Novel biomarkers of cardiometabolic risk are associated with plasma glucose within non-diabetic range. The Brazilian Longitudinal Study of Adult Health - ELSA-Brasil.

Abnormal glucose metabolism preceding overt diabetes is associated with increased cardiovascular risk. Whether novel biomarkers are useful to identify this condition is unclear. The objective was to investigate associations of biomarkers of atherogenesis with plasma glucose within non-diabetic range. 998 participants (35-54 years) of the Brazilian Longitudinal Study of Adult Health without diabetes or cardiovascular disease were classified as normal glucose tolerance (NGT), impaired fasting glycemia (IFG) and impaired glucose tolerance (IGT). Traditional risk factors and markers of atherogenesis were evaluated among groups and across plasma glucose concentrations. IFG and IGT had worse profile considering traditional cardiovascular risk factors than the NGT group, although these values were within the reference range. NGT, IFG and IGT groups differed (medians and interquartile intervals) regarding transforming growth factor-β1 [12.2 (6.4-22.3), 16.8 (8.4-26.5), and 15.5 (8.0-26.1)pg/mL, p<0.05], C-reactive protein [1.1 (0.6-2.9), 1.2 (0.6-2.7), and 1.4 (0.8-3.7)ng/mL, p<0.001] and monocyte chemoattractant protein-1 [35.9 (21.2-57.8), 32.2 (18.7-55.8), and 34.1 (18.6-52.4)pg/mL, p<0.05]. TGF-β1 and E-selectin concentrations increased while MCP-1 decreased across quartiles of fasting plasma glucose. C-reactive protein increased with increments in 2-h plasma glucose. In linear regression, TGF-β1 was independently associated with fasting plasma glucose, and C-reactive protein with 2-h plasma glucose after adjustments. In conclusion, association of TGF-β1, E-selectin, C-reactive protein and MCP-1 with slight elevations in glycemia may be anticipating alterations in traditional cardiovascular risk factors. Independent association of TGF-β1 with plasma glucose suggests that this may be useful to identifying atherogenic process, deserving further investigation on the prediction of cardiovascular outcomes.