Body Mass Index and Polycystic Ovary Syndrome: A 2-Sample Bidirectional Mendelian Randomization Study

Effects of weight loss intervention on anxiety, depression and quality of life in women with severe obesity and polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women that is associated with an increased risk of anxiety and depression and with a lower health-related quality of life (HRQoL). PCOS is closely associated with obesity, which per se can lead to symptoms of anxiety and depression and lower HRQoL. The first-line treatment for PCOS is weight loss through lifestyle intervention, which has been shown to improve all symptoms of the syndrome. The aim of this study was to investigate symptoms of anxiety and depression and HRQoL in women with severe obesity (BMI ≥ 35) with and without PCOS, and to evaluate the effect of a one-year structured weight loss intervention. A total of 246 women with severe obesity (PCOS n = 63, non-PCOS n = 183) were included. The comprehensive psychopathological rating scale self-rating scale for affective symptoms (CPRS-S-A) and the short form-36 (SF-36) were used to assess symptoms of anxiety and depression and HRQoL. In total 72 women of the 246 women with severe obesity completed a one-year weight loss programme and were followed up and compared with baseline data. In women with severe obesity, there were no differences in symptoms of anxiety and depression and HRQoL between women with and without PCOS at baseline. Clinically relevant anxiety symptoms were present in 71.3% (PCOS) and 65.6% (non-PCOS), and depression symptoms were present in 56.4% (PCOS) and 52.2% (non-PCOS). Significant weight loss improved physical HRQoL in all women, but reduced symptoms of anxiety and depression only in women without PCOS. There were no differences when comparing the changes between the groups. Women with severe obesity are severely affected by symptoms of anxiety and depression, independent of PCOS. Weight loss improved symptoms of anxiety and depression in women without PCOS, but there were no differences between groups in change from baseline to follow-up.Trial registration number: Clinical trial.gov: NCT01319162, March 18, 2011. Date of registration and enrolment of the first subject September 2011.

Causal relationships between modifiable risk factors and polycystic ovary syndrome: a comprehensive Mendelian randomization study

Background

Polycystic Ovary Syndrome (PCOS) is a heritable condition with an as yet unclear etiology. Various factors, such as genetics, lifestyle, environment, inflammation, insulin resistance, hyperandrogenism, iron metabolism, and gut microbiota, have been proposed as potential contributors to PCOS. Nevertheless, a systematic assessment of modifiable risk factors and their causal effects on PCOS is lacking. This study aims to establish a comprehensive profile of modifiable risk factors for PCOS by utilizing a two-sample Mendelian Randomization (MR) framework.

Methods

After identifying over 400 modifiable risk factors, we employed a two-sample MR approach, including the Inverse Variance Weighted (IVW) method, Weighted Median method, and MR-Egger, to investigate their causal associations with PCOS. The reliability of our estimates underwent rigorous examination through sensitivity analyses, encompassing Cochran's Q test, MR-Egger intercept analysis, leave-one-out analysis, and funnel plots.

Results

We discovered that factors such as smoking per day, smoking initiation, body mass index, basal metabolic rate, waist-to-hip ratio, whole body fat mass, trunk fat mass, overall health rating, docosahexaenoic acid (DHA) (22:6n-3) in blood, monounsaturated fatty acids, other polyunsaturated fatty acids apart from 18:2 in blood, omega-3 fatty acids, ratio of bisallylic groups to double bonds, omega-9 and saturated fatty acids, total lipids in medium VLDL, phospholipids in medium VLDL, phospholipids in very large HDL, triglycerides in very large HDL, the genus Oscillibacter, the genus Alistipes, the genus Ruminiclostridium 9, the class Mollicutes, and the phylum Tenericutes, showed a significant effect on heightening genetic susceptibility of PCOS. In contrast, factors including fasting insulin interaction with body mass index, sex hormone-binding globulin, iron, ferritin, SDF1a, college or university degree, years of schooling, household income, the genus Enterorhabdus, the family Bifidobacteriaceae, the order Bifidobacteriales, the class Actinobacteria, and the phylum Actinobacteria were determined to reduce risk of PCOS.

Conclusion

This study innovatively employs the MR method to assess causal relationships between 400 modifiable risk factors and the susceptibility of PCOS risk. It supports causal links between factors like smoking, BMI, and various blood lipid levels and PCOS. These findings offer novel insights into potential strategies for the management and treatment of PCOS.

Polycystic ovary syndrome

Despite affecting ~11-13% of women globally, polycystic ovary syndrome (PCOS) is a substantially understudied condition. PCOS, possibly extending to men's health, imposes a considerable health and economic burden worldwide. Diagnosis in adults follows the International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome, requiring two out of three criteria - clinical or biochemical hyperandrogenism, ovulatory dysfunction, and/or specific ovarian morphological characteristics or elevated anti-Müllerian hormone. However, diagnosing adolescents omits ovarian morphology and anti-Müllerian hormone considerations. PCOS, marked by insulin resistance and hyperandrogenism, strongly contributes to early-onset type 2 diabetes, with increased odds for cardiovascular diseases. Reproduction-related implications include irregular menstrual cycles, anovulatory infertility, heightened risks of pregnancy complications and endometrial cancer. Beyond physiological manifestations, PCOS is associated with anxiety, depression, eating disorders, psychosexual dysfunction and negative body image, collectively contributing to diminished health-related quality of life in patients. Despite its high prevalence persisting into menopause, diagnosing PCOS often involves extended timelines and multiple health-care visits. Treatment remains ad hoc owing to limited understanding of underlying mechanisms, highlighting the need for research delineating the aetiology and pathophysiology of the syndrome. Identifying factors contributing to PCOS will pave the way for personalized medicine approaches. Additionally, exploring novel biomarkers, refining diagnostic criteria and advancing treatment modalities will be crucial in enhancing the precision and efficacy of interventions that will positively impact the lives of patients.

