Next Generation Sequencing Methylation Profiling in Skeletal Muscle from Lean and Obese Subjects
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE73304 | GEO | 2015/11/01
SECONDARY ACCESSION(S): PRJNA296560
REPOSITORIES: GEO
Similar Datasets
Project description:Obesity is a metabolic disease caused by environmental, genetic, and epigenetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to identify skeletal muscle DNA methylation patterns in obesity.
2015-11-01 | GSE73303 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-11-01 | E-GEOD-73304 | biostudies-arrayexpress
Project description:Obesity is a metabolic disease caused by environmental, genetic, and epigenetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to identify skeletal muscle DNA methylation patterns in combination with transcriptomic changes in obesity. Muscle biopsies were obtained basally from lean (n=10) and obese (n=10) participants in combination with euglycemic hyperinsulinemic clamps to assess insulin sensitivity. We performed microarray (SurePrint G3 Human Gene Expression 8x60K v2) analysis on RNA isolated from vastus lateralis muscle biopsies. This represents the expression profiling component only.
2015-11-01 | E-GEOD-73078 | biostudies-arrayexpress
Project description:Obesity is a metabolic disease caused by environmental, genetic, and epigenetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to identify skeletal muscle DNA methylation patterns in obesity. Muscle biopsies were obtained basally from lean (n=11) and obese (n=9) participants in combination with euglycemic hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing next generation methylation analysis on DNA isolated from vastus lateralis muscle biopsies.
2015-11-01 | E-GEOD-73303 | biostudies-arrayexpress
Project description:Obesity is a metabolic disease caused by environmental, genetic, and epigenetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to identify skeletal muscle DNA methylation patterns in combination with transcriptomic changes in obesity.
2015-11-01 | GSE73078 | GEO
Project description:Next Generation Sequencing Methylation Profiling in Skeletal Muscle from Lean and Obese Subjects
| PRJNA296560 | ENA
Project description:The obese people with abnormal BMI are predisposed to insulin resistance and diabetes. At the same time, human subjects with obesity and high BMI that are otherwise insulin sensitive are an interesting group to study the underlying gene expression patterns which provide them with such protective phenotype. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between β-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the β-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation.
2015-12-15 | GSE73034 | GEO
Project description:The obese people with abnormal BMI are predisposed to insulin resistance and diabetes. At the same time, human subjects with obesity and high BMI that are otherwise insulin sensitive are an interesting group to study the underlying gene expression patterns which provide them with such protective phenotype. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between β-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the β-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation. Gene expression from muscle biopsies of Lean, Obese insulin sensitive (OIS), Obese insulin resistant (OIR) and obese T2D patients (T2D) were compared for differential expression between the groups (n=7 in each group)
2015-12-15 | E-GEOD-73034 | biostudies-arrayexpress
Project description:Low environmental temperatures have a profound effect on biological processes in the body, including the immune system. Cold exposure coincides with hormonal changes, which may directly or indirectly alter the immune system, even in the skeletal muscle. The aim of the present study was to investigate the effect of cold acclimation on immune composition in skeletal muscle. Skeletal muscle biopsies were obtained from 17 healthy lean subjects before and after 10 days of mild cold exposure (15 °: C, 6 h/day). Nonshivering thermogenesis was calculated by indirect calorimetry. We found that cold acclimation increased nonshivering thermogenesis from 10.8 ± 7.5 before to 17.8 ± 11.1% after cold acclimation (P < 0.01), but did not affect plasma catecholamine nor cytokine levels. In contrast, cold acclimation affected mRNA expression of several immune cell markers in skeletal muscle. It downregulated expression of the Th17 markers RORC (-28%, P < 0.01) and NEDD4L (-15%, P < 0.05), as well as the regulatory T-cell marker FOXP3 (-13%, P < 0.05). Furthermore, cold acclimation downregulated expression of the M2 macrophage markers CCL22 (-50%, P < 0.05), CXCL13 (-17%, P < 0.05) and CD209 (-15%, P < 0.05), while the M1 macrophage marker IL12B was upregulated (+141%, P < 0.05). Cold acclimation also enhanced several markers related to interferon (IFN) signaling, including TAP1 (+12%, P < 0.01), IFITM1/3 (+11%, P < 0.05), CD274 (+36%, P < 0.05) and STAT 2 (+10%, P < 0.05). In conclusion, 10 days of intermittent cold exposure induces marked changes in the expression of immune cell markers in skeletal muscle of healthy lean subjects. The physiological consequences and therapeutic relevance of these changes remain to be determined.
| S-EPMC4552515 | biostudies-literature
Project description:Insulin resistance is a well-known physiological adaptation to prolonged fasting in healthy skeletal muscle. Obesity is associated with insulin resistance and metabolic inflexibility in skeletal muscle, and a pronounced increase in the risk of metabolic complications. Under the hypothesis that the metabolic traits of insulin resistance associated with prolonged fasting are different from insulin resistance associated with obesity, we examined nine obese and nine lean participants during 12 and 72h of fasting, respectively. Insulin resistance in obese participants was associated with impaired insulin signaling, and reduced levels of glucose-6-phosphate and TCA-cycle intermediates. 72h of fasting in lean participants reduced insulin-stimulated glucose uptake to levels similar to obese participants fasted for 12h. This was associated with increased lipid oxidation, but not accumulation of diacylglycerol or acylcarnitines and impairment of insulin signaling. Prolonged fasting was associated with pronounced increases in ?-hydroxybutyrate and ?- hydroxybutyrylcarnitine levels in skeletal muscle suggesting augmented ketone body metabolism. Fasting induced insulin resistance may be a consequence of substrate competition. The underlying mechanism behind insulin resistance in obesity is thus not comparable to the physiological adaptations in skeletal muscle induced by prolonged fasting in lean participants.
| S-EPMC6124727 | biostudies-literature