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      Butyrate attenuated fat gain through gut microbiota modulation in db/db mice following dapagliflozin treatment

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          Abstract

          We investigated the effect of a combination treatment with dapagliflozin (Dapa), a sodium-glucose cotransporter-2 inhibitor and butyrate on weight change in db/db mice. Six-week-old male db/db mice were assigned to four groups: vehicle with normal chow diet (NCD), Dapa with NCD, vehicle with 5% sodium butyrate-supplemented NCD (NaB), or Dapa with 5% NaB. After six weeks of treatment, faecal microbiota composition was analysed by sequencing 16S ribosomal RNA genes. In the vehicle with NaB and Dapa + NaB groups, body weight increase was attenuated, and amount of food intake decreased compared with the vehicle with the NCD group. The Dapa + NaB group gained the least total and abdominal fat from baseline. Intestinal microbiota of this group was characterized by a decrease of the Firmicutes to Bacteroidetes ratio, a decrease of Adlercreutzia and Alistipes, as well as an increase of Streptococcus. In addition, the proportion of Adlercreutzia and Alistipes showed a positive correlation with total fat gain, whereas Streptococcus showed a negative correlation. Inferred metagenome function revealed that tryptophan metabolism was upregulated by NaB treatment. We demonstrated a synergistic effect of Dapa and NaB treatment on adiposity reduction, and this phenomenon might be related to intestinal microbiota alteration.

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          Most cited references19

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          Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

          In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013. We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Bill & Melinda Gates Foundation. Copyright © 2014 Elsevier Ltd. All rights reserved.
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            Meta-analyses of human gut microbes associated with obesity and IBD.

            Recent studies have linked human gut microbes to obesity and inflammatory bowel disease, but consistent signals have been difficult to identify. Here we test for indicator taxa and general features of the microbiota that are generally consistent across studies of obesity and of IBD, focusing on studies involving high-throughput sequencing of the 16S rRNA gene (which we could process using a common computational pipeline). We find that IBD has a consistent signature across studies and allows high classification accuracy of IBD from non-IBD subjects, but that although subjects can be classified as lean or obese within each individual study with statistically significant accuracy, consistent with the ability of the microbiota to experimentally transfer this phenotype, signatures of obesity are not consistent between studies even when the data are analyzed with consistent methods. The results suggest that correlations between microbes and clinical conditions with different effect sizes (e.g. the large effect size of IBD versus the small effect size of obesity) may require different cohort selection and analysis strategies.
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              How does multiple testing correction work?

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                Author and article information

                Contributors
                ohtjmd@gmail.com
                sulwj@cau.ac.kr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                30 December 2019
                30 December 2019
                2019
                : 9
                : 20300
                Affiliations
                [1 ]ISNI 0000 0004 0647 3378, GRID grid.412480.b, Department of Internal Medicine, , Seoul National University Bundang Hospital, ; Seongnam, Korea
                [2 ]ISNI 0000 0004 0470 5905, GRID grid.31501.36, Department of Internal Medicine, , Seoul National University College of Medicine, ; Seoul, Korea
                [3 ]ISNI 0000 0001 0789 9563, GRID grid.254224.7, Department of Systems Biotechnology, , Chung-Ang University, ; Anseong, Korea
                [4 ]ISNI 0000 0001 0302 820X, GRID grid.412484.f, Department of Internal Medicine, , Seoul National University Hospital, ; Seoul, Korea
                Article
                56684
                10.1038/s41598-019-56684-5
                6937275
                31889105
                8f64b00b-05e7-4ccc-bbc9-c9d65be16ee2
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 August 2019
                : 16 December 2019
                Funding
                Funded by: Korean Diabetes Association, South Korea
                Award ID: 2015F-5
                Award Recipient :
                Funded by: Seoul National University Bundang Hospital
                Award ID: 14-2017-011
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                endocrine system and metabolic diseases,microbiome
                Uncategorized
                endocrine system and metabolic diseases, microbiome

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