Anthropometric, clinical, and metabolic comparisons of the four Rotterdam PCOS phenotypes: A prospective study of PCOS women

Relationship Between Lipid Profile and Body Mass Index in Patients With Polycystic Ovarian Syndrome: A Cross-Sectional Study Among Indian Women of Reproductive Age

Introduction Characterized by a range of symptoms including irregular menstrual cycles, hirsutism, and infertility, polycystic ovarian syndrome (PCOS) also poses substantial metabolic challenges. Among these, dyslipidemia and obesity are particularly concerning due to their long-term implications for cardiovascular health. The present study explores the intricate relationship between lipid profile and body mass index (BMI) in patients with PCOS presenting to the Department of Obstetrics and Gynaecology, King George's Medical University, Lucknow, a tertiary care teaching hospital in Northern India. Methods The present work involves analysis of clinical characteristics of 230 premenopausal women between 18-45 years of age diagnosed with PCOS (according to Rotterdam Criteria). Patients with conditions such as congenital adrenal hyperplasia; Cushing's syndrome; uncontrolled hypertension, smoking, hypogonadism; using oral contraceptives; pregnant or lactating mothers; smoking or drug addiction; psychiatric illness; and those diagnosed with androgen-secreting tumors were excluded. For each participant, data was collected pertaining to demographics (age, marital status), clinical presentation, height, and weight (for BMI calculation), and total lipid profile comprising of total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and very low-density lipoprotein cholesterol (VLDL-C). The patients were stratified according to their BMI as per the WHO Asian classification, and Pearson's correlation coefficient was calculated to see the correlation between lipid profile and BMI. Results The final analysis was done on 228 patients, with a mean age of 25.22 (±4.82) years, and 45.6% were currently married. Among the participants, 28.1% of the participants were overweight, and 42.5% of them classified as obese, while the remaining 29.4% had a BMI in the normal range. The mean (SD) total cholesterol was 172.26 (49.55) mg/dl, and 65 patients (28.5%) had elevated serum cholesterol (≥200 mg/dl). Triglycerides were raised (≥ 150 mg/dl) in a majority of the study participants (n=160, 70.2%). While none of the patients had high VLDL-C, LDL-C was elevated in 52 patients (22.8%). HDL-C levels were lower than the threshold value of 50 mg/dl in 152 participants (66.7%). On performing correlation analysis, a significant negative correlation was noted between HDL-C and BMI in the entire study cohort (r=-0.342, p=0.003). Overweight patients exhibited a statistically significant positive correlation between triglycerides and BMI (r=2.628, p=0.002). Participants with BMI in the overweight range demonstrated statistically significant correlations with HDL-C (r=-0.497, p=0.017) and triglycerides (r=2.628, p=0.002); and BMI of obese patients significantly correlated with total cholesterol (r=0.301, p=0.037) and triglycerides (r=0.146, p=0.028). Conclusion The findings of the study underscore the multifaceted nature of PCOS, affecting reproductive health as well as metabolic components. The significant correlations between BMI and lipid parameters, specifically, HDL-C, triglycerides, and total cholesterol, highlight the importance of weight management in reducing cardiovascular risks in women with PCOS.

Distribution and anthropometric characteristics of Rotterdam criteria-based phenotypic forms of Polycystic ovaries syndrome in Ukraine

OBJECTIVE

To explore the distribution of Rotterdam-based PCOS phenotypes and their associations with anthropometric parameters predictive of cardiometabolic risks in Ukrainian referral PCOS women.

STUDY DESIGN

It was a cross-sectional study conducted by the Ukrainian Society of Gynecological Endocrinology between September 2021 and January 2022 involving 42 clinics in 10 regional centres representing the major geographical parts of Ukraine. Two hundred obstetrician-gynecologists whose practice facilities corresponded to study criteria were committed to entering records of their PCOS patients aged 20-45 years into the uniform data collection forms. The recorded parameters were: PCOS phenotype with the mandatory assessment of biochemical hyperandrogenism, age, BMI, waist circumference, and hyperandrogenism symptoms.

RESULTS

5254 patients' records were completed. Phenotype A was the most prevalent - 47.7 %, phenotypes B, C, and D were almost equally distributed in the studied population: 17.6 %, 17.4 %, and 17.3 % respectively. The total prevalence of androgenic phenotypes based on the presence of biochemical hyperandrogenism was 82.7 %. The incidence of obesity and hyperandrogenism symptoms, and mean BMI values were higher in phenotypes A and B compared to C and D. At the same time, the presence of 34.1 % and 46.2 % of normal-weight subjects in phenotypes A and B respectively, supports the fact that the excessive BMI is not a universal characteristic of androgenic phenotypes. In younger age groups, phenotypes C and D demonstrated the predominance of normal weight, but in older subgroups, the situation changed: in the age group of 36-45 y.o. compared to 18-25 y.o., the percentage of overweight and obese subjects for the non-classic phenotypes increased more than for the classic ones: C (OR = 3.91, 95 % CI: 2.41-6.38), D (OR = 4.14, 95 % CI: 2.64-6.52), A (OR = 2.30, 95 % CI:1.72-2.08), and B (OR = 2.56, 95 % CI:1.69-3.89).

CONCLUSIONS

In thoroughly assessed Ukrainian referral PCOS population the classic phenotypes prevailed as in other clinical cohorts. The classic phenotypes were characterized by the higher rate of adiposity and severity of clinical hyperandrogenism. At the same time, obese, overweight, and normal-weight subjects were present in all phenotypes, and the risk of obesity in non-classic phenotypes was higher in older age groups.

Triglyceride-glucose index is associated with metabolic syndrome in women with polycystic ovary syndrome

OBJECTIVE

To explore the correlation of triglyceride-glucose index (TyG) index with metabolic syndrome (MetS) and metabolic risk factors, and to assess the predictive value of TyG for MetS in women with PCOS.

METHODS

This is a retrospective cross-sectional study that included 819 women diagnosed with PCOS and 3122 women without PCOS from January 2018 to December 2021. The definition of MetS adopted in this study was the International Diabetes Federation (IDF) criteria. The TyG index was calculated as the ln (fasting triglyceride level [mg/dL] × fasting glucose level [mg/dL]/2).

