Chronotypes in middle-aged women with polycystic ovary syndrome: A population-based study.

INTRODUCTION: Circadian rhythm disruption has been associated with the risk of polycystic ovary syndrome (PCOS), as the evening chronotype (EC) shares several traits with PCOS, including metabolic disorders, cardiovascular diseases, and psychiatric disorders. It has been suggested that the biological clock could be targeted with new, preventive, and therapeutic strategies for PCOS in women with biorhythm disorders. We evaluated inner circadian rhythmicity in middle-aged women with PCOS in a population-based setting, focusing on whether women with PCOS and an EC have a specific subtype in relation to their clinical characteristics. MATERIAL AND METHODS: The data derived from the Northern Finland Birth Cohort, a population-based longitudinal birth cohort of 12 058 individuals born in 1966. We compared the circadian phenotype between 314 women with PCOS (according to the Rotterdam criteria) and 1248 women without PCOS at age 46 years using the validated Finnish shortened 6-item Morningness-Eveningness Questionnaire (sMEQ) and the single-item self-assessed morningness-eveningness question. RESULTS: PCOS was not associated with the EC by the sMEQ (p = 0.495) or self-assessment (p = 0.303). The self-assessed morningness-eveningness values differed from the sMEQ chronotype distribution (p < 0.001), nevertheless, the most frequent chronotype was the intermediate chronotype (IC) determined by both chronotyping methods (sMEQ PCOS 47.7% vs. 45.2% non-PCOS; self-assessment PCOS 66.5% vs. 68.4% non-PCOS). The hyperandrogenic PCOS phenotypes A-C did not differ from the non-hyperandrogenic phenotype D as for the chronotype (p = 0.271). The EC was associated in both groups with depressive and anxiety symptoms (PCOS p = 0.012, non-PCOS p < 0.001) and the use of sleep medication (PCOS p = 0.017, non-PCOS p < 0.001). CONCLUSIONS: The EC was not over-represented in middle-aged women with PCOS or in the hyperandrogenic PCOS phenotypes A-C in our study. This does not support the need for chronotyping in the comprehensive assessment of women with PCOS. However, as chronotypes tend to change with aging, cross-sectional studies in different age groups are warranted to draw conclusions on the role of chronotypes in PCOS and the associated metabolic risks.

Women with PCOS are at risk for emotional and uncontrolled eating at midlife: a population-based cohort study.

OBJECTIVE: To investigate eating behavior domains -emotional, uncontrolled, and cognitive restraint eating- in women with polycystic ovary syndrome (PCOS) with different PCOS phenotypes and women without PCOS at midlife. DESIGN: A prospective cohort study. Eating behavior domains were assessed at age 46. Predictors of eating behaviors were evaluated using variables collected at ages 31 and 46. SUBJECTS: Women identified as having PCOS (n=251) at age 31 using the updated Rotterdam criteria were compared to women without any PCOS criteria (n=935). The PCOS population comprised women with the classic A+B-phenotype (hyperandrogenism and oligomenorrhea, with or without elevated anti-Müllerian hormone, n=60), C-phenotype (hyperandrogenism and elevated anti-Müllerian hormone, n=84), and D-phenotype (oligomenorrhea and elevated anti-Müllerian hormone, n=86). EXPOSURE: The main explanatory variables for the eating behavior domains were PCOS, body mass index, a history of weight loss attempts, a perception of being overweight, and psychological distress. MAIN OUTCOME MEASURES: Revised Three-Factor Eating Questionnaire-18 scores for eating behavior domains. RESULTS: Compared to women without PCOS, women with PCOS exhibited higher scores for emotional (33.1±27.8 vs. 39.0±29.9, p=0.005) and uncontrolled eating (26.7±18.2 vs. 30.7±19.4, p=0.003) but no difference in cognitive restraint (46.6±18.6 vs. 45.9±18.5, p=0.563) at age 46. Emotional and uncontrolled eating scores were higher in the A+B-phenotype compared to women without PCOS, while uncontrolled eating scores in the C-phenotype were higher than in women without PCOS and the D-phenotype. At age 46, the perception of overweight was an independent predictor of emotional eating among women with PCOS (B=11.96 [95% confidence interval [CI]: 2.81-20.29], p=0.008), while a history of weight loss attempts was a predictor of uncontrolled eating (B=6.06 [95% CI: 1.05-10.83], p=0.015). Among women with PCOS, higher psychological distress at age 31 was a significant risk factor for scoring in the highest quartile of emotional (adjusted odds ratio [aOR]: 2.85 [95% CI: 1.19-6.85], p=0.019) and uncontrolled eating (aOR: 4.37 [95% CI: 1.77-10.80], p=0.001) at age 46. CONCLUSION: Women with PCOS at midlife showed a high tendency for unfavorable eating behaviors. Our findings emphasize the need for sensitivity in weight management counseling and addressing psychological distress to prevent unfavorable eating in this population.

