Targeted gene expression profiling for accurate endometrial receptivity testing

Cell type and region-specific transcriptional changes in the endometrium of women with RIF identify potential treatment targets

Recurrent implantation failure (RIF) is a devastating condition that leaves many undergoing fertility treatment childless. The human endometrium is receptive to a blastocyst for a brief period, the window of implantation. Critical knowledge underpinning biological processes leading to RIF, essential for effective treatment, is lacking. We employed spatial transcriptomics to define region- and cell-type-specific differences in endometrial gene expression in luteinizing hormone timed biopsies between women with RIF (n = 8) and fertile controls (FC) (n = 8). Differentially expressed genes (DEGs) were identified when comparing endometrial regions between FC and RIF (685 luminal epithelium, 293 glandular epithelium, 419 subluminal stroma, 264 functionalis stroma, 1,125 subluminal stromal CD45+ leukocytes, and 1,049 functionalis stromal CD56+ leukocytes). Only 57 DEGs were common to all subregions and cell types, which highlights that multiple DEGs are lost when the endometrium is examined as a single entity. When RIF-specific DEGs were leveraged against knowledge from mouse genetic models, genes associated with aberrant embryo implantation phenotypes were observed, mostly in immune cell populations. Dysregulated pathways in specific endometrial regions included the "WNT signaling pathway," altered in the functionalis and subluminal stroma. "Response to estradiol" and "ovulation cycle" pathways were dysregulated in the subluminal stroma. In silico drug screening identified potential compounds that can reverse the RIF gene expression profile (e.g., raloxifene, bisoprolol). Our findings, in a well-characterized cohort, highly endorse consideration of each endometrial region and cell type as separate entities. Ignoring individual regions and composite cell populations will overlook important aberrations, forego potential treatment targets, and lead to research waste pursuing clinically irrelevant treatment options.

Multi-omics analysis of uterine fluid extracellular vesicles reveals a resemblance with endometrial tissue across the menstrual cycle: biological and translational insights

STUDY QUESTION

Does the molecular composition of uterine fluid extracellular vesicles (UF-EVs) reflect endometrial tissue changes across the menstrual cycle?

SUMMARY ANSWER

Concordance between endometrial tissue and UF-EVs exists on miRNA and mRNA levels along the menstrual cycle phases and UF-EV surface proteomic signatures suggest EVs originate from several major endometrial cell populations.

WHAT IS KNOWN ALREADY

The clinical value of endometrial receptivity testing is restricted by invasiveness and the use of only one omics level of input. There is promising evidence that UF-EVs can reflect changes in mid-secretory endometrium, highlighting the potential to establish endometrial receptivity testing right before embryo transfer. However, the dynamic changes of UF-EVs molecular cargo have not been directly compared to endometrial tissue on multiple omics levels.

STUDY DESIGN SIZE DURATION

This cross-sectional study included fertile women from four menstrual cycle phases: proliferative and early-, mid-, and late-secretory phases. In total, 26 paired samples of UF and endometrial tissue were collected. mRNA and miRNA were sequenced, and differential analysis was performed on consecutive phases. UF-EVs were profiled for various protein surface markers associated with different cell types. EVs from epithelial endometrial organoid-conditioned culture media were used as a reference of pure epithelial endometrial EVs.

PARTICIPANTS/MATERIALS SETTING METHODS

Paired UF and endometrial tissue samples were collected from 26 fertile, reproductive-age women. EV isolation from UF was validated using electron microscopy and western blotting, and particle numbers were measured by nanoparticle tracking analysis. The transcriptome and miRNome of UF-EVs and endometrial tissue were sequenced, and differential expression analysis was conducted on consecutive phases of the menstrual cycle. Bead-based EV flow cytometry targeting 37 surface protein markers was used to characterize EVs from UF and endometrial organoids.

MAIN RESULTS AND THE ROLE OF CHANCE

Surface proteome analysis revealed that UF-EVs from the mid-secretory phase had significantly increased expression of natural killer cell marker CD56 (P < 0.005), pan-leukocyte marker CD45 (P < 0.005), pan-T-cell marker CD3 (P < 0.005), and coagulation-related protein CD142 (P < 0.005) compared to those from the proliferative phase, whereas markers associated with endometrial epithelial cells (CD29, CD133, and CD326) did not significantly change across the menstrual cycle. Transcriptomic analysis highlighted differential expression of histone and metallothionein genes that correlated between paired UF-EVs and endometrial tissues in each tested menstrual cycle phase. Principal component analysis of miRNomes of paired UF-EVs and endometrial tissue samples resulted in similar clustering patterns, where mid- and late-secretory samples clustered closely, and proliferative and early-secretory phase samples clustered separately. Half of the differentially expressed miRNAs in each phase in UF-EVs were also differentially expressed in the endometrium. Importantly, nine mid-secretory phase UF-EV DE miRNAs were identified, five of which were common between UF-EVs and endometrial biopsies, including hsa-miR-30d-5p and hsa-miR-200b-3p, both of which were previously implicated in implantation. Notably, three of the nine miRNAs, hsa-miR-200b-3p, hsa-miR-141-3p, and hsa-miR-200a-3p, were predicted to regulate mRNAs in the endometrial tissue and the pre-implantation embryo trophectoderm.