Neck Circumference in Polycystic Ovary Syndrome: A Systematic Review and Bootstrapped Meta-Analysis with GRADE Approach

INTRODUCTION

Our aim was to perform a systematic review and meta-analysis for the association of neck circumference (NC) in polycystic ovary syndrome (PCOS) patients as compared to non-PCOS controls.

METHODS

Primarily the PubMed/MEDLINE database and others such as SCOPUS, Google Scholar, Cochrane Library, were searched up to November 15, 2023 for observational studies comparing NC in PCOS versus non-PCOS women. The mean and SD values of NC and other covariates in PCOS and control groups were extracted by two independent reviewers, and the quality and risk of bias assessment was done using Newcastle-Ottawa Scale. The meta-analysis employed combined standardized mean differences (SMD) with 95% confidence intervals (CI) to compare NC between PCOS patients and controls. The heterogeneity and validity were addressed by subgroup, meta-regression, and sensitivity analyses. We conducted a Bootstrapped meta-analysis using 1,000 and 10,000 simulations to test the accuracy of the obtained results. The certainty of evidence was assessed by the GRADE approach.

RESULTS

Our meta-analysis included 9 observational studies. The PCOS patients showed significantly higher NC values than the non-PCOS controls (SMD: 0.66, 95% CI: 0.41-0.91, p < 0.0001). In the bootstrap meta-analysis, the accuracy of the observed findings was proved (SMD = 0.66, 95% CI = 0.42-0.91) for the NC outcome. No publication bias was detected in the funnel plot analysis using Begg's and Egger's tests. The 95% prediction interval of 0.036-1.28 suggests that the true outcomes of the studies are generally in the same direction as the estimated average outcome. The sensitivity analysis provided the robustness of the outcome, and no single study was overly influential on the pooled estimate.

CONCLUSION

This meta-analysis provides accurate evidence for significantly higher NC values in PCOS as compared to non-PCOS controls. There is no sufficient evidence on the diagnostic accuracy measures for NC in PCOS. Hence, further research on its diagnostic utility in PCOS is needed.

Distinct Reproductive Phenotypes Segregate With Differences in Body Weight in Adolescent Polycystic Ovary Syndrome

Introduction

Polycystic ovary syndrome (PCOS) is a heterogenous clinical syndrome defined by hyperandrogenism and irregular menses. In adult women with PCOS, discrete metabolic and reproductive subgroups have been identified. We hypothesize that distinct phenotypes can be distinguished between adolescent girls who are lean (LN-G) and girls with obesity (OB-G) at the time of PCOS diagnosis.

Methods

Data were extracted from the CALICO multisite PCOS database. Clinical data collected at the time of diagnosis were available in 354 patients (81% with obesity) from 7 academic centers. Patients with body mass index (BMI) < 85th percentile for age and sex were characterized as lean (LN-G) and those with BMI percentile ≥ 95th percentile as obese (OB-G). We compared metabolic and reproductive phenotypes in LN-G and OB-G.

Results

Reproductive phenotypes differed between the groups, with LN-G having higher total testosterone, androstenedione, and LH levels, while OB-G had lower sex hormone binding globulin (SHBG) and higher free testosterone. Metabolic profiles differed as expected, with OB-G having higher hemoglobin A1c, alanine aminotransferase, and serum triglycerides and more severe acanthosis nigricans.

Conclusion

LN-G with PCOS had a distinct reproductive phenotype characterized by increased LH, total testosterone, and androstenedione levels, suggesting neuroendocrine-mediated ovarian androgen production. In contrast, phenotypes in OB-G suggest hyperandrogenemia is primarily driven by insulin resistance with low SHBG levels. These observations support the existence of distinct metabolic and reproductive subtypes in adolescent PCOS characterized by unique mechanisms for hyperandrogenemia.

Proteomic analysis shows decreased type I fibers and ectopic fat accumulation in skeletal muscle from women with PCOS

Background

Polycystic ovary syndrome's (PCOS) main feature is hyperandrogenism, which is linked to a higher risk of metabolic disorders. Gene expression analyses in adipose tissue and skeletal muscle reveal dysregulated metabolic pathways in women with PCOS, but these differences do not necessarily lead to changes in protein levels and biological function.

Methods

To advance our understanding of the molecular alterations in PCOS, we performed global proteomic and phosphorylation site analysis using tandem mass spectrometry, and analyzed gene expression and methylation. Adipose tissue and skeletal muscle were collected at baseline from 10 women with and without PCOS, and in women with PCOS after 5 weeks of treatment with electrical stimulation.

Results

Perilipin-1, a protein that typically coats the surface of lipid droplets in adipocytes, was increased whereas proteins involved in muscle contraction and type I muscle fiber function were downregulated in PCOS muscle. Proteins in the thick and thin filaments had many altered phosphorylation sites, indicating differences in protein activity and function. A mouse model was used to corroborate that androgen exposure leads to a shift in muscle fiber type in controls but not in skeletal muscle-specific androgen receptor knockout mice. The upregulated proteins in muscle post treatment were enriched in pathways involved in extracellular matrix organization and wound healing, which may reflect a protective adaptation to repeated contractions and tissue damage due to needling. A similar, albeit less pronounced, upregulation in extracellular matrix organization pathways was also seen in adipose tissue.

Conclusions

Our results suggest that hyperandrogenic women with PCOS have higher levels of extra-myocellular lipids and fewer oxidative insulin-sensitive type I muscle fibers. These could be key factors leading to insulin resistance in PCOS muscle while electric stimulation-induced tissue remodeling may be protective.

Funding

Swedish Research Council (2020-02485, 2022-00550, 2020-01463), Novo Nordisk Foundation (NNF22OC0072904), and IngaBritt and Arne Lundberg Foundation. Clinical trial number NTC01457209.

Inflammation mediates the effect of adiposity and lipid metabolism indicators on the embryogenesis of PCOS women undergoing in vitro fertilization/intracytoplasmic sperm injection

Background

Polycystic ovary syndrome (PCOS) is a complex reproductive endocrine and metabolic disease affecting women of reproductive age. The low-grade chronic inflammation in PCOS is considered to be associated with obesity and dyslipidemia. We aim to investigate the potential mediating role of white blood cell (WBC) count, a representative inflammatory marker, in the effect of adiposity and lipid metabolism indicators on IVF/ICSI outcomes in PCOS women.

