Dataset Information

Divergent effects of a combined hormonal oral contraceptive on insulin sensitivity in lean versus obese women.

ABSTRACT:

Objective

To evaluate the effects of a commonly used combined hormonal oral contraceptive (OC) on carbohydrate metabolism in obese as compared with lean women.

Design

6-month prospective study.

Setting

Clinical research center at an academic medical center.

Patient(s)

Premenopausal nondiabetic women with body mass index <25 kg/m(2) (n = 15) or >30 kg/m(2) (n = 14).

Intervention(s)

Ethinyl estradiol (35 ?g) and norgestimate (0.18/0.215/0.25 mg) for 6 cycles.

Main outcome measure(s)

Insulin sensitivity by frequent sampling intravenous glucose tolerance test; other indices of insulin sensitivity (homeostatic model assessment of insulin sensitivity index [ISI HOMA], the Matsuda index); fasting lipid panel.

Result(s)

Insulin sensitivity changed from 6.62 ± 3.69 min(-1)/mIU/L (baseline) to 8.23 ± 3.30 min(-1)/mIU/L (6 months) in lean women, and from 4.36 ± 2.32 to 3.82 ± 2.32 min(-1)/mIU/L in obese women. Divergent effects on insulin sensitivity were also observed with ISI HOMA and the Matsuda index. Low-density lipoprotein increased by approximately 20 mg/dL in both the lean and obese groups.

Conclusion(s)

Lean and obese women exhibit differential changes in insulin sensitivity when given 6 months of a commonly used oral contraceptive. The mechanisms of these differences and whether these divergent effects persist in the long term require further investigation.

SUBMITTER: Cheang KI

PROVIDER: S-EPMC3143285 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Divergent effects of a combined hormonal oral contraceptive on insulin sensitivity in lean versus obese women.

Cheang Kai I KI Essah Paulina A PA Sharma Susmeeta S Wickham Edmond P EP Nestler John E JE

Fertility and sterility 20110615 2

<h4>Objective</h4>To evaluate the effects of a commonly used combined hormonal oral contraceptive (OC) on carbohydrate metabolism in obese as compared with lean women.<h4>Design</h4>6-month prospective study.<h4>Setting</h4>Clinical research center at an academic medical center.<h4>Patient(s)</h4>Premenopausal nondiabetic women with body mass index <25 kg/m(2) (n = 15) or >30 kg/m(2) (n = 14).<h4>Intervention(s)</h4>Ethinyl estradiol (35 μg) and norgestimate (0.18/0.215/0.25 mg) for 6 cycles.<h4 ...[more]

PMID: 21676394

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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

Divergent effects of a combined hormonal oral contraceptive on insulin sensitivity in lean versus obese women.

Objective

Design

Setting

Patient(s)

Intervention(s)

Main outcome measure(s)

Result(s)

Conclusion(s)

Publications

Divergent effects of a combined hormonal oral contraceptive on insulin sensitivity in lean versus obese women.

Similar Datasets

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