Aims: Identification of novel biomarkers of diabetes risk help to understand mechanisms of pathogenesis and improve risk prediction. Our objectives were to examine the relationships between adipokines, biomarkers of inflammation and endothelial function and development of type 2 diabetes; and to assess the relevance of including these biomarkers in type 2 diabetes prediction risk models. Methods: 1345 subjects from the SU.VI.MAX study, who were free of diabetes at baseline and who completed 13 years of follow-up were included in the present analyses. Odds ratios (OR) with 95% confidence intervals (95% CI) of incident type 2 diabetes associated with a 1-SD increase in adiponectin, leptin, C-reactive protein (CRP), soluble intracellular adhesion modecule-1 (sICAM-1), soluble vascular cell adhesion molecule 1 (sVCAM-1), E-selectin and monocyte chemoattractant protein-1 (MCP-1) were estimated. Predicitive performances of models including biomarkers were assessed with area under the receiver operating curves (AUC) and integrated discrimination improvement (IDI) statistics. Results: 82 subjects developed type 2 diabetes during follow-up. The risk of developing type 2 diabetes increased with increasing concentrations of leptin (2.04 (1.28;3.26)), sICAM-1 (1.39 (1.08;1.78)) and sVCAM-1 (1.29 (1.01;1.64)). Type 2 diabetes associations with leptin remained significant after adjusting for a combination of biomarkers. Models adjusted for novel biomarkers had improved performance compared to models adjusted for classical risk factors as assessed by IDI, but not by AUC. Conclusions: Adipokines, biomarkers of inflammation and endothelial function were significantly associated to onset of type 2 diabetes. However their inclusion in predictive scores is not supported by the present study.
All Science Journal Classification (ASJC) codes
- Internal Medicine
- Endocrinology, Diabetes and Metabolism