Methods

We conducted a retrospective cohort study of 1,534 PCOS women who underwent their first IVF/ICSI cycles with autologous oocytes at a reproductive center from January 2018 to December 2020. The associations between PCOS women's adiposity and lipid metabolism indicators and WBC count and IVF/ICSI outcomes were examined using multivariable generalized linear models. Mediation analyses were conducted to evaluate the possible mediating role of WBC count.

Results

We found significant dose-dependent correlations between adiposity and lipid metabolism indicators and IVF/ICSI outcomes (i.e., hormone levels on the ovulatory triggering day, oocyte development outcomes, fertilization, early embryo development outcomes, and pregnancy outcomes) (all p < 0.05), as well as between adiposity and lipid metabolism indicators and WBC count (all p < 0.001). Increasing WBC count was associated with adverse oocyte and embryonic development outcomes (all p < 0.05). Mediation analyses suggested that increasing serum TG and LDL-C levels and decreasing serum HDL-C level were significantly associated with reduced high-quality Day 3 embryo count in PCOS women, with 21.51%, 9.75%, and 14.10% mediated by WBC count, respectively (all p < 0.05).

Conclusions

We observed significant associations between lipid metabolism indicators and high-quality Day 3 embryo count in PCOS women, partially mediated by inflammation-related mechanisms, suggesting the potential intervention target for improving embryo quality in PCOS women.

Adiposity and lipid metabolism indicators mediate the adverse effect of glucose metabolism indicators on oogenesis and embryogenesis in PCOS women undergoing IVF/ICSI cycles

BACKGROUND

Polycystic ovary syndrome (PCOS) women have high incidences of dyslipidemia, obesity, impaired glucose tolerance (IGT), diabetes, and insulin resistance (IR) and are fragile to female infertility. Obesity and dyslipidemia may be the intermediate biological mechanism for the associations between glucose metabolism dysfunction and abnormal oogenesis and embryogenesis.

METHODS

This retrospective cohort study was performed at a university-affiliated reproductive center. A total of 917 PCOS women aged between 20 and 45 undergoing their first IVF/ICSI embryo transfer cycles from January 2018 to December 2020 were involved. Associations between glucose metabolism indicators, adiposity and lipid metabolism indicators, and IVF/ICSI outcomes were explored using multivariable generalized linear models. Mediation analyses were further performed to examine the potential mediation role of adiposity and lipid metabolism indicators.

RESULTS

Significant dose-dependent relationships were found between glucose metabolism indicators and IVF/ICSI early reproductive outcomes and between glucose metabolism indicators and adiposity and lipid metabolism indicators (all P < 0.05). Also, we found significant dose-dependent relationships between adiposity and lipid metabolism indicators and IVF/ICSI early reproductive outcomes (all P < 0.05). The mediation analysis indicated that elevated FPG, 2hPG, FPI, 2hPI, HbA1c, and HOMA2-IR were significantly associated with decreased retrieved oocyte count, MII oocyte count, normally fertilized zygote count, normally cleaved embryo count, high-quality embryo count, or blastocyst formation count after controlling for adiposity and lipid metabolism indicators. Serum TG mediated 6.0-31.0% of the associations; serum TC mediated 6.1-10.8% of the associations; serum HDL-C mediated 9.4-43.6% of the associations; serum LDL-C mediated 4.2-18.2% of the associations; and BMI mediated 26.7-97.7% of the associations.

CONCLUSIONS

Adiposity and lipid metabolism indicators (i.e., serum TG, serum TC, serum HDL-C, serum LDL-C, and BMI) are significant mediators of the effect of glucose metabolism indicators on IVF/ICSI early reproductive outcomes in PCOS women, indicating the importance of preconception glucose and lipid management and the dynamic equilibrium of glucose and lipid metabolism in PCOS women.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

Long-term health outcomes in young women with polycystic ovary syndrome: A narrative review

Polycystic ovary syndrome (PCOS) has long been recognized as a common disorder in young women leading to reproductive and cutaneous sequelae. However, the associated health risks are now known to extend beyond these familiar manifestations to a range of longer-term comorbidities. Here we review the evidence for an association of PCOS with adverse long-term health outcomes, discussing the pathophysiological mechanisms involved in addition to opportunities for therapeutic intervention. Cross-sectional and longitudinal studies point to an increased risk of type 2 diabetes, hypertension and dyslipidaemia, with recent data confirming that these translate to an increased risk of cardiovascular events independently of obesity. Obstructive sleep apnoea, nonalcoholic fatty liver disease and endometrial cancer are also more prevalent, while mental health disorders, notably anxiety and depression, are common but under-appreciated associations. Uncertainties remain as to whether these risks are apparent in all patients with PCOS or are confined to particular subtypes, whether risks persist post-menopausally and how risk may be affected by ethnicity. Further work is also needed in establishing if systematic screening and targeted intervention can lead to improved outcomes. Until such data are available, clinicians managing women with PCOS should counsel patients on long-term health risks and invest in strategies that limit progression to metabolic and non-metabolic morbidities.

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 Mass Index and Risk of Diabetic Nephropathy: A Mendelian Randomization Study

CONTEXT

The associations of obesity and diabetic nephropathy (DN) in type 2 diabetes are inconsistent in observational studies, and causality remains unclear.

OBJECTIVE

To explore the causal effect of body mass index (BMI) on DN, estimated glomerular filtration rate (eGFR), and proteinuria in type 2 diabetes by a 2-sample Mendelian randomization (MR) analysis.

METHODS

A total of 56 genetic variants were selected as instrumental variables for BMI in 158 284 participants from BioBank Japan, and their effects on DN risk, eGFR, and proteinuria were estimated in 3972 individuals with type 2 diabetes. Then, sex-stratified MR analysis was performed between BMI and DN. We selected generalized summary MR analysis as the primary method and 6 other robust methods to test MR assumptions.

