Body mass index stratified meta-analysis of genome-wide association studies of polycystic ovary syndrome in women of European ancestry.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex multifactorial disorder with a substantial genetic component. However, the clinical manifestations of PCOS are heterogeneous with notable differences between lean and obese women, implying a different pathophysiology manifesting in differential body mass index (BMI). We performed a meta-analysis of genome-wide association study (GWAS) data from six well-characterised cohorts, using a case-control study design stratified by BMI, aiming to identify genetic variants associated with lean and overweight/obese PCOS subtypes. RESULTS: The study comprised 254,588 women (5,937 cases and 248,651 controls) from individual studies performed in Australia, Estonia, Finland, the Netherlands and United States of America, and separated according to three BMI stratifications (lean, overweight and obese). Genome-wide association analyses were performed for each stratification within each cohort, with the data for each BMI group meta-analysed using METAL software. Almost half of the total study population (47%, n = 119,584) were of lean BMI (≤ 25 kg/m2). Two genome-wide significant loci were identified for lean PCOS, led by rs12000707 within DENND1A (P = 1.55 × 10-12) and rs2228260 within XBP1 (P = 3.68 × 10-8). One additional locus, LINC02905, was highlighted as significantly associated with lean PCOS through gene-based analyses (P = 1.76 × 10-6). There were no significant loci observed for the overweight or obese sub-strata when analysed separately, however, when these strata were combined, an association signal led by rs569675099 within DENND1A reached genome-wide significance (P = 3.22 × 10-9) and a gene-based association was identified with ERBB4 (P = 1.59 × 10-6). Nineteen of 28 signals identified in previous GWAS, were replicated with consistent allelic effect in the lean stratum. There were less replicated signals in the overweight and obese groups, and only 4 SNPs were replicated in each of the three BMI strata. CONCLUSIONS: Genetic variation at the XBP1, LINC02905 and ERBB4 loci were associated with PCOS within unique BMI strata, while DENND1A demonstrated associations across multiple strata, providing evidence of both distinct and shared genetic features between lean and overweight/obese PCOS-affected women. This study demonstrated that PCOS-affected women with contrasting body weight are not only phenotypically distinct but also show variation in genetic architecture; lean PCOS women typically display elevated gonadotrophin ratios, lower insulin resistance, higher androgen levels, including adrenal androgens, and more favourable lipid profiles. Overall, these findings add to the growing body of evidence supporting a genetic basis for PCOS as well as differences in genetic patterns relevant to PCOS BMI-subtype.

Clinical Relevance of Vaginal and Endometrial Microbiome Investigation in Women with Repeated Implantation Failure and Recurrent Pregnancy Loss.

Recent studies have investigated if and how the vaginal and endometrial microbiome might affect endometrial receptivity and reproductive health. Although there is no consensus on the existence of a core uterine microbiome yet, evidence shows that the dominance of Lactobacillus spp. in the female reproductive tract is generally associated with eubiosis and improved chances of successful implantation and an ongoing pregnancy. Conversely, vaginal and endometrial dysbiosis can cause local inflammation and an increase of pro-inflammatory cytokines, compromising the integrity and receptivity of the endometrial mucosa and potentially hampering successful embryonic implantation. This review provides a critical appraisal of the influence of the vaginal and endometrial microbiome as parts of the female reproductive tract on fertility outcomes, focusing on repeated implantation failure (RIF) and recurrent pregnancy loss (RPL). It seems that RIF as well as RPL are both associated with an increase in microbiome diversity and a loss of Lactobacillus dominance in the lower female reproductive system.

Can we predict menopause and premature ovarian insufficiency?

The prediction of menopause and premature ovarian insufficiency (POI) involves understanding the factors that contribute to the timing of these events. Menopause is a natural biological process marked by the cessation of menstrual periods, typically occurring around the age of 51. On the other hand, POI refers to the loss of ovarian function before the age of 40. Several factors have been used to predict menopause and POI such as age, antimüllerian hormone, inhibins and follicle-stimulating hormone serum levels, antral follicle counts, menstrual cycle length, and, recently, some genetic markers. It seems that age has the best predictive power and all the other ones are only adding in a very limited way to the prediction of menopause. Low levels of antimüllerian hormone in young women might indicate a greater risk for POI and could facilitate early diagnosis. It is, however, important to note that predicting the exact timing of menopause and POI is challenging, and individual variations are significant. Although these factors can provide some insights, they are not foolproof predictors. Advances in medical research and technology may lead to more accurate methods for predicting menopause and POI in the future.

