Elucidating the impact of obesity on hormonal and metabolic perturbations in polycystic ovary syndrome phenotypes in Indian women

PCOS phenotype focus: phenotype D under the magnifying glass

Polycystic ovary syndrome (PCOS) is defined as the combination of polycystic morphology, hyperandrogenism, and ovulatory disruption; this heterogeneity presents a conundrum for the medical community. The Rotterdam criteria have governed the diagnosis of PCOS, separating the patient cohort into four distinct phenotypes. It has been suggested that the lone normoandrogenic phenotype, so-called phenotype D, should not be classified as a PCOS subtype, with phenotypes A, B, and C displaying a hyperandrogenic biochemical and clinical profile thought to be characteristic of PCOS. To understand how to treat phenotype D patients, this review shines a spotlight on the phenotype, gathering various reports of how phenotype D is differentiated from the other PCOS phenotypes.

Comparative Study of Insulin Sensitivity and Resistance and Their Correlation with Androgens in Lean and Obese Women with Polycystic Ovary Syndrome

There is a lack of consensus on the optimal screening strategy for insulin resistance (IR), particularly in lean women with polycystic ovary syndrome (PCOS). Therefore, we conducted a cross-sectional study in 80 women with PCOS (28 lean/52 obese) and 80 age- and body mass index (BMI)-matched controls. Using a 5-point 75-g oral glucose tolerance test (OGTT) (0, 30, 60, 90, 120 min), we examined glucose and insulin excursions, IR, insulin sensitivity, beta-cell function (ßF), and the effect of androgens on IR. Lean and obese women with PCOS had similar glucose but higher insulin (except fasting in lean women) and insulin AUC as compared to their respective controls (p < 0.05). Lean women with PCOS were equally insulin-resistant but more hyperinsulinemic than the obese controls (p < 0.05). Although ßF ([1st phase: 481.71 ± 263.53 vs. 430.56 ± 232.37], [2nd phase: 815.16 ± 447.12 vs. 752.66 ± 428.95]) was comparable in lean and obese women with PCOS, lean women had better insulin sensitivity (112.78 ± 66.26 vs. 75.49 ± 55.6) (p < 0.05). Dehydroepiandrosterone sulfate (DHEAS) and androstenedione decreased with increasing BMI in lean women, and this correlated with deteriorating insulin sensitivity and exaggerated hyperinsulinemia. In obese women with PCOS, sex hormone-binding globulin (SHBG) correlated negatively with BMI and hyperinsulinemia, and positively with insulin sensitivity. This data suggests that estimating only fasting insulin may miss IR in lean women with PCOS; hence, additional time points in OGTT will add value to screening for IR. DHEAS and androstenedione may have a beneficial effect on insulin sensitivity and may be used to screen IR in lean women, while SHBG can be used as a predictive marker for IR in obese women with PCOS.

Cardio-metabolic risk in Rotterdam clinical phenotypes of PCOS

BACKGROUND AND AIMS

Elevated anti-Müllerian hormone (AMH) in polycystic ovary syndrome (PCOS) characterizes the clinical severity of the 4 phenotypes; but whether it also reflects the corresponding differences in cardio-metabolic risk remains to be elucidated. This study aimed to compare metabolic profile between the 4 clinical phenotypes of PCOS and to determine the influence of AMH levels on metabolic severity.

METHODS

One hundred and forty-four women with PCOS, aged between 20 and 40years, were recruited in this cross-sectional study and categorized according to the 4 phenotypes of the Rotterdam criteria. Anthropometry and blood pressure were recorded. Fasting lipid profile, fasting glucose, fasting insulin, homeostasis model assessment insulin resistance, total testosterone and AMH were estimated. Clinical, anthropometric and metabolic profiles were compared between the 4 phenotypes.

RESULTS

There were significant differences in menstrual abnormalities, weight, hip circumference, clinical hyperandrogenism, ovarian volume and AMH levels between the 4 phenotypes. Cardio-metabolic risk factors and rates of metabolic syndrome (MS) and insulin resistance (IR) were comparable.

CONCLUSION

Cardio-metabolic risk is similar in all phenotypes of PCOS despite differences in anthropometry and AMH levels. All women diagnosed with PCOS should undergo screening and lifelong surveillance for MS, IR and cardiovascular diseases, irrespective of clinical phenotype or AMH level. This needs further validation in prospective multi-center studies across the country, with larger sample sizes and adequate power.

Clinical and laboratory features in women with different phenotypes of polycystic ovary syndrome

BACKGROUND

Misdiagnosis is still an obstacle in the workup of polycystic ovary syndrome. We compared patients' characteristics among phenotypes of the syndrome and assessed the association of the characteristics with oligo-anovulation, hyperandrogenism, and polycystic ovary.

