Aging promotes accumulation of senescent and multiciliated cells in human endometrial epithelium.

STUDY QUESTION: What changes occur in the endometrium during aging, and do they impact fertility? SUMMARY ANSWER: Both the transcriptome and cellular composition of endometrial samples from women of advanced maternal age (AMA) are significantly different from that of samples from young women, suggesting specific changes in epithelial cells that may affect endometrial receptivity. WHAT IS KNOWN ALREADY: Aging is associated with the accumulation of senescent cells in aging tissues. Reproductive aging is mostly attributed to the decline in ovarian reserve and oocyte quality, whereas the endometrium is a unique complex tissue that is monthly renewed under hormonal regulation. Several clinical studies have reported lower implantation and pregnancy rates in oocyte recipients of AMA during IVF. Molecular studies have indicated the presence of specific mutations within the epithelial cells of AMA endometrium, along with altered gene expression of bulk endometrial tissue. STUDY DESIGN SIZE DURATION: Endometrial transcriptome profiling was performed for 44 women undergoing HRT during the assessment of endometrial receptivity before IVF. Patients younger than 28 years were considered as the young maternal age (YMA) group (age 23-27 years) and women older than 45 years were considered as the AMA group (age 47-50 years). Endometrial biopsies were obtained on Day 5 of progesterone treatment and RNA was extracted. All endometrial samples were evaluated as being receptive based on the expression of 68 common endometrial receptivity markers. Endometrial samples from another 24 women classified into four age groups (YMA, intermediate age group 1 (IMA1, age 29-35), intermediate age group 2 (IMA2, age 36-44), and AMA) were obtained in the mid-secretory stage of a natural cycle (NC) and used for validation studies across the reproductive lifespan. PARTICIPANTS/MATERIALS SETTING METHODS: A total of 24 HRT samples (12 YMA and 12 AMA) were subject to RNA sequencing (RNA-seq) and differential gene expression analysis, 20 samples (10 YMA and 10 AMA) were used for qPCR validation, and 24 NC samples (6 YMA, 6 IMA1, 6 IMA2 and 6AMA) were used for RNA-seq validation of AMA genes across the woman's reproductive lifespan. Immunohistochemistry (IHC) was used to confirm some expression changes at the protein level. Computational deconvolution using six endometrial cell type-specific transcriptomic profiles was conducted to compare the cellular composition between the groups. MAIN RESULTS AND THE ROLE OF CHANCE: Comparisons between YMA and AMA samples identified a lower proportion of receptive endometria in the AMA group (P = 0.007). Gene expression profiling identified 491 differentially expressed age-sensitive genes (P adj < 0.05) that revealed the effects of age on endometrial epithelial growth and receptivity, likely contributing to decreased reproductive performance. Our results indicate that changes in the expression of the cellular senescence marker p16INK4a and genes associated with metabolism, inflammation, and hormone response are involved in endometrial aging. Importantly, we demonstrate that the proportion of multi-ciliated cells, as discovered based on RNA-seq data deconvolution and tissue IHC results, is affected by endometrial aging, and propose a putative onset of age-related changes. Furthermore, we propose that aging has an impact on the transcriptomic profile of endometrial tissue in the context of endometrial receptivity. LARGE SCALE DATA: The raw sequencing data reported in this article are deposited at the Gene Expression Omnibus under accession code GSE236128. LIMITATIONS REASONS FOR CAUTION: This retrospective study identified changes in the endometrium of patients undergoing hormonal replacement and validated these changes using samples obtained during a NC. However, future studies must clarify the importance of these findings on the clinical outcomes of assisted reproduction. WIDER IMPLICATIONS OF THE FINDINGS: The findings reported in this study have important implications for devising future strategies aimed at improving fertility management in women of advanced reproductive age. STUDY FUNDING/COMPETING INTERESTS: This research was funded by the Estonian Research Council (grant no. PRG1076), Horizon 2020 innovation grant (ERIN, grant no. EU952516), Enterprise Estonia (grant no. EU48695), MSCA-RISE-2020 project TRENDO (grant no. 101008193), EU 874867 project HUTER, the Horizon Europe NESTOR grant (grant no. 101120075) of the European Commission, the EVA specialty program (grant no. KP111513) of the Maastricht University Medical Center (MUMC+), MICIU/AEI/10.13039/501100011033 and FEDER, EU projects Endo-Map (grant no. PID2021-12728OB-100), ROSY (grant no. CNS2022-135999), and the National Science Fund of Bulgaria (grant no. KII-06 H31/2). The authors declare no competing interests.