Human Endometrial Pericytes: A Comprehensive Overview of Their Physiological Functions and Implications in Uterine Disorders.

Pericytes are versatile cells integral to the blood vessel walls of the microcirculation, where they exhibit specific stem cell traits. They are essential in modulating blood flow, ensuring vascular permeability, and maintaining homeostasis and are involved in the tissue repair process. The human endometrium is a unique and complex tissue that serves as a natural scar-free healing model with its cyclical repair and regeneration process every month. The regulation of pericytes has gained increasing attention due to their involvement in various physiological and pathological processes. However, endometrial pericytes are less well studied compared to the pericytes in other organs. This review aims to provide a comprehensive overview of endometrial pericytes, with a focus on elucidating their physiological function and potential implications in uterine disorders.

Women's health study (WENDY) - a protocol of a population-based study assessing gynecological and metabolic health in women in their mid-30s.

The Women's Health Study (WENDY) was conducted to improve insights into women's health and health burden. It provides a unique, comprehensive data source that can be broadly utilised to understand gynaecological symptoms, diseases, and their relation to metabolic and overall health more deeply in a population-based setting. The study was conducted in Finland from May 2020 to October 2022. It included 1,918 women (33-37 years old) who were born in Northern Finland between July 1985 and December 1987. Data collection comprised one three-to-four-hour study visit that included clinical measurements, biological samples, ultrasound examinations and an extensive questionnaire on gynaecological and reproductive history, physical and mental health, quality of life, lifestyles, current life situations, health awareness and opinions. The study also included a menstrual cycle follow-up and cognitive testing up to three months via a mobile application. Given that all participants' data can be linked to all Finnish national registers, and the NFBC participants' data can be linked to the birth cohort data set collected from gestational week 24 onwards, WENDY study forms one of the largest datasets worldwide to investigate gynecological and metabolic health burden in women.

Stanniocalcin Protein Expression in Female Reproductive Organs: Literature Review and Public Cancer Database Analysis.

Stanniocalcin (STC) 1 and 2 serve as antihyperglycemic polypeptide hormones with critical roles in regulating calcium and phosphate homeostasis. They additionally function as paracrine and/or autocrine factors involved in numerous physiological processes, including female reproduction. STC1 and STC2 contribute to the pathophysiology of several diseases, including female infertility- and pregnancy-associated conditions, and even tumorigenesis of reproductive organs. This comprehensive review highlights the dynamic expression patterns and potential dysregulation of STC1 and STC2, restricted to female fertility, and infertility- and pregnancy-associated diseases and conditions, such as endometriosis, polycystic ovary syndrome (PCOS), abnormal uterine bleeding, uterine polyps, and pregnancy complications, like impaired decidualization, preeclampsia, and preterm labor. Furthermore, the review elucidates the role of dysregulated STC in the progression of cancers of the reproductive system, including endometrial, cervical, and ovarian cancers. Additionally, the review evaluates the expression patterns and prognostic significance of STC in gynecological cancers by utilizing existing public datasets from The Cancer Genome Atlas to help decipher the multifaceted roles of these pleiotropic hormones in disease progression. Understanding the intricate mechanisms by which STC proteins influence all these reviewed conditions could lead to the development of targeted diagnostic and therapeutic strategies in the context of female reproductive health and oncology.

