| Literature DB >> 28250848 |
Priscila Sala1, Raquel Susana Matos de Miranda Torrinhas1, Danielle Cristina Fonseca1, Graziela Rosa Ravacci1, Dan Linetzky Waitzberg1, Daniel Giannella-Neto2.
Abstract
Eating habits, lifestyles, and exposure to specific environmental factors can greatly impact the risk of developing type 2 diabetes (T2D), influence the genome epigenetically, and affect the expression of genes, including genes related to glycemic control, at any stage of life. The epigenetic mechanism underlying obesity and T2D pathogenesis remains poorly understood. Conventional strategies for the treatment of obesity and its comorbidities often have poor long-term adherence, and pharmacological interventions are limited. Bariatric surgery is the most effective current option to treat severe obesity, and Roux-en-Y gastric bypass (RYGB) is the most applied technique worldwide. Epigenetic changes differ depending on the approach used to treat obesity and its associated comorbidities (clinical or surgical). Compared to primary clinical care, bariatric surgery leads to much greater loss of body weight and higher remission rates of T2D and metabolic syndrome, with methylation profiles in promoter regions of genes in obese individuals becoming similar to those of normal-weight individuals. Bariatric surgery can influence DNA methylation in parallel with changes in gene expression pattern. Changes in clinical biomarkers that reflect improvements in glucose and lipid metabolism after RYGB often occur before major weight loss and are coordinated by surgery-induced changes in intestinal hormones. Therefore, the intestine methylation profile would assist in understanding the mechanisms involved in improved glycemic control after bariatric surgery. The main objectives in this area for the future are to identify epigenetic marks that could be used as early indicators of metabolic risk, and to develop treatments able to delay or even reverse these epigenetic changes. Studies that provide the "human epigenetic profile" will be of considerable value to identify tissue-specific epigenetic signatures and their role in the development of chronic diseases. Further studies should apply methods based on global analysis of the genome to identify methylated sites associated with disease and epigenetic marks associated with the remodeling response to bariatric surgery. This review describes the main epigenetic alterations associated with obesity and T2D and the potential role of RYGB in remodeling these changes.Entities:
Keywords: Bariatric surgery; DNA methylation; Epigenetic; Obesity; Type 2 diabetes
Year: 2017 PMID: 28250848 PMCID: PMC5322591 DOI: 10.1186/s13098-017-0214-4
Source DB: PubMed Journal: Diabetol Metab Syndr ISSN: 1758-5996 Impact factor: 3.320
Fig. 1DNA methylation of mammalian genomes
Fig. 2Mammalian DNA demethylation process (modified from [19]). Cytosine may be methylated by DNMTs and affect gene transcription. In the process of demethylation, the methylated product 5mC can be actively reversed by TET proteins and TDG, thereby reverting to the cytosine form. Intermediate products include 5hmC, 5FC, and 5caC. Amount of 5hmC reflects DNA demethylation status
Fig. 3Proposed hypothesis of epigenetic mechanisms in liver contributing to IR in severe obesity, based on findings from Kirchner et al. [47]. Increased hepatic glycolysis and de novo lipogenesis are associated with DNA hypomethylation within ATF motifs of genes involved in glycolysis and IR. An excess of pyruvate from glycolysis is not used for ATP synthesis in the tricarboxylic acid (TCA) cycle and is converted to fatty free acids (FFA), which activate transcription of CƐ kinase that remains silenced by hypomethylation, increasing CE kinase (PRKCE) levels. The action and increased levels of PRKCE have been implicated in decreased insulin signaling. Therefore, the liver of severely obese patients is programmed to become insulin-resistant, possibly contributing to T2D and nonalcoholic fatty liver disease (NAFLD). Continuous arrows represent activation of studied glycolysis and lipogenesis pathways. Discontinuous arrows represent the proposed hypothesis
Summary of main studies of DNA methylation in obesity, T2D, and RYGB
| Study design | Sample | Methylation sites and methods | Main results |
|---|---|---|---|
| Gene methylation: obesity | |||
| Methylation of TNFα promoter in eutrophic women with decreased central adiposity ( | White blood cells | Methylation of 20 CpG regions of | Women with low central adiposity showed greater methylation in 2 CpG regions, associated with lower BMI and % of body fat |
| Association between methylation profile and BMI in very young children ( | Whole blood | Methylation of 10 CpG regions of | An 0.8% decrease in |
| Methylation status of 2 CpG regions of | Whole blood | Methylation in 2 CpG regions of | Lean adolescents had lower levels of |