RESULTS

One SD increase in BMI was causally associated with higher DN risk [odds ratio (OR) 3.76, 95% CI 1.88-7.53, P < 0.001] and lower eGFR level (OR 0.71, 95% CI 0.59-0.86, P < 0.001). However, BMI was not causally associated with proteinuria (P = 0.22). Sex-stratified analyses indicated the causal effect of BMI on DN was stronger in women (OR 14.81, 95% CI 2.67-82.05, P = 0.002) than in men (OR 3.48, 95% CI 1.18-10.27, P = 0.02). Sensitivity analyses did not show evidence for violation of the MR assumptions.

CONCLUSIONS

Genetic evidence showed that higher BMI levels were causally associated with increased risk of DN and decreased eGFR levels. Moreover, the increase in BMI level had a greater impact on DN risk in women.

Polycystic ovary syndrome: a "risk-enhancing" factor for cardiovascular disease

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women of reproductive age and is hallmarked by hyperandrogenism, oligo-ovulation, and polycystic ovarian morphology. Polycystic ovary syndrome, particularly the hyperandrogenism phenotype, is associated with several cardiometabolic abnormalities, including obesity, dyslipidemia, elevated blood pressure, and prediabetes or type 2 diabetes. Many, but not all, studies have suggested that PCOS is associated with increased risk of cardiovascular disease (CVD), including coronary heart disease and stroke, independent of body mass index and traditional risk factors. Interpretation of the data from these observational studies is limited by the varying definitions and ascertainment of PCOS and CVD across studies. Recent Mendelian randomization studies have challenged the causality of PCOS with coronary heart disease and stroke. Future longitudinal studies with clearly defined PCOS criteria and newer genetic methodologies may help to determine association and causality. Nevertheless, CVD risk screening remains critical in this patient population, as improvements in metabolic profile and reduction in CVD risk are achievable with a combination of lifestyle management and pharmacotherapy. Statin therapy should be implemented in women with PCOS who have elevated atherosclerotic CVD risk. If CVD risk is uncertain, measurement of subclinical atherosclerosis (carotid plaque or coronary artery calcium) may be a useful tool to guide shared decision-making about initiation of statin therapy. Other medications, such as metformin and glucagon-like peptide-1 receptor agonists, also may be useful in reducing CVD risk in insulin-resistant populations. Additional research is needed to determine the best pathways to mitigate PCOS-associated CVD risk.

Causal relationship between polycystic ovary syndrome and coronary artery disease: A Mendelian randomisation study

OBJECTIVE

Polycystic ovary syndrome (PCOS) has been associated with an increased risk of coronary artery disease (CAD). However, it remains uncertain whether this increased risk is the result of PCOS per se or, alternatively, is explained by obesity, a common feature of PCOS. The aim of this study was to assess the causal association between PCOS and CAD and the role of obesity herein.

DESIGN AND METHODS

We conducted two-sample Mendelian randomisation analyses in large-scale, female-specific datasets to study the association between genetically predicted (1) risk of PCOS and risk of CAD, (2) body mass index (BMI) and risk of PCOS and (3) BMI and risk of CAD. Primary analyses were conducted with the inverse-variance weighted (IVW) method. Simple median, penalized weighted median and contamination mixture analyses were performed to assess the robustness of the outcomes.

RESULTS

IVW analyses did not show a statistically significant association between PCOS and CAD (odds ratio [OR]: 0.99, 95% confidence interval [CI]: 0.89, 1.11). In contrast, genetically predicted BMI was statistically significantly associated with an increased odds of PCOS (OR: 3.21, 95% CI: 2.26, 4.56) and CAD (OR: 1.38, 95% CI: 1.14, 1.67). Similar results were obtained when secondary analyses were performed.

CONCLUSION

These sex-specific analyses show that the genetically predicted risk of PCOS is not associated with the risk of CAD. Instead, the genetically predicted risk of obesity (and its downstream metabolic effects) is the common denominator of both PCOS and CAD risk.

Experimentally Induced Hyperinsulinemia Fails to Induce Polycystic Ovary Syndrome-like Traits in Female Rhesus Macaques

As in women with polycystic ovary syndrome (PCOS), hyperinsulinemia is associated with anovulation in PCOS-like female rhesus monkeys. Insulin sensitizers ameliorate hyperinsulinemia and stimulate ovulatory menstrual cycles in PCOS-like monkeys. To determine whether hyperinsulinemia (>694 pmol/L), alone, induces PCOS-like traits, five PCOS-like female rhesus monkeys with minimal PCOS-like traits, and four control females of similar mid-to-late reproductive years and body mass index, received daily subcutaneous injections of recombinant human insulin or diluent for 6−7 months. A cross-over experimental design enabled use of the same monkeys in each treatment phase. Insulin treatment unexpectedly normalized follicular phase duration in PCOS-like, but not control, females. In response to an intramuscular injection of 200 IU hCG, neither prenatally androgenized nor control females demonstrated ovarian hyperandrogenic responses while receiving insulin. An intravenous GnRH (100 ng/kg) injection also did not reveal evidence of hypergonadotropism. Taken together, these results suggest that experimentally induced adult hyperinsulinemia, alone, is insufficient to induce PCOS-like traits in female rhesus monkeys and to amplify intrinsic PCOS-like pathophysiology.

Causes and Consequences of Polycystic Ovary Syndrome: Insights From Mendelian Randomization

CONTEXT

Although polycystic ovary syndrome (PCOS) is the most common endocrinopathy affecting women of reproductive age, risk factors that may cause the syndrome are poorly understood. Based on epidemiologic studies, PCOS is thought to cause several adverse outcomes such as cardiovascular disease; however, the common presence of comorbidities such as obesity may be responsible for such associations, rather than PCOS in and of itself. To overcome the limitations of observational studies, investigators have employed Mendelian randomization (MR), which uses genetic variants to interrogate causality between exposures and outcomes.

