Polycystic ovary syndrome and risks for COVID-19 infection: A comprehensive review : PCOS and COVID-19 relationship.

This comprehensive review aimed to evaluate the relationship between SARS-CoV-2 infection (the cause of coronavirus disease 2019, or COVID-19) and the metabolic and endocrine characteristics frequently found in women with polycystic ovary syndrome (PCOS). In the general population, COVID-19 is more severe in subjects with dyslipidemia, obesity, diabetes mellitus, and arterial hypertension. Because these conditions are comorbidities commonly associated with PCOS, it was hypothesized that women with PCOS would be at higher risk for acquiring COVID-19 and developing more severe clinical presentations. This hypothesis was confirmed in several epidemiological studies. The present review shows that women with PCOS are at 28%-50% higher risk of being infected with the SARS-CoV-2 virus at all ages and that, in these women, COVID-19 is associated with increased rates of hospitalization, morbidity, and mortality. We summarize the mechanisms of the higher risk of COVID-19 infection in women with PCOS, particularly in those with carbohydrate and lipid abnormal metabolism, hyperandrogenism, and central obesity.

The connection of alpha-1 acid glycoprotein inflammatory marker with anthropometric, hormonal, and metabolic characteristic of women with polycystic ovary syndrome.

AIM: To investigate the connection of alpha-1 acid glycoprotein inflammatory biomarker with clinical, hormonal, and metabolic characteristics in women with polycystic ovary syndrome (PCOS) and normal cycling controls. METHODS: A cross-sectional study was conducted on 235 women with PCOS and 92 normal cycling controls attended between 2008 and 2018. Alpha-1 acid glycoprotein levels were correlated with clinical, anthropometric, anthropometric-metabolic indexes, and hormones of women with PCOS and controls. Simple and multivariate stepwise linear regression, matched for age and body mass index confounding variables, was performed. RESULTS: Alpha-1 acid glycoprotein levels were higher in women with PCOS (p = 0.0016). In controls, it was positively correlated with waist circumference, fat mass, body adiposity index, and lipid accumulation product, and negatively correlated with sex hormone-binding globulin (p < 0.005 for all comparisons). In PCOS, it was positively correlated with testosterone, most biomarkers of central adiposity, homeostatic model assessment of insulin-resistant, erythrocyte sedimentation rate, and negatively correlated with sex hormone-binding globulin, high-density lipoprotein cholesterol, glucose/insulin ratio, and lymphocytes (p < 0.055 for all comparisons). After multivariate regression in women with PCOS, alpha-1 acid glycoprotein retained a significant positive correlation with erythrocyte sedimentation rate and C-reactive protein. CONCLUSIONS: In PCOS, alpha-1 acid glycoprotein is correlated with biomarkers of adiposity, carbohydrate metabolism, and total testosterone. This inflammatory marker is also correlated with erythrocyte sedimentation rate, neutrophils, and lymphocytes, frequent markers of an inflammation state.

Differential Effects of Various Androgens on Polycystic Ovary Syndrome.

The hyperandrogenism in polycystic ovary syndrome (PCOS) is associated with the risk for the future development of the cardiovascular disease. The objective of the study is to verify whether different androgens have the same harmful effect. This cross-sectional study enrolled 823 women with PCOS: 627 (76.2%) with biochemical hyperandrogenism and 196 (23.8%) with normal androgen levels. The role of individual androgen was evaluated using univariate and multivariate logistic regression. In normoandrogenemic PCOS (NA-PCOS), free androgen index (FAI) predicted significant abnormality in visceral adipose index (VAI, OR=9.2, p=0.002) and dehydroepiandrosterone (DHEA) predicted against alteration in ß-cell function (OR=0.5, p=0.007). In hyperandrogenemic PCOS (HA-PCOS), FAI predicted derangements in waist triglyceride index (WTI), VAI, and lipid accumulation product (LAP) (OR ranging from 1.6 to 5.8, p<0.05). DHEA weakly predicted against VAI (OR 0.7, p=0.018), dehydroepiandrosterone sulfate (DHEAS) tended to predict against the conicity index (OR=0.7, p=0.037). After multiple regression, FAI retained significant strength to predict various anthropometric and metabolic abnormalities (OR ranging from 1.1 to 3.0, p<0.01), DHEA was kept as a protector factor against WTI, LAP, and VAI (OR ranging from 0.6 to 0.9; p<0.01) and DHEAS against the conicity index (OR=0.5, p<0.001). In conclusion, the free androgen index was the most powerful predictor of anthropometric and metabolic abnormalities of polycystic ovary syndrome. Conversely, DHEA and DHEAS demonstrated protective effects against disorders in some markers of obesity and abnormal metabolism.

