-
EBioMedicine Nov 2023Polycystic ovary syndrome (PCOS) is the most common endocrine disorder leading to anovulatory infertility. Abnormalities in the central neuroendocrine system governed by...
BACKGROUND
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder leading to anovulatory infertility. Abnormalities in the central neuroendocrine system governed by gonadotropin-releasing hormone (GnRH) neurons might be related to ovarian dysfunction in PCOS, although the link in this disordered brain-to-ovary communication remains unclear. Here, we manipulated GnRH neurons using chemogenetics in adult female mice to unveil whether chronic overaction of these neurons would trigger PCOS-like hormonal and reproductive impairments.
METHODS
We used adult Gnrh1 female mice to selectively target and express the designer receptors exclusively activated by designer drugs (DREADD)-based chemogenetic tool hM3D(Gq) in hypophysiotropic GnRH neurons. Chronic chemogenetic activation protocol was carried out with clozapine N-oxide (CNO) i.p. injections every 48 h over a month. We evaluated the reproductive and hormonal profile before, during, and two months after chemogenetic manipulations.
FINDINGS
We discovered that the overactivation of GnRH neurons was sufficient to disrupt reproductive cycles, promote hyperandrogenism, and induce ovarian dysfunction. These PCOS features were detected with a long-lasting neuroendocrine dysfunction through abnormally high luteinizing hormone (LH) pulse secretion. Additionally, the GnRH-R blockade prevented the establishment of long-term neuroendocrine dysfunction and androgen excess in these animals.
INTERPRETATION
Taken together, our results show that hyperactivity of hypothalamic GnRH neurons is a major driver of reproductive and hormonal impairments in PCOS and suggest that antagonizing the aberrant GnRH signaling could be an efficient therapeutic venue for the treatment of PCOS.
FUNDING
European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement n◦ 725149).
Topics: Humans; Female; Mice; Animals; Polycystic Ovary Syndrome; Luteinizing Hormone; Gonadotropin-Releasing Hormone; Neurons
PubMed: 37898094
DOI: 10.1016/j.ebiom.2023.104850 -
European Radiology Experimental Dec 2023To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based...
PURPOSE
To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.
METHODS
A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established "no-new-Net" framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.
RESULTS
Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10, 3 × 10, 4 × 10, respectively), and for the omental lesions on the evaluation set (p = 1 × 10). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.
CONCLUSION
Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.
RELEVANCE STATEMENT
Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.
KEY POINTS
• The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented. • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists. • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines.
Topics: Humans; Female; Deep Learning; Ovarian Cysts; Ovarian Neoplasms; Neural Networks, Computer; Tomography, X-Ray Computed
PubMed: 38057616
DOI: 10.1186/s41747-023-00388-z -
Journal of Ovarian Research Jul 2023Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disorder that frequently exhibits low-grade inflammation, pro-oxidant activity, and gut dysbiosis....
BACKGROUND
Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disorder that frequently exhibits low-grade inflammation, pro-oxidant activity, and gut dysbiosis. PCOS has become one of the leading causes of female infertility worldwide. Recently, omega-3 polyunsaturated fatty acids (PUFAs) have been proven to benefit metabolic disorders in PCOS patients. However, its roles in the regulation of metabolic and endocrinal balances in PCOS pathophysiology are not clear. In the present study, we aimed to explore how omega-3 PUFAs alleviate ovarian dysfunction and insulin resistance in mice with dehydroepiandrosterone (DHEA)-induced PCOS by modulating the gut microbiota.
METHODS
We induced PCOS in female mice by injecting them with DHEA and then treated them with omega-3 PUFAs. 16S ribosomal DNA (rDNA) amplicon sequencing, fecal microbiota transplantation (FMT) and antibiotic treatment were used to evaluate the role of microbiota in the regulation of ovarian functions and insulin resistance (IR) by omega-3 PUFAs. To further investigate the mechanism of gut microbiota on omega-3-mediated ovarian and metabolic protective effects, inflammatory and oxidative stress markers in ovaries and thermogenic markers in subcutaneous and brown adipose tissues were investigated.
RESULTS
We found that oral supplementation with omega-3 PUFAs ameliorates the PCOS phenotype. 16S rDNA analysis revealed that omega-3 PUFA treatment increased the abundance of beneficial bacteria in the gut, thereby alleviating DHEA-induced gut dysbiosis. Antibiotic treatment and FMT experiments further demonstrated that the mechanisms underlying omega-3 benefits likely involve direct effects on the ovary to inhibit inflammatory cytokines such as IL-1β, TNF-α and IL-18. In addition, the gut microbiota played a key role in the improvement of adipose tissue morphology and function by decreasing multilocular cells and thermogenic markers such as Ucp1, Pgc1a, Cited and Cox8b within the subcutaneous adipose tissues.
