Close correlation between hyperandrogenism and insulin resistance in women with polycystic ovary syndrome-Based on liquid chromatography with tandem mass spectrometry measurements

Plasma Corin: A New Biochemical Marker for Polycystic Ovary Syndrome

INTRODUCTION

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder. Atrial natriuretic peptide (ANP) is a risk factor for PCOS. Corin protein has an essential role in ANP synthesis. This study aimed to evaluate corin as a sensitive biomarker for PCOS.

MATERIALS AND METHODS

A case-control study was conducted with 70 PCOS patients and 70 healthy females. Plasma Corin levels were quantified using enzyme-linked immunosorbent assay.

RESULTS

The median plasma corin levels in PCOS patients and controls were 1785 and 822.5 pg/mL, respectively. Plasma corin levels were significantly elevated in PCOS patients than in the controls (p < 0.001). The optimal cut-off value was set at 1186 pg/mL. The sensitivity and specificity of Corin were 100% and 97.1%, respectively. Plasma corin levels were surrogate predictors for infertility in women with PCOS. It had an odds ratio of 5.9 (95% confidence interval: 1.1-32.7) (p = 0.04). Plasma corin levels were more highly detected in patients with PCOS than in the controls.

CONCLUSION

Plasma corin level has reasonable diagnostic interpretation for PCOS. Corin appears as a worthy distinct predictor of infertility in PCOS women. Therefore, Corin may be a substantial biomarker for PCOS.

Questioning PCOS phenotypes for reclassification and tailored therapy

Precise diagnoses are essential for defining appropriate treatments. This is particularly true for polycystic ovary syndrome (PCOS), whose phenotypical manifestations have recently suggested a possible diversity of etiological factors. PCOS is defined on the basis of gynecological and endocrinological alterations, but the patients often display considerable metabolic impairments, such as insulin resistance, that may worsen typical symptoms. The Rotterdam criteria fail to address this aspect, and the medical community has recently started to consider them as misleading diagnostic tools, casting doubts on whether the term PCOS is suited to describe all the clinical manifestations observed. This Opinion collects and critically discusses the scientific reports that question the definition of PCOS, calling for a revision of the current diagnostic criteria.

Lean mass and associated factors in women with PCOS with different phenotypes

Although current evidence suggests increased risk of obesity, insulin resistance, and metabolic alterations in patients with polycystic ovary syndrome (PCOS), especially of a hyperandrogenic phenotype, the impact of each one of these variables on muscle mass remains uncertain. In this case-control study, we evaluated clinical and hormonal characteristics related to lean body mass according to the different PCOS phenotypes. We performed clinical, metabolic, and hormonal assessments and evaluated body compartments by dual-energy X-ray absorptiometry in 133 women of reproductive age. Creatinine served as an indirect marker of lean mass. Median age was 28 (range, 17-37) years. Women with phenotypes A and B (n = 59) had higher body mass index (BMI) and metabolic syndrome prevalence than those with phenotype C (n = 23) and controls (n = 51) (p<0.005). Women with phenotypes A and B also had higher Ferriman-Gallwey score (p<0.001), insulin levels (p = 0.006), HOMA-IR (p = 0.008), testosterone (p = 0.008), free androgen index (FAI) (p<0.001), fat mass index (FMI) (p = 0.015), android-to-gynoid fat ratio (p = 0.036), and bone mineral density (BMD) at lumbar spine (p = 0.027) and total femur (p = 0.013) than controls. Median appendicular lean mass index (ALMI) was higher in phenotypes A and B than in controls (7.01 [IQR, 6.33-8.02] vs. 6.69 [IQR, 5.94-7.09], p = 0.024), but it did not differ significantly from that in phenotype C (6.60 [IQR, 6.16-7.22], p = 0.222). Even after adjusting for BMI, ALMI correlated positively with creatinine in women with phenotypes A and B (rho = 0.319, p = 0.023) but not in those with phenotype C (p = 0.238) or controls (p = 0.097). In multivariate linear regression analyses, ALMI was positively associated with insulin, FAI, FMI, and total femur BMD. The present results suggest that fasting insulin, FAI, fat mass, and total femur BMD were positively associated with increased lean mass in women with PCOS phenotypes A and B.

Milicia excelsa (Moraceae) reversed the effects of letrozole-induced aromatase inhibition in rats with polycystic ovary syndrome

OBJECTIVES

Polycystic ovary syndrome (PCOS) is an endocrinopathy affecting 5-20% of women of childbearing age. There is no single drug for the treatment of PCOS and current therapies have significant side effects. This study evaluated the ability of Milica excelsa to improve PCOS symptoms in rats.

METHODS

Induction of PCOS was achieved using letrozole (a reversible aromatase inhibitor; 1 mg/kg; given orally for 21 days). From day 22, PCOS rats received the aqueous extract of M. excelsa roots (14 and 140 mg/kg). Clomiphene citrate (1 mg/kg) was administered to the positive control. The negative and the normal controls received the vehicle (5% DMSO). Treatments were given orally for 7 or 14 days. Vaginal smears were scrutinized daily during the experiment. Body weight was measured hebdomadal. Animals were sacrificed after the two treatment periods for biochemical and histological analyses.