RESULTS

MetS was diagnosed in 266 women (32.5%) among 819 subjects with PCOS, and in 287 women (9.2%) among 3122 subjects without PCOS. Logistic regression analysis showed that women in the highest tertile of TyG index had the highest prevalence of MetS (OR = 3.66, 95%CI: 1.28-10.49) after adjusting for confounding factors. Compared with the lowest tertile, PCOS women in the highest tertile showed the highest odds ratio of hypertension, obesity, central obesity, hyperglycemia and dyslipidemia. Furthermore, TyG index was able to identify MetS in women with PCOS, and the optimal cutoff values were 8.65 (Youden index = 0.65).

CONCLUSION

TyG index was positively and independently correlated with the prevalence of MetS, which also indicated a good predictive ability in women with PCOS.

Pre-polycystic ovary syndrome and polymenorrhoea as new facets of polycystic ovary syndrome (PCOS): Evidences from a single centre data set

OBJECTIVE

Polycystic ovary syndrome (PCOS) is a complex disorder with diverse metabolic implications. Diagnosis typically relies on oligo-amenorrhoea (OA), hyperandrogenism (HA), and polycystic ovarian morphology (PCOM). However, the role of polymenorrhoea in PCOS remains understudied. Additionally, limited information exists regarding metabolic disturbances in women with partial PCOS phenotypes that do not meet diagnostic criteria. This extensive database aims to provide substantial evidence on the metabolic implications of polymenorrhoea and partial PCOS phenotypes.

DESIGN

Prospective observational study.

PATIENTS AND MEASUREMENTS

In this single-centre study, 6463 women with PCOS-like characteristics and 3142 age-matched healthy women were included. The study compared clinical (anthropometry, modified Ferriman Gallwey [mFG] score), hormonal (serum testosterone), and metabolic (plasma glucose, serum lipids, insulin) characteristics between women diagnosed with PCOS, those with partial PCOS phenotypes, and the healthy control group RESULTS: In all, 5174 women met Rotterdam criteria for PCOS diagnosis, while 737 were classified as Pre-PCOS, including HA (n = 538), OA (n = 121), or PCOM (n = 78). Common clinical features included oligomenorrhoea (75.5%), hirsutism (82.9%), obesity (27.2%), hypertension (1.6%), metabolic syndrome (19.6%), and diabetes mellitus (5.6%). Women diagnosed with PCOS, HA only, and OA only exhibited higher average body mass index, plasma glucose levels (both fasting and 2 h after the oral glucose tolerance test), and lipid fractions in comparison to those with PCOM and the healthy controls. However, indices of insulin resistance were similar among women with PCOS, HA, PCOM, and OA, albeit higher than in the healthy controls. The polymenorrhoea subgroup (5.9%) had lower BMI and serum testosterone, but similar mFG score, plasma glucose, insulin, and lipid levels as the oligomenorrhoea subgroup.

CONCLUSION

The metabolic disturbances observed in Pre-PCOS women highlight the need to reassess diagnostic criteria. Including the polymenorrhoea subcategory in PCOS criteria is recommended due to similar metabolic dysfunctions as the oligomenorrhoea group.

Effects of body mass index and insulin resistance on first-time assisted conception and perinatal outcomes in young polycystic ovary syndrome patients

Objective

The objective of the study was to explore the effect of body mass index (BMI) and insulin resistance (IR) levels on first-time assisted conception results and perinatal outcomes in young polycystic ovary syndrome (PCOS) patients.

Design

This was a single-center, retrospective, observational cohort study.

Patients

Young women with PCOS undergoing their first embryo transfer were included in the study.

Main outcome measure

Early pregnancy loss rate was the main outcome measure.

Results

The early pregnancy loss rate in the overweight + insulin resistance group (OW+IR group) was significantly higher than that in the non-overweight + non-insulin resistance group (NOW+NIR group) (18.16% vs. 9.02%, Bonferroni correction, P = 0.012). The early pregnancy loss rate in the non-overweight + insulin resistance group (NOW+IR group) and overweight + non-insulin resistance group (OW+NIR group) (18.18% and 17.14%, respectively) were also higher than that in the NOW+NIR group (6.07%), but the difference was not statistically significant (Bonferroni correction, all P > 0.05). No significant difference was found in clinical pregnancy rate, live birth rate, and macrosomia rate (all P > 0.05). After adjusting for confounding factors, BMI and IR levels were identified as independent risk factors for early pregnancy loss rate.

Conclusion

BMI and IR levels are independent risk factors for early pregnancy loss in young PCOS patients during the first embryo transfer cycle. Multiple indicators should be considered when assessing pregnancy outcomes, which will promote individualized pregnancy guidance and treatment procedures for PCOS patients.

Correlation of Body Mass Index with Anthropometric and Biochemical Parameters Among Polycystic Ovary Syndrome Phenotypes

This was a prospective observational study, conducted at a tertiary care health centre in Rajasthan. A total of 68 women with PCOS (Rotterdam criteria) attending OPD at Department of Obstetrics and Gynecology qualified as per inclusion and exclusion criteria were included in the study. Each participant was examined for anthropometric and biochemical parameters. The largest phenotypic group was phenotype A, (41.17%); followed by B (26.47%); C (20.58%), and D (P + O) phenotypes (11.76%). Hyperandrogenic phenotypes (A, B, C), had significantly higher prevalence of deranged serum glucose (fasting and postprandial), lipid profile and serum TSH than normoandrogenic phenotype D. BMI was strongly correlated with anthropometric (p < 0.001) and biochemical parameters (p < 0.05) in phenotype A among four phenotypes of PCOS. Phenotype A was the most common form of PCOS and a strong correlation of BMI with waist circumference (WC), dyslipidemia and Sub-clinical hypothyroidism (SCH) was observed in women of this phenotype of PCOS. These results indicate that phenotype A is at increased risk of CVD and diabetes and phenotype D has least metabolic risks.

Ethnicity in polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is the commonest gynecological endocrinopathy. Little is known about the exact etiopathogenesis and cardiometabolic mortality and morbidity in women with PCOS. PCOS is beyond the cosmetic concerns of an adolescent and fertility concerns of an adult and can cause serious unhealthy consequences in perimenopausal and postmenopausal age. This area needs to be assessed and addressed since the majority of these patients are lost to follow-up after completion of their families. Good evidence suggests that there are significant racial and ethnic differences in prevalence, insulin resistance, metabolic syndrome, hyperandrogenemia and the related cardiometabolic risk in women with PCOS.

Serum anti-Müllerian hormone as a predictor of polycystic ovarian syndrome among women of reproductive age

BACKGROUND

Polycystic ovarian syndrome (PCOS) affects up to one-fifth of women of reproductive age and causes anovulatory subfertility. Some studies have recommended that an anti-Müllerian hormone (AMH) level greater than 3.8-5 ng/mL can be used for diagnosing PCOS. This study aims to analyse serum AMH levels among PCOS women of reproductive age to use AMH as a biomarker predictor along with other Rotterdam criteria.