Association of Accelerometer-Determined Physical Activity and Sedentary Behavior With the Gut Microbiome in Middle-Aged Women: A Compositional Data Approach.

The beneficial effects of physical activity (PA) on gut microbiome have been reported, nevertheless the findings are inconsistent, with the main limitation of subjective methods for assessing PA. It is well accepted that using an objective assessment of PA reduces the measurement error and also allows objective assessment of sedentary behavior (SB). We aimed to study the associations between accelerometer-assessed behaviors (i.e., SB, light-intensity physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) with the gut microbiome using compositional data analysis, a novel approach that enables to study these behaviors accounting for their inter-dependency. This cross-sectional study included 289 women from the Northern Finland Birth Cohort 1966. Physical activity was measured during 14 days by wrist-worn accelerometers. Analyses based on the combined effect of MVPA and SB, and compositional data analyses in association with the gut microbiome data were performed. The microbial alpha- and beta-diversity were not significantly different between the MVPA-SB groups, and no differentially abundant microorganisms were detected. Compositional data analysis did not show any significant associations between any movement behavior (relative to the others) on microbial alpha-diversity. Butyrate-producing bacteria such as Agathobacter and Lachnospiraceae CAG56 were significantly more abundant when reallocating time from LPA or SB to MVPA (γ = 0.609 and 0.113, both p-values = 0.007). While PA and SB were not associated with microbial diversity, we found associations of these behaviors with specific gut bacteria, suggesting that PA of at least moderate intensity (i.e., MVPA) could increase the abundance of short-chain fatty acid-producing microbes.

Systematic review and meta-analysis of pregnancy outcomes in women with polycystic ovary syndrome.

Screening for polycystic ovary syndrome (PCOS) in antenatal care is inadequate, largely owing to the lack of clarity around whether PCOS is an independent risk factor for pregnancy complications. This systematic review and meta-analysis include 104 studies and 106,690 pregnancies in women with and without PCOS from inception until 13th July 2022. We report that women with PCOS are younger and have higher body mass index (BMI) around conception and have greater gestational weight gain. The odds of miscarriage, gestational diabetes mellitus, gestational hypertension, pre-eclampsia and cesarean section are higher in women with PCOS. The increased odds of adverse outcomes in PCOS remain significant when age and BMI are matched and when analyses are restricted to high-quality studies. This work informed the recommendations from the 2023 international evidence-based guideline for the assessment and management of polycystic ovary syndrome, emphasizing that PCOS status should be captured in all women who are planning to, or have recently become pregnant to facilitate prevention of adverse outcomes and improve pregnancy outcomes.

Systematic review and meta-analysis of birth outcomes in women with polycystic ovary syndrome.

It is unclear whether polycystic ovary syndrome (PCOS) is an independent risk factor for adverse birth outcomes in the offspring of affected women. Here, we investigate the association of PCOS with birth outcomes in the offspring of women with PCOS overall and by potential confounders. This systematic review and meta-analysis included 73 studies and 92,881 offspring of women with and without PCOS from inception until 13th July 2022. We report that mothers with PCOS are younger and have higher body mass index (BMI) around conception and have greater gestational weight gain. The odds of preterm birth, fetal growth restriction and low birth weight are higher and mean birthweight is lower in PCOS of which a lower mean birthweight and a higher small for gestational age are probably independent of BMI. This work informed the recommendations from the 2023 international evidence-based guideline for the assessment and management of polycystic ovary syndrome, emphasizing that PCOS status should be captured at pregnancy to identify risk and improve birth outcomes in the offspring.

AI-algorithm training and validation for identification of endometrial CD138+ cells in infertility-associated conditions; polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF).

