Relationships between adipokines, biomarkers of endothelial function and inflammation and risk of type 2 diabetes
Relationships between adipokines, biomarkers of endothelial function and inflammation and risk of type 2 diabetes
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DOI：
10.1016/j.diabres.2014.05.001
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发表时间：
2014-08-01
影响因子：
5.1
通讯作者：
Fezeu, L.
中科院分区：
文献类型：
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作者：
Julia, C.;Czernichow, S.;Fezeu, L.
目的：识别糖尿病风险的新型生物标志物有助于了解发病机制并改进风险预测。我们的目标是检查脂肪因子、炎症生物标志物和内皮功能与 2 型糖尿病发展之间的关系；并评估将这些生物标志物纳入 2 型糖尿病预测风险模型的相关性。方法：SU.VI.MAX 研究中的 1345 名受试者纳入本次分析，他们在基线时未患糖尿病，并完成了 13 年的随访。与脂联素、瘦素、C反应蛋白 (CRP)、可溶性细胞内粘附模块-1 (sICAM-1)、可溶性血管细胞粘附分子 1 (sVCAM-1)、E-选择素和单核细胞趋化蛋白-1 (MCP-1) 1-SD 增加相关的 2 型糖尿病事件的 95% 置信区间 (95% CI) 的比值比 (OR) 为估计。使用受试者工作曲线下面积 (AUC) 和综合辨别改善 (IDI) 统计数据评估模型（包括生物标志物）的预测性能。结果：82 名受试者在随访期间患上 2 型糖尿病。患 2 型糖尿病的风险随着瘦素 (2.04 (1.28; 3.26))、sICAM-1 (1.39 (1.08; 1.78)) 和 sVCAM-1 (1.29 (1.01; 1.64)) 浓度的增加而增加。在调整生物标志物组合后，2 型糖尿病与瘦素的关联仍然显着。与根据 IDI（而非 AUC）评估的经典危险因素调整的模型相比，根据新型生物标志物调整的模型具有改善的性能。结论：脂肪因子、炎症和内皮功能的生物标志物与 2 型糖尿病的发病显着相关。然而，本研究不支持将它们纳入预测分数。 (C) 2014 Elsevier Ireland Ltd. 保留所有权利。
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. (C) 2014 Elsevier Ireland Ltd. All rights reserved.