Abstract
Objective. Metabolic syndrome (MS) and type 2 diabetes mellitus (T2DM) share a chronic low-grade inflammatory milieu driven by adiposity. C-X-C motif chemokine ligand 1 (CXCL1) has been linked to insulin resistance and endothelial dysfunction, but its diagnostic relevance remains unclear.
Methods. Our study employed a cross-sectional design and enrolled 104 adults: 52 newly diagnosed treatment-naive T2DM patients and 52 normoglycemic controls matched for age and sex. Serum CXCL1, high-sensitivity C-reactive protein (hs-CRP), and metabolic parameters were measured. Logistic regression models to discriminate MS and T2DM status were constructed (base model: age, sex, BMI) and then expanded by adding hs-CRP, CXCL1, or both. Model performance was assessed for discrimination (AUC), calibration (Integrated Calibration Index [ICI], Expected Calibration Error [ECE]), and clinical utility (decision curve analysis, DCA) in accordance with TRIPOD 2024.
Results. CXCL1 correlated with BMI (r=0.33, q=0.004) and hs-CRP (r=0.29, q=0.021), but not glycemic indices. For MS, CXCL1 marginally improved the base model (ΔAUC=+0.003, p=0.81); for T2DM, ΔAUC=+0.007 (p=0.60). hs-CRP performed better (AUC=0.744 for T2DM; 0.743 for MS) and the combined panel achieved the highest discrimination (AUC=0.769 and 0.745, respectively).
Conclusions. CXCL1 reflects adiposity-related inflammation but provides only minimal incremental discrimination for metabolic syndrome and T2DM beyond conventional markers such as age, sex, BMI, and hs-CRP. The combined hs-CRP+CXCL1 panel achieved the best overall statistical performance, although its clinical utility remains limited. These findings emphasize the need for integrated multi-marker approaches rather than single-biomarker screening in metabolic risk assessment.