Background: Endometrial CD138+ plasma cells serve as a diagnostic biomarker for endometrial inflammation, and their elevated occurrence correlates positively with adverse pregnancy outcomes. Infertility-related conditions like polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) are closely associated with systemic and local chronic inflammatory status, wherein endometrial CD138+ plasma cell accumulation could also contribute to endometrial pathology. Current methods for quantifying CD138+ cells typically involve laborious and time-consuming microscopic assessments of only a few random areas from a slide. These methods have limitations in accurately representing the entire slide and are susceptible to significant biases arising from intra- and interobserver variations. Implementing artificial intelligence (AI) for CD138+ cell identification could enhance the accuracy, reproducibility, and reliability of analysis. Methods: Here, an AI algorithm was developed to identify CD138+ plasma cells within endometrial tissue. The AI model comprised two layers of convolutional neural networks (CNNs). CNN1 was trained to segment epithelium and stroma across 28,363 mm2 (2.56 mm2 of epithelium and 24.87 mm2 of stroma), while CNN2 was trained to distinguish stromal cells based on CD138 staining, encompassing 7345 cells in the object layers (6942 CD138- cells and 403 CD138+ cells). The training and performance of the AI model were validated by three experienced pathologists. We collected 193 endometrial tissues from healthy controls (n = 73), women with PCOS (n = 91), and RIF patients (n = 29) and compared the CD138+ cell percentages based on cycle phases, ovulation status, and endometrial receptivity utilizing the AI model. Results: The AI algorithm consistently and reliably distinguished CD138- and CD138+ cells, with total error rates of 6.32% and 3.23%, respectively. During the training validation, there was a complete agreement between the decisions made by the pathologists and the AI algorithm, while the performance validation demonstrated excellent accuracy between the AI and human evaluation methods (intraclass correlation; 0.76, 95% confidence intervals; 0.36-0.93, p = 0.002) and a positive correlation (Spearman's rank correlation coefficient: 0.79, p < 0.01). In the AI analysis, the AI model revealed higher CD138+ cell percentages in the proliferative phase (PE) endometrium compared to the secretory phase or anovulatory PCOS endometrium, irrespective of PCOS diagnosis. Interestingly, CD138+ percentages differed according to PCOS phenotype in the PE (p = 0.03). On the other hand, the receptivity status had no impact on the cell percentages in RIF samples. Conclusion: Our findings emphasize the potential and accuracy of the AI algorithm in detecting endometrial CD138+ plasma cells, offering distinct advantages over manual inspection, such as rapid analysis of whole slide images, reduction of intra- and interobserver variations, sparing the valuable time of trained specialists, and consistent productivity. This supports the application of AI technology to help clinical decision-making, for example, in understanding endometrial cycle phase-related dynamics, as well as different reproductive disorders.

Polycystic ovary syndrome presents as a multimorbid condition by age 50: birth cohort linkage to national register data.

OBJECTIVE: This population-based follow-up study investigated register-based disease diagnoses and medication use up till age of 50 years among women with polycystic ovary syndrome (PCOS) that were identified from a population-based birth cohort. DESIGN: Population-based longitudinal cohort study. PATIENTS: Women reporting oligo/amenorrhea and hirsutism at age 31 and/or who were diagnosed with PCOS by a physician by age 46 (n = 244) and women without PCOS symptoms or diagnosis (n = 1556) in the Northern Finland Birth Cohort 1966. MAIN OUTCOME MEASURES: National register data on diagnosed diseases (International Statistical Classification of Diseases [ICD]-8-10) and medication use (Anatomical Therapeutic Chemical) until the age of 50. RESULTS: Women with PCOS had a 26% higher risk for any registered diagnosis (risk ratio [RR]: 1.26 [1.09-1.46]) and a 24% higher risk for medication use (RR: 1.24 [1.05-1.46]) compared with non-PCOS women, even after adjusting for several confounders. Several main ICD categories were more prevalent among women with PCOS versus non-PCOS controls, eg, endocrine, metabolic, nervous system, musculoskeletal, and genitourinary diseases in addition with different symptoms and injuries. Surprisingly, even though the overall morbidity was only increased in women with PCOS with a body mass index (BMI) ≥ 25 kg/m2, there were several ICD main categories that showed higher comorbidity risk especially in women with PCOS with a BMI < 25 kg/m2. Several medications were prescribed more often to women with PCOS versus non-PCOS controls, eg, medications related to the alimentary tract and metabolism, the cardiovascular system, genitourinary system drugs and sex hormones, dermatologic and hormonal preparations, and medications to treat the musculoskeletal, nervous, and respiratory systems. CONCLUSION: Women with PCOS are burdened with multimorbidity and higher medication use, independent of BMI and other confounders. Accordingly, preventive strategies are needed to alleviate the disease burden and improve the health outcomes of women with PCOS.

