Association between Proinflammatory Markers, Leukocyte-Endothelium Interactions, and Carotid Intima-Media Thickness in Type 2 Diabetes: Role of Glycemic Control

Abstract

Glycated hemoglobin monitorization could be a tool for maintaining type 2 diabetes (T2D) under control and delaying the appearance of cardiovascular events. This cross-sectional study was designed to assess the role of glycemic control in modulating early-stage markers of cardiovascular complications. One hundred and eight healthy controls and 161 type 2 diabetic patients were recruited and distributed according to their glycemic control, setting the threshold at 6.5% (good control). Biochemical and anthropometrical parameters were registered during the initial visit, and peripheral blood was extracted to obtain polymorphonuclear cells and analyze inflammatory markers, adhesion molecules, leukocyte-endothelium interactions, and carotid intima-media thickness. Correlations between these parameters were explored. We found that inflammatory markers and adhesion molecules were augmented in type 2 diabetic subjects with poor glycemic control. Polymorphonuclear leukocytes interacted more with the endothelium in the diabetic population, and even more significantly in the poorly controlled subjects. In parallel, carotid intima-media thickness was also increased in the diabetic population, and the difference was greater among poorly controlled subjects. Finally, correlation measurement revealed that carotid intima-media thickness was related to glycemic control and lipid metabolism in diabetic patients. Our results suggest that glycemic control delays the onset of cardiovascular comorbidities in diabetic subjects.

Keywords: carotid intima–media thickness; endothelial function; glycated hemoglobin; inflammation; type 2 diabetes.

Figure 1

TNFα, IL-6, and mtROS measurements. Serum levels of proinflammatory cytokines TNFα (A,B) and IL-6 (C,D), and fluorescence levels of mtROS (E,F). Differences between control and T2D groups (A,C,E) or between control, well-controlled (HbA_1c ≤ 6.5%) and poorly controlled diabetic groups (HbA_1c > 6.5%) (B,D,F) are shown. Statistical analysis was performed using a t-test to compare two groups, and using ANOVA with Bonferroni post-test for three groups. *p < 0.05 vs. control; # p < 0.05 vs. T2D HbA1c < 6.5%.

Figure 2

Serum levels of soluble adhesion molecules and measurement of PMN–endothelium interactions. Differences in adhesion molecules between control and T2D groups (A,C,E) or between control, well-controlled diabetics (HbA_1c ≤ 6.5%), and poorly controlled diabetics (HbA_1c > 6.5%) (B,D,F) are shown. The number of rolling cells (G,H), their velocity (I,J), and the adhesion of these cells to the endothelial monolayer (K,L) were analyzed. Differences between control and T2D groups (G,I,K) or between control, well-controlled diabetics (HbA_1c ≤ 6.5%), and poorly controlled diabetic groups (HbA_1c > 6.5%) (H,J,L) are shown. Statistical analysis was performed by means of a t-test to compare two groups, and using ANOVA with Bonferroni post-test for three groups. * p < 0.05; ** p < 0.01; *** p < 0.001 vs. control.

Figure 3

Measurement of carotid intima–media thickness (CIMT). Left carotid (A,B) and right carotid (C,D) were analyzed. Differences between control and T2D groups (A,C) or between control, well-controlled (HbA_1c ≤ 6.5%), and poorly controlled diabetic groups (HbA_1c > 6.5%) (B,D) are shown in the graphs. Statistical analysis was performed by means of a t-test to compare two groups, and using ANOVA with a Bonferroni post-test for three groups. ** p < 0.01; *** p < 0.001 vs. control group; # p < 0.05 vs HbA_1c ≤ 6.5% group.

Figure 4

Correlation graphs of adhesion assay vs. CIMT measures. Graphs show correlations between number of rolling PMN and left (A) and right CIMT (B); rolling velocity and left (C) and right CIMT (D); and cell adhesion and left (E) and right CIMT (F). Spearman correlation analysis was performed.

Figure 5

Correlation graphs of biochemical and anthropometrical parameters vs. CIMT measures. Graphs show correlation between glucose levels and left (A) and right CIMT (B); HOMA index and left (C) and right CIMT (D); BMI and left (E) and right CIMT (F); and HbA_1c and left (G) and right (H) CIMT. Spearman correlation analysis was performed.

Figure 6

Correlation graphs of lipid metabolism parameters vs. CIMT measurements. Graphs show a correlation of HDL-c with left (A) and right CIMT (B); of VLDL index with left (C) and right CIMT (D); of cholesterol/HDL-c index with left (E) and right CIMT (F); and of atherogenic index (AIP) with left (G) and right (H) CIMT. A Spearman correlation analysis was performed. r coefficient and statistical significance, if any existed, are shown in the graph.