In-depth analysis of transcriptomes in ovarian cortical follicles from children and adults reveals interfollicular heterogeneity.

The ovarian cortical reserve of follicles is vital for fertility. Some medical treatments are toxic to follicles, leading to premature ovarian insufficiency. Ovarian tissue cryopreservation is an established method to preserve fertility in adults and even applied in prepuberty despite unproven efficacy. Here, we analyze transcriptomes of 120 cortical follicles from children and adults for detailed comparison. We discover heterogeneity with two main types of follicles in both age groups: one with expected oocyte-granulosa profiles and another with predicted role in signaling. Transcriptional changes during growth to the secondary stage are similar overall in children and adults, but variations related to extracellular matrix, theca cells, and miRNA profiles are found. Notably, cyclophosphamide dose correlates with interferon signaling in child follicles. Additionally, morphology alone is insufficient for follicle categorization suggesting a need for additional markers. Marker genes for early follicle activation are determined. These findings will help refine follicular classification and fertility preservation techniques across critical ages.

Endometriotic lesions exhibit distinct metabolic signature compared to paired eutopic endometrium at the single-cell level.

Current therapeutics of endometriosis focus on hormonal disruption of endometriotic lesions (ectopic endometrium, EcE). Recent findings show higher glycolysis utilization in EcE, suggesting non-hormonal strategy for disease treatment that addresses cellular metabolism. Identifying metabolically altered cell types in EcE is important for targeted metabolic drug therapy without affecting eutopic endometrium (EuE). Here, using single-cell RNA-sequencing, we examine twelve metabolic pathways in paired samples of EuE and EcE from women with confirmed endometriosis. We detect nine major cell types in both EuE and EcE. Metabolic pathways are most differentially regulated in perivascular, stromal, and endothelial cells, with the highest changes in AMPK signaling, HIF-1 signaling, glutathione metabolism, oxidative phosphorylation, and glycolysis. We identify transcriptomic co-activation of glycolytic and oxidative metabolism in perivascular and stromal cells of EcE, indicating a critical role of metabolic reprogramming in maintaining endometriotic lesion growth. Perivascular cells, involved in endometrial stroma repair and angiogenesis, may be potential targets for non-hormonal treatment of endometriosis.

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.

Reduced ovarian cholesterol and steroid biosynthesis along with increased inflammation are associated with high DEHP metabolite levels in human ovarian follicular fluids.

The plasticizer di(2-ethylhexyl) phthalate (DEHP) is known to have endocrine-disrupting properties mediated by its many metabolites that form upon exposure in biological systems. In a previous study, we reported an inverse association between DEHP metabolites in the human ovarian follicular fluid (FF) and the responsiveness of the follicles to controlled ovarian stimulation during in vitro fertilization (IVF) treatments. Here, we explored this association further through molecular analysis of the ovarian FF samples. Ninety-six IVF patients from Swedish (N = 48) and Estonian (N = 48) infertility clinics were selected from the previous cohort (N = 333) based on the molar sum of DEHP metabolites in their FF samples to arrive at "high" (mean 7.7 ± SD 2.3 nM, N = 48) and "low" (0.8 ± 0.4 nM, N = 48) exposure groups. Extracellular miRNA levels and concentrations of 15 steroid hormones were measured across FF samples. In addition, FF somatic cells, available for the Estonian patients, were used for RNA sequencing. Differential expression (DE) and interactions between miRNA and mRNA networks revealed that the expression levels of genes in the cholesterol biosynthesis and steroidogenesis pathways were significantly decreased in the high compared to the low DEHP group. In addition, the DE miRNAs were predicted to target key enzymes within these pathways (FDR < 0.05). A decreased 17-OH-progesterone to progesterone ratio was observed in the FF of the high DEHP group (p < 0.05). Additionally, the expression levels of genes associated with inflammatory processes were elevated in the FF somatic cells, and a computational cell-type deconvolution analysis suggested an increased immune cell infiltration into the high DEHP follicles (p < 0.05). In conclusion, elevated DEHP levels in FF were associated with a significantly altered follicular milieu within human ovaries, involving a pro-inflammatory environment and reduced cholesterol metabolism, including steroid synthesis. These results contribute to our understanding of the molecular mechanisms of female reprotoxic effects of DEHP.

