The Role of Anti-Müllerian Hormone in Ovarian Function.

Anti-Müllerian hormone (AMH) is a member of the transforming growth factor ß (TGFß) superfamily, whose actions are restricted to the endocrine-reproductive system. Initially known for its role in male sex differentiation, AMH plays a role in the ovary, acting as a gatekeeper in folliculogenesis by regulating the rate of recruitment and growth of follicles. In the ovary, AMH is predominantly expressed by granulosa cells of preantral and antral follicles (i.e., post primordial follicle recruitment and prior to follicle-stimulating hormone (FSH) selection). AMH signals through a BMP-like signaling pathway in a manner distinct from other TGFß family members. In this review, the latest insights in AMH processing, signaling, its regulation of spatial and temporal expression pattern, and functioning in folliculogenesis are summarized. In addition, effects of AMH variants on ovarian function are reviewed.

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.

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.

Comparison of 3 Different AMH Assays With AMH Levels and Follicle Count in Women With Polycystic Ovary Syndrome.

CONTEXT: Anti-Müllerian hormone (AMH) levels strongly correlate with the number of antral follicles (total follicle count, TFC) in the ovary. In women with polycystic ovary syndrome (PCOS), this is reflected by significantly increased serum AMH levels. Different assays have been developed to measure AMH. However, little is known about the interassay correlation in women with increased AMH levels. OBJECTIVE: To investigate the correlation of AMH values between different AMH assays and with TFC in PCOS patients. METHODS: AMH levels were measured in 1660 PCOS patients, using 3 different AMH assays: Gen II (Beckman Coulter); picoAMH (Ansh Labs); and Elecsys (Roche). Passing Bablok regression was used to compare assay methods. Spearman's correlation was used to correlate AMH levels and TFC. RESULTS: Strong interassay correlations were present over the total range of AMH levels (0.81-0.94). Stratification in subgroups, revealed an AMH level-dependent interassay correlation with strong interassay correlations in the low (<2.80 ng/mL) and high (>7.04 ng/mL) subgroups (0.62-0.86). However, the correlation in the mid-AMH subgroup (2.80-7.04 ng/mL) was only moderate (0.28-0.56). A strong correlation was present between the total range of AMH levels and TFC (0.57-0.62). However, in all 3 AMH subgroups the correlation became moderate at best, independently of assay method (0.11-0.45). CONCLUSION: In conclusion, both the interassay correlation and the correlation between AMH level and follicle count depend on the range of serum AMH levels. This once more emphasizes the need of a standardization of AMH measurement for an accurate interpretation of AMH in clinical practice.

Association between an AMH promoter polymorphism and serum AMH levels in PCOS patients.