Circulating anti-Müllerian hormone levels in pre-menopausal women: novel genetic insights from a genome-wide association meta-analysis.

STUDY QUESTION: Can a genome-wide association study (GWAS) meta-analysis, including a large sample of young premenopausal women from a founder population from Northern Finland, identify novel genetic variants for circulating anti-Müllerian hormone (AMH) levels and provide insights into single-nucleotide polymorphism enrichment in different biological pathways and tissues involved in AMH regulation? SUMMARY ANSWER: The meta-analysis identified a total of six loci associated with AMH levels at P < 5 × 10-8, three of which were novel in or near CHEK2, BMP4, and EIF4EBP1, as well as highlighted significant enrichment in renal system vasculature morphogenesis, and the pituitary gland as the top associated tissue in tissue enrichment analysis. WHAT IS KNOWN ALREADY: AMH is expressed by preantral and small antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with several health conditions. However, the biological mechanisms underlying the association between health conditions and AMH levels are not yet fully understood. Previous GWAS have identified loci associated with AMH levels in pre-menopausal women, in or near MCM8, AMH, TEX41, and CDCA7. STUDY DESIGN, SIZE, DURATION: We performed a GWAS meta-analysis for circulating AMH level measurements in 9668 pre-menopausal women. PARTICIPANTS/MATERIALS, SETTING, METHODS: We performed a GWAS meta-analysis in which we combined 2619 AMH measurements (at age 31 years) from a prospective founder population cohort (Northern Finland Birth Cohort 1966, NFBC1966) with a previous GWAS meta-analysis that included 7049 pre-menopausal women (age range 15-48 years) (N = 9668). NFBC1966 AMH measurements were quantified using an automated assay. We annotated the genetic variants, combined different data layers to prioritize potential candidate genes, described significant pathways and tissues enriched by the GWAS signals, identified plausible regulatory roles using colocalization analysis, and leveraged publicly available summary statistics to assess genetic and phenotypic correlations with multiple traits. MAIN RESULTS AND THE ROLE OF CHANCE: Three novel genome-wide significant loci were identified. One of these is in complete linkage disequilibrium with c.1100delC in CHEK2, which is found to be 4-fold enriched in the Finnish population compared to other European populations. We propose a plausible regulatory effect of some of the GWAS variants linked to AMH, as they colocalize with GWAS signals associated with gene expression levels of BMP4, TEX41, and EIFBP41. Gene set analysis highlighted significant enrichment in renal system vasculature morphogenesis, and tissue enrichment analysis ranked the pituitary gland as the top association. LARGE SCALE DATA: The GWAS meta-analysis summary statistics are available for download from the GWAS Catalogue with accession number GCST90428625. LIMITATIONS, REASONS FOR CAUTION: This study only included women of European ancestry and the lack of sufficiently sized relevant tissue data in gene expression datasets hinders the assessment of potential regulatory effects in reproductive tissues. WIDER IMPLICATIONS OF THE FINDINGS: Our results highlight the increased power of founder populations and larger sample sizes to boost the discovery of novel trait-associated variants underlying variation in AMH levels, which aided the characterization of GWAS signals enrichment in different biological pathways and plausible genetic regulatory effects linked with AMH level variation for the first time. 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 Sklodowska-Curie Grant Agreement No. 813707 and Oulu University Scholarship Foundation and Paulon Säätiö Foundation. (N.P.-G.), Academy of Finland, Sigrid Jusélius Foundation, Novo Nordisk, University of Oulu, Roche Diagnostics (T.T.P.). This work was supported by the Estonian Research Council Grant 1911 (R.M.). J.R. was supported by the European Union's Horizon 2020 Research and Innovation Program under Grant Agreements No. 874739 (LongITools), 824989 (EUCAN-Connect), 848158 (EarlyCause), and 733206 (LifeCycle). U.V. was supported by the Estonian Research Council grant PRG (PRG1291). The NFBC1966 received financial support from University of Oulu Grant No. 24000692, Oulu University Hospital Grant No. 24301140, and ERDF European Regional Development Fund Grant No. 539/2010 A31592. T.T.P. has received grants from Roche, Perkin Elmer, and honoraria for scientific presentations from Gedeon Richter, Exeltis, Astellas, Roche, Stragen, Astra Zeneca, Merck, MSD, Ferring, Duodecim, and Ajaton Terveys. For all other authors, there are no competing interests.

