Disorders of the Glucose Metabolism Correlate With the Phenotype and the Severity in Women With Polycystic Ovary Syndrome

Josef van Helden; Osman Evliyaoglu; Andreas Küberl; Ralf Weiskirchen

Disclosures

Clin Endocrinol. 2020;93(1):44-51. 

In This Article

Results

Age, BMI, AMH, fasting glucose and insulin (0 minute) distributed normal, and the other parameters were evaluated as nonparametric. Patient's characteristics are given in Table 1. The number of patients without impaired glucose metabolism was 33 out of 130 in the whole study group, which corresponds to a percentage of 25.4%. Eighteen of these 33 patients showed ovulation, and 22 of whom showed hyperandrogenemia. In the second subgroup, 22 (16.9%) patients had normal fasting insulin but showed an insulin overstimulation of more than 5 times the initial value after 60 minutes. In 12 patients, the ovulatory phenotype with normoandrogenemia was present, 4 others ovulated with hyperandrogenemia, and six patients had anovulation. In the third subgroup, 75 (57.7%) had insulin resistance. All patients in this subgroup had hyperandrogenemia, and 66 were suffered from chronic anovulation. The table shows the mean values and standard deviations of each specific parameter for each subgroup. In the group with insulin overstimulation, the lowest values were found for fasting glucose, for insulin before and after glucose administration and for HOMA-IR and AMH. Also, the highest values could be demonstrated for sAMHR2 and for adiponectin. In contrast, the highest values were found in the insulin resistance group for BMI, AMH, proinsulin and glucose and insulin values, while the lowest values were shown for sAMHR2 and adiponectin.

In our study group, we found a strong correlation between sAMHR2 and adiponectin (r = 0.827, P < .001) (Figure 1). The other significant correlations between study parameters are presented in Table 2. There was no significant difference in age and CRP levels between the all subgroups. The significant change of study parameters in different impaired glucose metabolism conditions is shown in Table 3. Strong significant differences in patients between the three subgroups could be demonstrated for sAMHR2, adiponectin levels, sAMHR2/AMH ratio (Figure 2A) and BMI, AMH, AMH z -score (Figure 2B) and HOMA Index, proinsulin (Figure 2C) and insulin levels in 0-60-120 minutes in the glucose tolerance test (Figure 2D).

Figure 1.

Correlation of sAMHR2 and Adiponectin concentrations. Both proteins significantly correlated in the study group. (r = .827, P < .0001) [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 2.

Significant differences of biomarkers in different stages of insulin resistance (A) sAMHR2, adiponectin levels, sAMHR2/AMH ratio, (B) BMI AMH, AMH z -score, (C), HOMA Index intact proinsulin, C-peptide and (D) insulin levels at time points 0, 60 and 120 minutes of glucose tolerance test [Colour figure can be viewed at wileyonlinelibrary.com]

In Figure 3, the diagnostic performances of all parameters with regard to the different states of the glucose metabolism were tested using ROC analysis. For each of these parameters the AUC was reported (see Table S1) with the respective 95% confidence interval as well as the significance. In the group with normal insulin sensitivity, the parameter with the highest selectivity is the quotient of age and 60 minutes insulin value. With a cut-off of 0.67, the sensitivity is 100% with a corresponding specificity of 92%. The positive predictive value is 93.6%. The most meaningful parameter for the diagnosis of insulin resistance is the HOMA-IR. With a cut-off of 1.95 the sensitivity is 97%, the specificity 96% and the PPV 97.5%. For insulin overstimulation, the quotients of sAMHR2 or adiponectin and basal insulin are the parameters with the highest diagnostic performance and thus slightly higher than the respective singular parameters. Here, the respective cut-offs are 0.16 and 1.16. The sensitivities are both 91% with specificities of 84% and 90%, respectively. The PPV's are 92.3% and 94.3%, respectively.

Figure 3.

Diagnostic performance of distinct parameters. The diagnostic performance with regard to (A) insulin resistance (IR−), (B) insulin sensitivity (IR+) and (C) hyperinsulinemia (HI) was tested using ROC and AUC analysis [Colour figure can be viewed at wileyonlinelibrary.com]

Table 3 shows the significance of the various study parameters for different impairments in glucose metabolism, impaired fasting glucose, impaired glucose tolerance and diabetes mellitus. Here, it could be demonstrated that for almost all investigated parameters significant changes of the glucose metabolism, parameters of the ovarian function (AMH, sAMHR2), as well as the calculated parameters derived thereof occurred. Only with regard to the impaired glucose tolerance, some parameters showed no significant differences.

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