Sexual function in women with premature ovarian insufficiency (POI): Systematic review and meta-analysis.

Premature ovarian insufficiency (POI) is a rare condition characterized by loss of ovarian function before the age of 40. POI seems associated with mood disorders and sexual dysfunction. However, there is a lack of high-quality evidence relating to the impact of POI on sexual function. Therefore, we conducted a systematic review and meta-analysis to evaluate sexual function in women with POI compared to women without the condition. The following online databases were systematically searched up to January 2023: EMBASE, Medline (Ovid), Web of Science, Cochrane, PsychInfo, and Google Scholar. Random effects models were used for analyses, with data reported as Hedges' g and 95 % confidence interval, and the risk of heterogeneity was evaluated. The protocol of this study was registered with PROSPERO (CRD42023437203). A total of 10 studies were included in the systematic review and 5 studies involving 352 women with POI were included in the meta-analysis. Eight of the ten studies concluded that women with POI have reduced sexual function. An overall medium Hedges' g effect size of -0.72 was found (ranging between -0.20 and -1.29) in favor of control women, with moderate heterogeneity (I2 = 64 %). Stratified studies of women on systemic hormone replacement therapy (HRT) showed an even higher Hedges' g effect size, of -0.82 (95 % CI -1.18, -0.47). In conclusion, sexual function in women with POI is reduced compared with control women. Sexual function should be discussed with women with POI and they should be offered psychosexual counseling.

Anti-müllerian hormone as a diagnostic biomarker for polycystic ovary syndrome and polycystic ovarian morphology: a systematic review and meta-analysis.

IMPORTANCE: As part of the 2023 international evidence-based polycystic ovary syndrome (PCOS) guideline, this meta-analysis investigated the inclusion of Anti-Müllerian hormone (AMH) levels in the diagnostic criteria for PCOS. OBJECTIVE: To answer the following three questions: 1) Are AMH levels effective in diagnosing PCOS in adult women? 2) Are AMH levels effective in diagnosing PCOS in adolescents? Are AMH levels effective in diagnosing polycystic ovarian morphology (PCOM)? DATA SOURCES: Searches were conducted in six databases until July 31, 2023. STUDY SELECTION AND SYNTHESIS: Eligible studies were those conducted in humans, published in English, and reporting sensitivity, specificity, and/or area under the curve values. Extracted data included study population, age, body mass index, AMH assay, cut-off value of AMH levels, sensitivity, specificity, and area under the curve values. The risk of bias was assessed using the quality assessment of diagnostic accuracy studies tool. A random effects model was used to test diagnostic accuracy. MAIN OUTCOMES: Pooled sensitivity and specificity to use AMH levels for PCOS diagnosis in adults as well as adolescents and for detecting PCOM in adults. RESULTS: Eighty-two studies were included. The adult AMH-PCOS meta-analyses (n = 68) showed a pooled sensitivity and specificity of 0.79 (95% confidence interval [CI], 0.76-0.82; I2 = 86%) and 0.87 (95% CI, 0.84-0.89; I2 = 91%). The adolescent AMH-PCOS meta-analysis (n = 11) showed a pooled sensitivity and specificity of 0.66 (95% CI, 0.58-0.73; I2 = 74%) and 0.78 (95% CI, 0.71-0.83; I2 = 45%). The adult AMH-PCOM meta-analysis (n = 7) showed a pooled sensitivity and specificity of 0.79 (95% CI, 0.72-0.85; I2 = 94%) and 0.87 (95% CI, 0.78-0.93; I2 = 94%). CONCLUSION AND RELEVANCE: This study investigated the most profound change in the 2023 international evidence-based PCOS guideline, which now recommends AMH levels for defining PCOM in adults in accordance with the diagnostic algorithm. Antimüllerian hormone levels alone are insufficient for PCOS diagnosis and are nonspecific for PCOM in adolescents. Multiple factors influence AMH levels and cause heterogeneity as well as limitations in this study. Consequently, no international cut-off value could be recommended, emphasizing the need for research on more individualized cut-off values.

Clustering Identifies Subtypes With Different Phenotypic Characteristics in Women With Polycystic Ovary Syndrome.

