Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Oct;44(10):2123-2130.
doi: 10.1007/s40618-020-01430-2. Epub 2021 Mar 9.

Using metabolic markers to identify insulin resistance in premenopausal women with and without polycystic ovary syndrome

M R Blum  1   2 , R A Popat  1 , A Nagy  3 , N A Cataldo  4 , T L McLaughlin  5
Affiliations

Using metabolic markers to identify insulin resistance in premenopausal women with and without polycystic ovary syndrome

M R Blum et al. J Endocrinol Invest. 2021 Oct.

Abstract

Background: Insulin resistance (IR) is associated with increased risk for type 2 diabetes mellitus and cardiovascular disease. Quantifying IR is invasive and time-consuming, and thus not routinely used in clinical practice. Simple metabolic markers to predict IR exist, but have not been validated in premenopausal women or women with polycystic ovary syndrome (PCOS).

Objective: To evaluate the ability of metabolic markers to identify premenopausal women with/without PCOS who are insulin resistant.

Design/setting: Cross-sectional analysis.

Participants: One hundred and seventy-one non-diabetic premenopausal overweight/obese women without PCOS and 71 women with PCOS.

Methods: IR was quantified by the steady-state plasma glucose during the modified insulin-suppression test. Metabolic markers (BMI, lipid/lipoprotein concentrations, and fasting glucose) were evaluated for their discriminative ability to identify IR, using area under the receiver-operating-characteristic curve (AUROC) analysis. Optimal cut-points were evaluated for predictive power.

Results: In the non-PCOS group, the triglyceride/HDL cholesterol ratio (TG/HDL-C) was the best marker (AUROC 0.73). Optimal diagnostic cut-point was 1.9. In the PCOS group, the TG/HDL-C ratio, cholesterol/HDL-C ratio (TC/HDL-C), and HDL-C performed well (AUROC > 0.80), with optimal cut-points for TG/HDL-C 1.3, TC/HDL-C 3.4, and HDL-C 52 mg/dL: TG/HDL-C was more sensitive, but HDL-C had a higher PPV for IR.

Conclusion: TG/HDL-C can identify IR in premenopausal women with and/without PCOS; diagnostic cut-points differ from those of men and postmenopausal women. HDL-C is an alternative predictor in women with PCOS. These simple metabolic markers, which are standardized between labs, inexpensive, and routinely measured, can be used to tailor lifestyle and medical interventions to improve health outcomes in insulin-resistant premenopausal women.

Keywords: Insulin resistance; Metabolic marker; Polycystic ovary syndrome; Premenopausal.

PubMed Disclaimer

References

    1. Lillioja S, Mott DM, Spraul M, Ferraro R, Foley JE, Ravussin E et al (1993) Insulin resistance and insulin secretory dysfunction as precursors of non-insulin-dependent diabetes mellitus. Prospective studies of Pima Indians. N Engl J Med 329(27):1988–1992 - DOI
    1. Després J-P, Lamarche B, Mauriège P, Cantin B, Dagenais GR, Moorjani S et al (1996) Hyperinsulinemia as an independent risk factor for ischemic heart disease. N Engl J Med 334(15):952–958. https://doi.org/10.1056/nejm199604113341504 - DOI - PubMed
    1. Zavaroni I, Bonini L, Gasparini P, Barilli AL, Zuccarelli A, Dall’Aglio E et al (1999) Hyperinsulinemia in a normal population as a predictor of non-insulin-dependent diabetes mellitus, hypertension, and coronary heart disease: the Barilla factory revisited. Metabolism 48(8):989–994. https://doi.org/10.1016/s0026-0495(99)90195-6 - DOI - PubMed
    1. Yip J, Facchini FS, Reaven GM (1998) Resistance to insulin-mediated glucose disposal as a predictor of cardiovascular disease. J Clin Endocrinol Metab 83(8):2773–2776 - DOI
    1. Facchini FS, Hua N, Abbasi F, Reaven GM (2001) Insulin resistance as a predictor of age-related diseases. J Clin Endocrinol Metab 86(8):3574–3578 - DOI

MeSH terms

LinkOut - more resources