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Abstract Background Prenatal alcohol exposure (PAE) affects embryonic development, causing a variable fetal alcohol spectrum disorder (FASD) phenotype with neuronal disorders and birth defects. We hypothesize that early alcohol-induced epigenetic changes disrupt the accurate developmental programming of embryo and consequently cause the complex phenotype of developmental disorders. To explore the etiology of FASD, we collected unique biological samples of 80 severely alcohol-exposed and 100 control newborns at birth. Methods We performed genome-wide DNA methylation (DNAm) and gene expression analyses of placentas by using microarrays (EPIC, Illumina) and mRNA sequencing, respectively. To test the manifestation of observed PAE-associated DNAm changes in embryonic tissues as well as potential biomarkers for PAE, we examined if the changes can be detected also in white blood cells or buccal epithelial cells of the same newborns by EpiTYPER. To explore the early effects of alcohol on extraembryonic placental tissue, we selected 27 newborns whose mothers had consumed alcohol up to gestational week 7 at maximum to the separate analyses. Furthermore, to explore the effects of early alcohol exposure on embryonic cells, human embryonic stem cells (hESCs) as well as hESCs during differentiation into endodermal, mesodermal, and ectodermal cells were exposed to alcohol in vitro. Results DPPA4, FOXP2, and TACR3 with significantly decreased DNAm were discovered—particularly the regulatory region of DPPA4 in the early alcohol-exposed placentas. When hESCs were exposed to alcohol in vitro, significantly altered regulation of DPPA2, a closely linked heterodimer of DPPA4, was observed. While the regulatory region of DPPA4 was unmethylated in both control and alcohol-exposed hESCs, alcohol-induced decreased DNAm similar to placenta was seen in in vitro differentiated mesodermal and ectodermal cells. Furthermore, common genes with alcohol-associated DNAm changes in placenta and hESCs were linked exclusively to the neurodevelopmental pathways in the enrichment analysis, which emphasizes the value of placental tissue when analyzing the effects of prenatal environment on human development. Conclusions Our study shows the effects of early alcohol exposure on human embryonic and extraembryonic cells, introduces candidate genes for alcohol-induced developmental disorders, and reveals potential biomarkers for prenatal alcohol exposure.

Abstract 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.

Abstract 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.

Abstract 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 0.05). 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.

Olive leaf is a byproduct of the olive tree that is rich in phenolic compounds with potential anticarcinogenic effects against various cancers, including breast cancer. Nevertheless, the ingestion or topical application of such plant extracts faces certain limitations. These limitations can be addressed by encapsulating the extracts in nanovesicles to enhance their release and bioavailability. This study aims to develop nanovesicles using Olea europaea leaf extract to exploit its potential anti-cancer properties. Soy lecithin was used to form liposomes for encapsulation of the olive leaf extract. In addition, ethanol and glycerol were added to form ethosomes and glycerosomes, respectively. The antiproliferative effect of both the free extract and the three formed nanovesicles was tested in MCF7 and MCF10A cell lines. To comprehend the mechanisms leading to reduced cell viability after exposure to olive leaf extract and its nanovesicles, levels of reactive oxygen species (ROS), mitochondrial membrane potential, and apoptotic stage were evaluated. The results suggest that both, the nanovesicles and the free extract, are antiproliferative agents against MCF7 tumour cells. However, when examining the impact of olive leaf extract and the formulated nanovesicles on MCF10A cells, no reduction in cell viability was observed. Our findings indicate that the anti-tumour effect of the extract and its nanovesicles may be due to increased oxidative stress, mediated by mitochondrial damage. The mechanism through which olive leaf extract exerts its antiproliferative effect on the breast cancer tumour line implies that apoptosis may be induced by the extract via the involvement of a mitochondria-dependent ROS-mediated pathway.

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

Abstract 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 17β-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

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

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.

Abstract 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.

Abstract Background Peritonsillar abscess (PTA) is a severe deep neck space infection with an insufficiently characterized bacterial etiology. We aimed to reveal the bacteria associated with PTA applying next generation sequencing (NGS). Tonsil biopsies and pus samples of 91 PTA patients were analysed applying NGS method. Results Over 400 genera and 800 species belonging to 34 phyla were revealed. The most abundant species in both sample types were Streptococcus pyogenes, Fusobacterium necrophorum and Fusobacterium nucleatum. When present, S. pyogenes was normally a predominant species, although it was recovered as a minor population in some samples dominated by F. nucleatum and occasionally F. necrophorum. S. pyogenes and F. necrophorum were the predominant species (> 10% in a community) in 28 (31%) pus samples, while F. nucleatum in 21 (23%) and S. anginosus in 8 (9%) pus samples. We observed no substantial differences between the microbial findings in pus and tonsil biopsies. Conclusions The most probable causative agents of PTA according to our NGS-study include Streptococcus pyogenes, Fusobacterium necrophorum and Fusobacterium nucleatum. Some other streptococci (S. anginosus) and anaerobes (Prevotella, Porphyromonas) may contribute to the infection as well. Pus of the peritonsillar abscess is more representative specimen for microbiological examination than the tonsillar tissue. Our results are important in the context of optimizing the handling of the PTA patients.

This paper presents a technique that can potentially help to determine the receptivity stage of the endometrium from histology images by automatically measuring the stromal nuclear changes. The presented technique is composed of an image segmentation model and the statistical evolution of segmented areas in hematoxylin and eosin (HE)-stained histology images. Three different endometrium receptivity stages, namely pre-receptive, post-receptive, and receptive, were compared. An ensemble-based AI model was proposed for histology image segmentation, which is based on individual UNet++, UNet, and ResNet34-UNet segmentation models. The performance of the ensemble-based technique was assessed using the Dice score and intersection over unit (IoU) values. In comparison to alternative segmentation architectures that were applied singly, the current ensemble-based method obtained higher Dice score (0.95) and IoU (0.90) values. The statistical comparison highlighted a noticeable difference in the number of nuclei and the size of the stroma tissue. The proposed technique demonstrated the positive potential for practical implementation for automatic endometrial tissue analysis.

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.

Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10-8, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10-8, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10-9, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10-8, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.

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. [ABSTRACT FROM AUTHOR]

Abstract Background Permanent progression of paternal age and development of reproductive medicine lead to increase in number of children conceived with assisted reproductive techniques (ART). Although it is uncertain if ARTs have direct influence on offspring health, advanced paternal age, associated comorbidities and reduced fertility possess significant risks of genetic disorders to the offspring. With a broad implementation of a non-invasive prenatal testing (NIPT), more cases of genetic disorders, including sex discordance are revealed. Among biological causes of sex discordance are disorders of sexual development, majority of which are associated with the SRY gene. Case presentation We report a case of a non-invasive prenatal testing and ultrasound sex discordance in a 46,XY karyotype female fetus with an SRY pathogenic variant, who was conceived through an intracytoplasmic sperm injection (ICSI) due to severe oligozoospermia of the father. Advanced mean age of ICSI patients is associated with risk of de novo mutations and monogenic disorders in the offspring. Additionally, ICSI patients have higher risk to harbour infertility-predisposing mutations, including mutations in the SRY gene. These familial and de novo genetic factors predispose ICSI-conceived children to congenital malformations and might negatively affect reproductive health of ICSI-patients’ offspring. Conclusions Oligozoospermic patients planning assisted reproduction are warranted to undergo genetic counselling and testing for possible inherited and mosaic mutations, and risk factors for de novo mutations.