METHODS

In the infertility department of a teaching hospital, we performed a cross-sectional study. Based on the Rotterdam Criteria, we included 136 patients with polycystic ovary syndrome and 46 healthy controls.

RESULTS

The most common phenotype was A (N.=45;33%). Overall, A and C had larger Body Mass Index (P=0.019 and 0.030, respectively) and waist circumference (P=0.005 and 0.003) than control. Also, A and D had higher serum anti-mullerian hormone than control (both P<0.001) or phenotype C (P<0.001 and 0.01). Phenotypes A and C had higher insulin than control (both P=0.004). The highest level of estradiol was for control and the lowest for B. The lowest high-density lipoprotein was for C; and A to C phenotypes had higher triglyceride than control (P=0.002, <0.001, and 0.041). Larger body mass was associated with hyperandrogenism (adjusted Odds Ratio 95% CI=1.11 [1.01, 1.23], P=0.034); higher anti-mullerian hormone and high-density lipoprotein were related to oligo-anovulation (1.2 [1.07, 1.37], P=0.004; 1.1 [1.00, 1.13], P=0.041). Higher insulin and lower high-density lipoprotein were associated with polycystic ovary (1.11 [1.03, 1.21], P=0.013; 0.9 [0.82, 0.97], P=0.014).

CONCLUSIONS

There are potentials in Body Mass Index, waist circumference, serum anti-mullerian hormone, insulin, estradiol, high-density lipoprotein, and triglyceride concentration for differentiating the phenotypes of polycystic ovary syndrome and for more precise diagnosis of hyperandrogenism, oligo-anovulation, and polycystic ovary morphology.

Anthropometric, Metabolic, and Endocrine Parameters as Predictors of Estimated Average Glucose and Other Biomarkers of Dysglycemia in Women with Different Phenotypes of Polycystic Ovary Syndrome

The aim of the study was to evaluate the efficacy of anthropometric, metabolic, and endocrine abnormalities as predictors of estimated average glucose and other biomarkers of dysglycemia in women with different phenotypes of polycystic ovary syndrome (PCOS). This cross-sectional study included 648 women with PCOS and 330 controls. A single protocol of investigation was applied for all subjects. PCOS women were divided by phenotypes according to the Rotterdam criteria. Biomarkers of dysglycemia were considered dependent variables and anthropometric, lipid, and hormone alterations as independent variables using univariate and multivariate logistic regressions. Univariate logistic regression analysis, controlled for age and BMI, showed that many biomarkers of dysglycemia could be predicted by anthropometric, lipid, and endocrine variables. Multivariate logistic models showed that in non-PCOS women estimated average glucose (eAG) was predicted by lower TSH levels (OR=0.39; p=0.045); fasting glucose was predicted by increased T (OR=2.3). For PCOS, phenotype A, eAG was predicted by decreased HDL-C (OR=0.17, p=0.023) and high levels of free estradiol (OR=7.1, p<0.001). Otherwise, in PCOS, phenotype D, eAG was predicted by higher levels of HDL-C. The current study demonstrated that eAG was poorly predicted by anthropometric, lipid, and hormone parameters. Nevertheless, without adding significant benefits, it was comparable with other established markers of dysglycemia in women with different PCOS phenotypes.

Differential Gene Expression Analysis of Human Ovarian Follicular Cumulus and Mural Granulosa Cells Under the Influence of Insulin in IVF Ovulatory Women and Polycystic Ovary Syndrome Patients Through Network Analysis

BACKGROUND

Polycystic ovarian syndrome (PCOS) is a commonly occurring reproductive disorder among the reproductive-aged women. Its global occurrence varies based on diagnostic guidelines, ethnicities, and locations of concern. Insulin resistance (IR) is commonly observed around 65-70% of women diagnosed with PCOS, representing a prevalent association. Consequently, the study was designed with an objective of illustrating the effect of insulin on mural and cumulus granulosa cells (GCs) of PCOS patients in comparison to normal ovulating women.

METHODOLOGY

This study is a case-control design, wherein a total of 80 participants were recruited meeting criterion of inclusion and exclusion, divided into 8 groups with each group consisting of 10 samples. The process involves the isolation and culturing of mural granulosa cells (MGC) and cumulus granulosa cells (CGC) with and without exposure to insulin. The proteins released by untreated GCs and insulin-treated GCs were extracted, and complex protein mixtures were digested with trypsin, followed by tandem mass spectrometry analysis and data processing using bioinformatics.

RESULTS

We found 595 proteins in both control and PCOS samples, of which 310 were contributed by MGCs and 285 by CGCs. The PCOS MGCs expressed 20%, both the normal MGCs and CGCs have equal representation of 16% by each, whereas the PCOS CGCs proteins contributed 15% of the total of the proteomic expression. However, the poor expression observed with the Insulin exposure, the Insulin treated PCOS CGCs contributes 13%, PCOS MGCs contributes 8%. The normal MGCs upon the Insulin treatment give 8% then and there only 4% of proteins expressed by normal CGCs after Insulin treatment. The Venn analysis widened on their precise expression topographies. The examination of strings exhibited important protein-protein interaction pathways.

