Objective:

To explore the value of SMOC1, HSP90B1, and OPTN as potential serum biomarkers for coronary artery calcification (CAC) and construct an individualized risk prediction model, highlighting their clinical significance.

Key Findings:

• 39 differentially expressed proteins were identified (18 upregulated and 21 downregulated), with statistical significance noted.
• SMOC1 (upregulated), HSP90B1 (downregulated), and OPTN (downregulated) were identified as candidate proteins.
• The AUC of the logistic regression model for predicting CAC was 0.894, significantly higher than the baseline model (AUC = 0.845).
• Calibration curves showed good agreement between predicted and observed probabilities.

Interpretation:

The study identifies SMOC1, HSP90B1, and OPTN as potential serum biomarkers for CAC and demonstrates the effectiveness of a nomogram model that incorporates these biomarkers along with clinical indicators, suggesting its utility in clinical practice.

Limitations:

• The study's findings may not be generalizable beyond the enrolled patient population; further validation in diverse cohorts is needed to confirm the predictive model's applicability.

Conclusion:

SMOC1, HSP90B1, and OPTN are potential serum biomarkers for coronary artery calcification (CAC). A nomogram model incorporating these biomarkers and clinical indicators performs well in predicting CAC.