RESULTS

Aromatase inhibition caused hyperandrogenism (p<0.001), overweight (p<0.001) and fat accumulation (p<0.001). It also blocked the estrous cycle at the diestrus phase and altered ovarian dynamics as evidenced by the accumulation of cystic (p<0.001) and atretic (p<0.001) follicles. In contrast, M. excelsa induced weight loss (p<0.001), reduction in fat weight (p<0001), and lower serum androgen and LH levels (p<0.001). It also restored the estrous cycle and improved ovarian dynamics by increasing the amount of Graafian follicles (p<0.001) and corpora lutea (p<0.001), and decreasing that of cystic and atretic follicles (p<0.001).

CONCLUSIONS

Milica excelsa corrected hyperandrogenism and overweight in PCOS animals, and reduced cyst formation and follicle atresia in their ovaries.

Steroid Hormone Profiling in Hyperandrogenism and Non-hyperandrogenism Women with Polycystic Ovary Syndrome

The purpose of this study is to explore the differences in the steroid metabolic network between hyperandrogenic and non-hyperandrogenic women with polycystic ovary syndrome (PCOS). A sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed for the quantification of 36 kinds of serum steroids in 80 PCOS women during their follicular phase. Compared with those in non-hyperandrogenemia PCOS women (NA-PCOS), the levels of 17-hydroprogesterone (P = 0.009), androstenedione (P < 0.001), total testosterone (P < 0.001), dihydrotestosterone (P = 0.025), estrone (P = 0.007), and estradiol (P < 0.001) were increased in hyperandrogenemia PCOS (HA-PCOS) women. It was suggested that HA-PCOS may have increased activity of P450c17 (17-hydropregnenolone/pregnenolone, P = 0.008), 3βHSD2 (androstenedione/dehydroepiandrosterone, P = 0.004), and 17βHSD3 (testosterone/dehydroepiandrosterone, P = 0.01) and decreased activity of 5α reductase (dihydrotestosterone/testosterone, P = 0.008). Moreover, the ratio of luteinizing hormone (LH) to follicle stimulating hormone (FSH) was found to be related to these increased steroids and enzyme activities. In conclusion, the HA-PCOS and the NA-PCOS women showed different steroid profiles, and the different enzyme activities in steroidogenic pathway may be the main reason for the difference.

Steroid Mass Spectrometry for the Diagnosis of PCOS

The most appropriate steroids to measure for the diagnosis of hyperandrogenism in polycystic ovary syndrome (PCOS) are still open to debate but should preferably be measured using a high-quality method such as liquid chromatography tandem mass spectrometry (LC-MS/MS). Measurement of testosterone is recommended in all of the current clinical guidelines but other steroids, such as androstenedione and dehydroepiandrosterone sulfate (DHEAS), have also been shown to be useful in diagnosing PCOS and may give additional information on metabolic risk. The 11-oxygenated steroids, and in particular 11KT derived mainly from the adrenal gland, are also increasing in prominence and have been shown to be the dominant androgens in this condition. Polycystic ovary syndrome is a complex syndrome and it is not surprising that each of the clinical phenotypes are associated with different patterns of steroid hormones; it is likely that steroid profiling with LC-MS/MS may be better at identifying hyperandrogensim in each of these phenotypes. Research into PCOS has been hampered by the small sample size of clinical studies previously undertaken and larger studies, preferably using LC-MS/MS profiling of steroids, are needed

Close correlation between hyperandrogenism and insulin resistance in women with polycystic ovary syndrome-Based on liquid chromatography with tandem mass spectrometry measurements

BACKGROUND

To investigate the correlation between hyperandrogenism (HA) and insulin resistance (IR) in women with polycystic ovary syndrome (PCOS) by measuring serum total testosterone (TT) using a liquid chromatography and tandem mass spectrometry assay (LC-MS/MS).

METHODS

This cohort study included 332 patients with PCOS, 63 patients with IR and 276 with controls. TT levels were measured by LC-MS/MS and chemiluminescent immunoassay (CLIA); glucose and insulin levels were determined by an oral glucose tolerance test (OGTT).

RESULTS

Compared with CLIA, LC-MS/MS differentiated more cases with high TT levels among the non-PCOS subjects with IR In patients with PCOS, LC-MS/MS-based TT levels or a combination with the mFG score detected a significantly higher incidence of HA in subjects with IR identified by hyperinsulinemia (HIN), HOMA-IR or impaired fasting glucose (IFG) than in those without IR Conversely, the IR rates demonstrated by HIN, HOMA-IR, or IFG were remarkably higher in the LC-MS/MS-defined high TT subgroup than in the normal TT subgroup. However, the CLIA platform could not discern a difference in HA incidence between IR and non-IR subgroups or in IR rate between high and normal TT populations. ROC curves also proved that HIN, HOMA-IR, and IFG were positive contributors to HA as measured by LC-MS/MS CONCLUSIONS: The correlation between HA and IR has always been underestimated, partly owing to the less accurate methods previously used to measure TT. HIN, HOMA-IR, and IFG are likely to contribute to the development of HA from a clinical perspective.