EVIDENCE ACQUISITION

To clarify causes and consequences of PCOS, this review will describe MR studies involving PCOS, both as an exposure and as an outcome. The literature was searched using the terms "Mendelian randomization," "polycystic ovary syndrome," "polycystic ovarian syndrome," and "PCOS" (to May 2021).

EVIDENCE SYNTHESIS

MR studies have suggested that obesity, testosterone levels, fasting insulin, serum sex hormone-binding globulin concentrations, menopause timing, male-pattern balding, and depression may play a causal role in PCOS. In turn, PCOS may increase the risk of estrogen receptor-positive breast cancer, decrease the risk of endometrioid ovarian cancer, and have no direct causal effect on type 2 diabetes, coronary heart disease, or stroke.

CONCLUSIONS

The accumulation of genome-wide association studies in PCOS has enabled multiple MR analyses identifying factors that may cause PCOS or be caused by PCOS. This knowledge will be critical to future development of measures to prevent PCOS in girls at risk as well as prevent complications in those who have PCOS.

Genomic correlation, shared loci, and causal relationship between obesity and polycystic ovary syndrome: a large-scale genome-wide cross-trait analysis

BACKGROUND

The comorbidity between polycystic ovary syndrome (PCOS) and obesity has long been observed in clinical settings, but their shared genetic basis remains unclear.

METHODS

Leveraging summary statistics of large-scale GWAS(s) conducted in European-ancestry populations on body mass index (adult BMI, Nfemale=434,794; childhood BMI, N=39,620), waist-to-hip ratio (WHR, Nfemale=381,152), WHR adjusted for BMI (WHRadjBMI, Nfemale=379,501), and PCOS (Ncase=10,074, Ncontrol=103,164), we performed a large-scale genome-wide cross-trait analysis to quantify overall and local genetic correlation, to identify shared loci, and to infer causal relationship.

RESULTS

We found positive genetic correlations between PCOS and adult BMI (rg=0.47, P=2.19×10-16), childhood BMI (rg=0.31, P=6.72×10-5), and WHR (rg=0.32, P=1.34×10-10), all withstanding Bonferroni correction. A suggestive significant genetic correlation was found between PCOS and WHRadjBMI (rg=0.09, P=0.04). Partitioning the whole genome into 1703 nearly independent regions, we observed a significant local genetic correlation for adult BMI and PCOS at chromosome 18: 57630483-59020751. We identified 16 shared loci underlying PCOS and obesity-related traits via cross-trait meta-analysis including 9 loci shared between BMI and PCOS (adult BMI and PCOS: 5 loci; childhood BMI and PCOS: 4 loci), 6 loci shared between WHR and PCOS, and 5 loci shared between WHRadjBMI and PCOS. Mendelian randomization (MR) supported the causal roles of both adult BMI (OR=2.92, 95% CI=2.33-3.67) and childhood BMI (OR=2.76, 95% CI=2.09-3.66) in PCOS, but not WHR (OR=1.19, 95% CI=0.93-1.52) or WHRadjBMI (OR=1.03, 95% CI=0.87-1.22). Genetic predisposition to PCOS did not seem to influence the risk of obesity-related traits.

CONCLUSIONS

Our cross-trait analysis suggests a shared genetic basis underlying obesity and PCOS and provides novel insights into the biological mechanisms underlying these complex traits. Our work informs public health intervention by confirming the important role of weight management in PCOS prevention.

Mendelian Randomization: A Review of Methods for the Prevention, Assessment, and Discussion of Pleiotropy in Studies Using the Fat Mass and Obesity-Associated Gene as an Instrument for Adiposity

Pleiotropy assessment is critical for the validity of Mendelian randomization (MR) analyses, and its management remains a challenging task for researchers. This review examines how the authors of MR studies address bias due to pleiotropy in practice. We reviewed Pubmed, Medline, Embase and Web of Science for MR studies published before 21 May 2020 that used at least one single-nucleotide polymorphism (SNP) in the fat mass and obesity-associated (FTO) gene as instrumental variable (IV) for body mass index, irrespective of the outcome. We reviewed: 1) the approaches used to prevent pleiotropy, 2) the methods cited to detect or control the independence or the exclusion restriction assumption highlighting whether pleiotropy assessment was explicitly stated to justify the use of these methods, and 3) the discussion of findings related to pleiotropy. We included 128 studies, of which thirty-three reported one approach to prevent pleiotropy, such as the use of multiple (independent) SNPs combined in a genetic risk score as IVs. One hundred and twenty studies cited at least one method to detect or account for pleiotropy, including robust and other IV estimation methods (n = 70), methods for detection of heterogeneity between estimated causal effects across IVs (n = 72), methods to detect or account associations between IV and outcome outside thought the exposure (n = 85), and other methods (n = 5). Twenty-one studies suspected IV invalidity, of which 16 explicitly referred to pleiotropy, and six incriminating FTO SNPs. Most reviewed MR studies have cited methods to prevent or to detect or control bias due to pleiotropy. These methods are heterogeneous, their triangulation should increase the reliability of causal inference.

Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndrome

STUDY QUESTION

Can we identify novel variants associated with polycystic ovary syndrome (PCOS) by leveraging the unique population history of Northern Europe?

SUMMARY ANSWER

We identified three novel genome-wide significant associations with PCOS, with two putative independent causal variants in the checkpoint kinase 2 (CHEK2) gene and a third in myosin X (MYO10).

WHAT IS KNOWN ALREADY

PCOS is a common, complex disorder with unknown aetiology. While previous genome-wide association studies (GWAS) have mapped several loci associated with PCOS, the analysis of populations with unique population history and genetic makeup has the potential to uncover new low-frequency variants with larger effects.

