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Cited by 336Ovarian function and disordersMetabolism, Diabetes, and CancerDiabetes, Cardiovascular Risks, and Lipoproteins

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Cellular mechanisms of insulin resistance in polycystic ovarian syndrome

Ciaraldi, T. P.·1992·Journal of Clinical Endocrinology & Metabolism
DOI 10.1210/jc.75.2.577
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Abstract

Insulin resistance is a predominant feature in women with polycystic ovarian syndrome (PCO). The cellular mechanisms for this insulin resistance have not been defined. In this study, major steps in the insulin action cascade, receptor binding, kinase activity, and glucose transport activity were evaluated in isolated adipocytes prepared from PCO subjects (n = 8) without acanthosis nigricans and in a group of age and weight-matched controls [normal cycling (NC) n = 8]. The PCO group was hyperinsulinemic and displayed elevated insulin responses to an iv glucose load. The binding of 125I-insulin to adipocytes was similar in cells from PCO and NC subjects. In PCO, autophosphorylation of the insulin receptor-subunit in the absence of insulin was normal but a significant decrease (30% below control) in maximal insulin stimulated autophosphorylation was observed. However, receptor kinase activity measured against the exogenous substrate poly glu:tyr (4:1) was normal. Cells from PCO subjects transported glucose at the same rate, in both the absence and presence of a maximal insulin concentration, as those from NC subjects. Strikingly, there was a large rightward shift in the insulin dose-response curve for transport stimulation in PCO cells (EC50 = 87 +/- 14 pmol in NC vs. 757 +/- 138 in PCO, P less than 0.0005); 8-fold greater insulin concentrations were required to attain comparable glucose transport rates in cells from PCO against NC. In conclusion, our results suggest that insulin resistance in PCO, as assessed in the adipocyte, is accompanied by normal function of insulin receptors, but involves a novel postreceptor defect in the insulin signal transduction chain between the receptor kinase and glucose transport.

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Crossref · 10.1210/jc.75.2.577

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Metadata

Authors
Ciaraldi, T. P.
Affiliations
University of California System (US)
ORCID
Ciaraldi, T. P.
Venue
Journal of Clinical Endocrinology & Metabolism
Publisher
The Endocrine Society
Published
1992-08-01
Volume
75
Issue
2
Pages
577-583
ISSN
0021-972X (ISSN-L)
DOI
10.1210/jc.75.2.577
OpenAlex
W2028242557
Cited by
336
References
21
Citations by year
2026: 1 · 2025: 6 · 2024: 3 · 2023: 6 · 2022: 13 · 2021: 11 · 2020: 11 · 2019: 7 · 2018: 8 · 2017: 8 · 2016: 7 · 2015: 7 · 2014: 4 · 2013: 13 · 2012: 8
FWCI
6.58
Type
journal article
Language
en
Open access
closed
Locations
  • The Journal of Clinical Endocrinology & Metabolism (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institute of Diabetes and Digestive and Kidney Diseases (DK-33649, DK-33651)
  • NIH Clinical Center
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD-12303-14)
Topics
  • Health Sciences › Medicine › Reproductive Medicine › Ovarian function and disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolism, Diabetes, and Cancer
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Keywords
insulin resistance, polycystic ovary syndrome, adipocytes, insulin receptor autophosphorylation, glucose transport, insulin signaling, postreceptor defect, hyperinsulinemia, insulin dose-response
MeSH terms
Adipose Tissue, Adolescent, Adult, Female, Glucose Tolerance Test, Humans, Injections, Intravenous, Insulin, Insulin Resistance, Monosaccharide Transport Proteins, Polycystic Ovary Syndrome, Protein-Tyrosine Kinases, Receptor, Insulin, Reference Values

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.