METHODS

In this cross-sectional study, a total of 98 women visiting the fertility center of a private hospital in Lahore, Pakistan, were screened. Data were obtained from 51 PCOS newly diagnosed women aged 28.24 years (SD ± 4.84 years) meeting at least two of the Rotterdam criteria and specific inclusion criteria. Baseline variables, menstrual cycle length, ovarian morphology on ultrasound, hirsutism, sex hormones, gonadotropin, and serum AMH levels were analysed during the follicular phase (1-5 days) of the menstrual cycle. Serum AMH was measured by an enzyme-linked immunosorbent assay.

RESULTS

A high serum AMH level (7.23 ± 4.67 ng/ml) was recorded with normal sex hormone levels. Women with oligo-/amenorrhea had a significant mean difference for luteinizing hormone (p = 0.02) and AMH levels (p = 0.03) when compared with women of normal menstrual cycle length. PCOS women with high AMH levels (≥ 3.9 ng/ml) showed a significant difference in ovarian morphology (p < 0.05) when compared with the normal AMH group.

CONCLUSIONS

An elevated serum AMH level can be used as a strong predictor to reflect the certainty of PCOS diagnosis among women of reproductive age when study concurrently with the other Rotterdam criteria.

Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study

Background

Artificial intelligence and digital health care have substantially advanced to improve and enhance medical diagnosis and treatment during the prolonged period of the COVID-19 global pandemic. In this study, we discuss the development of prediction models for the self-diagnosis of polycystic ovary syndrome (PCOS) using machine learning techniques.

Objective

We aim to develop self-diagnostic prediction models for PCOS in potential patients and clinical providers. For potential patients, the prediction is based only on noninvasive measures such as anthropomorphic measures, symptoms, age, and other lifestyle factors so that the proposed prediction tool can be conveniently used without any laboratory or ultrasound test results. For clinical providers who can access patients’ medical test results, prediction models using all predictor variables can be adopted to help health providers diagnose patients with PCOS. We compare both prediction models using various error metrics. We call the former model the patient model and the latter, the provider model throughout this paper.

Methods

In this retrospective study, a publicly available data set of 541 women’s health information collected from 10 different hospitals in Kerala, India, including PCOS status, was acquired and used for analysis. We adopted the CatBoost method for classification, K-fold cross-validation for estimating the performance of models, and SHAP (Shapley Additive Explanations) values to explain the importance of each variable. In our subgroup study, we used k-means clustering and Principal Component Analysis to split the data set into 2 distinct BMI subgroups and compared the prediction results as well as the feature importance between the 2 subgroups.

Results

We achieved 81% to 82.5% prediction accuracy of PCOS status without any invasive measures in the patient models and achieved 87.5% to 90.1% prediction accuracy using both noninvasive and invasive predictor variables in the provider models. Among noninvasive measures, variables including acanthosis nigricans, acne, hirsutism, irregular menstrual cycle, length of menstrual cycle, weight gain, fast food consumption, and age were more important in the models. In medical test results, the numbers of follicles in the right and left ovaries and anti-Müllerian hormone were ranked highly in feature importance. We also reported more detailed results in a subgroup study.

Conclusions

The proposed prediction models are ultimately expected to serve as a convenient digital platform with which users can acquire pre- or self-diagnosis and counsel for the risk of PCOS, with or without obtaining medical test results. It will enable women to conveniently access the platform at home without delay before they seek further medical care. Clinical providers can also use the proposed prediction tool to help diagnose PCOS in women.

Metabolic syndrome and its components in different phenotypes of polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is the most common endocrinopathy affecting reproductive-age women. Important factors in its pathogenesis are hyperinsulinaemia and insulin resistance, which lead to higher risk of metabolic syndrome (MetS) and its complications. With the implementation of the Rotterdam diagnostic criteria in 2003, the group of PCOS patients became highly heterogeneous, with varying metabolic risk reported for different phenotypes of the syndrome. The aim of the present review is to assess the prevalence and severity of MetS and its components in patients with the four phenotypes of PCOS. A comprehensive search of Pubmed database was performed to identify studies comparing metabolic characteristics between PCOS patients with different phenotypes of the syndrome. The results of 60 studies published between 2004 and 2020 were retrieved and analysed. More adverse metabolic profile was observed in PCOS patients with hyperandrogenic phenotypes in comparison to normoandrogenic patients, as well as in classic phenotypes, defined by National Institutes of Health criteria, in comparison to newer phenotypes introduced by the Rotterdam criteria. In the majority of observations, normoandrogenic PCOS patients did not differ significantly from controls in terms of metabolic characteristics, although some East Asian studies reported more adverse metabolic profile in normoandrogenic phenotype in comparison to healthy women. In conclusion, metabolic abnormalities in PCOS seem to be associated with joint effects of hyperandrogenism, insulin resistance and visceral obesity. The differences observed between the four phenotypes of PCOS underline the need for individualised diagnostic and therapeutic approach.

Natural Molecules in the Management of Polycystic Ovary Syndrome (PCOS): An Analytical Review

Polycystic ovary syndrome (PCOS) is a heterogenous disorder characterized by chronic ovulation dysfunction and hyperandrogenism. It is considered the most common endocrinological disorder, affecting up to 25% of women of reproductive age, and associated with long-term metabolic abnormalities predisposing to cardiovascular risk, such as insulin resistance (IR), dyslipidemia, endothelial dysfunction, and systemic inflammation. PCOS is also characterized by elevated serum levels of luteinizing hormone (LH), causing a condition of hyperandrogenism and a consequent altered ratio between LH and the follicle stimulating hormone (FSH). Over the years, several different approaches have been proposed to alleviate PCOS symptoms. Supplementation with natural molecules such as inositols, resveratrol, flavonoids and flavones, vitamin C, vitamin E and vitamin D, and omega-3 fatty acids may contribute to overcoming PCOS pathological features, including the presence of immature oocyte, IR, hyperandrogenism, oxidative stress and inflammation. This review provides a comprehensive overview of the current knowledge about the efficacy of natural molecule supplementation in the management of PCOS.

Divergences in Clinical, Anthropometric, Metabolic, and Hormonal Parameters among Different Phenotypes of Polycystic Ovary Syndrome Presenting at Endocrinology Outpatient Departments: A Multicenter Study from Bangladesh

Background

Polycystic ovary syndrome (PCOS) is a heterogeneous androgen-excess disorder. Data comparing the PCOS phenotypes in Bangladesh are scarce.