Utility of Serum Anti-Müllerian Hormone Measurement as Part of Polycystic Ovary Syndrome Diagnosis.

The 2023 international evidence-based guideline update for the assessment and management of polycystic ovary syndrome (PCOS) recommends using the Rotterdam criteria for the diagnosis of PCOS. The updated guideline has evidence-based recommendation for the diagnosis, and it now also includes serum anti-Müllerian hormone (AMH) measurement as an alternative tool for gynecological ultrasound to diagnose polycystic ovary morphology (PCOM). The aim of this new recommendation was to facilitate PCOS diagnostic workup in primary care and other disciplines, as currently most diagnosing is done in gynecology and infertility clinics. Here, we review factors affecting AMH levels as well as the utility of AMH in PCOS diagnosis. We identified relevant studies that report different cut-offs for AMH to diagnose PCOM as part of PCOS diagnosis. There are, however, some limitations when using AMH that should be acknowledged. These include physiological aspects like age, ethnicity, and obesity and iatrogenic causes like hormonal medication and ovarian surgery. Also reference ranges are different depending on AMH assay used. As a summary, we conclude that AMH is a usable tool in PCOM diagnostics, but it does not have a single cut-off. Therefore, further studies are needed to establish age and assay-based reference ranges.

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.

Dynamic changes in AI-based analysis of endometrial cellular composition: Analysis of PCOS and RIF endometrium.

