Abstract
INTRODUCTION: To explore serum zinc-α2-glycoprotein (ZAG) and adiponectin in metabolically healthy non-obese (MHNO), metabolically healthy obesity (MHO), metabolically abnormal obesity (MAO) and metabolically abnormal diabetic obese (MADO) subjects and the relationship with metabolically phenotypes of obesity. METHODS: Two hundred twenty-five subjects including 32 with MHNO, 40 with MHO, 104 with MAO and 49 with MADO were enrolled. Baseline clinical data and biochemical variables were collected. Serum ZAG and adiponectin levels were measured by enzyme-linked immunosorbent assay (ELISA) kits. Metabolically healthy (<3 metabolic abnormalities) or abnormal (≥3 metabolic abnormalities) subjects were classified based on the National Cholesterol Education Program-Adult Treatment Panel III (NCEP/ATP III) criteria. Obesity (body mass index ≥28 kg/m(2)) was recommended by China Obesity Task Force. RESULTS: Serum ZAG levels were higher in the MHO group, but were progressively lower in MAO and MADO groups (P all<0.05). In all subjects, total cholesterol, 2-hour postprandial blood glucose and homeostasis model assessment of adiponectin were independent variables to serum ZAG levels. Compared with subjects in the highest tertile of ZAG, the odds ratio (OR) of metabolically abnormal risks of subjects in the lowest and median tertiles of ZAG were higher both in a univariate and three adjustment models (P all<0.05). Serum ZAG could discriminate the metabolically abnormal phenotype with receiver operating characteristic (ROC) curve area of 0.622 (95% CI, 0.539-0.706, P<0.05). Combination of ZAG and adiponectin had improved diagnosis value accuracy, with ROC curve area of 0.703 (95% CI, 0.629-0.776, P<0.05), and 62.7% sensitivity and 73.6% specificity. CONCLUSION: Serum ZAG levels were higher in MHO subjects, but lower in MAO and MADO subjects. The decreased serum ZAG levels were closely related to the metabolically abnormal phenotype of obese patients. Serum ZAG, especially the combination with adiponectin might be the potential diagnostic biomarkers for metabolically abnormal obese patients.