2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Bariatric surgery-induced weight loss and associated genome-wide DNA-methylation alterations in obese individuals

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Obesity is a multifactorial and chronic condition of growing universal concern. It has recently been reported that bariatric surgery is a more successful treatment for severe obesity than other noninvasive interventions, resulting in rapid significant weight loss and associated chronic disease remission. The identification of distinct epigenetic patterns in patients who are obese or have metabolic imbalances has suggested a potential role for epigenetic alterations in causal or mediating pathways in the development of obesity-related pathologies. Specific changes in the epigenome (DNA methylome), associated with metabolic disorders, can be detected in the blood. We investigated whether such epigenetic changes are reversible after weight loss using genome-wide DNA methylome analysis of blood samples from individuals with severe obesity (mean BMI ~ 45) undergoing bariatric surgery.

          Results

          Our analysis revealed 41 significant (Bonferroni p < 0.05) and 1169 (false discovery rate p < 0.05) suggestive differentially methylated positions (DMPs) associated with weight loss due to bariatric surgery. Among the 41 significant DMPs, 5 CpGs were replicated in an independent cohort of BMI-discordant monozygotic twins (the heavier twin underwent diet-induced weight loss). The effect sizes of these 5 CpGs were consistent across discovery and replication sets ( p < 0.05). We also identified 192 differentially methylated regions (DMRs) among which SMAD6 and PFKFB3 genes were the top hypermethylated and hypomethylated regions, respectively. Pathway enrichment analysis of the DMR-associated genes showed that functional pathways related to immune function and type 1 diabetes were significant. Weight loss due to bariatric surgery also significantly decelerated epigenetic age 12 months after the intervention (mean =  − 4.29; p = 0.02).

          Conclusions

          We identified weight loss-associated DNA-methylation alterations targeting immune and inflammatory gene pathways in blood samples from bariatric-surgery patients. The top hits were replicated in samples from an independent cohort of BMI-discordant monozygotic twins following a hypocaloric diet. Energy restriction and bariatric surgery thus share CpGs that may represent early indicators of response to the metabolic effects of weight loss. The analysis of bariatric surgery-associated DMRs suggests that epigenetic regulation of genes involved in endothelial and adipose tissue function is key in the pathophysiology of obesity.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13148-022-01401-9.

          Related collections

          Most cited references74

          • Record: found
          • Abstract: found
          • Article: not found

          Genome-wide methylation profiles reveal quantitative views of human aging rates.

          The ability to measure human aging from molecular profiles has practical implications in many fields, including disease prevention and treatment, forensics, and extension of life. Although chronological age has been linked to changes in DNA methylation, the methylome has not yet been used to measure and compare human aging rates. Here, we build a quantitative model of aging using measurements at more than 450,000 CpG markers from the whole blood of 656 human individuals, aged 19 to 101. This model measures the rate at which an individual's methylome ages, which we show is impacted by gender and genetic variants. We also show that differences in aging rates help explain epigenetic drift and are reflected in the transcriptome. Moreover, we show how our aging model is upheld in other human tissues and reveals an advanced aging rate in tumor tissue. Our model highlights specific components of the aging process and provides a quantitative readout for studying the role of methylation in age-related disease. Copyright © 2013 Elsevier Inc. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Gene Set Knowledge Discovery with Enrichr

            Profiling samples from patients, tissues, and cells with genomics, transcriptomics, epigenomics, proteomics, and metabolomics ultimately produces lists of genes and proteins that need to be further analyzed and integrated in the context of known biology. Enrichr (Chen et al., 2013; Kuleshov et al., 2016) is a gene set search engine that enables the querying of hundreds of thousands of annotated gene sets. Enrichr uniquely integrates knowledge from many high-profile projects to provide synthesized information about mammalian genes and gene sets. The platform provides various methods to compute gene set enrichment, and the results are visualized in several interactive ways. This protocol provides a summary of the key features of Enrichr, which include using Enrichr programmatically and embedding an Enrichr button on any website. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Analyzing lists of differentially expressed genes from transcriptomics, proteomics and phosphoproteomics, GWAS studies, or other experimental studies Basic Protocol 2: Searching Enrichr by a single gene or key search term Basic Protocol 3: Preparing raw or processed RNA-seq data through BioJupies in preparation for Enrichr analysis Basic Protocol 4: Analyzing gene sets for model organisms using modEnrichr Basic Protocol 5: Using Enrichr in Geneshot Basic Protocol 6: Using Enrichr in ARCHS4 Basic Protocol 7: Using the enrichment analysis visualization Appyter to visualize Enrichr results Basic Protocol 8: Using the Enrichr API Basic Protocol 9: Adding an Enrichr button to a website.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The epidemiology of obesity