Carboxypeptidase Inhibitor LXN Expression in Endometrial Tissue Is Menstrual Cycle Phase-Dependent and Is Upregulated in Endometriotic Lesions.

Endometriosis is a chronic hormone-dependent disease characterized by the spread of endometrial cells outside the uterus, which form endometriotic lesions and disrupt the functions of the affected organs. The etiopathogenesis of endometriosis is still unclear, and thus it is important to examine the genes that may contribute to the establishment of endometriotic lesions. The aim of this study was to investigate the expression of new potential candidate gene latexin (LXN), an inhibitor of carboxypeptidases, in endometrium and endometriotic lesions to elucidate its possible role in endometriosis development. LXN expression in tissues was assessed using quantitative reverse transcription PCR (qRT-PCR) analysis and immunohistochemical staining (IHC). The functions of LXN were examined using Transwell and MTT assays. qRT-PCR analysis revealed that LXN expression in endometrium was menstrual cycle-dependent, being lowest in the early-secretory phase and highest in the late-secretory phase and was significantly upregulated in endometriotic lesions. IHC confirmed LXN expression in endometrial stromal cells, and in vitro assays demonstrated that knockdown of LXN effectively reduced the migratory capacity of endometrial stromal cells while promoting cell viability. In conclusion, our results showed that LXN can be involved in the pathogenesis of endometriosis by regulating the proliferation and migration activity of endometriotic stromal cells.

Epidemiologically relevant phthalates affect human endometrial cells in vitro through cell specific gene expression changes related to the cytoskeleton and mitochondria.

Phthalates are endocrine disrupting chemicals (EDCs) found in common consumer products such as soft plastics and cosmetics. Although the knowledge regarding the adverse effects of phthalates on female fertility are accumulating, information on the hormone sensitive endometrium is still scarce. Here, we studied the effects of phthalates on endometrial cell proliferation and gene expression. Human endometrial primary epithelial and stromal cells were isolated from healthy fertile-aged women (n=3), and were compared to endometrial cell lines T-HESC and Ishikawa. Three different epidemiologically relevant phthalate mixtures were used, defined by urine samples in the Midlife Women Health Study (MWHS) cohort. Mono (2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) was used as a single phthalate control. Cells were harvested for proliferation testing and transcriptomic analyses after 24 h exposure. Even though all cell models responded differently to the phthalate exposures, many overlapping differentially expressed genes (DEGs, FDR<0.1), related to cell adhesion, cytoskeleton and mitochondria were found in all cell types. The qPCR analysis confirmed that MEHHP significantly affected cell adhesion gene vinculin (VCL) and NADH:ubiquinone oxidoreductase subunit B7 (NDUFB7), important for oxidative phosphorylation. Benchmark dose modelling showed that MEHHP had significant concentration-dependent effects on cytoskeleton gene actin-beta (ACTB). In conclusion, short 24 h phthalate exposures significantly altered gene expression cell-specifically in human endometrial cells, with six shared DEGs. The mixture effects were similar to those of MEHHP, suggesting MEHHP could be the main driver in the mixture. Impact of phthalate exposures on endometrial functions including receptivity should be addressed.

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.

Gut microbiome in endometriosis: a cohort study on 1000 individuals.

BACKGROUND: Endometriosis, defined as the presence of endometrial-like tissue outside of the uterus, is one of the most prevalent gynecological disorders. Although different theories have been proposed, its pathogenesis is not clear. Novel studies indicate that the gut microbiome may be involved in the etiology of endometriosis; nevertheless, the connection between microbes, their dysbiosis, and the development of endometriosis is understudied. This case-control study analyzed the gut microbiome in women with and without endometriosis to identify microbial targets involved in the disease. METHODS: A subsample of 1000 women from the Estonian Microbiome cohort, including 136 women with endometriosis and 864 control women, was analyzed. Microbial composition was determined by shotgun metagenomics and microbial functional pathways were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Partitioning Around Medoids (PAM) algorithm was performed to cluster the microbial profile of the Estonian population. The alpha- and beta-diversity and differential abundance analyses were performed to assess the gut microbiome (species and KEGG orthologies (KO)) in both groups. Metagenomic reads were mapped to estrobolome-related enzymes' sequences to study potential microbiome-estrogen metabolism axis alterations in endometriosis. RESULTS: Diversity analyses did not detect significant differences between women with and without endometriosis (alpha-diversity: all p-values > 0.05; beta-diversity: PERMANOVA, both R 2 < 0.0007, p-values > 0.05). No differential species or pathways were detected after multiple testing adjustment (all FDR p-values > 0.05). Sensitivity analysis excluding women at menopause (> 50 years) confirmed our results. Estrobolome-associated enzymes' sequence reads were not significantly different between groups (all FDR p-values > 0.05). CONCLUSIONS: Our findings do not provide enough evidence to support the existence of a gut microbiome-dependent mechanism directly implicated in the pathogenesis of endometriosis. To the best of our knowledge, this is the largest metagenome study on endometriosis conducted to date.