STUDY DESIGN, SIZE, DURATION

A population-based case-control GWAS was carried out.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We identified PCOS cases from national registers by ICD codes (ICD-10 E28.2, ICD-9 256.4, or ICD-8 256.90), and all remaining women were considered controls. We then conducted a three-stage case-control GWAS: in the discovery phase, we had a total of 797 cases and 140 558 controls from the FinnGen study. For validation, we used an independent dataset from the Estonian Biobank, including 2812 cases and 89 230 controls. Finally, we performed a joint meta-analysis of 3609 cases and 229 788 controls from both cohorts. Additionally, we reran the association analyses including BMI as a covariate, with 2169 cases and 160 321 controls from both cohorts.

MAIN RESULTS AND THE ROLE OF CHANCE

Two out of the three novel genome-wide significant variants associating with PCOS, rs145598156 (P = 3.6×10-8, odds ratio (OR) = 3.01 [2.02-4.50] minor allele frequency (MAF) = 0.005) and rs182075939 (P = 1.9×10-16, OR = 1.69 [1.49-1.91], MAF = 0.04), were found to be enriched in the Finnish and Estonian populations and are tightly linked to a deletion c.1100delC (r2 = 0.95) and a missense I157T (r2 = 0.83) in CHEK2. The third novel association is a common variant near MYO10 (rs9312937, P = 1.7 × 10-8, OR = 1.16 [1.10-1.23], MAF = 0.44). We also replicated four previous reported associations near the genes Erb-B2 Receptor Tyrosine Kinase 4 (ERBB4), DENN Domain Containing 1A (DENND1A), FSH Subunit Beta (FSHB) and Zinc Finger And BTB Domain Containing 16 (ZBTB16). When adding BMI as a covariate only one of the novel variants remained genome-wide significant in the meta-analysis (the EstBB lead signal in CHEK2 rs182075939, P = 1.9×10-16, OR = 1.74 [1.5-2.01]) possibly owing to reduced sample size.

LARGE SCALE DATA

The age- and BMI-adjusted GWAS meta-analysis summary statistics are available for download from the GWAS Catalog with accession numbers GCST90044902 and GCST90044903.

LIMITATIONS, REASONS FOR CAUTION

The main limitation was the low prevalence of PCOS in registers; however, the ones with the diagnosis most likely represent the most severe cases. Also, BMI data were not available for all (63% for FinnGen, 76% for EstBB), and the biobank setting limited the accessibility of PCOS phenotypes and laboratory values.

WIDER IMPLICATIONS OF THE FINDINGS

This study encourages the use of isolated populations to perform genetic association studies for the identification of rare variants contributing to the genetic landscape of complex diseases such as PCOS.

STUDY FUNDING/COMPETING INTEREST(S)

This work has received funding from the European Union's Horizon 2020 research and innovation programme under the MATER Marie Skłodowska-Curie grant agreement No. 813707 (N.P.-G., T.L., T.P.), the Estonian Research Council grant (PRG687, T.L.), the Academy of Finland grants 315921 (T.P.), 321763 (T.P.), 297338 (J.K.), 307247 (J.K.), 344695 (H.L.), Novo Nordisk Foundation grant NNF17OC0026062 (J.K.), the Sigrid Juselius Foundation project grants (T.L., J.K., T.P.), Finska Läkaresällskapet (H.L.) and Jane and Aatos Erkko Foundation (H.L.). The funders had no role in study design, data collection and analysis, publishing or preparation of the manuscript. The authors declare no conflicts of interest.

A Model for Predicting Polycystic Ovary Syndrome Using Serum AMH, Menstrual Cycle Length, Body Mass Index and Serum Androstenedione in Chinese Reproductive Aged Population: A Retrospective Cohort Study

BACKGROUND

A clinical diagnosis of polycystic ovary syndrome (PCOS) can be tedious with many different required tests and examinations. Furthermore, women with PCOS have increased risks for several metabolic complications, which need long-term health management. Therefore, we attempted to establish an easily applicable model to identify such women at an early stage.

OBJECTIVE

To develop an easy-to-use tool for screening PCOS based on medical records from a large assisted reproductive technology (ART) center in China.

MATERIALS AND METHODS

A retrospective observational cohort from Peking University Third Hospital was used in the study. Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression with 10-fold cross-validation was applied to construct the model. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity values were used to evaluate and compare the models.

DESIGN SETTING AND PARTICIPANTS

This retrospective cohort study included 21,219 ovarian stimulation cycle records from January to December 2019 in Peking University Third Hospital.

MAIN OUTCOMES AND MEASURES

The main outcome was whether there was a clinical diagnosis of PCOS. The independent variables included were age, body mass index (BMI), upper limit of menstrual cycle length (UML), basal serum levels of anti-Müllerian hormone (AMH), testosterone androstenedione, antral follicle counts et al.

RESULTS

We have established a new mathematical model for diagnosing PCOS using serum AMH and androstenedione levels, UML, and BMI, with AUC values of 0.855 (0.838-0.870), 0.848 (0.791-0.891), 0.846 (0.812-0.875) in the training, validation, and testing sets, respectively. The contribution of each predictor to this model were: AMH 41.2%; UML 35.2%; BMI 4.3%; and androstenedione 3.7%. The top 10 groups of women most predicted to develop PCOS were demonstrated. An online tool (http://121.43.113.123:8888/) has been developed to assist Chinese ART clinics.

CONCLUSIONS

The models and online tool we established here might be helpful for screening and identifying women with undiagnosed PCOS in Asian populations and could assist in the long-term management of related metabolic disorders.

A new immunometabolic perspective of intervertebral disc degeneration

Intervertebral disc (IVD) degeneration is a common finding on spine imaging that increases in prevalence with age. IVD degeneration is a frequent cause of low back pain, which is a leading cause of disability. The process of IVD degeneration consists of gradual structural change accompanied by severe alterations in metabolic homeostasis. IVD degeneration, like osteoarthritis, is a common comorbidity in patients with obesity and type 2 diabetes mellitus, two metabolic syndrome pathological conditions in which adipokines are important promoters of low-grade inflammation, extracellular matrix degradation and fibrosis. Impairment in white adipose tissue function, due to the abnormal fat accumulation in obesity, is characterized by increased production of specific pro-inflammatory proteins such as adipokines by white adipose tissue and of cytokines such as TNF by immune cells of the stromal compartment. Investigations into the immunometabolic alterations in obesity and type 2 diabetes mellitus and their interconnections with IVD degeneration provide insights into how adipokines might affect the pathogenesis of IVD degeneration and impair IVD function and repair. Toll-like receptor-mediated signalling has also been implicated as a promoter of the inflammatory response in the metabolic alterations associated with IVD and is thus thought to have a role in IVD degeneration. Pathological starvation, obesity and adipokine dysregulation can result in immunometabolic alterations, which could be targeted for the development of new therapeutics.

