value and discriminatory power, particularly in identifying stable CAD.

METHODS

This single-center, cross-sectional study included 176 patients who underwent coronary angiography. Participants were classified into normal coronary artery (NCA; symptomatic control), stable CAD, and ACS groups. Demographic, clinical, and biochemical data were recorded. Blood samples were collected for the analysis of TGF-β1 and PDGF-BB levels using ELISA kits.

RESULTS

Hypertension and diabetes mellitus were significantly more prevalent in the stable CAD group compared to others (p < 0.001). Both TGF-β and PDGF-BB levels were significantly elevated in patients with stable CAD compared to individuals with normal coronary arteries and those with ACS (p < 0.001). Multivariate regression analysis identified hypertension, diabetes, TGF-β, and PDGF-BB as independent predictors of stable CAD (p < 0.01 for all). ROC curve analysis demonstrated good diagnostic performance for TGF-β and PDGF-BB individually (AUC = 0.847, 0.798, respectively), with combined assessment further improving accuracy (AUC = 0.924).

CONCLUSION

Serum TGF-β and PDGF-BB levels are significantly increased in stable CAD patients relative to those with ACS and normal coronary anatomy. The combined evaluation of these biomarkers provides high diagnostic accuracy in distinguishing stable CAD, underscoring their potential role in the non-invasive assessment of chronic atherosclerotic disease. These findings support the use of TGF-β and PDGF-BB as complementary biomarkers for early identification and risk stratification in stable CAD.