Prevalence and associated factors of bacterial vaginosis among pregnant women in Hue, Vietnam.

INTRODUCTION: Bacterial vaginosis (BV) is the most frequent vaginal infection affecting women of childbearing age worldwide. It is associated with significant adverse healthcare outcomes, especially during pregnancy. Although screening for BV could reduce potential pregnancy-related obstetric complications, there is no routine screening of pregnant women for BV in Vietnam. We aimed to identify the prevalence of BV among pregnant women and the associated factors in two tertiary hospitals in Hue, Vietnam. METHODOLOGY: This cross-sectional descriptive study included 885 pregnant women in third trimester, who received routine antenatal care in the Hue Central Hospital and Hue University Hospital of Medicine and Pharmacy, Hue city, Thua Thien Hue province, Vietnam. Gram-stained vaginal smears were used for calculating the Nugent score and recording the fungal elements. RESULTS: In total, 435 (49.1%) women had a normal BV score, 352 (39.8%) had intermediate vaginal microbiota, and 98 (11.1%) had BV. Among the 98 women with BV, 71 (72.4%) also had fungal infection. There was a significant association of BV with discharge (p = 0.004) and abnormal cervix (p = 0.014). BV was significantly more frequent among the women who reported previous abortion or miscarriage (p = 0.007). CONCLUSIONS: About a tenth of women in Thua Thien Hue province have BV in the third trimester of pregnancy being associated with previous adverse outcome. Discharge with fishy odour is still a characteristic feature among subtle clinical presentations of BV. Better awareness about this disease and routine test-and-treat management during pregnancy may improve pregnancy outcome.

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.

Endometrial Proliferative Phase-Centered View of Transcriptome Dynamics across the Menstrual Cycle.

The endometrium, the inner mucosal lining of the uterus, undergoes complex molecular and cellular changes across the menstrual cycle in preparation for embryo implantation. Transcriptome-wide analyses have mainly been utilized to study endometrial receptivity, the prerequisite for successful implantation, with most studies, so far, comparing the endometrial transcriptomes between (i) secretory and proliferative endometrium or (ii) mid-secretory and early secretory endometrium. In the current study, we provide a complete transcriptome description of the endometrium across the entire menstrual cycle and, for the first time, comprehensively characterize the proliferative phase of the endometrium. Our temporal transcriptome analysis includes five time points including the mid-proliferative, late proliferative (peri-ovulatory phase), early secretory, mid-secretory, and late secretory phases. Thus, we unveil exhaustively the transitions between the consecutive proliferative and secretory phases, highlighting their unique gene expression profiles and possible distinct biological functions. The transcriptome analysis reveals many differentially expressed genes (DEGs) across the menstrual cycle, most of which are phase-specific. As an example of coordinated gene activity, the expression profile of histone-encoding genes within the HIST cluster on chromosome 6 shows an increase in cluster activity during the late proliferative and a decline during the mid-secretory phase. Moreover, numerous DEGs are shared among all phases. In conclusion, in the current study, we delineate the endometrial proliferative phase-centered view of transcriptome dynamics across the menstrual cycle. Our data analysis highlights significant transcriptomic and functional changes occurring during the late proliferative phase-an essential transition point from the proliferative phase to the secretory phase. Future studies should explore how the biology of the late proliferative phase endometrium impacts the achievement of mid-secretory endometrial receptivity or contributes to molecular aberrations leading to embryo implantation failure.

The profile of steroid hormones in human fetal and adult ovaries.