The Role of Visceral Adiposity Index as Predictor of Metabolic Syndrome in Obese and Nonobese Women with Polycystic Ovary Syndrome.

Background: To evaluate anthropometric-metabolic biomarkers as predictors of metabolic syndrome (MS) in women with polycystic ovary syndrome (PCOS) with and without obesity. Methods: This was an observational cross-sectional study. Patients were classified as nonobese-PCOS (body mass index, BMI <30 kg/m2, n = 385), and obese-PCOS (BMI ≥30 kg/m2, n = 261). The anthropometric parameters waist circumference, waist/hip ratio, lean body mass, fat body mass, visceral adiposity index (VAI), lipid accumulating product, and biomarkers of glucose and lipid metabolisms were compared between groups. Binominal logistic regression analyses were performed to identify predictors of MS. Results: Obesity was diagnosed in 40% of all PCOS women (P < 0.001). Blood pressure and anthropometric abnormalities were significantly more frequent in obese-PCOS women (P < 0.001, for all comparisons). Glucose metabolism markers were higher in obese-PCOS compared with nonobese-PCOS (P < 0.001, for all comparisons). High-density lipoprotein cholesterol was lower in obese group than in nonobese group (1.26 mM vs. 1.08 mM, P < 0.001). MS was found in 23 of 385 (6%) nonobese-PCOS and in 116 of 261 (44.4%) obese-PCOS (P < 0.001). VAI was the best predictor of MS in both nonobese-PCOS (OR = 4.1, 95% CI 1.5-11.1) and obese-PCOS (OR = 12.9, 95% CI 5.7-29.0). Conclusions: MS is more prevalent in PCOS women with obesity. VAI was the strongest predictor of MS in both obese and nonobese PCOS women, and can be applied in clinical practice for early detection of risk for MS and precocious intervention in women with PCOS, particularly in obese women.

Comparison of metabolic and obesity biomarkers between adolescent and adult women with polycystic ovary syndrome.

PURPOSE: Knowledge of adolescent and adult phenotypes of women with polycystic ovary syndrome (PCOS) might drive opportune management. The aim of this study was to compare metabolic and obesity biomarkers between adolescent and adult women with PCOS. METHODS: This observational study compared biomarkers of obesity and metabolism derangements between adolescent (n = 62) and adult (n = 248) women with PCOS. Predictors of metabolic syndrome (MS) were investigated using univariate and multivariate binary logistic regression analysis. RESULTS: The postmenarcheal age of adolescents was 4.9 ± 0.03 years. Systolic blood pressure was lower in adolescents than in adults (112.3 mmHg vs 117.0 mmHg, p = 0.001) Diastolic blood pressure was also lower in adolescents (70.7 mmHg vs 75.8 mmHg, p < 0.001). Glucose intolerance (12.0% vs 19.3%) and insulin resistance (18.2% vs 17.7%) were similar in both groups (p > 0.05, for comparisons). Impaired fasting glucose was lower in adolescents (1.8% vs 11.6%, p = 0.015). Total cholesterol and low-density lipoprotein cholesterol were lower in adolescents (p < 0.001). MS in adolescents and adults were found in 10.3% and 27.8%, respectively (p = 0.005). Visceral adiposity index (VAI) was a good predictor of MS in both adolescents (OR = 12.2), and adults (OR = 9.7). CONCLUSIONS: Most biomarkers of glucose metabolism abnormalities were similar in adolescents and adults with PCOS. The prevalence of MS was lower in adolescents. VAI was a strong predictor of metabolic syndrome, both in adolescent and adult women with PCOS.

Relationship of Biological Markers of Body Fat Distribution and Corticosteroidogenic Enzyme Activities in Women with Polycystic Ovary Syndrome.

