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Amelioration of insulin resistance by rosiglitazone is associated with increased adipose cell size in obese type 2 diabetic patients.

ABSTRACT: Early studies reported that the size of adipose cells positively correlates with insulin resistance, but recent evidence suggests that the relationship between adipose cell size and insulin resistance is more complex. We previously reported that among BMI-matched moderately obese subjects who were either insulin sensitive or resistant insulin resistance correlated with the proportion of small adipose cells, rather than the size of the large adipose cells, whereas the size of large adipose cells was found to be a predictor of insulin resistance in the first-degree relatives of type 2 diabetic (T2D) patients. The relationship between adipose cellularity and insulin resistance thus appears to depend on the metabolic state of the individual. We did a longitudinal study with T2D patients treated with the insulin-sensitizer rosiglitazone to test the hypothesis that improved insulin sensitivity is associated with increased adipocyte size. Eleven T2D patients were recruited and treated with rosiglitazone for 90 days. Blood samples and needle biopsies of abdominal subcutaneous fat were taken at six time points and analyzed for cell size distributions. Rosiglitazone treatment ameliorated insulin resistance as evidenced by significantly decreased fasting plasma glucose and increased index of insulin sensitivity, QUICKI. In association with this, we found significantly increased size of the large adipose cells and, with a weaker effect, increased proportion of small adipose cells. We conclude rosiglitazone treatment both enlarges existing large adipose cells and recruits new small adipose cells in T2D patients, improving fat storage capacity in adipose tissue and thus systemic insulin sensitivity.

SUBMITTER: Eliasson B

PROVIDER: S-EPMC4550676 | biostudies-literature | 2014 Oct-Dec

REPOSITORIES: biostudies-literature

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Amelioration of insulin resistance by rosiglitazone is associated with increased adipose cell size in obese type 2 diabetic patients.

Eliasson Bjorn B Smith Ulf U Mullen Shawn S Cushman Samuel W SW Sherman Arthur S AS Yang Jian J

Adipocyte 20141001 4

Early studies reported that the size of adipose cells positively correlates with insulin resistance, but recent evidence suggests that the relationship between adipose cell size and insulin resistance is more complex. We previously reported that among BMI-matched moderately obese subjects who were either insulin sensitive or resistant insulin resistance correlated with the proportion of small adipose cells, rather than the size of the large adipose cells, whereas the size of large adipose cells ...[more]

PMID: 26317056

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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.

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 Î²-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 Î²-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)

Project description:The expression of adipogenic genes is decreased in obesity and diabetes mellitus Samuel T. Nadler*, Jonathan P. Stoehr*, Kathryn L. Schueler*, Gene Tanimoto, Brian S. Yandell, and Alan D. Attie*,§ Departments of * Biochemistry, and Statistics and Horticulture, University of Wisconsin, Madison, WI, 53706; and Affymetrix, Inc., Santa Clara, CA 95051 Communicated by Neal L. First, University of Wisconsin, Madison, WI, July 13, 2000 (received for review April 3, 2000) Obesity is strongly correlated with type 2 diabetes mellitus, a common disorder of glucose and lipid metabolism. Although adipocytes are critical in obesity, their role in diabetes has only recently been appreciated. We conducted studies by using DNA microarrays to identify differences in gene expression in adipose tissue from lean, obese, and obese-diabetic mice. The expression level of over 11,000 transcripts was analyzed, and 214 transcripts showed significant differences between lean and obese mice. Surprisingly, the expression of genes normally associated with adipocyte differentiation were down-regulated in obesity. Not all obese individuals will become diabetic; many remain normoglycemic despite profound obesity. Understanding the transition to obesity with concomitant diabetes will provide important clues to the pathogenesis of type 2 diabetes. Therefore, we examined the levels of gene expression in adipose tissue from five groups of obese mice with varying degrees of hyperglycemia, and we identified 88 genes whose expression strongly correlated with diabetes severity. This group included many genes that are known to be involved in signal transduction and energy metabolism as well as genes not previously examined in the context of diabetes. Our data show that a decrease in expression of genes normally involved in adipogenesis is associated with obesity, and we further identify genes important for subsequent development of type 2 diabetes mellitus. Keywords: Genetic modifications and strain difference

Dataset Information

Amelioration of insulin resistance by rosiglitazone is associated with increased adipose cell size in obese type 2 diabetic patients.

Publications

Amelioration of insulin resistance by rosiglitazone is associated with increased adipose cell size in obese type 2 diabetic patients.

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