CONCLUSION

This is a pioneering investigation aimed to establish the link between hyperinsulinemia in localized follicular GCs and PCOS mechanisms by comparing them to control group. The examination of various attributes, mechanisms, and traits shown by genes and proteins in individuals with PCOS compared to control populations, alongside the investigation of the dynamics of these genes and proteins following exposure to insulin, holds promise for the formulation of novel hypotheses and strategies in the identification of new biomarkers.

Delineating the role of single-nucleotide polymorphism of CYP19 gene on aromatase activity in South Indian women with polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome is a common multifactorial endocrinopathy disorder affecting 5-15% of reproductive women worldwide. The CYP19 gene encodes key enzyme aromatase involved in androgen-to-estrogen conversion which plays a crucial role in the pathophysiology of the syndrome. Very few studies have been done in the Indian population; hence, we investigated whether CYP19 gene rs2414096 SNP is associated with PCOS and hyperandrogenism susceptibility in Karnataka women.

METHODS

Three-hundred subjects including 150 PCOS and 150 age-matched controls were involved in the current case-control study. Sex hormones and biochemical estimation were performed by ELISA. Sanger sequencing and PCR-RFLP were used to genotype the SNP rs2414096. Genotypic-phenotypic association was studied. Statistical analysis was performed.

RESULTS

The GG genotype was more common in patients, while the GA genotype was more common in control women. LH/FSH was significantly increased in GG genotype in PCOS when compared with AA and GA genotypes. Variations of CYP19 rs2414096 were not statistically significant with PCOS.

CONCLUSION

CYP19 rs2414096 polymorphism was not associated with PCOS; however, the homozygous wild GG genotype may exhibit reduced aromatase activity with subsequent hyperandrogenism implicating endocrine abnormalities.

Therapeutic effects of aqueous extract of bioactive active component of Ageratum conyzoides on the ovarian-uterine and hypophysis-gonadal axis in rat with polycystic ovary syndrome: Histomorphometric evaluation and biochemical assessment

Background

Polycystic ovary syndrome (PCOS) is an endocrine disorder, affecting women of reproductive age. Ageratum conyzoïdes (AGC) is used traditionally in the treatment of fever, rheumatism, and ulcer. This study investigates the effects of AGC on ovarian-uterine in PCOS rats.

Methods

Female rats were randomized into four groups (n = 6). Group A control received 2 ml distilled water. Group B received a single dose of 4 mg/kg body weight (bwt) i.p estradiol valerate (EV). Group C received 500 mg/kg bwt AGC and group D received a single dose of 4 mg/kg bwt i.p EV followed by 500 mg/kg bwt AGC orally for 30 days. Parameters tested include follicle-stimulating hormone (FSH), luteinizing hormone (LH), testosterone (T), estradiol (E2), progesterone (P), C-reactive protein (CRP), interleukin (IL)-6, IL-18 and tumor necrosis factor (TNF)- α, malondialdehyde (MDA), superoxide dismutase (SOD), Catalase (CAT), total protein (TP), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and ovary and uterus histomorphometric.

Results

Ageratum conyzoides decrease insulin resistance, obesity indices, TC, TG, LDL, MDA, T, LH, FSH, CRP, IL-6, IL-18, and TNF- α in PCOS rats. And increase HDL, E2, P, TP, CAT, and SOD in PCOS rats. AGC improved ovary and uterus histo-architecture, tertiary, and Graafian follicles, corpus luteum and endometrial thickness increased,and cystic and atretic follicles decreased.

Conclusion

Ageratum conyzoides improved insulin sensitivity, antioxidant activities, hormonal imbalance, inflammatory makers, and histological changes in PCOS rats. Therefore AGC can be used as a potential adjuvant agent in the treatment of PCOS.

Clinical management of pregnancy in women with polycystic ovary syndrome: An expert opinion

Polycystic ovary syndrome (PCOS) is associated with a higher risk for pregnancy and birth complications according to the specific features associated with PCOS. The features include obesity before and during pregnancy, hyperandrogenism, insulin resistance, infertility, cardiometabolic risk factors, and poor mental health. PCOS is not often recognized as a risk factor for poor pregnancy and birth outcomes in pregnancy care guidelines, while its associated features are. Pregnancy-related risk profile should ideally be assessed for modifiable risk factors (e.g., lifestyle and weight management) at preconception in women with PCOS. Hyperglycaemia should be screened using a 75-g oral glucose tolerance test at preconception or within the first 20 weeks of pregnancy if it has not been performed at preconception and should be repeated at 24-28 weeks of pregnancy. In the absence of evidence of benefit for strategies specific to women with PCOS, the international evidence-based guidelines for the assessment and management of PCOS recommend screening, optimizing, and monitoring risk profile in women with PCOS (at preconception, during and postpregnancy) consistent with the recommendations for the general population. Recommended factors include blood glucose, weight, blood pressure, smoking, alcohol, diet, exercise, sleep and mental health, emotional, and sexual health among women with PCOS. The guidelines recommend Metformin in addition to lifestyle for assisting with weight management and improving cardiometabolic risk factors, particularly in those with overweight or obesity. Letrozole is considered the first-line pharmacological treatment for anovulatory infertility in PCOS. Individualized approach should be considered in the management of pregnancy in PCOS.