The aim of the study is to determine the impact of different anthropometric measurements of fat distribution on baseline sex-steroid concentrations and corticosteroidogenic enzyme activity in women with polycystic ovary syndrome compared to those with regular menstrual cycles. The current cross-sectional study included 106 normal cycling controls and 268 polycystic ovary syndrome patients. Patients with polycystic ovary syndrome, diagnosed by Rotterdam criteria, were divided in normoandrogenemic (n=91) and hyperandrogenemic (n=177). Anthropometric, biochemical, and hormone parameters were assessed and correlated with corticosteroidogenic enzyme activities in all three groups. Corticosteroidogenic enzyme activities were calculated using product-to-precursor ratios. Regarding sex-steroids individually, anthropometric parameters correlated with the concentrations of several androgens in polycystic ovary syndrome patients, most of them in patients with biochemical hyperandrogenism. The androgen precursors androstenedione, 17-hydroxyprogesterone, and dehydroepiandrosterone were less correlated with anthropometric parameters. The 17,20 lyase activity, in both Δ4 and Δ5 pathways, correlated with several anthropometric measurements in normo- and hyperandrogenemic polycystic ovary syndrome patients. The 17,20 lyase enzyme activity (Δ4 pathway) also correlated with conicity index, visceral adiposity index, and lipid accumulation product in the control group. 17-Hydroxylase activity positively correlated with waist-height ratio in both polycystic ovary syndrome groups. In contrast, 17-hydroxilase negatively correlated with the conicity index. Anthropometric markers of adiposity are associated with androgen levels and their precursors in blood. Body fat distribution correlates with the activities of some steroidogenic enzyme in both normo-and hyperandrogenemic polycystic ovary syndrome phenotypes. The molecular mechanisms involved in these associations are largely unclear and more investigations are required.

Subclinical Hypothyroidism Impact on the Characteristics of Patients with Polycystic Ovary Syndrome. A Meta-Analysis of Observational Studies.

BACKGROUND/AIMS: Definitive polycystic ovary syndrome (PCOS) diagnosis should exclude thyroid dysfunctions. The purpose of the study is to examine the impact of subclinical hypothyroidism on the characteristics of PCOS patients. METHODS: A meta-analysis of the published observational studies was conducted. Medline, Scopus, and Cochrane database search was performed to identify the studies that compared euthyroid PCOS and subclinical hypothyroidism (SCH)-PCOS patients. A total of 9 studies were selected, totalizing the inclusion of 1,537 euthyroid PCOS and 301 SCH-PCOS. The data were expressed as raw mean difference and standard error, using the random-effects model. Heterogeneity among studies was examined using the Cochran's test (Q) and I2 statistics. RESULTS: Anthropometrical parameters were similar in both groups. Total cholesterol (TC) and triglyceride (TG) were higher in SCH-PCOS (p = 0.036 and p = 0.012). High-density lipoprotein cholesterol was lower in the SCH-PCOS group (p = 0.018). Fasting glucose was lower in euthyroid PCOS (p = 0.022). All androgen levels were similar in both group (p > 0.05 for all). CONCLUSION: TC, TG and fasting glucose were higher in SCH-PCOS patients. Because of the heterogeneity among studies, some summarized results should be interpreted with caution. Consistent data for future studies addressing PCOS diagnosis are provided.

The Role of C-Peptide as Marker of Cardiometabolic Risk in Women With Polycystic Ovary Syndrome: A Controlled Study.

BACKGROUND: The aim of this study was to examine the role of C-peptide as a biological marker of cardiometabolic risk in polycystic ovary syndrome (PCOS). METHODS: This case-control study enrolled 385 PCOS patients and 240 normal cycling women. Anthropometric and clinical variables were taken at first visit. Fasting C-peptide, glucose, lipids, and hormone measurements were performed. Simple and multiple correlations between C-peptide and other variables associated with dysmetabolism and cardiovascular disease were examined. RESULTS: C-peptide was well correlated with several anthropometric, metabolic, and endocrine parameters. In PCOS patients, stepwise multiple regression including C-peptide as the criterion variable and other predictors of cardiovascular disease risk provided a significant model in which the fasting C-peptide/glucose ratio, glucose, body weight, and free estrogen index (FEI) were retained (adjusted R2 = 0.988, F = 7.161, P = 0.008). CONCLUSION: C-peptide levels alone or combined with C-peptide/glucose ratio, glucose, body weight, and FEI provided a significant model to identify PCOS patients with higher risk of future cardiometabolic diseases.

Combined Oral Contraceptive Effects on Low-Grade Chronic Inflammatory Mediators in Women with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis.

Polycystic ovary syndrome is associated with dyslipidemia, dysglycemia, metabolic syndrome, and low-grade chronic inflammation, which increase the risks for cardiovascular disease. Combined oral contraceptives may affect the mediators of low-grade chronic inflammation with potential additive risk in PCOS patients. This meta-analysis investigates the impact of oral contraceptive on markers of chronic inflammation in PCOS patients. Pubmed, Scopus, and Cochrane database were used to search studies reporting on this matter in the target population. Twenty seven studies were selected, including a total of 838 women. The data were expressed as the standardized mean difference. The random-effects model was used to summarize effect sizes. Heterogeneity was examined using Cochran's test (Q) and I2 statistics. Most of the preparations increased C-reactive protein (CRP) in PCOS patients (p >0.001). The increase in homocysteine levels was not significant (p >0.05). Follistatin significantly increased with pills containing cyproterone acetate (p= 0.008). Interleukin-6 changes were inconsistent and plasminogen activator inhibitor-1 decreased with pills containing desogestrel, norgestimate, and drospirenone. Collectively, the results of this review indicate that oral contraceptives modify most inflammatory markers of PCOS patients. However, the clinical implications are not clear yet and future studies must consider longer follow-up and the inclusion of objective clinical parameters.

