Dataset Information

Recombinant human leptin treatment does not improve insulin action in obese subjects with type 2 diabetes.

ABSTRACT:

Objective

Leptin therapy improves insulin sensitivity in people with leptin deficiency, but it is not known whether it improves insulin action in people who are not leptin deficient. The purpose of the current study was to determine whether leptin treatment has weight loss-independent effects on insulin action in obese subjects with type 2 diabetes.

Research design and methods

We conducted a randomized, placebo-controlled trial in obese subjects (BMI: 35.4 ± 0.6 kg/m(2); mean ± SE) with newly diagnosed type 2 diabetes. Subjects were randomized to treatment with placebo (saline), low-dose (30 mg/day), or high-dose (80 mg/day) recombinant methionyl human (r-Met hu) leptin for 14 days. Multiorgan insulin sensitivity before and after treatment was evaluated by using the hyperinsulinemic-euglycemic clamp procedure in conjunction with stable isotopically labeled tracer infusions to measure glucose, glycerol, and fatty acid kinetics.

Results

Low-dose and high-dose leptin treatment resulted in a threefold (P < 0.01) and 150-fold (P < 0.001) increase in basal plasma leptin concentrations, respectively. However, neither low-dose nor high-dose therapy had an effect on insulin-mediated suppression of glucose, glycerol, or palmitate rates of appearance into plasma compared with placebo. In addition, leptin treatment did not increase insulin-mediated stimulation of glucose disposal compared with placebo (14.3 ± 3.1, 18.4 ± 3.6, 16.7 ± 2.4 vs. 17.5 ± 2.5, 20.7 ± 3.0, 19.1 ± 3.3 μmol/kg body wt/min before vs. after treatment in the placebo, low-dose, and high-dose leptin groups, respectively).

Conclusions

r-Met hu leptin does not have weight loss-independent, clinically important effects on insulin sensitivity in obese people with type 2 diabetes.

SUBMITTER: Mittendorfer B

PROVIDER: S-EPMC3292320 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Publications

Recombinant human leptin treatment does not improve insulin action in obese subjects with type 2 diabetes.

Mittendorfer Bettina B Horowitz Jeffrey F JF DePaoli Alex M AM McCamish Mark A MA Patterson Bruce W BW Klein Samuel S

Diabetes 20110316 5

<h4>Objective</h4>Leptin therapy improves insulin sensitivity in people with leptin deficiency, but it is not known whether it improves insulin action in people who are not leptin deficient. The purpose of the current study was to determine whether leptin treatment has weight loss-independent effects on insulin action in obese subjects with type 2 diabetes.<h4>Research design and methods</h4>We conducted a randomized, placebo-controlled trial in obese subjects (BMI: 35.4 ± 0.6 kg/m(2); mean ± SE ...[more]

PMID: 21411512

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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)

Dataset Information

Recombinant human leptin treatment does not improve insulin action in obese subjects with type 2 diabetes.

Objective

Research design and methods

Results

Conclusions

Publications

Recombinant human leptin treatment does not improve insulin action in obese subjects with type 2 diabetes.

Similar Datasets

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