BACKGROUND: Reproduction in women is at risk due to exposure to chemicals that can disrupt the endocrine system during different windows of sensitivity throughout life. Steroid hormone levels are fundamental for the normal development and function of the human reproductive system, including the ovary. This study aims to elucidate steroidogenesis at different life-stages in human ovaries. METHODS: We have developed a sensitive and specific LC-MS/MS method for 21 important steroid hormones and measured them at different life stages: in media from cultures of human fetal ovaries collected from elective terminations of normally progressing pregnancy and in media from adult ovaries from Caesarean section patients, and follicular fluid from women undergoing infertility treatment. Statistically significant differences in steroid hormone levels and their ratios were calculated with parametric tests. Principal component analysis (PCA) was applied to explore clustering of the ovarian-derived steroidogenic profiles. RESULTS: Comparison of the 21 steroid hormones revealed clear differences between the various ovarian-derived steroid profiles. Interestingly, we found biosynthesis of both canonical and "backdoor" pathway steroid hormones and corticosteroids in first and second trimester fetal and adult ovarian tissue cultures. 17α-estradiol, a less potent naturally occurring isomer of 17ß-estradiol, was detected only in follicular fluid. PCA of the ovarian-derived profiles revealed clusters from: adult ovarian tissue cultures with relatively high levels of androgens; first trimester and second trimester fetal ovarian tissue cultures with relatively low estrogen levels; follicular fluid with the lowest androgens, but highest corticosteroid, progestogen and estradiol levels. Furthermore, ratios of specific steroid hormones showed higher estradiol/ testosterone and estrone/androstenedione (indicating higher CYP19A1 activity, p < 0.01) and higher 17-hydroxyprogesterone/progesterone and dehydroepiandrosterone /androstenedione (indicating higher CYP17A1 activity, p < 0.01) in fetal compared to adult ovarian tissue cultures. CONCLUSIONS: Human ovaries demonstrate de novo synthesis of non-canonical and "backdoor" pathway steroid hormones and corticosteroids. Elucidating the steroid profiles in human ovaries improves our understanding of physiological, life-stage dependent, steroidogenic capacity of ovaries and will inform mechanistic studies to identify endocrine disrupting chemicals that affect female reproduction.

Mitochondrial Venus is more likely to have a lower birthweight.

Assisted reproductive technologies (ART) are associated with a moderately higher risk of preterm birth and low birthweight, but the causes are unknown. A recent study by Mertens et al. reveals a link between being born through ART, ovarian stimulation, and an increased incidence of mitochondrial heteroplasmic variants that correlate with lower birthweight.

Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.

STUDY QUESTION: Can generative artificial intelligence (AI) models produce high-fidelity images of human blastocysts? SUMMARY ANSWER: Generative AI models exhibit the capability to generate high-fidelity human blastocyst images, thereby providing substantial training datasets crucial for the development of robust AI models. WHAT IS KNOWN ALREADY: The integration of AI into IVF procedures holds the potential to enhance objectivity and automate embryo selection for transfer. However, the effectiveness of AI is limited by data scarcity and ethical concerns related to patient data privacy. Generative adversarial networks (GAN) have emerged as a promising approach to alleviate data limitations by generating synthetic data that closely approximate real images. STUDY DESIGN, SIZE, DURATION: Blastocyst images were included as training data from a public dataset of time-lapse microscopy (TLM) videos (n = 136). A style-based GAN was fine-tuned as the generative model. PARTICIPANTS/MATERIALS, SETTING, METHODS: We curated a total of 972 blastocyst images as training data, where frames were captured within the time window of 110-120 h post-insemination at 1-h intervals from TLM videos. We configured the style-based GAN model with data augmentation (AUG) and pretrained weights (Pretrained-T: with translation equivariance; Pretrained-R: with translation and rotation equivariance) to compare their optimization on image synthesis. We then applied quantitative metrics including Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) to assess the quality and fidelity of the generated images. Subsequently, we evaluated qualitative performance by measuring the intelligence behavior of the model through the visual Turing test. To this end, 60 individuals with diverse backgrounds and expertise in clinical embryology and IVF evaluated the quality of synthetic embryo images. MAIN RESULTS AND THE ROLE OF CHANCE: During the training process, we observed consistent improvement of image quality that was measured by FID and KID scores. Pretrained and AUG + Pretrained initiated with remarkably lower FID and KID values compared to both Baseline and AUG + Baseline models. Following 5000 training iterations, the AUG + Pretrained-R model showed the highest performance of the evaluated five configurations with FID and KID scores of 15.2 and 0.004, respectively. Subsequently, we carried out the visual Turing test, such that IVF embryologists, IVF laboratory technicians, and non-experts evaluated the synthetic blastocyst-stage embryo images and obtained similar performance in specificity with marginal differences in accuracy and sensitivity. LIMITATIONS, REASONS FOR CAUTION: In this study, we primarily focused the training data on blastocyst images as IVF embryos are primarily assessed in blastocyst stage. However, generation of an array of images in different preimplantation stages offers further insights into the development of preimplantation embryos and IVF success. In addition, we resized training images to a resolution of 256 × 256 pixels to moderate the computational costs of training the style-based GAN models. Further research is needed to involve a more extensive and diverse dataset from the formation of the zygote to the blastocyst stage, e.g. video generation, and the use of improved image resolution to facilitate the development of comprehensive AI algorithms and to produce higher-quality images. WIDER IMPLICATIONS OF THE FINDINGS: Generative AI models hold promising potential in generating high-fidelity human blastocyst images, which allows the development of robust AI models as it can provide sufficient training datasets while safeguarding patient data privacy. Additionally, this may help to produce sufficient embryo imaging training data with different (rare) abnormal features, such as embryonic arrest, tripolar cell division to avoid class imbalances and reach to even datasets. Thus, generative models may offer a compelling opportunity to transform embryo selection procedures and substantially enhance IVF outcomes. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by a Horizon 2020 innovation grant (ERIN, grant no. EU952516) and a Horizon Europe grant (NESTOR, grant no. 101120075) of the European Commission to A.S. and M.Z.E., the Estonian Research Council (grant no. PRG1076) to A.S., and the EVA (Erfelijkheid Voortplanting & Aanleg) specialty program (grant no. KP111513) of Maastricht University Medical Centre (MUMC+) to M.Z.E. TRIAL REGISTRATION NUMBER: Not applicable.

