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      Magnesium in Obesity, Metabolic Syndrome, and Type 2 Diabetes

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          Abstract

          Magnesium (Mg 2+) deficiency is probably the most underestimated electrolyte imbalance in Western countries. It is frequent in obese patients, subjects with type-2 diabetes and metabolic syndrome, both in adulthood and in childhood. This narrative review aims to offer insights into the pathophysiological mechanisms linking Mg 2+ deficiency with obesity and the risk of developing metabolic syndrome and type 2 diabetes. Literature highlights critical issues about the treatment of Mg 2+ deficiency, such as the lack of a clear definition of Mg 2+ nutritional status, the use of different Mg 2+ salts and dosage and the different duration of the Mg 2+ supplementation. Despite the lack of agreement, an appropriate dietary pattern, including the right intake of Mg 2+, improves metabolic syndrome by reducing blood pressure, hyperglycemia, and hypertriglyceridemia. This occurs through the modulation of gene expression and proteomic profile as well as through a positive influence on the composition of the intestinal microbiota and the metabolism of vitamins B1 and D.

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          Most cited references 136

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          Richness of human gut microbiome correlates with metabolic markers.

          We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previously unknown bacterial species at different proportions; individuals with a low bacterial richness (23% of the population) are characterized by more marked overall adiposity, insulin resistance and dyslipidaemia and a more pronounced inflammatory phenotype when compared with high bacterial richness individuals. The obese individuals among the lower bacterial richness group also gain more weight over time. Only a few bacterial species are sufficient to distinguish between individuals with high and low bacterial richness, and even between lean and obese participants. Our classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.
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            Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies.

            Association between obesity and depression has repeatedly been established. For treatment and prevention purposes, it is important to acquire more insight into their longitudinal interaction. To conduct a systematic review and meta-analysis on the longitudinal relationship between depression, overweight, and obesity and to identify possible influencing factors. Studies were found using PubMed, PsycINFO, and EMBASE databases and selected on several criteria. Studies examining the longitudinal bidirectional relation between depression and overweight (body mass index 25-29.99) or obesity (body mass index > or =30) were selected. Unadjusted and adjusted odds ratios (ORs) were extracted or provided by the authors. Overall, unadjusted ORs were calculated and subgroup analyses were performed for the 15 included studies (N = 58 745) to estimate the effect of possible moderators (sex, age, depression severity). Obesity at baseline increased the risk of onset of depression at follow-up (unadjusted OR, 1.55; 95% confidence interval [CI], 1.22-1.98; P or =60 years) but not among younger persons (aged <20 years). Baseline depression (symptoms and disorder) was not predictive of overweight over time. However, depression increased the odds for developing obesity (OR, 1.58; 95% CI, 1.33-1.87; P < .001). Subgroup analyses did not reveal specific moderators of the association. This meta-analysis confirms a reciprocal link between depression and obesity. Obesity was found to increase the risk of depression, most pronounced among Americans and for clinically diagnosed depression. In addition, depression was found to be predictive of developing obesity.
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              Inflammatory mechanisms linking obesity and metabolic disease.

               Alan Saltiel (corresponding) ,  Jerrold Olefsky (2017)
              There are currently over 1.9 billion people who are obese or overweight, leading to a rise in related health complications, including insulin resistance, type 2 diabetes, cardiovascular disease, liver disease, cancer, and neurodegeneration. The finding that obesity and metabolic disorder are accompanied by chronic low-grade inflammation has fundamentally changed our view of the underlying causes and progression of obesity and metabolic syndrome. We now know that an inflammatory program is activated early in adipose expansion and during chronic obesity, permanently skewing the immune system to a proinflammatory phenotype, and we are beginning to delineate the reciprocal influence of obesity and inflammation. Reviews in this series examine the activation of the innate and adaptive immune system in obesity; inflammation within diabetic islets, brain, liver, gut, and muscle; the role of inflammation in fibrosis and angiogenesis; the factors that contribute to the initiation of inflammation; and therapeutic approaches to modulate inflammation in the context of obesity and metabolic syndrome.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                22 January 2021
                February 2021
                : 13
                : 2
                Affiliations
                [1 ]Department of Biomedical and Clinical Sciences “L. Sacco”, Università di Milano, 20157 Milan, Italy; gabriele.piuri@ 123456unimi.it (G.P.); monica.zocchi@ 123456unimi.it (M.Z.); matteo.dellaporta@ 123456unimi.it (M.D.P.); valentina.ficara@ 123456unimi.t (V.F.); gianvincenzo.zuccotti@ 123456unimi.it (G.V.Z.); jeanette.maier@ 123456unimi.it (J.A.M.)
                [2 ]Department of Health, Animal Science and Food Safety, Università di Milano, 20133 Milan, Italy; michele.manoni@ 123456unimi.it (M.M.); luciano.pinotti@ 123456unimi.it (L.P.)
                [3 ]Department of Pediatrics, Ospedale dei Bambini, 2154 Milan, Italy
                Author notes
                [†]

                These authors contributed equally to this work.

                Article
                nutrients-13-00320
                10.3390/nu13020320
                7912442
                33499378
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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