Should Subclinical Hypothyroidism Be an Exclusion Criterion for the Diagnosis of Polycystic Ovary Syndrome?

BACKGROUND: The purpose of the study was to examine whether patients with subclinical hypothyroidism (SCH) should be excluded before making a diagnosis of polycystic ovary syndrome (PCOS). METHODS: Seven hundred sixteen patients, 462 with true PCOS, 31 with PCOS-SCH, and 223 normal cycling women were enrolled. Clinical, metabolic, and hormonal parameters among the groups were investigated. Continuous variables were compared by one-way analysis of variance. Proportions were compared using Z test. Fisher test was used to compare categorical variables. Simple correlation was performed using Spearman's coefficient. Correlation between thyroid stimulating hormone (TSH) and dependent variables were performed using backward multiple regression. The significance level was set at 0.05. RESULTS: True polycystic ovary and polycystic ovary with subclinical hypothyroidism patients presented similar anthropometrical parameters. C-peptide was higher in polycystic ovary patients than in the other groups (p=0.014). Prevalence of glucose intolerance (p=0.186) and insulin resistance (p=0.293) was not statistically different in polycystic ovary and polycystic ovary with subclinical hypothyroidism. TSH levels showed positive correlation with lean body mass (p=0.032), total cholesterol (p=0.046, insulin (p=0.048) and prolactin (p=0.047). Backward multiple regression model retained TC, insulin, and PRL as predictors of TSH levels (p=0.011). CONCLUSION: Anthropometric parameters and ovary morphology were similar in both PCOS and PCOS-with-SCH patients. Regarding hormones, only C-peptide was higher in PCOS group. TSH correlated with total cholesterol, insulin, and prolactin. Before PCOS diagnosis, the exclusion criterion thyroid dysfunction should be standardized and subclinical hypothyroidism should not exclude a diagnosis of PCOS.

Metabolic and endocrine connections of 17-hydroxypregnenolone in polycystic ovary syndrome women.

OBJECTIVE: To examine the anthropometric, and metabolic connections of 17-hydroxypregnenolone in the normo- and hyperandrogenemic polycystic ovary syndrome phenotypes. MATERIALS AND METHODS: This cohort study was conducted at the Julio Muller University Hospital, Cuiabá, Brazil, between January 2014 and July 2016, and 91 normal cycling healthy women, 46 normoandrogenemic and 147 hyperandrogenemic, patients with polycystic ovary syndrome (PCOS) were enrolled according to the Rotterdam criteria. Several anthropometric, biochemical and hormonal parameters were properly verified and correlated with 17-hydroxypregnenolone (17-OHPE) concentrations. RESULTS: 17-OHPE was higher in hyperandrogenemic PCOS than in normoandrogenemic PCOS and in control groups (P = 0.032 and P < 0.001, respectively). In healthy controls, 17-OHPE was positively associated with glucose, free estrogen index, DHEAS and negatively associated with compounds S. In normoandrogenemic PCOS patients, 17-OHPE presented positive correlations with VAI, LAP, cortisol, insulin and HOMA-IR. In the hyperandrogenemic group, 17-OHPE presented significant negative correlations with most anthropometric parameters, HOMA-IR, HOMA %B, estradiol, free estrogen index (FEI), C-peptide, and TG levels and positive correlations with HOMA-S and high-density lipoprotein cholesterol (HDL-C), sex-hormone binding globulin (SHBG), androstenedione (A4) and dehydroepiandrosterone (DHEA). Regarding hyperandrogenemic PCOS, and using a stepwise multiple regression, only HOMA-S and WHR were retained in the model (R2 = 0.294, P < 0.001). CONCLUSION: 17-OHPE exhibited different relationships with anthropometric, and biochemical parameters in PCOS patients, depending on the androgen levels. In PCOS subjects with high androgen concentrations, 17-OHPE was negatively associated with most anthropometric parameters, particularly with those used as markers of adipose tissue dysfunction and frequently employed as predictors of cardiovascular disease risk; otherwise, 17-OHPE was positively associated with HDL-C and HOMA-S in this patients. Future studies are required to evaluate the clinical implications of these novel findings.