LARGE SCALE DATA

N/A.

LIMITATIONS REASONS FOR CAUTION

The clinical dating of the menstrual cycle phase is based on the first day of menstruation and the time of the LH peak, which does not exclude the possibility that the expected endometrial phase was not reached. The wider limitation of our study is the lack of standardized procedures for collecting UF samples in gynaecological practice, which could challenge the replication of our findings.

WIDER IMPLICATIONS OF THE FINDINGS

Evidence that UF-EVs reflect endometrial phases of menstrual cycle supports the use of UF-EVs in endometrial receptivity testing. Additionally, further studies of UF-EVs in endometrial pathologies could be beneficial for diagnostics, considering that more invasive tissue biopsies only reflect the biopsy site and not the full endometrium.

STUDY FUNDING/COMPETING INTERESTS

This study was supported by the European Regional Development Fund Enterprise Estonia's Applied Research Program under the grant agreement number 2014-2020.4.02.21-0398 (EVREM), the Estonian Research Council (grant nos. PRG1076 and PSG1082), the Horizon Europe NESTOR grant (grant no. 101120075) of the European Commission, the Swedish Research Council (grant no. 2024-02530), the Novo Nordisk Fonden (grant no. NNF24OC0092384), and the National Recovery and Resilience Plan of the Republic of Bulgaria, project number BG-RRP-2.004-0001-C01. A.S.L. received funding from the Becas Fundación Ramón Areces para Estudios Postdoctorales. All the authors declare no conflict of interest.

Factors influencing endometrial receptivity in women with recurrent implantation failure

BACKGROUND

Embryo implantation involves two key elements: a good quality embryo and receptive endometrium. Endometrial receptivity abnormalities are known as one of the possible causes of recurrent implantation failure (RIF), especially when the embryo is euploid. This study was aimed to evaluate the impact of age and other clinical factors on endometrial receptivity in women with RIF.

METHODS

68 women with RIF (defined as at least three unsuccessful transfers of good quality embryo of at least 1BB category of blastocysts) and 49 controls (women undergoing IVF treatment because of idiopathic infertility or male factor) were included to the study. After preparation of the endometrium by the hormone replacement therapy endometrial biopsies were taken from each patient and sequenced with beREADY test TAC targeting 67 biomarker genes for endometrial receptivity. Depending on the test result patients were classified into one of four different groups: pre-receptive (n = 16), early-receptive (n = 54), receptive (n = 44) and late-receptive (n = 3).

RESULTS

In women with RIF pre-receptive endometrium has been detected substantially more often than in controls - 13 (19,1%) vs. 3 (6,1%) patients (p = 0,043). Early-receptive endometrium was diagnosed in the majority of patients with idiopathic infertility - 12 (66.7%) vs. 6 (33.3%) women (p = 0.042) and with polycystic ovary syndrome (PCOS) - 12 (70,6%) vs. 3 (17.7%) women (p = 0,0447). We found significant association between abnormal endometrial receptivity and patient's age and duration of infertility. Young women were diagnosed significantly more often as normal or late-receptive, whereas older women with longer history of infertility as early-receptive and pre-receptive.

CONCLUSIONS

In patients with RIF in comparison to other women undergoing IVF procedures, patient's age and infertility duration are the most important factors related to endometrial receptivity abnormalities, indicating that older women with a longer history of infertility may benefit the most from endometrial receptivity testing.

TRIAL REGISTRATION

Not applicable.

Uterus didelphys: the first case report on molecular profiling of endometrial tissue from both uterine cavities

BACKGROUND

A didelphic uterus represents a unique and infrequent congenital condition in which a woman possesses two distinct uteri, each with its own cervix. This anomaly arises due to partial or incomplete merging of the Müllerian ducts during the developmental stages in the womb. Accounting for uterine malformations, a didelphic uterus is a relatively rare condition, affecting approximately 0.5-2% of the population and is considered one of the more uncommon types of uterine abnormalities.