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.

The endometrial transcriptome of infertile women with and without implantation failure.

INTRODUCTION: Implantation failure after transferring morphologically "good-quality" embryos in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) may be explained by impaired endometrial receptivity. Analyzing the endometrial transcriptome analysis may reveal the underlying processes and could help in guiding prognosis and using targeted interventions for infertility. This exploratory study investigated whether the endometrial transcriptome profile was associated with short-term or long-term implantation outcomes (ie success or failure). MATERIAL AND METHODS: Mid-luteal phase endometrial biopsies of 107 infertile women with one full failed IVF/ICSI cycle, obtained within an endometrial scratching trial, were subjected to RNA-sequencing and differentially expressed genes analysis with covariate adjustment (age, body mass index, luteinizing hormone [LH]-day). Endometrial transcriptomes were compared between implantation failure and success groups in the short term (after the second fresh IVF/ICSI cycle) and long term (including all fresh and frozen cycles within 12 months). The short-term analysis included 85/107 women (33 ongoing pregnancy vs 52 no pregnancy), excluding 22/107 women. The long-term analysis included 46/107 women (23 'fertile' group, ie infertile women with a live birth after ≤3 embryos transferred vs 23 recurrent implantation failure group, ie no live birth after ≥3 good quality embryos transferred), excluding 61/107 women not fitting these categories. As both analyses drew from the same pool of 107 samples, there was some sample overlap. Additionally, cell type enrichment scores and endometrial receptivity were analyzed, and an endometrial development pseudo-timeline was constructed to estimate transcriptomic deviations from the optimum receptivity day (LH + 7), denoted as ΔWOI (window of implantation). RESULTS: There were no significantly differentially expressed genes between implantation failure and success groups in either the short-term or long-term analyses. Principal component analysis initially showed two clusters in the long-term analysis, unrelated to clinical phenotype and no longer distinct following covariate adjustment. Cell type enrichment scores did not differ significantly between groups in both analyses. However, endometrial receptivity analysis demonstrated a potentially significant displacement of the WOI in the non-pregnant group compared with the ongoing pregnant group in the short-term analysis. CONCLUSIONS: No distinct endometrial transcriptome profile was associated with either implantation failure or success in infertile women. However, there may be differences in the extent to which the WOI is displaced.

Genome-wide association study in Estonia reveals importance of vaginal epithelium associated genes in case of recurrent vaginitis.

