Relationship between High-sensitivity C-reactive protein and components of metabolic syndrome

Abstract

Metabolic syndrome is defined by a constellation of interconnected physiological, biochemical, clinical, and metabolic factors that directly increases the risk of cardiovascular disease, type 2 diabetes mellitus, and all-cause mortality. Recently, studies demonstrated that elevated high-sensitivity C-reactive protein concentration has emerged as an independent predictor of cardiovascular disease. The aim of this study was evaluating of association between components of metabolic syndrome and high-sensitivity C-reactive protein in patients with metabolic syndrome compared with healthy persons. In a cross sectional case control study, 150 patients with metabolic syndrome compared with 150 healthy persons enrolled. Body mass index, waist circumference, fasting blood glucose, blood pressure, lipids, and high-sensitivity C-reactive protein were measured. Metabolic syndrome was defined by According to guidelines from the National Heart, Lung, and Blood Institute and the American Heart Association. In this study, mean +/- SD high-sensitivity C-reactive protein concentration in metabolic syndrome and in healthy persons were 2.44 +/- 0.16 mg/dl and 1.69 +/- 0.31mg/dl respectively so that there was significant difference between two groups (p=0.02). Sensitivity of high-sensitivity C-reactive protein in metabolic syndrome was 68% and other metabolic components were waist circumference 93%, blood pressure 98%, TG 81%, fasting blood glucose 98% and high density lipoprotein 21%. Sensitivity of high-sensitivity C-reactive protein in comparison with other components was significant. There was a significant close relationship between high-sensitivity C-reactive protein and metabolic syndrome components. This observation may in part account for the association of high-sensitivity C-reactive protein with markers of the metabolic syndrome. These data suggest that measurement of high-sensitivity C-reactive protein with other metabolic components have clinically important prognostic information and strong predictor of metabolic syndrome.