Is there a shared genetic basis and causal relationship between polycystic ovary syndrome and psychiatric disorders: evidence from a comprehensive genetic analysis

STUDY QUESTION

Is there a shared genetic basis or causal relationship between polycystic ovary syndrome (PCOS) and a range of psychiatric disorders?

SUMMARY ANSWER

Genome-wide genetic correlation analysis and bidirectional Mendelian randomisation (MR) analysis suggest no shared genetic basis or causal relationship of PCOS with psychiatric disorders including depression, anxiety, schizophrenia and bipolar disorder.

WHAT IS KNOWN ALREADY

The comorbidity of PCOS with a range of psychiatric disorders has been recognised by epidemiological investigations yet a causal relationship remains unclear. Understanding of how genetic variations contribute to the susceptibility to PCOS and psychiatry disorders could provide meaningful insights into disease mechanisms.

STUDY DESIGN, SIZE, DURATION

We incorporated summary statistics from the hitherto largest genome-wide association studies (GWAS) conducted in subjects with PCOS (Ncase = 9322) or four common psychiatric disorders (depression, anxiety, schizophrenia and bipolar disorder) (Ncase ranges between 20 352 and 246 363), all of European ancestry.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We quantified pairwise genetic correlation to understand the shared genetic predisposition using genome-wide genetic variants. We performed a two-sample bidirectional Mendelian randomisation analysis to make causal inferences, using GWAS-identified 102 depression-associated genetic instruments, 6 anxiety-associated instruments, 179 schizophrenia-associated instruments, 30 bipolar disorder-associated instruments and 14 PCOS-associated instruments. We performed several important sensitivity analyses examining sex hormones and utilising different MR approaches.

MAIN RESULTS AND THE ROLE OF CHANCE

We did not find significant genetic correlations (rg) for PCOS with psychiatric disorders (depression (rg = 0.09, P = 0.06), anxiety (rg = 0.15, P = 0.06), schizophrenia (rg = 0.02, P = 0.59), bipolar disorder (rg = 0.08, P = 0.19)). Genetic predisposition to PCOS was associated with depression in some of our MR approaches, without any evidence of pleiotropy (PMR-Egger intercept = 0.60). However, this weak PCOS-depression causal association attenuated to null after adjusting for BMI (1.00 (0.99-1.02), P = 0.28). On the contrary, we did not observe any statistically significant association between genetically instrumented PCOS with other psychiatric disorders (anxiety 1.01 (0.93-1.08), P = 0.89; schizophrenia 1.03 (0.97-1.10), P = 0.37; bipolar disorder 0.96 (0.90-1.03), P = 0.26). Bidirectional MR did not reveal an effect by which mental health conditions influenced PCOS risk.

LIMITATIONS, REASONS FOR CAUTION

Despite our study being the largest in sample size of its kind, the overall negligible causal relationship between PCOS and psychiatric outcomes may reflect a true null association but may also be due to a true effect too modest to be detected. We were not able to investigate PCOS subtypes and used an overall heterogenous PCOS sample due to limited availability of data.

WIDER IMPLICATIONS OF THE FINDINGS

Our comprehensive analysis does not identify a shared genetic basis of PCOS with psychiatric diseases. Although genetically instrumented PCOS appears to correlate with depression, such an effect is likely mediated by BMI, suggesting a role of non-genetic exposures underlying the observed comorbidity.

STUDY FUNDING/COMPETING INTEREST(S)

The work was supported by the Swedish Medical Research Council 2018-02435 (to E.S.V.), Novo Nordisk Foundation NNF19OC0056647 (to E.S.V.), the Adlerbert Research Foundation (to E.S.V.), the SRP in Diabetes at Karolinska Institutet (to E.S.V.) and the Swedish Research Council VR 2018-02247 (to X.J.). The funders had no influence on the data collection, analyses or conclusions of the study. No conflict of interests to declare.

TRIAL REGISTRATION NUMBER

N/A.

Genetically Predicted Cigarette Smoking in Relation to Risk of Polycystic Ovary Syndrome

Background

Evidence from observational studies has suggested a link between cigarette smoking and the risk of polycystic ovary syndrome (PCOS). However, it remains uncertain whether the observed relationship is causal or due to biases inherent in observational studies. Therefore, we adopted two-sample Mendelian randomization (MR) design to assess the potential causal association between smoking and the risk of PCOS.

Methods

Summary level data of PCOS was obtained from a genome-wide association study (GWAS) meta-analysis including 4,138 cases and 20,129 controls of European ancestry. Single-nucleotide polymorphisms (SNPs) associated with smoking initiation (n=360) were selected and used as genetic instrumental variables (IVs). MR analysis was performed using inverse-variance weighted (IVW) method, supplemented with the likelihood-based method, weighted median method, MR pleiotropy residual sum and outlier (MR-PRESSO) test, and MR-Egger regression.

Results

Genetically predicted smoking initiation was associated with an increased risk of PCOS in the primary analysis (odds ratio (OR) =1.38, 95% confidence interval (CI) =1.12–1.69). MR-Egger regression did not detect the horizontal pleiotropy. Sensitivity analyses using alternative MR methods and restricted IVs produced similar results.

Conclusion

Our study provided evidence to support a potential causal association between smoking initiation and an increased risk of PCOS, providing a better understanding of the etiology and prevention of PCOS. Further studies are warranted to clarify the underlying biological mechanisms of smoking in the development of PCOS.