Recurrent vaginitis is a leading reason for visiting a gynaecologist, with bacterial vaginosis (BV) and vulvovaginal candidiasis (VVC) being the most common diagnoses. Reasons and mechanisms behind their recurrent nature are poorly understood. We conducted a genome-wide association study (GWAS) to find possible genetic risk factors for recurrent vaginitis using data from a large population-based biobank, the Estonian Biobank. The study included 6870 cases (at least two episodes of vaginitis) and 5945 controls (no vaginitis episodes). GWAS approach included single marker and gene-based analyses, followed by functional annotation of associated variants and candidate gene mapping.In single marker analysis, one statistically significant (P = 7.8 × 10-9) variant rs1036732378 was identified on chromosome 10. The gene-based association analysis identified one gene, KRT6A, that exceeded the recommended significance threshold (P = 2.6 × 10-6). This is a member of the keratin protein family and is expressed during differentiation in epithelial tissues.Functional mapping and annotation of genetic associations by using adjusted significance level identified 22 potential risk loci that may be associated with recurrent vaginitis phenotype. Comparison of our results with previous studies provided nominal support for LBP (associated with immune response to vaginal bacteria) and PRKCH genes (possible role in keratinocyte differentiation and susceptibility to candidiasis).In conclusion, this study is the first highlighting a potential role of the vaginal epithelium in recurrent vaginitis.

Investigating the impact of vitrification on bovine ovarian tissue morphology, follicle survival, and transcriptomic signature.

PURPOSE: Ovarian tissue cryopreservation is vital for fertility preservation, yet its effect on ovarian tissue follicle survival and transcriptomic signature requires further investigation. This study delves into the effects of vitrification on tissue morphology, function, and transcriptomic changes, helping to find possibilities for vitrification protocol improvements. METHODS: Ovarian cortex from 19 bovine animals were used to conduct pre- and post-vitrification culture followed by histological assessment, immunohistochemistry, and TUNEL assay. Follicles' functionality was assessed for viability and growth within the tissue and in isolated cultures. RNA-sequencing of ovarian tissue was used to explore the transcriptomic alterations caused by vitrification. RESULTS: Follicle density, cell proliferation, and DNA damage in ovarian stroma were unaffected by vitrification. However, vitrified cultured tissue exhibited reduced follicle density of primordial/primary and antral follicles, while freshly cultured tissue manifested reduction of antral follicles. Increased stromal cell proliferation and DNA damage occurred in both groups post-culture. Isolated follicles from vitrified tissue exhibited similar viability to fresh follicles until day 4, after which the survival dropped. RNA-sequencing revealed minor effects of vitrification on transcriptomic signatures, while culture induced significant gene expression changes in both groups. The altered expression of WNT and hormonal regulation pathway genes post-vitrification suggests the molecular targets for vitrification protocol refinement. CONCLUSION: Vitrification minimally affects tissue morphology, follicle density, and transcriptomic signature post-thawing. However, culture revealed notable changes in vitrified tissue samples, including reduced follicle density, decreased isolated follicle survival, and alteration in WNT signalling and ovarian hormonal regulation pathways, highlighted them as possible limitations of the current vitrification protocol.

Inhibition of epigenetic and cell cycle-related targets in glioblastoma cell lines reveals that onametostat reduces proliferation and viability in both normoxic and hypoxic conditions.

The choice of targeted therapies for treatment of glioblastoma patients is currently limited, and most glioblastoma patients die from the disease recurrence. Thus, systematic studies in simplified model systems are required to pinpoint the choice of targets for further exploration in clinical settings. Here, we report screening of 5 compounds targeting epigenetic writers or erasers and 6 compounds targeting cell cycle-regulating protein kinases against 3 glioblastoma cell lines following incubation under normoxic or hypoxic conditions. The viability/proliferation assay indicated that PRMT5 inhibitor onametostat was endowed with high potency under both normoxic and hypoxic conditions in cell lines that are strongly MGMT-positive (T98-G), weakly MGMT-positive (U-251 MG), or MGMT-negative (U-87 MG). In U-251 MG and U-87 MG cells, onametostat also affected the spheroid formation at concentrations lower than the currently used chemotherapeutic drug lomustine. In T98-G cell line, treatment with onametostat led to dramatic changes in the transcriptome profile by inducing the cell cycle arrest, suppressing RNA splicing, and down-regulating several major glioblastoma cell survival pathways. Further validation by immunostaining in three cell lines confirmed that onametostat affects cell cycle and causes reduction in nucleolar protein levels. In this way, inhibition of epigenetic targets might represent a viable strategy for glioblastoma treatment even in the case of decreased chemo- and radiation sensitivity, although further studies in clinically more relevant models are required.