Objectives

The objective of this study was to find out the distribution of Rotterdam classified PCOS phenotypes and to compare the phenotypes concerning clinical, anthropometric, metabolic, and hormonal parameters.

Subjects and Methods

In this cross-sectional study, 370 PCOS cases in the age group of 20-45 years diagnosed by the Rotterdam consensus criteria were recruited from the endocrinology outpatient departments of several tertiary hospitals of Bangladesh. Metabolic syndrome (MetS) was diagnosed using the International Diabetes Federation criteria.

Results

The prevalence of phenotypes A, B, C, and D were 59.2%, 14.1%, 11.9%, and 14.9%, respectively. More than one-third (34.6%) of the women had pre-hypertension (pre-HTN)/hypertension (HTN), 34.1% had abnormal glucose intolerance (AGT), 93.0% had dyslipidemia, and 57.0% had MetS. The hyperandrogenic phenotypes (A, B, and C) had higher prevalence of pre-HTN/HTN, AGT, dyslipidemia, and MetS compared to the normoandrogenic phenotype D, though the differences were statistically insignificant. The clinical and biochemical markers of hyperandrogenism (Ferriman-Gallwey score, hirsutism, acne, and serum testosterone levels) did not differ among the hyperandrogenic phenotypes. The serum prolactin level was highest in phenotype C. No differences were observed in most other clinical, anthropometric, metabolic, and hormonal parameters among the four phenotypes.

Conclusion

Phenotype A is the most prevalent phenotype of PCOS in our setting. The prevalence of MetS was considerably high. Most of the clinical, anthropometric, and metabolic parameters were similar across the four PCOS phenotypes in this study.

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

Polycystic ovary syndrome is a complex endocrinopathy with heterogeneous presentation and multifactorial etiology. We have undertaken this case-control study to compare metabolic and endocrine characteristics in different phenotypic subgroups of women with PCOS and the impact of obesity on them. Women with PCOS (n = 489) were classified into 4 phenotypes according to Rotterdam criteria. Comparisons of clinical, biochemical and hormonal parameters were performed across all phenotypic groups of PCOS and with controls (n = 270) by Welch’s ANOVA with subsequent Games-Howell post-hoc test. We found maximum prevalence of normoandrogenic phenotype D, which is milder form of PCOS in terms of insulin resistance, gonadotropin levels and dyslipidemia, followed by phenotype A, in our total study population. After classification of the study group into lean and obese groups, only few insulin and lipid-related traits showed marked differences between phenotypes. Further, we noted that obese women showed adverse metabolic but not androgenic traits compared to lean counterparts in the same phenotype. Metabolic syndrome frequency is increased in hyperandrogenic phenotypes with HDL-C and waist circumference being most predominant contributing factors in total, lean and obese groups. We demonstrate that in our study population there is greater occurrence of phenotype D of PCOS. Our study highlights the importance of clinicians concurrently employing Rotterdam criteria along with obesity status for ascertaining accurate PCOS status and formulating suitable therapeutic intervention.

Prevalence of metabolic syndrome among women with different PCOS phenotypes - a prospective study

OBJECTIVE

To study prevalence of different polycystic ovary syndrome (PCOS) phenotypes in our population and to compare the anthropometric measurements and metabolic syndrome (MetS) risk factors among different phenotypes.

MATERIAL AND METHODS

Two hundred and forty-eight PCOS women were prospectively classified into four phenotypes based on Rotterdam criteria, over a period of 18 months from June 2018 to November 2019. MetS was defined as per International diabetes federation consensus held in 2009. To evaluate the prevalence of MetS, we measured serum triglyceride levels, HDL cholesterol, fasting blood glucose, blood pressure, and waist circumference.

RESULTS

The mean age group of the study population was 23.16 ± 4.42, with maximum cases belonging to 20-25 years age group (40.72%). The prevalence of Phenotypes A, B, C, and D were 36.7%, 10.1%, 4.4%, and 48.8%, respectively. Phenotype D had the highest prevalence of MetS (14.9%). Phenotype A had significantly higher waist circumference, hip circumference, cholesterol, triglycerides, and LDL values as compared to Phenotype D (p<.05).

CONCLUSIONS

Phenotype A was at higher risk of adverse MetS risk profile. The overall prevalence of MetS was quite low as compared to similar Indian studies. A substantial proportion of study cohort had higher waist circumference (almost 60%) and lower HDL levels (88.70% cases), hence all women with PCOS should be screened for metabolic profile risk factors at a young age itself.

Neck circumference is a good predictor for insulin resistance in women with polycystic ovary syndrome

OBJECTIVE

To assess the role of neck circumference (NC) in assessing insulin resistance (IR) in polycystic ovary syndrome (PCOS).

DESIGN

A cross-sectional study.

SETTING

University-affiliated hospital.

PATIENT(S)

One hundred forty-three women with PCOS were recruited from November 2018 to February 2020.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

The associations of NC with IR and the cutoff points of NC for IR.

RESULT(S)

The prevalence rates of IR were 64.3%. The patients with PCOS with IR had significantly greater values of systolic blood pressure, NC, body mass index, waist-to-hip ratio, waist circumference, fasting blood glucose, fasting insulin, and homeostasis model assessment of insulin resistance (HOMA-IR). Pearson correlation analysis showed body mass index (log-transformed), waist circumference, waist-to-hip ratio, and HOMA-IR (log-transformed) were positively correlated with NC. Multivariable linear regression showed that NC was significantly associated with HOMA-IR (log-transformed), with the standardized regression coefficient of 0.330 with adjustment for potential confounding factors. Furthermore, multivariate logistic regression analyses showed NC was associated significantly with increased risk of IR, with the adjusted odds ratio of 1.423. Additionally, NC was able to identify IR in women with PCOS; the optimal cut-off points was 34.3 cm (Youden index = 0.586).

CONCLUSION(S)

Neck circumference is positively associated with IR in women with PCOS. We suggest NC as a novel, simple, practical, and reliable anthropometric measure to be used to predict the risk of IR in patients with PCOS.