Causality of anthropometric markers associated with polycystic ovarian syndrome: Findings of a Mendelian randomization study

Introduction

Using body mass index (BMI) as a proxy, previous Mendelian randomization (MR) studies found total causal effects of general obesity on polycystic ovarian syndrome (PCOS). Hitherto, total and direct causal effects of general- and central obesity on PCOS have not been comprehensively analyzed.

Objectives

To investigate the causality of central- and general obesity on PCOS using surrogate anthropometric markers.

Methods

Summary GWAS data of female-only, large-sample cohorts of European ancestry were retrieved for anthropometric markers of central obesity (waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR)) and general obesity (BMI and its constituent variables–weight and height), from the IEU Open GWAS Project. As the outcome, we acquired summary data from a large-sample GWAS (118870 samples; 642 cases and 118228 controls) within the FinnGen cohort. Total causal effects were assessed via univariable two-sample Mendelian randomization (2SMR). Genetic architectures underlying causal associations were explored. Direct causal effects were analyzed by multivariable MR modelling.

Results

Instrumental variables demonstrated no weak instrument bias (F > 10). Four anthropometric exposures, namely, weight (2.69–77.05), BMI (OR: 2.90–4.06), WC (OR: 6.22–20.27), and HC (OR: 6.22–20.27) demonstrated total causal effects as per univariable 2SMR models. We uncovered shared and non-shared genetic architectures underlying causal associations. Direct causal effects of WC and HC on PCOS were revealed by two multivariable MR models containing exclusively the anthropometric markers of central obesity. Other multivariable MR models containing anthropometric markers of both central- and general obesity showed no direct causal effects on PCOS.

Conclusions

Both and general- and central obesity yield total causal effects on PCOS. Findings also indicated potential direct causal effects of normal weight-central obesity and more complex causal mechanisms when both central- and general obesity are present. Results underscore the importance of addressing both central- and general obesity for optimizing PCOS care.

Body Composition and Its Impact on the Hormonal Disturbances in Women with Polycystic Ovary Syndrome

We investigated the relationship between selected body composition (BC) parameters and included 55 women diagnosed with PCOS and 29 women in which PCOS was excluded. Hormone concentration and BC parameters were assessed during hospitalization. Women with PCOS had higher concentration of luteinizing hormones, total testosterone, androstenedione, and Anti-Müllerian hormones compared to women that were not diagnosed with PCOS. We did not observe any significant differences in the BC parameters between both groups as well as between four PCOS phenotype subgroups. Only in the group of women with PCOS was the concentration of sex hormone binding globulin and free testosterone correlated with all investigated BC parameters. Correspondence analysis did not confirm unambiguously associations between phenotypes of PCOS and the value of BC parameters, while logistic regression revealed that increased Anti-Müllerian hormone concentration and the value of body mass index could be useful parameters in differentiating women with PCOS and women with other disorders. The ROC analysis performed on the entire group of women also confirmed that the concentration of Anti-Müllerian hormones could be a powerful parameter to categorize women as suffering from PCOS.

Mitochondrial Dysfunction and Chronic Inflammation in Polycystic Ovary Syndrome

Polycystic ovarian syndrome (PCOS) is the most common endocrine-metabolic disorder affecting a vast population worldwide; it is linked with anovulation, mitochondrial dysfunctions and hormonal disbalance. Mutations in mtDNA have been identified in PCOS patients and likely play an important role in PCOS aetiology and pathogenesis; however, their causative role in PCOS development requires further investigation. As a low-grade chronic inflammation disease, PCOS patients have permanently elevated levels of inflammatory markers (TNF-α, CRP, IL-6, IL-8, IL-18). In this review, we summarise recent data regarding the role of mtDNA mutations and mitochondrial malfunctions in PCOS pathogenesis. Furthermore, we discuss recent papers dedicated to the identification of novel biomarkers for early PCOS diagnosis. Finally, traditional and new mitochondria-targeted treatments are discussed. This review intends to emphasise the key role of oxidative stress and chronic inflammation in PCOS pathogenesis; however, the exact molecular mechanism is mostly unknown and requires further investigation.