CONCLUSION
These findings indicate that omega-3 PUFAs ameliorate androgen-induced gut microbiota dysbiosis. The gut microbiota plays a key role in the regulation of omega-3-mediated IR protective effects in polycystic ovary syndrome mice. Moreover, omega-3 PUFA-regulated improvements in the ovarian dysfunction associated with PCOS likely involve direct effects on the ovary to inhibit inflammation. Our findings suggest that omega-3 supplementation may be a promising therapeutic approach for the treatment of PCOS by modulating gut microbiota and alleviating ovarian dysfunction and insulin resistance.
Topics: Animals; Female; Mice; Dehydroepiandrosterone; Gastrointestinal Microbiome; Insulin Resistance; Polycystic Ovary Syndrome; Fatty Acids, Omega-3; Dietary Supplements
PubMed: 37443082
DOI: 10.1186/s13048-023-01227-w -
Frontiers in Immunology 2023Ovulation dysfunction is now a widespread cause of infertility around the world. Although the impact of immune cells in human reproduction has been widely investigated,...
INTRODUCTION
Ovulation dysfunction is now a widespread cause of infertility around the world. Although the impact of immune cells in human reproduction has been widely investigated, systematic understanding of the changes of the immune atlas under female ovulation remain less understood.
METHODS
Here, we generated single cell transcriptomic profiles of 80,689 PBMCs in three representative statuses of ovulation dysfunction, i.e., polycystic ovary syndrome (PCOS), primary ovarian insufficiency (POI) and menopause (MENO), and identified totally 7 major cell types and 25 subsets of cells.
RESULTS
Our study revealed distinct cluster distributions of immune cells among individuals of ovulation disorders and health. In patients with ovulation dysfunction, we observed a significant reduction in populations of naïve CD8 T cells and effector memory CD4 T cells, whereas circulating NK cells and regulatory NK cells increased.
DISCUSSION
Our results highlight the significant contribution of cDC-mediated signaling pathways to the overall inflammatory response within ovulation disorders. Furthermore, our data demonstrated a significant upregulation of oxidative stress in patients with ovulation disorder. Overall, our study gave a deeper insight into the mechanism of PCOS, POI, and menopause, which may contribute to the better diagnosis and treatments of these ovulatory disorder.
Topics: Female; Humans; Polycystic Ovary Syndrome; Transcriptome; Ovulation; Infertility, Female
PubMed: 38116006
DOI: 10.3389/fimmu.2023.1297484 -
ELife Jul 2023Variations in B cell numbers are associated with polycystic ovary syndrome (PCOS) through unknown mechanisms. Here, we demonstrate that B cells are not central mediators...
Variations in B cell numbers are associated with polycystic ovary syndrome (PCOS) through unknown mechanisms. Here, we demonstrate that B cells are not central mediators of PCOS pathology and that their frequencies are altered as a direct effect of androgen receptor activation. Hyperandrogenic women with PCOS have increased frequencies of age-associated double-negative B memory cells and increased levels of circulating immunoglobulin M (IgM). However, the transfer of serum IgG from women into wild-type female mice induces only an increase in body weight. Furthermore, RAG1 knockout mice, which lack mature T- and B cells, fail to develop any PCOS-like phenotype. In wild-type mice, co-treatment with flutamide, an androgen receptor antagonist, prevents not only the development of a PCOS-like phenotype but also alterations of B cell frequencies induced by dihydrotestosterone (DHT). Finally, B cell-deficient mice, when exposed to DHT, are not protected from developing a PCOS-like phenotype. These results urge further studies on B cell functions and their effects on autoimmune comorbidities highly prevalent among women with PCOS.
Topics: Humans; Female; Mice; Animals; Polycystic Ovary Syndrome; Androgens; Body Weight; Phenotype
PubMed: 37401759
DOI: 10.7554/eLife.86454 -
Biomolecules Jul 2023Polycystic ovary syndrome (PCOS) is a prevalent metabolic and reproductive disorder that causes low fertility in females. Despite its detrimental effects on women's... (Review)
Review
Polycystic ovary syndrome (PCOS) is a prevalent metabolic and reproductive disorder that causes low fertility in females. Despite its detrimental effects on women's health, care for PCOS has been impeded by its undefined pathogenesis. Thus, there is an urgent need to explore novel biomarkers and therapeutic targets for the diagnosis and treatment of PCOS. Circular RNAs (circRNAs) are a class of noncoding RNAs with covalently closed cyclic structures, present in high abundance, and show development-stage specific expression patterns. Recent studies have demonstrated that circRNAs participate in PCOS progression by modulating various biological functions, including cell proliferation, apoptosis, and steroidogenesis. In addition, circRNAs are widely present in the follicular fluid of women with PCOS, indicating their potential as diagnostic biomarkers and therapeutic targets for PCOS. This review provides the current knowledge of circRNAs in PCOS, including their regulatory functions and molecular mechanisms, and explores their potential as diagnostic biomarkers and therapeutic targets.