Epidemiology, pathogenesis, genetics & management of polycystic ovary syndrome in India

Polycystic ovary syndrome (PCOS) is a common endocrine disorder predominantly affecting women of reproductive age. Clinical manifestations are diverse including hyperandrogenism, anovulation, infertility and increased risk of metabolic diseases besides psychosocial dysfunction. This review provides information on the problem of PCOS in India, its pathophysiology, genetics and an overview of current management options to instigate further research in this field. Prevalence of PCOS in India ranges from 3.7 to 22.5 per cent depending on the population studied and the criteria used for diagnosis. Abnormalities in leptin-adiponectin (adipocyte biology), oxidative stress and autoimmunity are among the mechanisms studied regarding pathogenesis of PCOS. Many candidate gene studies have shown associations with PCOS in various studies. Studies have consistently demonstrated the relationship between the well-known manifestation of hyperandrogenism among Indian PCOS women and the metabolic morbidities including insulin resistance, glucose intolerance and cardiovascular risk. Management of individual components of PCOS can be achieved by medications or surgical methods, though further clarification regarding pathogenesis of PCOS is needed to sharpen our therapeutic armamentarium.

Prevalence of metabolic syndrome in four phenotypes of PCOS and its relationship with androgenic components among Iranian women: A cross-sectional study

BACKGROUND

Polycystic ovary syndrome (PCOS) increases the risk of metabolic syndrome (MetS). Insulin resistance (IR) plays a major role in the pathophysiology of both PCOS and MetS.

OBJECTIVE

This study was designed to compare the prevalence of MetS among different phenotypes of PCOS and its relationship with androgenic components.

MATERIALS AND METHODS

182 participants eligible for this five-group comparative study were selected by convenience sampling method. They were classified according to the Rotterdam criteria: clinical and/or biochemical hyperandrogenism (H) + PCOS on ultrasound (P) + ovulation disorders (O) (n = 41), clinical and/or biochemical H + PCOS on P (n = 33), PCOS on P + O (n = 40), clinical and/or biochemical H + O (n = 37), and control (without PCOS) (n = 31). MetS was measured based on the National Cholesterol Education Program Adult Treatment Panel III criteria. Androgenic components included free-androgen-index (FAI), total-testosterone (TT) level and sex-hormone-binding-globulin (SHBG).

RESULTS

A significant difference was observed between the study groups in terms of MetS prevalence (p = 0.01). In phenotype H+P+O, there was a statistically significant positive association between TG and TT, and a significant negative association between SBP and DBP with SHBG. In phenotype O+P, WC was inversely associated with SHBG. In phenotype H+O, FBS and TG were positively associated with FAI but HDL was inversely associated with FAI. Moreover, WC and DBP were positively associated with TT in phenotype H+O. No associations were detected between MetS parameters and androgenic components in other PCOS subjects (phenotype H+P) and in the control group. TT was significantly higher in the PCOS group suffering from MetS (p = 0.04).

CONCLUSION

According to the research results, hyperandrogenic components are potent predictors of metabolic disorders. Thus, we suggest that MetS screening is required for the prevention of MetS and its related complications in PCOS women.

Low intakes of dietary fiber and magnesium are associated with insulin resistance and hyperandrogenism in polycystic ovary syndrome: A cohort study

BACKGROUND

Women with polycystic ovary syndrome (PCOS) often have insulin resistance (IR) which may be worsened by obesity. The roles of dietary intake and activity are unclear. Our objectives were to determine whether (a) high caloric intake or inactivity explains obesity in PCOS, and (b) dietary composition is associated with PCOS phenotypes.

METHODS

Eighty-seven women with PCOS and 50 women without PCOS participated in this cohort study at a reproductive medicine center. Data collected included 3-day food and physical activity records, anthropometrics, and metabolic and hormonal assays.

RESULTS

Women with PCOS had increased body mass index (BMI) but similar caloric intake and activity to women without PCOS. There were no differences in protein, carbohydrates, fat, or glycemic load consumption, but women with PCOS consumed less fiber (medians: 19.6 vs. 24.7 g) and less magnesium (medians: 238.9 vs. 273.9 mg). In women with PCOS, those with IR consumed less fiber, less magnesium, and greater glycemic load than those without IR (medians: 18.2 vs. 22.1 g, 208.4 vs. 264.5 mg, 89.6 vs. 83.5). Fiber intake of women with PCOS was negatively correlated with IR, fasting insulin, glucose tolerance, testosterone, and dehydroepiandrosterone sulfate. Magnesium intake was negatively correlated with IR, C-reactive protein, and testosterone, but positively correlated with HDL cholesterol. Fiber intake and BMI accounted for 54.0% of the variance observed in IR.

CONCLUSIONS

Obesity in women with PCOS could not be explained by overeating or inactivity. Increasing dietary fiber and magnesium intakes may assist in reducing IR and hyperandrogenemia in women with PCOS.

Visceral Adiposity Index: Simple Tool for Assessing Cardiometabolic Risk in Women with Polycystic Ovary Syndrome

AIM

To study visceral adiposity index (VAI) and its association with cardiometabolic risk in different phenotypes of polycystic ovary syndrome (PCOS).

MATERIALS AND METHODS

It is a case-control cross-sectional study where 100 reproductive age (18-35 years) women with PCOS were classified in different phenotypes as per Rotterdam criteria and compared with age and Body mass index (BMI) matched 50 eumenorrheic and nonhirsute women. Various anthropometric, clinical, biochemical, and hormonal parameters were measured in both women with PCOS and controls. VAI was calculated using waist circumference (WC), BMI, serum triglyceride, and High density lipoprotein (HDL) cholesterol levels in all the subjects and compared between cases and controls. Subsequently, women with PCOS were assessed for cardiometabolic risk according to androgen excess society statement 2010 as "at risk" and "at high risk." Finally, risk was correlated with VAI for all the phenotypes of PCOS.

RESULTS

Mean VAI was significantly higher (P < 0.001) in cases than controls (2.07 vs. 1.27). Mean VAI in phenotype A (O+P+HA), B (O+HA), C (P+HA), and D (O+P) was 2.46, 2.48, 1.47, and 1.70, respectively. A total of 56% of women with PCOS were at risk and 12% at high risk for cardiometabolic disease. Metabolic syndrome was prevalent in 11% of cases and 1% had type 2 diabetes mellitus. Phenotypically, 88% of women with PCOS with phenotype A (O+P+HA), 67% of B (O+HA), 67% of C (P+HA), and 55% of D (O+P) were at increased risk. VAI was found to be positively correlated with WC (r, 0.550), waist to hip ratio (r, 0.295), Homeostasis model assessment of insulin resistance (HOMA IR) (r, 0.455), and cardiometabolic risk (r, 0.399). Also, it was the best factor associated with cardiometabolic risk (area under curve, 0.793).

