Insulin resistance in high fat diet mouse
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE73036 | GEO | 2015/12/07
SECONDARY ACCESSION(S): PRJNA296104
REPOSITORIES: GEO
Similar Datasets
Project description:Recent discovery reveals HFD insult can cause insulin resistance very rapidly, but the underlying mechanism is still not well understood. We performed a short term experiment in a Diet Induced Insulin resistance mouse model. 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. Comparison of gene expression in muscle tissue during High Fat Diet (HFD) time course (day 5 and day 42). Chow diet will serve as control for HFD. 4 samples per group serve as experimental replicates.
2015-12-07 | E-GEOD-73036 | biostudies-arrayexpress
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: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:Obesity and its accompanying metabolic complications have risen to epidemic proportions over the past 30 years. Together, these diseases are creating economic and social burdens that are expected to increase. Although multifactorial in their etiology and polygenic, the development of diseases such as metabolic syndrome in humans (obesity, fatty liver, insulin resistance [IR] and dyslipidemia) is facilitated by access to cheap, calorically dense foods. Many animal models, particularly laboratory rats and mice, have been developed to identify the underlying mechanisms involved in risk factors associated with metabolic diseases, especially Type II diabetes (T2D) and IR. Genetic models and dietary manipulations have aided our understanding of these disorders; however, it is important to recognize that examples of reversible obesity and IR occur in nature. Importantly, these conditions in animals are not associated with the negative consequences observed in humans. These observations together suggest that metabolic controls are sufficiently flexible to avoid the highly deleterious, maladapted process in humans and serve as a survival mechanism in some animals. An example of this is obesity of almost unlimited proportions (i.e., >50% body fat) and insulin resistance present in hibernating bears. Both phenotypes are reversible naturally. Our studies using cultured bear fat cells collected during hibernation recapitulate the natural insulin resistance observed in vivo. In addition, proteins or peptides found in active season serum can reverse this insulin resistance of cells from hibernating bears, indicating that circulating factors also play an important role in the seasonal modulation of insulin sensitivity. Experimentally, we can reverse the insulin resistance temporarily during hibernation by simply feeding glucose for a few weeks; thus, an important control can be added to minimize influences of body fat content, season, and diet composition. Bears therefore offer a unique model in which whole animal and cell culture systems can be used in highly standardized, easily manipulated, and controlled experiments to explore the underlying basis for reversible IR. By revealing the mechanisms involved in this reversible physiology we can gain a broader understanding of metabolic controls and the regulation of energy balance. The Washington State University (WSU) Bear Research, Education and Conservation Center is the only facility of its kind in the world dedicated to basic nutrition and physiological research using captive bears. Based on this rationale, the main objective of the proposed studies is to reveal the underlying molecular changes occurring in bears during different states of insulin sensitivity by identifying the serum proteins/peptides associated with hibernation by comparing serum from active season and hibernating bears, as well as bears that have restoring insulin sensitivity during hibernation.
2022-09-28 | PXD023555 | panorama
Project description:The aim of this study is to define the molecular alterations occurring in human adipose tissue leading to its dysfunction. While obesity (defined by BMI>30) is strongly associated with insulin resistance and metabolic disorders, some individuals with obesity remain insulin sensitive. Therefore, in this study, we have considered a control group (lean, insuln sensitive: BMI<25, HOMA-IR<2), a group with overweight/obesity but without insulin resistance (BMI>25, HOMA-IR<2) and a group with overweight and insulin resistance (BMI>25, HOMA-IR>3) to dissect the transcriptional changes in viscreal adipose tissue due to increased fat mass, and those associated with metabolic disorder.
2021-02-28 | GSE165932 | GEO
Project description:Insulin resistance is accompanied by chronic hyperinsulinemia and is associated with type 2 diabetes and other metabolic syndromes in a substantial portion of the population. The risk factors and features of insulin resistance have been thoroughly described but its mechanistic triggers are still under study. Here we consider a condensate model for insulin receptor (IR) function in normal conditions and when dysregulated in chronic hyperinsulinemia-induced insulin resistance. We find that IR is incorporated into liquid-like condensates at the plasma membrane, in the cytoplasm and in the nucleus of liver cells, and provide evidence for insulin-dependent IR function in condensates. Insulin stimulation promotes further incorporation of IR into these dynamic condensates in insulin sensitive cells, which form and dissolve on short, sub-minute time-scales. In contrast, insulin stimulation does not promote further incorporation of IR into condensates in insulin resistant cells, where IR molecules within condensates exhibit less dynamic behavior. Metformin treatment of insulin resistant cells rescues IR condensate dynamics and insulin responsiveness. Insulin resistant cells experience high levels of oxidative stress, which causes reduced condensate dynamics, and treatment of these cells with metformin reduces ROS levels and returns condensates to their normal dynamic behavior. The condensate model we propose can account for features of normal and dysregulated insulin response and has implications for improved therapeutic approaches to insulin resistance.