| Epigenetic modifications in normal-weight ( | White blood cells | Methylation in CpG regions of | Lean women had lower levels of methylation in CpG regions at |
| Methylation profiles in obesity among monozygotic twins ( | White blood cells | Methylation of 20 CpG regions of | An increase in |
| Methylation pattern and BMI in elderly men ( | White blood cells | Methylation of 8 CpG regions of | Methylation of one region of CpG in the |
| Methylation profile and BMI in obese adults ( | White blood cells | Methylation of | Methylation in several CpG regions in |
| Methylation profiles of lean ( | White blood cells | Methylation of >450,000 CpG regions, assessed by Illumina Infinium Human Methylation 450 BeadChip | Differential methylation was observed in 23,305 CpG regions between lean and obese adolescents |
| Methylation profiles of lean ( | Whole blood | Methylation of >27,000 CpG regions, assessed by Illumina Infinium Human Methylation 27 BeadChip | There was a 15.5% difference in methylation of 20 CpG regions between the lean and obese groups |
| Genes methylation: T2D | |||
| Methylation profiles in pancreatic islets from T2D ( | Pancreatic islets | Gene methylation and expression in >450,000 CpG regions, assessed by Illumina Infinium Human Methylation 450 BeadChip and Affymetrix GeneChip Human Gene 1.0 ST array, respectively | In T2D islets, 853 genes (i.e., |
| Methylation profile in T2D ( | Whole blood | Global methylation, assessed by Affymetrix SNP6 microarray | CpG region of |
| Methylation profile in T2D ( | Skeletal muscle | Methylation and expression of |
|
| Epigenetic regulation of | Pancreatic islets | Methylation and expression of |
|
| Methylation profiles in pancreatic islets from T2D ( | Pancreatic islets | Methylation of 25 CpG regions of |
|
| | Pancreatic islets | Methylation of 29 CpG regions of | In T2D patient islets, 10 CpG regions of |
| | White blood cells | Methylation of |
|
| Genes methylation: RYGB | |||
| Obese T2D women with weight loss after RYGB ( | Skeletal muscle | Methylation of |
|
| Folate levels and epigenetic alterations in liver from subjects with T2D [ | Liver | Methylation and gene expression of >450,000 CpG regions, assessed by Illumina Infinium Human Methylation 450 BeadChip and RT-qPCR, respectively | In T2D patients, 251 CpG regions, including regions in |
| DNA methylation and hydroxymethylationin relation to energy-restricted diet ( | Whole blood | Methylation assessed by PCR | Baseline |
| Promoter methylation after RYGB and VLCD in obese patients ( | Whole blood | Methylation of promoter regions of | VLCD decreased methylation of |
| Methylation in obese patients ( | Whole blood | Methylation of >450,000 CpG regions, assessed by Illumina Infinium Human Methylation 450 BeadChip |
|
| Differential methylation in obesity and T2D genes in siblings born before ( | Whole blood | Methylation of >450,000 CpG regions, assessed by Illumina Infinium Human Methylation 450 BeadChip | Comparing siblings born before vs. after surgery, 3074 genes were differentially methylated, with an overrepresentation of genes involved in insulin receptor, T2D, and leptin signaling in obesity. |
| DNA methylation analysis in obese patients with NAFLD before ( | Liver | Methylation and gene expression of >450.,000 CpG regions, assessed by Illumina Infinium Human Methylation 450 BeadChip and Affymetrix Human Gene 1.1 ST, respectively | Gene ontology and transcription factor binding site analyses revealed distinct postsurgery and NAFLD-specific methylation signatures, with >400-fold enrichment of |
| DNA methylation in adipose tissue from obese women ( | Subcutaneous and omental adipose tissue | Gene methylation and expression assessed for >450,000 CpG regions, by the Illumina Infinium Human Methylation 450 BeadChip and RT-qPCR, respectively | Differential methylation was observed in omental and subcutaneous adipose tissue ( |
| Fat cell epigenetic signature in women 2 years after RYGB ( | Subcutaneous adipose tissue | Methylation of >450,000 CpG regions and gene expression, assessed by Illumina Infinium Human Methylation 450 BeadChip and Human Gene 1.1 ST, respectively | After RYGB, 8504 CpG regions showed methylation in adipose tissue. After RYGB, 3717 genes were overexpressed and associated with cell differentiation pathways. Among the adipogenesis-associated genes, 27% presented altered methylation in patients after RYGB compared to the control group |
| Longitudinal genome-wide methylation study in obese patients ( | Whole blood | Methylation of >450,000 CpG regions, assessed by Illumina Infinium Human Methylation 450 BeadChip | There were 24 promoters associated with CpG regions. Data were correlated with systolic blood pressure changes after RYGB. Two CpG loci (cg00875989, cg09134341) were hypomethylated and associated with hypertension |