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      Circulating prolactin level is increased in metabolically healthy obesity

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          Abstract

          Objective

          Prolactin (PRL) has been demonstrated as a metabolic hormone to regulate energy metabolism recently. The present study aims to investigate the association between PRL and metabolic alterations in different obesity phenotypes.

          Methods

          A total of 451 drug-naive participants were recruited, comprising 351 obese patients and 100 age- and sex-matched healthy participants with normal weight. PRL, anthropometric, and clinical parameters were measured.

          Results

          In the obesity group, 15.1% (53/351) were categorized as 'metabolically healthy obesity (MHO)'. Besides favorable blood pressure, glucose, and lipids profiles, the MHO group exhibited increased PRL, and lower levels of high-sensitivity C-reactive protein (hsCRP), homeostasis model assessment of insulin resistance (HOMA-IR), and adipose tissue insulin resistance (adipo-IR) than the metabolically unhealthy obesity (MUHO) group (PRL, HOMA-IR, and adipo-IR: P < 0.01; hsCRP: P < 0.05). The severe MUHO group showed significantly decreased PRL levels than the mild MUHO group ( P < 0.05). Multivariate linear regression analysis indicated that fasting plasma glucose (FBG) and adipo-IR were significantly associated with PRL (FBG: β = −0.263, P < 0.05; adipo-IR: β = −0.464, P < 0.01). Multivariable logistic regression analysis showed that hsCRP (OR = 0.824) and PRL (OR = 1.211) were independent predictors of MHO (all P < 0.01).

          Conclusion

          The MHO group had significantly increased circulating PRL levels when compared with the control and MUHO groups, and multivariable logistic regression analysis showed that PRL was independent predictors of MHO. Our findings suggested that increased circulating PRL might be a compensatory response for favoring energy metabolism during obesity.

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          Most cited references34

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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.
            • Record: found
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            2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society.

              • Record: found
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              • Article: not found

              Obesity induces a phenotypic switch in adipose tissue macrophage polarization.

              Adipose tissue macrophages (ATMs) infiltrate adipose tissue during obesity and contribute to insulin resistance. We hypothesized that macrophages migrating to adipose tissue upon high-fat feeding may differ from those that reside there under normal diet conditions. To this end, we found a novel F4/80(+)CD11c(+) population of ATMs in adipose tissue of obese mice that was not seen in lean mice. ATMs from lean mice expressed many genes characteristic of M2 or "alternatively activated" macrophages, including Ym1, arginase 1, and Il10. Diet-induced obesity decreased expression of these genes in ATMs while increasing expression of genes such as those encoding TNF-alpha and iNOS that are characteristic of M1 or "classically activated" macrophages. Interestingly, ATMs from obese C-C motif chemokine receptor 2-KO (Ccr2-KO) mice express M2 markers at levels similar to those from lean mice. The antiinflammatory cytokine IL-10, which was overexpressed in ATMs from lean mice, protected adipocytes from TNF-alpha-induced insulin resistance. Thus, diet-induced obesity leads to a shift in the activation state of ATMs from an M2-polarized state in lean animals that may protect adipocytes from inflammation to an M1 proinflammatory state that contributes to insulin resistance.

                Author and article information

                Journal
                Endocr Connect
                Endocr Connect
                EC
                Endocrine Connections
                Bioscientifica Ltd (Bristol )
                2049-3614
                31 March 2021
                01 April 2021
                : 10
                : 4
                : 484-491
                Affiliations
                [1 ]Department of Endocrinology , Beijing Chao-yang Hospital, Capital Medical University, Chaoyang District, Beijing, China
                Author notes
                Correspondence should be addressed to G Wang: drwg6688@ 123456126.com
                Article
                EC-21-0040
                10.1530/EC-21-0040
                8111314
                33794504
                92fcd002-583f-474a-a41d-3d3a75597759
                © 2021 The authors

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

                History
                : 16 March 2021
                : 31 March 2021
                Categories
                Research

                prolactin,obesity,metabolically healthy obesity,insulin resistance

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