Dataset Information

Serum ZAG and Adiponectin Levels Were Closely Related to Obesity and the Metabolically Abnormal Phenotype in Chinese Population.

ABSTRACT: Introduction:To explore serum zinc-?2-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/m2) 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.

SUBMITTER: Liu M

PROVIDER: S-EPMC7457588 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Serum ZAG and Adiponectin Levels Were Closely Related to Obesity and the Metabolically Abnormal Phenotype in Chinese Population.

Liu Meijuan M Zhang Kun K Wang Linjie L Yang Hongbo H Yan Kemin K Pan Hui H Zhu Huijuan H Gong Fengying F

Diabetes, metabolic syndrome and obesity : targets and therapy 20200826

<h4>Introduction</h4>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.<h4>Methods</h4>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 we ...[more]

PMID: 32904655

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Project description:Introduction: Zinc-?2-glycoprotein (ZAG) is a novel adipokine, which is involved in metabolic syndrome (MetS). This study aimed to investigate the relationship between serum ZAG and MetS in Chinese adults, who diagnosed according to the 2005 International Diabetes Federation (IDF) criteria. Methods: A group of 151 MetS patients, 84 patients with central obesity and 70 healthy controls were enrolled. General clinical information, serum samples were obtained from all subjects and serum ZAG levels were determined via the commercial ELISA kits. Results: Serum ZAG levels were the highest in the control group, then gradually decreased with the severity of the metabolic abnormalities increased (8.78 ± 1.66 ?g/mL for control vs. 8.37 ± 1.52 ?g/mL for central obesity vs. 7.98 ± 0.94 ?g/mL for MetS, P < 0.05). It was also decreased progressively with an increasing number of the MetS components (P for trend = 0.002). Additionally, serum ZAG/fat mass ratio was calculated and the similar changes were observed in the three groups (0.85 ± 0.53 ?g/mL/kg for control vs. 0.39 ± 0.10 ?g/mL/kg for central obesity vs. 0.36 ± 0.08 ?g/mL/kg for MetS, P < 0.05). In the multiple regression analysis, group was a strong independent factor contributing to serum ZAG levels (P < 0.001). Furthermore, compared with subjects with the highest tertile of ZAG, subjects in the lowest tertile of ZAG had 1.946-fold higher risk of MetS (95% CI 1.419-6.117, P = 0.004). This phenomenon still existed after controlling for age, gender (Model 1), ALP, AST, Cr, UA, Urea based on Model 1 (Model 2), grip strength, smoking, drinking, birth place, current address, education level, manual labor, and exercise frequency based on Model 2 (Model 3). Receiver operation characteristic (ROC) curve analysis revealed that serum ZAG might serve as a candidate biomarker for MetS (sensitivity 57.6%, specificity 70.0% and area under the curve 0.655), and serum ZAG/fat mass ratio showed improved diagnosis value accuracy, with ROC curve area of 0.951 (95% CI, 0.920-0.983, P < 0.001), and 90.7% sensitivity and 88.6% specificity. Conclusions: Serum ZAG levels were lowered in patients with MetS and central obesity. The decreased serum ZAG levels were associated with the increased risks of MetS. Serum ZAG, especially serum ZAG/fat mass ratio might be the candidate diagnostic biomarkers for MetS.