CONCLUSION

This study concluded that visceral adiposity index can be used as simple and effective tool for assessing the cardiometabolic risk in women with PCOS as higher VAI values were observed in those cases who were at high risk for developing cardiometabolic disorder in future.

Cardiometabolic risks in PCOS: a review of the current state of knowledge

INTRODUCTION

Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting up to 18% women of reproductive age. It is associated with a range of metabolic, reproductive, and psychological features. Current evidence indicates a role of PCOS in the development of metabolic and increased cardiovascular risk factors (CVRF) with implications for compromised cardiovascular endpoint disease, which may have a considerable impact on health and health care costs.

AREAS COVERED

Existing studies examining long-term cardiometabolic health in PCOS are heterogeneous with inconsistent findings. In the current review, we aim to explore and critically review retrospective, prospective, meta-analysis and review articles relating to PCOS on cardiometabolic risk factors and clinical consequences to summarize the evidence, note evidence gaps, and suggest implications for future research.

EXPERT COMMENTARY

Although there is an established association between PCOS and metabolic health, implications on cardiac health are more uncertain with associations observed for CVRF and subclinical disease, yet limited and conflicting data on actual cardiovascular endpoints. There is a lack of population-based long-term studies examining cardiometabolic morbidity and mortality in PCOS with a need for further research to progress toward a better understanding of the long-term cardiometabolic impacts in women with PCOS.

Lean polycystic ovary syndrome (PCOS): an evidence-based practical approach

BACKGROUND

Polycystic ovary syndrome (PCOS) is a common endocrinopathy affecting women of reproductive age. Common features include menstrual irregularities, hyperandrogenism and polycystic ovarian morphology although the presentation can be heterogeneous. Insulin resistance is thought to be responsible for the hormonal and metabolic derangements observed. PCOS has two phenotypes, overweight/obese and lean, the latter being a much less common presentation of the syndrome.

AIMS

The aim of the present review is to summarise cardinal features, and to devise diagnostic and treatment algorithms for lean PCOS based on recent literature.

METHODS

We searched PubMed, EBSCOhost and Google Scholar using search terms such as 'lean polycystic ovary syndrome' OR 'lean polycystic ovarian syndrome' OR 'lean PCOS' OR 'lean polycystic ovary disease' OR 'lean polycystic ovarian disease' OR 'lean PCOD' OR 'hyperandrogenism' AND 'low BMI OR 'low body mass index' to identify potential articles to be included in the review. Citation searches were subsequently performed in order to find relevant literature.

RESULTS

Hormonal, metabolic and haematological profiles were altered in lean women with PCOS compared to healthy counterparts. However, the derangements were either comparable or less obvious compared to obese women with the syndrome. Insulin resistance seemed inherent in PCOS independent of obesity. Treatment options included weight maintenance, restoration of ovulation with insulin-sensitizers such as metformin, relief of symptoms such as hirsutism, acne and menstrual dysfunction, and assisted reproductive technologies in refractory cases, all of which showed promising results. The literature with evidence on lean PCOS is of low to moderate quality and there are still some uncertainties in the evidence base.

CONCLUSION

Carefully designed randomised controlled trials are required to confirm findings of previous studies in lean PCOS and to consolidate diagnostic and management algorithms proposed in this review. This paper will aid health professionals to improve their clinical approach in managing lean women with PCOS.

Reproductive health, obesity, and cardiometabolic risk factors among Samoan women

OBJECTIVES

Obesity leads to deleterious effects on not only cardiovascular health but also on the reproductive health of women. We estimate the prevalence of menstrual irregularity and of polycystic ovarian syndrome (PCOS) in Samoan women, among whom obesity prevalence is extremely high. We explore the association of these reproductive health conditions with adiposity, cardiometabolic risk factors, and androgen levels.

METHODS

A cross-sectional sample of Samoan women 25-39 years of age (n = 470) from a larger population-based genome-wide association study of adiposity and cardiometabolic disease was assessed for the prevalence of oligomenorrhea/amenorrhea (OM/AM) using a self-reported questionnaire. Serum androgens and anti-Müllerian hormone levels were assayed to determine hyperandrogenemia and presence of polycystic ovaries (PCO), respectively, using criterion values. PCOS was classified using NIH guidelines of having at least two of the three conditions: menstrual irregularity, hyperandrogenism, and PCO. We contrasted socio-demographic, reproductive health, and cardiometabolic risk factors between those with and without OM/AM and similarly for PCOS.

RESULTS

The prevalence of OM/AM was 7.4% (95% CI: 5.1, 9.8), and women with OM/AM had significantly higher central adiposity. PCOS was estimated at 6.8% (95% CI: 4.5, 9.1), and those with PCOS were younger but had higher overall and central adiposity measures, higher triglycerides, and higher prevalence of insulin resistance than women without PCOS.

CONCLUSIONS

The prevalence of menstrual irregularity and PCOS are less than hypothesized given the high levels of adiposity in this population. Nevertheless, Samoan women with menstrual irregularity and other features of PCOS have significantly poorer metabolic health.

Possible Link Between Stress-related Factors and Altered Body Composition in Women with Polycystic Ovarian Syndrome

Background

Stress is an invisible factor affecting modern day living and is strongly associated with many disease pathogenesis including polycystic ovarian syndrome (PCOS) in women. PCOS is the most frequent endocrinological disorder that affects women of reproductive age, leading to metabolic dysfunction and body composition alterations. Salivary amylase and cortisol are major stress mediators that have been implicated in PCOS. However, their role in altering body composition in PCOS is yet to be deciphered.

Aim

The present study aimed at understanding the relation between stress-associated factors and alterations in body composition among PCOS patients.

Design

This study enrolled a total of 100 patients (PCOS) and 60 age-matched controls. The female patients were of ages between 13 and 30 years.

Materials and Methods

Standard assay kits were used to evaluate the α-amylase activity and cortisol level in saliva. The participants were chosen on the basis of the Rotterdam American Society for Reproductive Medicine/European Society of Human Reproduction criteria. Saliva was collected from each participant as per the protocol of Salimetrics, USA.

Statistical Analysis

Statistical analysis was performed using SPSS version 20 for Windows. The quantitative variables are described as mean ± standard deviation. P < 0.05 was considered significant.

Results

Increased salivary cortisol level and α-amylase activity were seen in the PCOS population as compared to age-matched controls suggesting patients a sustained stress scenario in their system. Moreover, overweight PCOS participants reflected higher amylase activity than the lean patients participants. Pulse rate, body mass index (BMI), visceral adiposity, and waist-hip ratio (WHR) was considerably higher in the PCOS patients participants compared to controls. A significant correlation could be drawn between the α-amylase activity and BMI or WHR, respectively, among PCOS patients. These observations indicate a strong link between the stress marker and alterations in the body composition parameters of PCOS patients participants.

