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Clinical Trial
. 2017;87(6):359-367.
doi: 10.1159/000471804. Epub 2017 May 5.

Alterations in Glucose Effectiveness and Insulin Dynamics: Polycystic Ovary Syndrome or Body Mass Index

Patricia Vuguin  1 , Aviva B Sopher  1 , Hailey Roumimper  1 , Vivian Chin  1 , Miriam Silfen  1 , Donald J McMahon  2 , Ilene Fennoy  1 , Sharon E Oberfield  1
Affiliations
Clinical Trial

Alterations in Glucose Effectiveness and Insulin Dynamics: Polycystic Ovary Syndrome or Body Mass Index

Patricia Vuguin et al. Horm Res Paediatr. 2017.

Abstract

Background/aims: To delineate the relationship of polycystic ovary syndrome (PCOS), obesity, and hyperandrogenism (HA) with glucose and insulin dynamics in adolescents across a broad body mass index (BMI).

Methods: Seventy-four PCOS subjects (aged 16 years) and 82 controls (aged 16 years) were evaluated by an oral glucose tolerance test. Subjects were categorized by BMI: normal weight (21 ± 0.4), overweight/obesity (OO; 33 ± 1.0), and severe obesity (SO; 48 ± 1.4). Indices of glucose and insulin dynamics were determined. Multiple linear regression analysis was used to evaluate the contribution of PCOS, HA, and BMI to these indices.

Results: BMI was significantly associated with systolic and diastolic blood pressure and insulin resistance. A significant interaction between BMI and PCOS and indices of post-glucose load was observed. The mean difference in peak glucose, early glucose response, area under the curve for glucose, and glucose effectiveness (SgIo) between PCOS and control subjects was significantly different between OO and SO. In PCOS subjects, testosterone was positively associated with BMI, fasting insulin, early insulin response, and diastolic blood pressure, and negatively associated with SgIo.

Conclusions: Abnormal glucose dynamics in adolescents with PCOS is mainly due to SO. The combination of PCOS and SO has a synergistic effect on glucose dynamics when compared to all other groups.

Keywords: Glucose effectiveness; Insulin resistance; Metabolic dysregulation; Metabolic syndrome; Polycystic ovary syndrome in adolescents.

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Figures

Figure 1
Figure 1
Glucose and (b) insulin response during and OGTT in PCOS and C subjects.
Figure 2
Figure 2
Post Meal Indices of Carbohydrate Metabolism in PCOS and C divided into 6 groups based on their BMI-Normal weight (NW) PCOS and control: BMI < 25 kg/m2; overweight/obese (OO) PCOS and C: BMI 25 – < 40 kg/m2; severely obese (SO) PCOS and C: BMI ≥ 40 kg/m2. All data presented as mean ± SE for indices of PeakG (A), ΔG (B), GAUC (C) and IAUC (D). Multivariable analyses described in Table 3 represent the statistical differences between individual categories.
Figure 3
Figure 3
Hyperbolic relationship between Sglo and BMI in adolescent subjects with PCOS (open line) and control (closed line). PCOS subjects have lower SgI0 when BMI is greater than 36 (arrow) when compared to control subjects (P = 0.01). BMI = body mass index. Table represents the results of a multivariate linear regression analysis all variables entered into the model included those with a P < 0.15 in univariant analysis: BMI and the diagnosis of PCOS
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