2023-07-28 | GSE181096 | GEO
Project description:We developed a novel network inference approach, Biologically Anchored Knowledge Expansion (BAKE), to analyze large volume gene expression data obtained from a mouse model of insulin resistance progression. Both genetic aspects and dietary factors, specifically high caloric high-fat high-sugar diets, contribute to the progression of insulin resistance. To mimic genetic predisposition, we used a mouse model with double heterozygous deletion of early insulin signaling pathway intermediates, insulin receptor (IR) and insulin receptor substrate 1 (IRS1) genes. These mice were fed with high-fat (Western) or low-fat (Chow) diet for 8 and 16 weeks starting at 8 weeks of age. Gene expression data was collected from adipocytes isolated from these mice. Applying BAKE analysis to the adipocyte gene expression data, we demonstrate that we can accurately discover a novel regulatory gene in the insulin signaling pathway. The mouse model of double heterozygous deletion of insulin receptor (IR) and insulin receptor substrate 1 (IRS1) was originally introduced as a polygenic model to study the development of type 2 diabetes. This mouse model, on an atherosclerosis-prone ApoE null background (IR+/- IRS1+/- ApoE-/-), also shows increased atherosclerotic lesions due to impaired insulin signaling. For our study we used female double heterozygous mice (IR+/- IRS1+/-, 'Dhet' mice or 'Dâ mice) on an ApoE null background (ApoE-/-, âEâ) fed with a Western (high-fat) diet for 8 (DW8, n=5) and 16 (DW16, n=9) weeks starting at 8 weeks of age or with a Chow (low-fat) diet (DC8, n=7; DC16, n=5). There were also ApoE null mice (ApoE-/-, 'Eâ) fed either Western diet for 8 (EW8, n=6) and 16 (EW16, n=8) weeks or Chow diet for 16 weeks (EC16, n=5) starting at 8 weeks of age.
2015-12-31 | E-GEOD-76428 | biostudies-arrayexpress
Project description:Development of insulin resistance is a key pathogenic component underlying metabolic syndrome and Type 2 diabetes (T2DM). Despite its importance, the molecular mechanisms underlying insulin resistance are poorly understood. Genome-wide association studies for T2DM and other metabolic traits have led to the identification of many candidate SNPs, but the majority of these SNPs are noncoding and determination of associated causal genes and/or specific tissue sites of action have been difficult. Adipocytes are critical regulators of mammalian metabolic homeostasis, with important effects on appetite, satiety, glucose and lipid homeostasis, energy expenditure, blood pressure, and immune function. Although insulin resistance (IR) in skeletal muscle, the major source of glucose disposal, is responsible for the bulk of the hyperglycemia observed in T2DM, muscle IR KO mice are generally healthy, IR also occurs in adipocytes, and inflammation within adipose tissue has been proposed as a primary mediator of IR, resulting in excess release of free fatty acids as well as alterations in adipokine release. Absence of adipose tissue, as observed in various lipodystrophies, or adipocyte-specific knockout of genes such as GLUT4 or insulin receptor, also alter systemic IR and T2DM risk. Transcriptional changes in adipocytes associated with metabolic disease. Despite the importance of adipocytes to metabolic disease, we have a poor understanding of how the adipocyte transcriptome changes in the disease state. Studies investigating transcriptional changes in whole adipose tissue have shown decreases in genes involved in adipogenesis, as well as alterations in inflammation, mitochondrial metabolism, lipid metabolism, detoxification, and insulin signaling. However, the vast majority of these studies use total adipose tissue samples, which does not allow for the exclusive evaluation of gene expression in mature adipocytes due to the substantial number of nonadipocyte cells (immune cells, fibroblasts, endothelial cells, pre-adipocytes, and mesenchymal cells) that also reside in adipose tissue. This is particularly relevant when studying metabolic disorders related to obesity-associated insulin resistance because these conditions are characterized by an increased influx of inflammatory cells into the adipose tissue.
2022-01-11 | GSE174475 | GEO
Project description:Impaired ability of insulin to stimulate cellular glucose uptake and regulate metabolism, that is insulin resistance (IR), links adiposity to metabolic disorders such as type 2 diabetes (T2D), dyslipidemia and cardiovascular disease (Langenberg, 2012). Both genetic and epigenetic factors are implicated in development of systemic IR (Vaag, 2001). IR is characterized by elevated levels of fasting insulin in the general circulation. The aim of this study is to explore whether white adipose tissue (WAT) epigenetic dysregulation is associated with systemic IR by global CpG methylation and gene expression profiling in subcutaneous and visceral adipose tissue. A secondary aim is to determine whether the DNA methylation signature in peripheral blood mononuclear cells reflect WAT methylation, and can be used as marker for systemic IR. DNA methylation was analyzed in DNA extracted from SAT (subcutaneous adipose tissue) and VAT (visceral adipose tissue) pieces, as well as PBMCs (peripheral blood mononuclear cells), using the Infinium Human Methylation 450 BeadChip assay. This data is from PBMCs.
2016-08-01 | E-GEOD-76285 | biostudies-arrayexpress
Project description:Impaired ability of insulin to stimulate cellular glucose uptake and regulate metabolism, that is insulin resistance (IR), links adiposity to metabolic disorders such as type 2 diabetes (T2D), dyslipidemia and cardiovascular disease (Langenberg, 2012). Both genetic and epigenetic factors are implicated in development of systemic IR (Vaag, 2001). IR is characterized by elevated levels of fasting insulin in the general circulation. The aim of this study is to explore whether white adipose tissue (WAT) epigenetic dysregulation is associated with systemic IR by global CpG methylation and gene expression profiling in subcutaneous and visceral adipose tissue. A secondary aim is to determine whether the DNA methylation signature in peripheral blood mononuclear cells reflect WAT methylation, and can be used as marker for systemic IR. DNA methylation was analyzed in DNA extracted from SAT (subcutaneous adipose tissue) and VAT (visceral adipose tissue) pieces, as well as PBMCs (peripheral blood mononuclear cells), using the Infinium Human Methylation 450 BeadChip assay. This data is from SAT.
2016-08-01 | E-GEOD-76398 | biostudies-arrayexpress