STUDY QUESTION: Do polymorphisms in the anti-Müllerian hormone (AMH) promoter have an effect on AMH levels in patients with polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: We have identified a novel AMH promoter polymorphism rs10406324 that is associated with lower serum AMH levels and is suggested to play a role in the mechanism of regulation of AMH gene expression in women. WHAT IS KNOWN ALREADY: Follicle number is positively correlated with serum AMH levels, reflected by elevated AMH levels in women with PCOS. In addition, it is suggested that AMH production per follicle is higher in women with PCOS than in normo-ovulatory women, implying an altered regulation of AMH in PCOS. STUDY DESIGN, SIZE, DURATION: A discovery cohort of 655 PCOS women of Northern European ancestry and both an internal and external validation PCOS cohort (n = 458 and n = 321, respectively) were included in this study. Summary-level data of an AMH genome-wide association study meta-analysis including 7049 normo-ovulatory women was included as a control cohort. A genetic approach was taken through association analysis and in silico analysis of the associated variants in the AMH promoter. In vitro analysis was performed to investigate the functional mechanisms. PARTICIPANTS/MATERIALS, SETTING, METHODS: All common two-allelic single-nucleotide polymorphisms (SNPs) in the region Chr19:2 245 353-2 250 827 bp (Build 37) were selected for the analysis. Linear regression analyses were performed to determine the association between SNPs in the AMH promoter region and serum AMH levels. For the in silico analysis, the webtools 'HaploReg' v4.1 for ENCODE prediction weight matrices and 'atSNP' were used. In vitro analysis was performed using KK1 cells, a mouse granulosa cell line and COV434 cells, a human granulosa tumor cell line. Cells were transfected with the reference or the variant human AMH promoter reporter construct together with several transcription factors (TFs). Dual-Glo® Luciferase Assay was performed to measure the luciferase activity. MAIN RESULTS AND THE ROLE OF CHANCE: Polymorphism rs10406324 was significantly associated with serum AMH levels in all three PCOS cohorts. Carriers of the minor allele G had significantly lower log-transformed serum AMH levels compared to non-carriers (P = 8.58 × 10-8, P = 1.35 × 10-3 and P = 1.24 × 10-3, respectively). This result was validated in a subsequent meta-analysis (P = 3.24 × 10-12). Interestingly, rs10406324 was not associated with follicle count, nor with other clinical traits. Also, in normo-ovulatory women, the minor allele of this variant was associated with lower serum AMH levels (P = 1.04 × 10-5). These findings suggest that polymorphism rs10406324 plays a role in the regulation of AMH expression, irrespective of clinical background. In silico analysis suggested a decreased binding affinity of the TFs steroidogenenic factor 1, estrogen-related receptor alpha and glucocorticoid receptor to the minor allele G variant, however in vitro analysis did not show a difference in promoter activity between the A and G allele. LIMITATIONS, REASONS FOR CAUTION: Functional analyses were performed in a mouse and a human granulosa cell line using an AMH promoter reporter construct. This may have limited assessment of the impact of the polymorphism on higher order chromatin structures. Human granulosa cells generated from induced pluripotent stem cells, combined with gene editing, may provide a method to elucidate the exact mechanism behind the decrease in serum AMH levels in carriers of the -210 G allele. We acknowledge that the lack of follicle number in the external validation and the control cohort is a limitation of the paper. Although we observed that the association between rs10406324 and AMH levels was independent of follicle number in our discovery and internal validation PCOS cohorts, we cannot fully rule out that the observed effects on serum AMH levels are, in part, caused by differences in follicle number. WIDER IMPLICATIONS OF THE FINDINGS: These results suggest that variations in serum AMH levels are not only caused by differences in follicle number but also by genetic factors. Therefore, the genetic context should be taken into consideration when assessing serum AMH levels in women. This may have clinical consequences when serum AMH levels are used as a marker for the polycystic ovarian morphology phenotype. STUDY FUNDING/COMPETING INTEREST(S): No external funding was used. J.S.E.L. has received consultancy fees from the following companies: Ferring, Roche Diagnostics and Ansh Labs and has received travel reimbursement from Ferring. J.A.V. has received royalties from AMH assays, paid to the institute/lab with no personal financial gain. The other authors declare no competing interests. TRIAL REGISTRATION NUMBER: N/A.

Anti-Müllerian Hormone and Ovarian Reserve: Update on Assessing Ovarian Function.

CONTEXT: Anti-müllerian hormone (AMH) is produced by granulosa cells of small, growing follicles in the ovary. Serum AMH levels strongly correlate with the number of growing follicles, and therefore AMH has received increasing attention as a marker for ovarian reserve. This review summarizes recent findings and limitations in the application of serum AMH in ovarian reserve assessment. EVIDENCE ACQUISITION: A PubMed search was conducted to find recent literature on the measurements and use of serum AMH as a marker for ovarian reserve. EVIDENCE SYNTHESIS: Serum AMH levels are measured to assess the "functional ovarian reserve," a term that is preferred over "ovarian reserve," since AMH levels reflect the pool of growing follicles that potentially can ovulate. Serum AMH levels are used in individualized follicle-stimulating hormone dosing protocols and may predict the risk of poor response or ovarian hyperstimulation syndrome but has limited value in predicting ongoing pregnancy. Serum AMH levels are studied to predict natural or disease-related age of menopause. Studies show that the age-dependent decline rates of AMH vary among women. The generalized implementation of serum AMH measurement has also led to an increase in diagnostic assays, including automated assays. However, direct comparison of results remains problematic. CONCLUSION: Serum AMH remains the preferred ovarian reserve marker. However, the lack of an international standard for AMH limits comparison between AMH assays. Furthermore, little is known about endogenous and exogenous factors that influence serum AMH levels, which limits proper interpretation of AMH values in a clinical setting.