              Obesity is a complex multifactorial disease. The worldwide prevalence of overweight and obesity has doubled since 1980 to an extent that nearly a third of the world's population is now classified as overweight or obese. Obesity rates have increased in all ages and both sexes irrespective of geographical locality, ethnicity or socioeconomic status, although the prevalence of obesity is generally greater in older persons and women. This trend was similar across regions and countries, although absolute prevalence rates of overweight and obesity varied widely. For some developed countries, the prevalence rates of obesity seem to have levelled off during the past few years. Body mass index (BMI) is typically used to define overweight and obesity in epidemiological studies. However, BMI has low sensitivity and there is a large inter-individual variability in the percent body fat for any given BMI value, partly attributed to age, sex, and ethnicity. For instance, Asians have greater percent body fat than Caucasians for the same BMI. Greater cardiometabolic risk has also been associated with the localization of excess fat in the visceral adipose tissue and ectopic depots (such as muscle and liver), as well as in cases of increased fat to lean mass ratio (e.g. metabolically-obese normal-weight). These data suggest that obesity may be far more common and requires more urgent attention than what large epidemiological studies suggest. Simply relying on BMI to assess its prevalence could hinder future interventions aimed at obesity prevention and control.
                Bookmark

                Author and article information

                Contributors
                fazlur08@gmail.com
                diemdaviek@hotmail.com
                laskarr@iarc.fr
                anovoloaca@yahoo.fr
                cueninc@iarc.fr
                sbraccia@med.uniroma2.it
                lorenza.nistico@iss.it
                gheitt@iarc.fr
                massimo.tommasino@hotmail.com
                eugenia.dogliotti@iss.it
                paola.fortini@iss.it
                herceg@iarc.fr , HercegZ@iarc.fr
                Journal
                Clin Epigenetics
                Clin Epigenetics
                Clinical Epigenetics
                BioMed Central (London )
                1868-7075
                1868-7083
                18 December 2022
                18 December 2022
                2022
                : 14
                : 176
                Affiliations
                [1 ]GRID grid.17703.32, ISNI 0000000405980095, Epigenomics and Mechanisms Branch, International Agency for Research On Cancer (IARC), ; 150 Cours Albert Thomas, Lyon, France
                [2 ]GRID grid.17703.32, ISNI 0000000405980095, Early Detection, Prevention, and Infections Branch, International Agency for Research On Cancer (IARC), ; 150 Cours Albert Thomas, Lyon, France
                [3 ]GRID grid.416651.1, ISNI 0000 0000 9120 6856, Section of Mechanisms, Biomarkers and Models, Dept Environment and Health, , Istituto Superiore Di Sanità, ; Viale Regina Elena, No. 299, 00161 Rome, Italy
                [4 ]GRID grid.17703.32, ISNI 0000000405980095, Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC), ; 150 Cours Albert Thomas, Lyon, France
                [5 ]GRID grid.6530.0, ISNI 0000 0001 2300 0941, Obesity Center-Internal Medicine Unit, Department of Systems Medicine, , University of Rome Tor Vergata, ; 00133 Rome, Italy
                [6 ]GRID grid.416651.1, ISNI 0000 0000 9120 6856, Centre for Behavioral Sciences and Mental Health, , Istituto Superiore Di Sanità, Viale Regina Elena, ; No. 299, 00161 Rome, Italy
                [7 ]IRCCS, Istituto Tumori Giovanni Paolo ll, Bari, Italy
                Article
                1401
                10.1186/s13148-022-01401-9
                9759858
                36528638
                83dabbe1-40ef-4ebb-a70e-1f33e3b70b9a
                © The Author(s) 2022

                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
                : 3 August 2022
                : 6 December 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Genetics
                obesity,bariatric surgery,epigenetics,dna methylation,weight loss,epigenetic clock
                Genetics
                obesity, bariatric surgery, epigenetics, dna methylation, weight loss, epigenetic clock

                Comments

                Comment on this article