Menstrual dysfunction in polycystic ovary syndrome: association with dynamic state insulin resistance rather than hyperandrogenism

Abstract

Objective: To examine the relation of menstrual cyclicity abnormalities to hyperandrogenism (HA) and dynamic state insulin resistance (IR) in oligo-ovulatory women with polycystic ovary syndrome (PCOS).

Design: Prospective cross-sectional study.

Setting: Tertiary-care academic center.

Patient(s): Fifty-seven women with PCOS (1990 National Institutes of Health criteria) and 57 healthy control women matched by body mass index (BMI).

Intervention(s): Short insulin tolerance test (ITT).

Main outcome measure(s): Menstrual cyclicity, sex hormone-binding globulin (SHBG), measures of HA (i.e., modified Ferriman-Gallwey score, total and free testosterone, dehydroepiandrosterone sulfate), and the rate constant for plasma glucose disappearance (kITT) derived from the short ITT.

Result(s): Adjusting for age, BMI, and ethnicity, the mean androgen measures were higher and SHBG trended lower, kITT was lower, and the prevalence of IR was higher in PCOS than in controls, independent of menstrual cyclicity. The optimal cutoff point for IR was set at kITT value of 3.57%/minute or lower. Overall, 79% of the women with PCOS had IR. To control further for the effect of ethnicity, a subgroup of 46 non-Hispanic white PCOS participants were studied; those who exhibited amenorrhea (n = 15) or oligomenorrhea (n = 19) had or tended toward having a lower kITT and a higher prevalence of IR than the women with PCOS and oligo-ovulatory eumenorrhea (n = 12). The kITT trended lower and the prevalence of IR trended higher in women with PCOS and amenorrhea than those with oligomenorrhea. The measures of SHBG and HA were similar across the three menstrual groups.

Conclusion(s): Oligo-ovulatory women with PCOS and overt oligo/amenorrhea have greater degrees of IR but not HA when compared with oligo-ovulatory eumenorrheic women with PCOS, suggesting that IR and hyperinsulinemia but not HA play a role in determining the degree of menstrual dysfunction, which can be used as a clinical marker for the degree of IR in oligo-ovulatory PCOS.

Keywords: Dynamic state; PCOS; insulin resistance; menstrual dysfunction.

Fig. 1.. Differences in measures of in vivo whole-body IR between PCOS and controls.

Subjects in the all cohort (57 PCOS and 57 BMI-matched controls adjusted for age, BMI and race) are depicted. IR was estimated by kITT (%/min) after a short insulin tolerance test. ROC plot of kITT values in PCOS (-ve) and controls (+ve), with the optimal cut-off value for kITT of 3.57 (%/min) (horizontal line) providing 79.7% specificity and 81.5% sensitivity in discriminating between PCOS and control participants (Fig. 1A, Fig. 1B). A scatter plot of differences in mean kITT values between PCOS and control participants for all the cohort (57 PCOS and 57 BMI-matched controls adjusted for age, BMI and race) (Fig. 1B), and for all the cohort subdivided according to menstrual categories (Fig. 1C, 1D and 1E for oligo-ovulatory eumenorrheic, oligomenorrheic and amenorrheic PCOS groups vs. respective ovulatory eumenorrheic groups, respectively) are also depicted. The prevalence of IR between each menstrual subtype of PCOS vs. respective ovulatory eumenorrheic groups is also shown (Fig. 1F). AUC is area-under-the-curve; kITT is the rate constant for glucose disappearance during short ITT, and ROC is receiver operating characteristics (Fig. 1A). **P=0.049 and *P<0.001 (Fig. 1F).

Fig. 2.. Insulin sensitivity among women with PCOS, categorized by menstrual cyclicity (oligo-ovulatory eumenorrhea, oligomenorrhea and amenorrhea), are depicted.

The degree of insulin resistance (IR) estimated by mean kITT (adjusted for age and BMI) in all PCOS subjects (Fig. 2A), and a subgroup of NHW PCOS subjects (Fig. 2B) are shown. (a) Median values are represented by dark diamond, and median by the horizontal lines in the boxes. (b) The heights of the boxes denote the 25^th to 75^th ranges (c) The upper and lower frames represent the maximal and minimal values, respectively. The differences were adjusted for age and BMI