Background: The human endometrium undergoes a monthly cycle of tissue growth and degeneration. During the mid-secretory phase, the endometrium establishes an optimal niche for embryo implantation by regulating cellular composition (e.g., epithelial and stromal cells) and differentiation. Impaired endometrial development observed in conditions such as polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) contributes to infertility. Surprisingly, despite the importance of the endometrial lining properly developing prior to pregnancy, precise measures of endometrial cellular composition in these two infertility-associated conditions are entirely lacking. Additionally, current methods for measuring the epithelial and stromal area have limitations, including intra- and inter-observer variability and efficiency. Methods: We utilized a deep-learning artificial intelligence (AI) model, created on a cloud-based platform and developed in our previous study. The AI model underwent training to segment both areas populated by epithelial and stromal endometrial cells. During the training step, a total of 28.36 mm2 areas were annotated, comprising 2.56 mm2 of epithelium and 24.87 mm2 of stroma. Two experienced pathologists validated the performance of the AI model. 73 endometrial samples from healthy control women were included in the sample set to establish cycle phase-dependent dynamics of the endometrial epithelial-to-stroma ratio from the proliferative (PE) to secretory (SE) phases. In addition, 91 samples from PCOS cases, accounting for the presence or absence of ovulation and representing all menstrual cycle phases, and 29 samples from RIF patients on day 5 after progesterone administration in the hormone replacement treatment cycle were also included and analyzed in terms of cellular composition. Results: Our AI model exhibited reliable and reproducible performance in delineating epithelial and stromal compartments, achieving an accuracy of 92.40% and 99.23%, respectively. Moreover, the performance of the AI model was comparable to the pathologists' assessment, with F1 scores exceeding 82% for the epithelium and >96% for the stroma. Next, we compared the endometrial epithelial-to-stromal ratio during the menstrual cycle in women with PCOS and in relation to endometrial receptivity status in RIF patients. The ovulatory PCOS endometrium exhibited epithelial cell proportions similar to those of control and healthy women's samples in every cycle phase, from the PE to the late SE, correlating with progesterone levels (control SE, r2 = 0.64, FDR < 0.001; PCOS SE, r2 = 0.52, FDR < 0.001). The mid-SE endometrium showed the highest epithelial percentage compared to both the early and late SE endometrium in both healthy women and PCOS patients. Anovulatory PCOS cases showed epithelial cellular fractions comparable to those of PCOS cases in the PE (Anovulatory, 14.54%; PCOS PE, 15.56%, p = 1.00). We did not observe significant differences in the epithelial-to-stroma ratio in the hormone-induced endometrium in RIF patients with different receptivity statuses. Conclusion: The AI model rapidly and accurately identifies endometrial histology features by calculating areas occupied by epithelial and stromal cells. The AI model demonstrates changes in epithelial cellular proportions according to the menstrual cycle phase and reveals no changes in epithelial cellular proportions based on PCOS and RIF conditions. In conclusion, the AI model can potentially improve endometrial histology assessment by accelerating the analysis of the cellular composition of the tissue and by ensuring maximal objectivity for research and clinical purposes.

Validation of an Anti-Müllerian Hormone Cutoff for Polycystic Ovarian Morphology in the Diagnosis of Polycystic Ovary Syndrome in the HARMONIA Study: Protocol for a Prospective, Noninterventional Study.

BACKGROUND: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women and is diagnosed using the Rotterdam criteria, including diagnosis of polycystic ovarian morphology (PCOM) by transvaginal ultrasound (TVUS). Due to high cost, availability, and the impact of the operator and ultrasound equipment on the reliability of the antral follicle count (AFC) by TVUS, an unmet need exists for a diagnostic test to determine PCOM without TVUS. A strong positive correlation between elevated anti-Müllerian hormone (AMH) levels and AFCs has been demonstrated in women with PCOS. In addition, recent updates to the international evidence-based PCOS guidelines state that serum AMH can be used as an alternative to TVUS-determined AFC, in the diagnosis of PCOM. The retrospective APHRODITE study derived and validated an AMH cutoff of 3.2 ng/mL for the Elecsys AMH Plus or Elecsys AMH assays (Roche) to diagnose PCOM in patients with PCOS. OBJECTIVE: This study aims to further validate, in an independent prospective cohort, the AMH cutoff (3.2 ng/mL) for PCOM determination, which was previously derived and validated in the APHRODITE study. METHODS: This large, prospective, multicenter, population-based, noninterventional study will evaluate the previously established AMH cutoff for the determination of PCOM during the diagnosis of PCOS using the Elecsys AMH Plus immunoassay in an independent population. Participants were women born between July 1985 and December 1987 in Northern Finland; the study partially links to the Northern Finland Birth Cohort 1986. We assessed the enrolled women, determined with the 2023 PCOS Guidelines, for current PCOS status and divided them by phenotype if positive. Each participant had 1 study visit to collect serum samples, record clinical data, and undergo a gynecological examination including TVUS. All data were collected by highly trained midwives or trained gynecologists. Sensitivity, specificity, and agreement measures were used to validate the previously determined cutoff in the whole population and in subpopulations based on phenotype and relevant demographic or clinical factors. The minimum target sample size was approximately 1800 women, including approximately 10% with PCOS. RESULTS: At the time of manuscript submission, participant recruitment had concluded, and 1803 women were enrolled into the study. Data collection is complete and biostatistical analysis is planned for 2023. CONCLUSIONS: To limit variability, there were few TVUS operators and only 2 TVUS machines of the same type. Additionally, all women who were taking oral contraceptives were excluded from the primary analysis population. Selection bias was limited as this was a population-based study and participants were not seeking treatment for PCOS symptoms. Validating the AMH cutoff in a large, population-based study will provide further evidence on the utility of the Elecsys AMH Plus or Elecsys AMH assays in PCOM diagnosis as an alternative to TVUS. Measuring AMH for PCOM diagnosis could reduce delayed or missed diagnoses due to operator-dependent TVUS examinations. TRIAL REGISTRATION: ClinicalTrials.gov NCT05527353; http://tinyurl.com/2f3ffbdz. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48854.