Project description:Importance:Whether the metabolically healthy overweight (MHO) phenotype is resistant to metabolic abnormalities remains unknown. Objective:To evaluate the association of MHO with glucose level abnormalities and high blood pressure (BP) in Chinese adults. Design, Setting, and Participants:This prospective cohort study was conducted from January 1, 2013, to October 31, 2018, in the Health Management Center at Ren Ji Hospital, Shanghai, China, using data from 55 155 recruited Chinese adults. Body weight, fasting blood glucose (FBG) level, hemoglobin A1c (HbA1c) level, and BP were measured annually. Exposures:Metabolically healthy overweight was defined as a body mass index (calculated as weight in kilograms divided by height in meters squared) of 24.0 in 2013 (baseline) and 2014, no history of metabolic diseases, and normal FBG level, HbA1c level, BP, lipid profile, serum uric acid level, and liver ultrasonographic findings at baseline; the remaining participants were defined as being metabolically healthy normal. Main Outcomes and Measures:Glucose level abnormality was confirmed if the FBG level was 101 mg/dL or greater or the HbA1c level was 5.7%, and high BP was confirmed if the systolic BP was 130 mm Hg or higher or the diastolic BP was 80 mm Hg or higher at least twice during the subsequent 4 years of follow-up. Results:A total of 3204 metabolically healthy Chinese adults (mean [SD] age, 39.8 [10.9] years; 1940 women [60.5%]) were included in the study. The prevalence of MHO was 7.0%. A total of 146 incident cases of glucose level abnormality and 220 cases of high BP during 4 years of follow-up were identified. Compared with the metabolically healthy normal group, the MHO group had a higher risk of glucose level abnormality (adjusted hazard ratio, 2.36; 95% CI, 1.52-3.64) and high BP (adjusted hazard ratio, 1.73; 95% CI, 1.18-2.53) after adjusting for several potential confounders. Conclusions and Relevance:Metabolically healthy overweight may be associated with a high future risk of glucose abnormality and high BP in Chinese adults. If the individuals are confirmed with MHO, early interventions, including diet and exercise, should be recommended to decrease the risk of developing abnormalities of glucose and BP.

Project description:ObjectivesTo analyze sex differences in the prevalence of obesity phenotypes and their risk factors among children and adolescents aged 7-18 years in China.MethodsWe enrolled 15,114 children and adolescents aged 7-18 years into the final analysis. Obesity phenotypes were classified by body mass index (BMI) and metabolic status as metabolically healthy or unhealthy obesity. In addition, we collected four possible influencing factors on obesity phenotypes through questionnaires, including demographic, parental, early life, and lifestyle indicators. Multinomial logistic regression analysis in a generalized linear mixed model (GLMM) was selected to estimate the odds ratio (OR) and 95% confidence interval (95% CI) for identifying risk factors and control the cluster effects of schools. More importantly, the interaction terms of sex and each indicator were established to demonstrate the sex differences.ResultsThe prevalence of metabolically healthy obesity (MHO), metabolically unhealthy obesity (MUO), metabolically healthy overweight and obesity (MHOO), and metabolically unhealthy overweight and obesity (MUOO) were 3.5%, 5.6%, 11.1%, and 13.0% respectively, with higher prevalence in boys (5.3% vs. 1.6%, 7.9% vs. 3.1%, 14.3% vs. 7.7%, 15.6% vs. 10.1%). In addition, younger ages, single children, parental smoking, parental history of diseases (overweight, hypertension, diabetes), caesarean, premature, and delayed delivery time, high birth weight, insufficient sleep time, and excessive screen time were considered as important risk factors of MHO and MUO among children and adolescents (p < 0.05). More notably, boys were at higher risks of MUO when they were single children (boys: OR = 1.56, 95% CI: 1.24-1.96; girls: OR = 1.12, 95% CI: 0.82-1.54), while girls were more sensitive to MUO with parental smoking (girls: OR = 1.34, 95% CI: 1.02-1.76; boys: OR = 1.16, 95% CI: 0.97-1.39), premature delivery (girls: OR = 3.11, 95% CI: 1.59-6.07; boys: OR = 1.22, 95% CI: 0.67-2.22), high birth weight (girls: OR = 2.45, 95% CI: 1.63-3.69; boys: OR = 1.28, 95% CI: 0.96-1.70), and excessive screen time (girls: OR = 1.47, 95% CI: 1.06-2.04; boys: OR = 0.97, 95% CI: 0.79-1.20), with significant interaction term for sex difference (pinteraction < 0.05).ConclusionsMHO and MUO are becoming prevalent among Chinese children and adolescents. Significant sex differences in the prevalence of obesity phenotypes as well as their environmental and genetic risk factors suggest it might be necessary to manage obesity phenotypes problems from a sex perspective.

Dataset Information

Serum ZAG and Adiponectin Levels Were Closely Related to Obesity and the Metabolically Abnormal Phenotype in Chinese Population.

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Serum ZAG and Adiponectin Levels Were Closely Related to Obesity and the Metabolically Abnormal Phenotype in Chinese Population.

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