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      Association of metabolic syndrome components with circulating levels of cytokine clusters in young women

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          Abstract

          Background

          The purpose of this study was to investigate the relationship between circulating zinc α 2-glycoprotein (ZAG), irisin, betatrophin and adiponectin concentrations and metabolic syndrome (MetS) components and to analyze the effects of blood glucose and insulin on these cytokine concentrations in vivo.

          Methods

          A total of 196 young women, including 78 healthy women and 118 women with MetS components, were recruited for this cross-sectional study. An oral glucose tolerance test and euglycemic-hyperinsulinemic clamp (EHC) were performed in healthy subjects and women with MetS components. An ELISA kit was used to measure serum ZAG, irisin, betatrophin, and adiponectin levels, and their relationship with the MetS components was analyzed.

          Results

          In women with MetS components, circulating irisin and betatrophin levels were significantly higher than those in the healthy women ((207 (150–248) vs 178 (147–228); P < 0.05) for irisin; (0.51 (0.38–0.63) vs 0.38 (0.23–0.52); P < 0.001) for betatrophin), but circulating ZAG and adiponectin levels were significantly lower (39.8 (26.4–50.4) vs (46.7 (40.6–63.0); P < 0.001) for ZAG; (36.5 (22.0–47.6) vs 41.2 (35.7–54.7); P < 0.01) for adiponectin). FBG, WC, and triglyceride were significantly correlated with the circulating levels of these four cytokines ( P < 0.001 or <0.05). All four cytokines were associated with MetS and its components. In response to increasing insulin levels, circulating ZAG concentrations were markedly increased in both healthy subjects and women with MetS components during the EHC. However, serum irisin, betatrophin, and adiponectin levels in both healthy subjects and women with MetS components were significantly reduced compared with baseline.

          Conclusion

          Serum ZAG, irisin, betatrophin and adiponectin were associated with MetS and might be biomarkers for screening MetS components.

          Related collections

          Most cited references39

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          Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

          The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
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            A better index of body adiposity.

            Obesity is a growing problem in the United States and throughout the world. It is a risk factor for many chronic diseases. The BMI has been used to assess body fat for almost 200 years. BMI is known to be of limited accuracy, and is different for males and females with similar %body adiposity. Here, we define an alternative parameter, the body adiposity index (BAI = ((hip circumference)/((height)(1.5))-18)). The BAI can be used to reflect %body fat for adult men and women of differing ethnicities without numerical correction. We used a population study, the "BetaGene" study, to develop the new index of body adiposity. %Body fat, as measured by the dual-energy X-ray absorptiometry (DXA), was used as a "gold standard" for validation. Hip circumference (R = 0.602) and height (R = -0.524) are strongly correlated with %body fat and therefore chosen as principal anthropometric measures on which we base BAI. The BAI measure was validated in the "Triglyceride and Cardiovascular Risk in African-Americans (TARA)" study of African Americans. Correlation between DXA-derived %adiposity and the BAI was R = 0.85 for TARA with a concordance of C_b = 0.95. BAI can be measured without weighing, which may render it useful in settings where measuring accurate body weight is problematic. In summary, we have defined a new parameter, the BAI, which can be calculated from hip circumference and height only. It can be used in the clinical setting even in remote locations with very limited access to reliable scales. The BAI estimates %adiposity directly.
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              Impaired insulin action in puberty. A contributing factor to poor glycemic control in adolescents with diabetes.

              Patients with insulin-dependent diabetes mellitus often have poor metabolic control during puberty. To determine whether puberty is associated with decreased insulin-stimulated glucose metabolism, we compared the results of euglycemic insulin-clamp studies in adults and prepubertal and pubertal children with and without insulin-dependent diabetes. In nondiabetic pubertal children, insulin-stimulated glucose metabolism (201 +/- 12 mg per square meter of body surface area per minute) was sharply reduced, as compared with that of prepubertal children and adults (316 +/- 34 and 290 +/- 21 mg per square meter, respectively; P less than 0.01), despite comparable hyperinsulinemia (insulin levels of 80 to 90 microU per milliliter). Similarly, the response to insulin was 25 to 30 percent lower in the diabetic pubertal children than in the diabetic prepubertal children (P less than 0.05) and adults (P = 0.07). At each stage of development, the stimulating effect of insulin on glucose metabolism was decreased by 33 to 42 percent in the children with diabetes (P less than 0.01). In all the groups of children studied, the response to insulin was inversely correlated with mean 24-hour levels of growth hormone (r = -0.52, P = 0.01). Among the diabetic children, the glycosylated hemoglobin levels were substantially higher in the pubertal children than in the prepubertal children (P less than 0.02), although the daily insulin doses tended to be higher. These data suggest that insulin resistance occurs during puberty in both normal children and children with diabetes. The combined adverse effects of puberty and diabetes on insulin action may help explain why control of glycemia is so difficult to achieve in adolescent patients.

                Author and article information

                Journal
                Endocr Connect
                Endocr Connect
                EC
                Endocrine Connections
                Bioscientifica Ltd (Bristol )
                2049-3614
                January 2021
                03 December 2020
                : 10
                : 1
                : 66-75
                Affiliations
                [1 ]Department of Endocrinology , 9th People’s Hospital of Chongqing, Beibei City, Chongqong, China
                [2 ]Chongqing Prevention and Treatment Hospital for Occupational Diseases , Chongqing, China
                [3 ]Department of Endocrinology , The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
                Author notes
                Correspondence should be addressed to Y Wang: wangyi-med@ 123456sohu.com

                *(X Tan and W Hu contributed equally to this work)

                Author information
                http://orcid.org/0000-0003-1905-7528
                Article
                EC-20-0569
                10.1530/EC-20-0569
                7923046
                33289689
                f3ed027f-3eaf-42e9-a2e9-03fd44654e57
                © 2021 The authors

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 20 November 2020
                : 03 December 2020
                Categories
                Research

                cytokine,insulin resistance,metabolic syndrome,women
                cytokine, insulin resistance, metabolic syndrome, women

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