The relationships of sex hormone-binding globulin, total testosterone, androstenedione and free testosterone with metabolic and reproductive features of polycystic ovary syndrome

Objective

A recent Mendelian randomization study has suggested a causal role for sex hormone‐binding globulin (SHBG), total testosterone and free testosterone in the pathogenesis of polycystic ovary syndrome (PCOS). The aim of this study was to assess the relationships of SHBG, androstenedione, total and free testosterone with the individual metabolic and reproductive features of PCOS.

Design

Cross‐sectional data in PCOS patients (n=96) prospectively collected in a secondary/tertiary clinic for menstrual cycle disorders.

Methods

Multivariable regression analyses were conducted to study the associations between SHBG, androstenedione, total and free testosterone with metabolic (BMI, waist circumference, systolic and diastolic blood pressure, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides and homeostatic model assessment for insulin resistance [HOMA2‐IR]) and reproductive features (menstrual cycle length, antral follicle count, anti‐Müllerian hormone, luteinizing hormone, follicle‐stimulating hormone and Ferriman‐Gallwey score) of PCOS.

Results

Serum SHBG and free testosterone, but not total testosterone or androstenedione, were significantly associated with BMI, waist circumference, serum triglycerides, HDL cholesterol, LDL cholesterol and HOMA2‐IR. The strength of the associations with serum lipids was reduced after adjustment for BMI, but not for HOMA2‐IR. Total testosterone was significantly associated with antral follicle count. SHBG, total testosterone and androstenedione were significantly associated with serum AMH. Only the strength of the association for SHBG was reduced after adjustment for BMI.

Conclusions

Serum SHBG is associated with primarily metabolic features, whereas total testosterone and androstenedione are associated with reproductive features of PCOS. These results suggest a differential underlying pathophysiology for the metabolic and reproductive features of PCOS.

Polycystic Ovary Syndrome Susceptibility Loci Inform Disease Etiological Heterogeneity

Polycystic ovary syndrome (PCOS) is a complex disorder with heterogenous phenotypes and unclear etiology. A recent phenotypic clustering study identified metabolic and reproductive subtypes of PCOS. We hypothesize that the heterogeneity of PCOS manifestations reflects different mechanistic pathways and can be identified using a genetic approach. We applied k-means clustering to categorize the genome-wide significant PCOS variants into clusters based on their associations with selected quantitative traits that likely reflect PCOS etiological pathways. We evaluated the association of each cluster with PCOS-related traits and disease outcomes. We then applied Mendelian randomization to estimate the causal effects between the traits and PCOS. Three categories of variants were identified: adiposity, insulin resistant, and reproductive. Significant associations were observed for variants in the adiposity cluster with body mass index (BMI), waist circumference and breast cancer, and variants in the insulin-resistant cluster with fasting insulin, glucose values, and homeostatic model assessment of insulin resistance (HOMA-IR). Sex hormone binding globulin (SHBG) has strong association with all three clusters. Mendelian randomization suggested a causal role of BMI and SHBG on PCOS. No causal associations were observed for PCOS on disease outcomes.

Insulin resistance and PCOS: chicken or egg?

PCOS is a common and heterogeneous endocrine disorder in women of reproductive age, frequently associated with metabolic abnormalities. It was estimated that about 75% of these subjects have an impairment of insulin action, as measured by gold standard methods. While the relationship between insulin resistance and PCOS is consistently shown by a number of studies, the mechanisms underlying its primary origin still remains an unsolved issue. Insulin resistance and the associated hyperinsulinemia can induce both the endocrine and reproductive traits of PCOS. However, androgen excess, in turn, can impair insulin action, directly and/or through several changes occurring in different tissues. Body fat excess, which is another common feature in these women, can contribute to worsening the whole picture. Nevertheless, insulin resistance may also be found in many normal-weight individuals. Endocrine and metabolic abnormalities can develop in different moments, and probably there is fetal programming of these alterations. However, a number of vicious circles, with bidirectional relationships between androgen excess and insulin resistance, and with the contribution of several other factors, make it extremely difficult to understand where this process really originates. This review summarizes available evidence on this topic, in order to better understand the complex relationships linking hyperandrogenism and impaired insulin action in women with PCOS.

The Genetic Association of Polycystic Ovary Syndrome and the Risk of Endometrial Cancer: A Mendelian Randomization Study

The association between polycystic ovary syndrome (PCOS) and endometrial cancer remains unclear. We aimed to investigate the causal association between genetically predicted PCOS and endometrial cancer risk in two ethnic groups through a two-sample Mendelian randomization (MR) approach. Our study includes 13 single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) for PCOS in Europeans, and another 13 SNPs are used as IVs for PCOS in Asians. Outcome data were obtained from the largest published meta-GWAS of European ancestry to date, as well as from the BioBank Japan Project of Asian ancestry. Our study demonstrates that genetically predicted PCOS is not causally associated with the risk of overall endometrial cancer in either Europeans or Asians (odds ratio (OR) = 0.93, 95% confidence interval (CI) = 0.85-1.01, p = 0.09 and OR = 0.98, 95% CI 0.84-1.13, p = 0.75, respectively). Subgroup analyses according to histotype further illustrate that PCOS might not be associated with the risk of either endometrioid endometrial cancer or non-endometrioid endometrial cancer in European ancestry. No pleiotropy is found in our study, and a sensitivity analysis shows similar results. Our results indicate that genetically predicted PCOS might not be associated with the risk of endometrial cancer.

Intertwined reproductive endocrinology: Puberty and polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a heterogeneous familial disorder often emerging during the peri-pubertal years concomitantly with the onset of gonadarche and adrenarche. Both gonadarche and PCOS reflect functional changes in the hypothalamic-pituitary-ovarian axis. During this transition, normal girls manifest features consistent with PCOS such as irregular menses, mild hyperandrogenism, and multi-follicular ovary morphology. Themes common to puberty and PCOS, neuroendocrine features, androgen exposure, and insulin sensitivity, will be considered to address the possibility that PCOS interferes with the normal pubertal transition.