METHODS

This case report aims to study the physical separation in uterine didelphys and its impact on endometrial microbiome and inflammation, and the patterns of endometrial receptivity observed.

RESULTS

Endometrial receptivity analyses revealed a similar receptive state in both uteri, both in the early receptive phase. Differential markers of chronic endometritis, including CD138, and MUM1-positive cells, were observed when comparing endometrial biopsies from both uteri. The right uterus exhibited a higher prevalence of these positive cells. Regarding the microbiome, significant differences were found between the uteri, notably in the right uterus, a clear non-dominance of lactobacilli and the presence of genera such as Staphylococcus, Streptococcus, and Acinetobacter. Additionally, the right uterus presented a less 'favourable' microenvironment, a characteristic that was also reflected in the right cervix; both sites presenting less lactobacilli than the left side samples. A distinct metabolomic signature associated with the physical separation of the uteri contributed to the differences in endometrial milieu.

CONCLUSIONS

Our study revealed that physical separation, among other factors in uterus didelphys, affects the endometrial microbiome, metabolome, and inflammatory state, with significant microbiome variation observed between the uteri, although similar endometrial receptivity patterns were noted.

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.

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.

Development of a New Personalized Molecular Test Based on Endometrial Receptivity and Maternal-Fetal Dialogue: Adhesio

Successful embryo implantation relies on a receptive endometrium and a maternofetal dialogue. Abnormal receptivity is a common cause of implantation failure in assisted reproductive techniques. This study aimed to develop a novel transcriptomic-based diagnostic assay, Adhesio, for assessing endometrial receptivity and guiding personalized embryo transfer. Adhesio was developed based on an initial dataset of 74 endometrial biopsies. Two types of biopsy samples were involved: 45 endometrial biopsies collected during the optimal theoretical window of implantation (WOI) and 29 endometrial biopsies which cells have been cultured with or without an autologous embryo. Microarray analysis was performed to identify differentially expressed genes associated with endometrial receptivity and selected candidate genes were assessed using quantitative real-time polymerase chain reaction (RT-qPCR) on biopsy samples. Statistical analyses were conducted to assess the performance and accuracy of Adhesio. The microarray analysis identified three distinct clusters of endometrial samples with differential gene expression patterns. Cluster 1 exhibited 1717 differentially expressed genes involved in biological processes associated with endometrial receptivity. A specific transcriptomic signature of 60 genes associated with endometrial co-culture was obtained using class prediction approach. Thereafter, an original panel of 10 genes was selected as potential biomarkers for endometrial receptivity based on their expression profiles in both endometrial biopsies and co-cultured cells. This article outlines the methodology employed to develop Adhesio, a test that assesses endometrial receptivity using an original panel of 10 genes. These genes are not only involved during the WOI but are also influenced by the maternal-fetal dialogue.

The Role of the Endometrium in Implantation: A Modern View

According to the current data, the endometrium acts as a "sensor" of embryo quality, which promotes the implantation of euploid embryos and prevents the implantation and/or subsequent development of genetically abnormal embryos. The present review addresses the nature of the "sensory function" of the endometrium and highlights the necessity for assessing its functional status. The first section examines the evolutionary origin of the "sensory" ability of the endometrium as a consequence of spontaneous decidualization that occurred in placental animals. The second section details the mechanisms for implementing this function at the cellular level. In particular, the recent findings of the appearance of different cell subpopulations during decidualization are described, and their role in implantation is discussed. The pathological consequences of an imbalance among these subpopulations are also discussed. Finally, the third section summarizes information on currently available clinical tools to assess endometrial functional status. The advantages and disadvantages of the approaches are emphasized, and possible options for developing more advanced technologies for assessing the "sensory" function of the endometrium are proposed.

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.

A Comprehensive Review of the Endometrial Receptivity Array in Embryo Transfer: Advancements, Applications, and Clinical Outcomes

Embryo transfer is a pivotal procedure in assisted reproductive technologies (ART). Yet, the success of this process hinges on multiple factors, with endometrial receptivity playing a critical role in determining the likelihood of successful implantation. The endometrial receptivity array (ERA) is an advanced diagnostic tool designed to personalize embryo transfer timing by assessing the endometrium's receptivity. This review comprehensively examines the ERA, exploring its biological foundation, technological development, and clinical applications. The ERA's ability to analyze the expression of genes associated with endometrial receptivity offers a tailored approach to identifying the optimal window of implantation (WOI), particularly benefiting patients with recurrent implantation failure (RIF) or repeated unsuccessful in vitro fertilization (IVF) cycles. Clinical outcomes from ERA-guided embryo transfers indicate improvements in implantation rates and overall pregnancy success, although challenges such as result variability and cost-effectiveness persist. This review also discusses the latest advancements in ERA technology, including integrating genomic and transcriptomic analyses, non-invasive techniques, and using artificial intelligence (AI). Controversies regarding the widespread application of ERA and its necessity in all IVF cases are critically examined. By summarizing the current state of ERA in embryo transfer, this review aims to inform clinicians, researchers, and patients about its potential to enhance ART outcomes and to highlight areas for future research and innovation.