Conclusion

Higher prevalence of stress in PCOS patients participants has a critical role in their altered body composition.

Impaired branched-chain amino acid metabolism may underlie the nonalcoholic fatty liver disease-like pathology of neonatal testosterone-treated female rats

Polycystic ovary syndrome (PCOS) is frequently associated with non-alcoholic fatty liver disease (NAFLD), but the mechanisms involved in the development of NAFLD in PCOS are not well known. We investigated histological changes and metabolomic profile in the liver of rat models of PCOS phenotype induced by testosterone or estradiol. Two-day old female rats received sc injections of 1.25 mg testosterone propionate (Testos; n = 10), 0.5 mg estradiol benzoate (E2; n = 10), or vehicle (control group, CNT; n = 10). Animals were euthanized at 90-94 d of age and the liver was harvested for histological and metabolomic analyses. Findings showed only Testos group exhibited fatty liver morphology and higher levels of ketogenic and branched-chain amino acids (BCAA). Enrichment analysis showed effects of testosterone on BCAA degradation pathway and mitochondrial enzymes related to BCAA metabolism. Testos group also had a decreased liver fatty acid elongase 2 (ELOVL2) activity. E2 group had reduced lipid and acylcarnitine metabolites in the liver. Both groups had increased organic cation transporters (SLC22A4 and SLC16A9) activity. These findings indicate that neonatal testosterone treatment, but not estradiol, produces histological changes in female rat liver that mimic NAFLD with testosterone-treated rats showing impaired BCAA metabolism and dysfunctions in ELOVL2, SLC22A4 and SLC16A9 activity.

Correlations Between Anthropometry and Lipid Profile in Women With PCOS

BACKGROUND

Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in reproductive age women and is associated with both reproductive and metabolic abnormalities. Recent studies have demonstrated an early onset of abnormal cardiovascular risk profile in women with PCOS. Abnormal lipid profile patterns are common in women with PCOS, and these abnormalities are not uniform in all populations. Anthropometry is a simple and commonly used research tool for assessing metabolic risk in women with PCOS. Therefore, this study examined the correlations between anthropometric parameters and lipid profile in women with PCOS.

OBJECTIVES

The objectives of the study were (1) To study the anthropometric profile of women with PCOS, (2) To examine the lipid profile pattern of these women with PCOS and (3) To see whether there exists any correlation between these anthropometric parameters and lipid profile.

MATERIALS AND METHODS

This observational cross-sectional study examined anthropometry and lipid profile in 86 married women with PCOS in the age group of 18-35 years and correlated them by using Pearson's correlation coefficient.

RESULTS

More than 80% of the women with PCOS demonstrated abnormal anthropometric parameters, and in more than 70% women, lipid abnormalities such as low levels of high-density lipoprotein (HDL) cholesterol and high levels of triglycerides and low-density lipoprotein cholesterol were observed. Significant positive correlations were seen between body mass index (BMI) and triglycerides (P ≤ 0.001) and waist circumference (WC) and triglycerides (P ≤ 0.029). Negative correlations were observed between BMI and HDL cholesterol (P ≤ 0.013).

CONCLUSION

This study revealed that BMI and WC are the most important anthropometric parameters correlated to dyslipidemia in the south Indian women with PCOS.

Role of androgen ratios in the prediction of the metabolic phenotype in polycystic ovary syndrome

OBJECTIVE

To identify the androgen ratio that best predicts insulin resistance and metabolic syndrome among women with polycystic ovary syndrome (PCOS).

METHODS

Data for 180 women with PCOS and 180 healthy controls were extracted from two previous studies in Iran (conducted during 2008-2010 and 2011-2013). The diagnosis of PCOS was based on the Rotterdam criteria. The serum concentration of different androgens was measured. Receiver operating characteristic curve analysis was used to assess the ability of various androgen ratios to predict insulin resistance and metabolic syndrome.

RESULTS

Among women with PCOS, the testosterone-to-androstenedione ratio was the best predictor of insulin resistance (sensitivity 0.83, specificity 0.42) and metabolic syndrome (sensitivity 0.85, specificity 0.70). Among healthy controls, the ratio of free androgen index to testosterone was the best predictor of insulin resistance (sensitivity 0.84, specificity 0.33) and metabolic syndrome (sensitivity 0.91, specificity 0.17).

CONCLUSION

The prediction of insulin resistance and metabolic syndrome among women with PCOS was best accomplished with the testosterone-to-androstenedione ratio.

High-fat high-sugar diet induces polycystic ovary syndrome in a rodent model

Obesity has been linked with a host of metabolic and reproductive disorders including polycystic ovary syndrome (PCOS). While a clear association exists between obesity and PCOS, the exact nature of this relationship remains unexplained. The primary symptoms of PCOS include hyperandrogenism, anovulation, and polycystic ovaries. Most animal models utilize androgen treatments to induce PCOS. However, these models often fail to address the underlying causes of the disease and do not effectively reproduce key metabolic features such as hyperinsulinemia. Here, we present a novel rodent model of diet-induced obesity that recapitulates both the metabolic and reproductive phenotypes of human PCOS. Rats on a high-fat high-sugar (HFHS) diet not only demonstrated signs of metabolic impairment, but they also developed polycystic ovaries and experienced irregular estrous cycling. Though hyperandrogenism was not characteristic of HFHS animals as a group, elevated testosterone levels were predictive of high numbers of ovarian cysts. Alterations in steroidogenesis and folliculogenesis gene expression were also found via RNA sequencing of ovarian tissue. Importantly, the PCOS-like symptoms induced in these rats may share a similar etiology to PCOS in humans. Therefore, this model offers a unique opportunity to study PCOS at its genesis rather than following the development of disease symptoms.

Endocrine and Metabolic Profile of Different Phenotypes of Polycystic Ovarian Syndrome

BACKGROUND

Polycystic ovarian syndrome (PCOS) is a common endocrinopathy associated with wide heterogeneity and serious clinical implications. Prevalence and characteristics of different phenotypes are not well defined. Therefore, this study was planned to determine the prevalence of four phenotypes of PCOS and to evaluate their endocrine and metabolic parameters including insulin resistance and metabolic syndrome with respect to controls.