Low testosterone at age 31 associates with maternal obesity and higher body mass index from childhood until age 46: A birth cohort study.

BACKGROUND: Low testosterone (T) levels in men associate with increased risks of obesity, type 2 diabetes, metabolic syndrome, and cardiovascular diseases. However, most studies are cross-sectional with follow-up-time < 10 years, and data on early growth are limited. OBJECTIVE: To compare prenatal factors and body mass index (BMI) development from birth to age 46 in relation to low T at age 31. MATERIALS AND METHODS: Men with low T (T < 12.1 nmol/L, n = 132) and men with normal T at age 31 (n = 2561) were derived from the Northern Finland Birth Cohort 1966. Prenatal factors, longitudinal weight and height data from birth to age 14, and cross-sectional weight and height data at ages 31 and 46, and waist-hip-ratio (WHR) and T levels at age 31 were analyzed. Longitudinal modeling and timing of adiposity rebound (AR, second BMI rise at age 5-7 years) were calculated from fitted BMI curves. Results were adjusted for mother's pre-pregnancy BMI and smoking status, birth weight for gestational age, alcohol consumption, education level, smoking status, and WHR at age 31. RESULTS: Neither gestational age nor birth weight was associated with low T at age 31; however, maternal obesity during gestation was more prevalent among men with low T (9.8% vs. 3.5%, adjusted aOR: 2.43 [1.19-4.98]). Men with low T had earlier AR (5.28 vs. 5.82, aOR: 0.73 [0.56-0.94]) and higher BMI (p < 0.001) from AR onward until age 46. Men with both early AR and low T had the highest BMI from AR onward. CONCLUSIONS: In men, maternal obesity and early weight gain associate with lower T levels at age 31, independently of adulthood abdominal obesity. Given the well-known health risks related to obesity, and the rising prevalence of maternal obesity, the results of the present study emphasize the importance of preventing obesity that may also affect the later reproductive health of the offspring.

Induced Pluripotent Stem Cells as a Possible Approach for Exploring the Pathophysiology of Polycystic Ovary Syndrome (PCOS).

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine condition among women with pleiotropic sequelae possessing reproductive, metabolic, and psychological characteristics. Although the exact origin of PCOS is elusive, it is known to be a complex multigenic disorder with a genetic, epigenetic, and environmental background. However, the pathogenesis of PCOS, and the role of genetic variants in increasing the risk of the condition, are still unknown due to the lack of an appropriate study model. Since the debut of induced pluripotent stem cell (iPSC) technology, the ability of reprogrammed somatic cells to self-renew and their potential for multidirectional differentiation have made them excellent tools to study different disease mechanisms. Recently, researchers have succeeded in establishing human in vitro PCOS disease models utilizing iPSC lines from heterogeneous PCOS patient groups (iPSCPCOS). The current review sets out to summarize, for the first time, our current knowledge of the implications and challenges of iPSC technology in comprehending PCOS pathogenesis and tissue-specific disease mechanisms. Additionally, we suggest that the analysis of polygenic risk prediction based on genome-wide association studies (GWAS) could, theoretically, be utilized when creating iPSC lines as an additional research tool to identify women who are genetically susceptible to PCOS. Taken together, iPSCPCOS may provide a new paradigm for the exploration of PCOS tissue-specific disease mechanisms.