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      Weight loss after Roux-En-Y gastric bypass surgery reveals skeletal muscle DNA methylation changes

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          Abstract

          Background

          The mechanisms of weight loss and metabolic improvements following bariatric surgery in skeletal muscle are not well known; however, epigenetic modifications are likely to contribute. The aim of our study was to investigate skeletal muscle DNA methylation after weight loss induced by Roux-en-Y gastric bypass (RYGB) surgery. Muscle biopsies were obtained basally from seven insulin-resistant obese (BMI > 40 kg/m 2) female subjects (45.1 ± 3.6 years) pre- and 3-month post-surgery with euglycemic hyperinsulinemic clamps to assess insulin sensitivity. Four lean (BMI < 25 kg/m 2) females (38.5 ± 5.8 years) served as controls. We performed reduced representation bisulfite sequencing next generation methylation on DNA isolated from the vastus lateralis muscle biopsies.

          Results

          Global methylation was significantly higher in the pre- (32.97 ± 0.02%) and post-surgery (33.31 ± 0.02%) compared to the lean (30.46 ± 0.02%), P < 0.05. MethylSig analysis identified 117 differentially methylated cytosines (DMCs) that were significantly altered in the post- versus pre-surgery (Benjamini–Hochberg q < 0.05). In addition, 2978 DMCs were significantly altered in the pre-surgery obese versus the lean controls (Benjamini–Hochberg q < 0.05). For the post-surgery obese versus the lean controls, 2885 DMCs were altered (Benjamini–Hochberg q < 0.05). Seven post-surgery obese DMCs were normalized to levels similar to those observed in lean controls. Of these, 5 were within intergenic regions (chr11.68,968,018, chr16.73,100,688, chr5.174,115,531, chr5.1,831,958 and chr9.98,547,011) and the remaining two DMCs chr17.45,330,989 and chr14.105,353,824 were within in the integrin beta 3 ( ITGB3) promoter and KIAA0284 exon, respectively. ITGB3 methylation was significantly decreased in the post-surgery (0.5 ± 0.5%) and lean controls (0 ± 0%) versus pre-surgery (13.6 ± 2.7%, P < 0.05). This decreased methylation post-surgery was associated with an increase in ITGB3 gene expression (fold change + 1.52, P = 0.0087). In addition, we showed that ITGB3 promoter methylation in vitro significantly suppressed transcriptional activity ( P < 0.05). Transcription factor binding analysis for ITGB3 chr17.45,330,989 identified three putative transcription factor binding motifs; PAX-5, p53 and AP-2alphaA.

          Conclusions

          These results demonstrate that weight loss after RYGB alters the epigenome through DNA methylation. In particular, this study highlights ITGB3 as a novel gene that may contribute to the metabolic improvements observed post-surgery. Future additional studies are warranted to address the exact mechanism of ITGB3 in skeletal muscle.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13148-021-01086-6.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Obesity: global epidemiology and pathogenesis

            The prevalence of obesity has increased worldwide in the past ~50 years, reaching pandemic levels. Obesity represents a major health challenge because it substantially increases the risk of diseases such as type 2 diabetes mellitus, fatty liver disease, hypertension, myocardial infarction, stroke, dementia, osteoarthritis, obstructive sleep apnoea and several cancers, thereby contributing to a decline in both quality of life and life expectancy. Obesity is also associated with unemployment, social disadvantages and reduced socio-economic productivity, thus increasingly creating an economic burden. Thus far, obesity prevention and treatment strategies - both at the individual and population level - have not been successful in the long term. Lifestyle and behavioural interventions aimed at reducing calorie intake and increasing energy expenditure have limited effectiveness because complex and persistent hormonal, metabolic and neurochemical adaptations defend against weight loss and promote weight regain. Reducing the obesity burden requires approaches that combine individual interventions with changes in the environment and society. Therefore, a better understanding of the remarkable regional differences in obesity prevalence and trends might help to identify societal causes of obesity and provide guidance on which are the most promising intervention strategies.
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              The Epidemiology of Obesity: A Big Picture.

              The epidemic of overweight and obesity presents a major challenge to chronic disease prevention and health across the life course around the world. Fueled by economic growth, industrialization, mechanized transport, urbanization, an increasingly sedentary lifestyle, and a nutritional transition to processed foods and high-calorie diets over the last 30 years, many countries have witnessed the prevalence of obesity in its citizens double and even quadruple. A rising prevalence of childhood obesity, in particular, forebodes a staggering burden of disease in individuals and healthcare systems in the decades to come. A complex, multifactorial disease, with genetic, behavioral, socioeconomic, and environmental origins, obesity raises the risk of debilitating morbidity and mortality. Relying primarily on epidemiologic evidence published within the last decade, this non-exhaustive review discusses the extent of the obesity epidemic, its risk factors-known and novel-, sequelae, and economic impact across the globe.
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                Author and article information

                Contributors
                dcoletta@email.arizona.edu
                Journal
                Clin Epigenetics
                Clin Epigenetics
                Clinical Epigenetics
                BioMed Central (London )
                1868-7075
                1868-7083
                1 May 2021
                1 May 2021
                2021
                : 13
                : 100
                Affiliations
                [1 ]Department of Medicine, Division of Endocrinology, The University of Arizona College of Medicine, 1501 N. Campbell Ave, PO Box 245035, Tucson, AZ 85724-5035 USA
                [2 ]Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ USA
                [3 ]Department of Endocrinology, Metabolism and Diabetes, Mayo Clinic Arizona, Scottsdale, AZ USA
                [4 ]Mayo Clinic Hospital, Phoenix, AZ USA
                [5 ]Department of Physiology, The University of Arizona College of Medicine, Tucson, AZ USA
                Author information
                http://orcid.org/0000-0001-5819-5152
                Article
                1086
                10.1186/s13148-021-01086-6
                8088644
                33933146
                932e3a9a-bacc-4b99-83c3-1a40f381375a
                © The Author(s) 2021

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 8 January 2021
                : 21 April 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: R01DK094013
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Genetics
                dna methylation,next generation sequencing,skeletal muscle,obesity,bariatric surgery
                Genetics
                dna methylation, next generation sequencing, skeletal muscle, obesity, bariatric surgery

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