METHODS

This observational, case-control study was conducted in the gynecology outpatient department of a tertiary care center where 161 PCOS and 50 non-PCOS women were recruited and investigated.

RESULTS

All phenotypes of PCOS had higher BMI with respect to controls (P < 0.000). Overweight women were maximum in phenotype H + O followed by phenotype H + P. Significantly higher levels of luteinizing hormone (P < 0.01), testosterone (P < 0.0001), were observed in all phenotypes of PCOS as compared to controls. Serum cholesterol (P < 0.026) and triglycerides (P < 0.05) were significantly higher in all PCOS phenotypes compared to controls. Levels of fasting (P < 0.000) and post-prandial (P < 0.009) insulin were significantly higher in all phenotypes of PCOS with respect to controls. Mean insulin resistance (IR) was 24.09 % in PCOS and 2 % in controls, prevalence being highest in H + O phenotype followed by H + O + P. Prevalence of metabolic syndrome in women with PCOS was 36.02 %, being highest in H + O + P followed by H + O and that of control was 10 %.

CONCLUSION

All phenotypes of PCOS had deranged endocrine and metabolic profile compared to controls, but prevalence of IR and metabolic syndrome was maximum in hyperandrogenic phenotypes which require a strict surveillance for prospective metabolic disorders as compared to O + P phenotype.

Association of serum glypican-4 levels with cardiovascular risk predictors in women with polycystic ovary syndrome - a pilot study

OBJECTIVE

Glypican-4 (Gpc4) is an adipokine which interacts with the insulin receptor and affects insulin sensitivity in proteoglycans. Insulin resistance plays a crucial role in the etiology of polycystic ovary syndrome (PCOS). PCOS is associated with metabolic disturbances such as abdominal obesity, dyslipidemia and type 2 diabetes. Thus, higher levels of Gpc4 released from visceral adipose tissue in women with PCOS may suggest an increased risk of cardiovascular disease (CVD).

DESIGN

The aim of this pilot study was to determine whether the serum Gpc4 level is associated with cardiovascular risk predictors in women with PCOS.

METHODS

Sixty-two women with PCOS according to the Rotterdam criteria (20-35 years old) and 43 healthy controls were studied. Cardiovascular risk predictors such as obesity indices, fat deposits according to dual-energy X-ray absorptiometry, biochemical lipid profile parameters and Homeostasis Model Assessment were estimated.

RESULTS

The serum Gpc4 level in PCOS women was significantly higher (2.61 ± 1.17 ng/ml) than in the control group (1.55 ± 0.47 ng/ml) and correlated with waist circumference, waist-to-hip ratio, total fat and android fat deposit to gynoid fat deposit ratio only in the PCOS group.

CONCLUSION

The Gpc4 level was higher in the PCOS group and correlated with CVD risk predictors, especially fat distribution.

Clomiphene citrate, metformin or a combination of both as the first line ovulation induction drug for Asian Indian women with polycystic ovarian syndrome: A randomized controlled trial

AIM

To compare clomiphene citrate (CC), metformin or the combination of CC and metformin as the first line ovulation induction drug in Asian Indian women with polycystic ovary syndrome (PCOS).

METHODS

One hundred and five newly diagnosed, treatment naive PCOS women were recruited. They were randomized into any of the three groups: Group I (CC 50-150 mg/day), Group II (metformin 1700 mg/day), and Group III (CC + metformin in similar dosage to Groups I and II). Patients underwent follicular monitoring and advice on timed intercourse. The study period was 6 months, or till pregnant, or till CC resistant. Primary outcome studied was live birth rate (LBR). Secondary outcomes were ovulation rate, pregnancy rate, and early pregnancy loss rate.

RESULTS

There was no significant difference among the groups in baseline characteristics and biochemical parameters. LBR was 41.6%, 37.5%, and 28.1%, respectively in Groups III, II, and I. Group III (CC + metformin) had the highest ovulation (83.3%), pregnancy (50%), and LBRs (41.6%). Group II (metformin) was as good as Group I (CC) in all the outcomes. CC + metformin (Group III) had statistically significantly higher ovulation rate as compared to CC alone (Group I) (P = 0.03; odds ratio: 95% confidence interval: 3.888 [1.08-13.997]).

CONCLUSION

Thus, our study shows that metformin was as good as CC in terms of "LBR" and the combination of CC and metformin gave the highest ovulation and LBR.

Infertility etiologies are genetically and clinically linked with other diseases in single meta-diseases

The present review aims to ascertain whether different infertility etiologies share particular genes and/or molecular pathways with other pathologies and are associated with distinct and particular risks of later-life morbidity and mortality. In order to reach this aim, we use two different sources of information: (1) a public web server named DiseaseConnect ( http://disease-connect.org ) focused on the analysis of common genes and molecular mechanisms shared by diseases by integrating comprehensive omics and literature data; and (2) a literature search directed to find clinical comorbid relationships of infertility etiologies with only those diseases appearing after infertility is manifested. This literature search is performed because DiseaseConnect web server does not discriminate between pathologies emerging before, concomitantly or after infertility is manifested. Data show that different infertility etiologies not only share particular genes and/or molecular pathways with other pathologies but they have distinct clinical relationships with other diseases appearing after infertility is manifested. In particular, (1) testicular and high-grade prostate cancer in male infertility; (2) non-fatal stroke and endometrial cancer, and likely non-fatal coronary heart disease and ovarian cancer in polycystic ovary syndrome; (3) osteoporosis, psychosexual dysfunction, mood disorders and dementia in premature ovarian failure; (4) breast and ovarian cancer in carriers of BRCA1/2 mutations in diminished ovarian reserve; (5) clear cell and endometrioid histologic subtypes of invasive ovarian cancer, and likely low-grade serous invasive ovarian cancer, melanoma and non-Hodgkin lymphoma in endometriosis; and (6) endometrial and ovarian cancer in idiopathic infertility. The present data endorse the principle that the occurrence of a disease (in our case infertility) is non-random in the population and suggest that different infertility etiologies are genetically and clinically linked with other diseases in single meta-diseases. This finding opens new insights for clinicians and reproductive biologists to treat infertility problems using a phenomic approach instead of considering infertility as an isolated and exclusive disease of the reproductive system/hypothalamic-pituitary-gonadal axis. In agreement with a previous validation analysis of the utility of DiseaseConnect web server, the present study does not show a univocal correspondence between common gene expression and clinical comorbid relationship. Further work is needed to untangle the potential genetic, epigenetic and phenotypic relationships that may be present among different infertility etiologies, morbid conditions and physical/cognitive traits.