Abstract
BACKGROUND: This study investigated whether combinations of high-density lipoprotein (HDL) subfractions and inflammatory markers would add value to coronary artery disease (CAD) prediction. METHODS: Non-CAD subjects (n=245) were stratified into low/moderate/high-Framingham risk (L/M/H-FR) groups and 180 CAD patients were enrolled. Levels of HDL-C, HDL(2), HDL(3), monocyte chemoattractant protein-1 (MCP-1), and high-sensitivity C-reactive protein (hsCRP) were measured. Multivariable logistic models for CAD were estimated with a single parameter or all parameters together after adjustment for conventional risk factors (CRFs), and Z statistics, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to compare discrimination among different models. RESULTS: The results show that HDL-C, HDL(2,) and HDL(3) gradually decreased, while MCP-1 and hsCRP gradually increased from L/M/H-FR to the CAD group. When applying a single factor in the CRFs-adjusted models, HDL-C (OR 0.011, 95% CI, 0.002-0.071, P<0.05) and HDL(2) (OR 0.000072, 95% CI, 0.000001-0.004, P<0.05), but not HDL(3), were significantly related to CAD risk. Only HDL(2) (OR 0.000072, 95% CI, 0.000001-0.004, P<0.001) remained significant when applying all HDL parameters. In the model including all HDL and inflammatory parameters, HDL(2) (OR 0.001, 95% CI, 0.000027-0.051), MCP-1 (OR 1.066, 95% CI, 1.039-1.094), and hsCRP (OR 1.130, 95% CI, 1.041-1.227) showed significant differences (all P<0.05). This combined model showed improved discrimination over the models with a single factor (P<0.05) or all HDL parameters (Z=3.299, NRI =0.179, IDI =0.081, P<0.001). CONCLUSIONS: Large HDL(2) is superior to small HDL(3) in the inverse association with CAD. The combination of HDL(2), MCP-1, and hsCRP with CRFs provides an optimal prediction for CAD.