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.

A Comprehensive Review of the Endometrial Receptivity Array in Euploid Embryo Transfer Cycles

The Endometrial Receptivity Array (ERA) is a revolutionary molecular diagnostic tool that determines the optimal timing for embryo transfer by analyzing the gene expression profile of endometrial tissue. This comprehensive review examines the significance and application of ERA in euploid embryo transfer cycles, where the implantation of embryos with the correct number of chromosomes is critical for achieving successful pregnancy outcomes. This review underscores its role in enhancing implantation rates and reducing pregnancy loss by assessing the evolution, methodology, clinical applications, efficacy, and challenges associated with ERA. Key findings highlight ERA's superior accuracy in identifying the window of implantation compared to traditional methods, resulting in improved clinical outcomes in assisted reproductive technology (ART) cycles. Despite its benefits, the review acknowledges challenges such as cost, accessibility, and the need for standardization. Recommendations for clinical practice emphasize the integration of ERA into routine ART protocols, comprehensive patient counseling, and the importance of multidisciplinary collaboration. The review outlines promising prospects, including technological advancements to make ERA more cost-effective, the development of refined gene expression profiles, and the potential integration with other emerging ART technologies. Further research directions include long-term studies on the outcomes of ERA-guided pregnancies and exploring its application in cases of recurrent implantation failure and unexplained infertility. Overall, ERA represents a significant advancement in reproductive medicine, offering a personalized approach to embryo transfer timing that can significantly improve the success rates of euploid embryo transfers.

Polycystic ovary syndrome

Despite affecting ~11-13% of women globally, polycystic ovary syndrome (PCOS) is a substantially understudied condition. PCOS, possibly extending to men's health, imposes a considerable health and economic burden worldwide. Diagnosis in adults follows the International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome, requiring two out of three criteria - clinical or biochemical hyperandrogenism, ovulatory dysfunction, and/or specific ovarian morphological characteristics or elevated anti-Müllerian hormone. However, diagnosing adolescents omits ovarian morphology and anti-Müllerian hormone considerations. PCOS, marked by insulin resistance and hyperandrogenism, strongly contributes to early-onset type 2 diabetes, with increased odds for cardiovascular diseases. Reproduction-related implications include irregular menstrual cycles, anovulatory infertility, heightened risks of pregnancy complications and endometrial cancer. Beyond physiological manifestations, PCOS is associated with anxiety, depression, eating disorders, psychosexual dysfunction and negative body image, collectively contributing to diminished health-related quality of life in patients. Despite its high prevalence persisting into menopause, diagnosing PCOS often involves extended timelines and multiple health-care visits. Treatment remains ad hoc owing to limited understanding of underlying mechanisms, highlighting the need for research delineating the aetiology and pathophysiology of the syndrome. Identifying factors contributing to PCOS will pave the way for personalized medicine approaches. Additionally, exploring novel biomarkers, refining diagnostic criteria and advancing treatment modalities will be crucial in enhancing the precision and efficacy of interventions that will positively impact the lives of patients.

When the Embryo Meets the Endometrium: Identifying the Features Required for Successful Embryo Implantation

Evaluation of the optimal number of embryos, their quality, and the precise timing for transfer are critical determinants in reproductive success, although still remaining one of the main challenges in assisted reproduction technologies (ART). Indeed, the success of in vitro fertilization (IVF) treatments relies on a multitude of events and factors involving both the endometrium and the embryo. Despite concerted efforts on both fronts, the overall success rates of IVF techniques continue to range between 25% and 30%. The role of the endometrium in implantation has been recently recognized, leading to the hypothesis that both the "soil" and the "seed" play a central role in a successful pregnancy. In this respect, identification of the molecular signature of endometrial receptivity together with the selection of the best embryo for transfer become crucial in ART. Currently, efforts have been made to develop accurate, predictive, and personalized tests to identify the window of implantation and the best quality embryo. However, the value of these tests is still debated, as conflicting results are reported in the literature. The purpose of this review is to summarize and critically report the available criteria to optimize the success of embryo transfer and to better understand current limitations and potential areas for improvement.