CONTEXT: Hierarchical clustering (HC) identifies subtypes of polycystic ovary syndrome (PCOS). OBJECTIVE: This work aimed to identify clinically significant subtypes in a PCOS cohort diagnosed with the Rotterdam criteria and to further characterize the distinct subtypes. METHODS: Clustering was performed using the variables body mass index (BMI), luteinizing hormone (LH), follicle-stimulating hormone, dehydroepiandrosterone sulfate, sex hormone-binding globulin (SHBG), testosterone, insulin, and glucose. Subtype characterization was performed by analyzing the variables estradiol, androstenedione, dehydroepiandrosterone, cortisol, anti-Müllerian hormone (AMH), total follicle count (TFC), lipid profile, and blood pressure. Study participants were girls and women who attended our university hospital for reproductive endocrinology screening between February 1993 and February 2021. In total, 2502 female participants of European ancestry, aged 13 to 45 years with PCOS (according to the Rotterdam criteria), were included. A subset of these (n = 1067) fulfilled the National Institutes of Health criteria (ovulatory dysfunction and hyperandrogenism). Main outcome measures included the identification of distinct PCOS subtypes using cluster analysis. Additional clinical variables associated with these subtypes were assessed. RESULTS: Metabolic, reproductive, and background PCOS subtypes were identified. In addition to high LH and SHBG levels, the reproductive subtype had the highest TFC and levels of AMH (all P < .001). In addition to high BMI and insulin levels, the metabolic subtype had higher low-density lipoprotein levels and higher systolic and diastolic blood pressure (all P < .001). The background subtype had lower androstenedione levels and features of the other 2 subtypes. CONCLUSION: Reproductive and metabolic traits not used for subtyping differed significantly in the subtypes. These findings suggest that the subtypes capture distinct PCOS causal pathways.

Interindividual variation in ovarian reserve after gonadotoxic treatment in female childhood cancer survivors - a genome-wide association study: results from PanCareLIFE.

OBJECTIVE: To discover new variants associated with low ovarian reserve after gonadotoxic treatment among adult female childhood cancer survivors using a genome-wide association study approach. DESIGN: Genome-wide association study. SETTING: Not applicable. PATIENTS: A discovery cohort of adult female childhood cancer survivors from the pan-European PanCareLIFE cohort (n = 743; median age: 25.8 years), excluding those who received bilateral ovarian irradiation, bilateral oophorectomy, central nervous system or total body irradiation, or stem cell transplantation. Replication was attempted in the US-based St. Jude Lifetime Cohort (n = 391; median age: 31.3 years). EXPOSURE: Female childhood cancer survivors are at risk of therapy-related gonadal impairment. Alkylating agents are well-established risk factors, and the interindividual variability in gonadotoxicity may be explained by genetic polymorphisms. Data were collected in real-life conditions, and cyclophosphamide equivalent doses were used to quantify alkylation agent exposure. MAIN OUTCOME MEASURE: Anti-Müllerian hormone (AMH) levels served as a proxy for ovarian function, and the findings were combined in a meta-analysis. RESULTS: Three genome-wide significant (<5.0 × 10-8) and 16 genome-wide suggestive (<5.0 × 10-6) loci were associated with log-transformed AMH levels, adjusted for cyclophosphamide equivalent dose of alkylating agents, age at diagnosis, and age at study in the PanCareLIFE cohort. On the basis of the effect allele frequency (EAF) (>0.01 if not genome-wide significant), and biologic relevance, 15 single nucleotide polymorphisms were selected for replication. None of the single nucleotide polymorphisms were statistically significantly associated with AMH levels. A meta-analysis indicated that rs78861946 was associated with borderline genome-wide statistical significance (reference/effect allele: C/T; effect allele frequency: 0.04, beta (SE): -0.484 (0.091). CONCLUSION: This study found no genetic variants associated with a lower ovarian reserve after gonadotoxic treatment because the findings of this genome-wide association study were not statistically significant replicated in the replication cohort. Suggestive evidence for the potential importance of 1 variant is briefly discussed, but the lack of statistical significance calls for larger cohort sizes. Because the population of childhood cancer survivors is increasing, large-scale and systematic research is needed to identify genetic variants that could aid predictive risk models of gonadotoxicity as well as fertility preservation options for childhood cancer survivors.