Topics: Humans; Female; Polycystic Ovary Syndrome; RNA, Circular; Biomarkers; Follicular Fluid
PubMed: 37509138
DOI: 10.3390/biom13071101 -
Frontiers in Endocrinology 2023Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity....
INTRODUCTION
Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS.
METHODS
We applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022.
RESULTS
135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies).
CONCLUSION
Artificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier CRD42022295287.
Topics: Female; Humans; Artificial Intelligence; Polycystic Ovary Syndrome; Proteomics; Machine Learning; Cluster Analysis
PubMed: 37790605
DOI: 10.3389/fendo.2023.1106625 -
CMAJ : Canadian Medical Association... Jan 2024
-
Hormones (Athens, Greece) Sep 2023Polycystic ovary syndrome (PCOS) is a complex endocrine disease that can cause female infertility and bring economic burden to families and to society. The clinical... (Review)
Review
Polycystic ovary syndrome (PCOS) is a complex endocrine disease that can cause female infertility and bring economic burden to families and to society. The clinical and/or biochemical manifestations include hyperandrogenism, persistent anovulation, and polycystic ovarian changes, often accompanied by insulin resistance and obesity. Although its pathogenesis is unclear, PCOS involves the abnormal regulation of the hypothalamic-pituitary-ovarian axis and the abnormal activation of GnRH neurons. Neuropeptide Y (NPY) is widely distributed in the arcuate nucleus of the hypothalamus and functions as the physiological integrator of two neuroendocrine systems, one governing feeding and the other controlling reproduction. In recent years, an increasing number of studies have focused on the improvement of the reproductive and metabolic status of PCOS through the therapeutic application of NPY and its receptors. In this review, we summarize the central and peripheral regulation of NPY and its receptors in the development of PCOS and discuss the potential for NPY receptor-related therapies for PCOS.
Topics: Female; Humans; Polycystic Ovary Syndrome; Receptors, Neuropeptide Y; Hyperandrogenism; Gonadotropin-Releasing Hormone
PubMed: 37452264
DOI: 10.1007/s42000-023-00460-8 -
Current Obesity Reports Mar 2024The goal of the present review is to address the main adiposity-related alterations in Polycystic Ovary Syndrome (PCOS) focusing on hypothalamic-pituitary-ovarian... (Review)
Review
Hypothalamic-Ovarian axis and Adiposity Relationship in Polycystic Ovary Syndrome: Physiopathology and Therapeutic Options for the Management of Metabolic and Inflammatory Aspects.
PURPOSE OF REVIEW
The goal of the present review is to address the main adiposity-related alterations in Polycystic Ovary Syndrome (PCOS) focusing on hypothalamic-pituitary-ovarian (H-P-O) axis and to provide an overview of nutraceutical and pharmacological therapeutic strategies.
RECENT FINDINGS
Female reproduction is a complex and delicate interplay between neuroendocrine signals involving the H-P-O axis. Elements that disrupt the balance of these interactions can lead to metabolic and reproductive disorders, such as PCOS. This disorder includes menstrual, metabolic, and biochemical abnormalities as well as hyperandrogenism, oligo-anovulatory menstrual cycles, insulin resistance, and hyperleptinemia which share an inflammatory state with other chronic diseases. Moreover, as in a self-feeding cycle, high androgen levels in PCOS lead to visceral fat deposition, resulting in insulin resistance and hyperinsulinemia, further stimulating ovarian and adrenal androgen production. In fact, regardless of age and BMI, women with PCOS have more adipose tissue and less lean mass than healthy women. Excessive adiposity, especially visceral adiposity, is capable of affecting female reproduction through direct mechanisms compromising the luteal phase, and indirect mechanisms as metabolic alterations able to affect the function of the H-P-O axis. The intricate crosstalk between adiposity, inflammatory status and H-P-O axis function contributes to the main adiposity-related alterations in PCOS, and alongside currently available hormonal treatments, nutraceutical and pharmacological therapeutic strategies can be exploited to treat these alterations, in order to enable a more comprehensive synergistic and tailored treatment.
Topics: Female; Humans; Polycystic Ovary Syndrome; Insulin Resistance; Adiposity; Androgens; Hyperandrogenism; Obesity
PubMed: 38172476
DOI: 10.1007/s13679-023-00531-2