STUDY QUESTION Does age affect endometrial gene expression? SUMMARY ANSWER Using unsupervised artificial intelligence methods, we report for the first time that endometrial gene expression changes from 35 years of age in women. WHAT IS KNOWN ALREADY Female fertility declines with age, largely attributed to declining oocyte quality and ovarian reserve. Combined with other evidence, a longstanding paradigm holds that age does not affect the endometrial function and age has not been controlled for properly in endometrial studies. STUDY DESIGN, SIZE, DURATION A retrospective in silico analysis was performed of endometrial transcriptomic data from the Gene Expression Omnibus (GEO) sample repository for 27 women of different ages. Results were validated in an independent gene expression dataset of 20 endometrial samples from women aged 23–43 years. PARTICIPANTS/MATERIALS, SETTING, METHODS A systematic search was performed in GEO from October 2016 to January 2019 to identify transcriptomic studies involving women of different ages. Included samples were from norm-ovulatory, women of reproductive age (23–49 years) with regular menstrual cycles who were free of endometriosis and used as controls in a previous endometrial study. We used raw gene expression data and metadata from these samples to investigate the effect of age on endometrial gene expression. Files were downloaded, pre-processed and explored for potential confounding variables and outliers. Artificial intelligence methods were applied to define age groups, and differential expression and functional analyses were applied to demonstrate and understand the effect of age on gene expression at the molecular level. Functional results were validated in an independent gene expression dataset of 20 endometrial samples from women aged 23–43 years. MAIN RESULTS AND THE ROLE OF CHANCE Analysis of the initially retrieved endometrial datasets revealed the age of participants was not available (33.33%) or traceable (43.33%) in most studies. However, one study was suitable for age analysis (GSE4888, n = 27, 23–49 years). Samples showed different transcriptomic profiles according to age, beginning at 35 years. A total of 5778 differentially expressed genes and 27 significantly altered endometrial functions (false discovery rate (FDR) < 0.05) were associated with endometrial gene expression changes related to age. Interestingly, 81.48% of affected functions were related to up-regulation of ciliary processes, with 91 genes involved in cilia motility and ciliogenesis. Other functions included dysregulation of the vascular endothelial growth factor signalling pathway and inhibition of epithelial proliferation triggered by 37 genes involved in cell cycle arrest, angiogenesis, insulin signalling and telomere protection. These findings were validated in an independent dataset using a non-targeted approach; 20 up-regulated ciliary processes (FDR < 0.02) and 6 down-regulated functions related to cell cycle arrest were identified as affected by age, among other hallmarks of ageing such as DNA repair inhibition or sugar metabolism (FDR < 0.05). LARGE SCALE DATA Data underlying this article are available in GEO, IDs: GSE4888 (main dataset) and GSE102131 (validation dataset). LIMITATIONS, REASONS FOR CAUTION This study is limited in size, as are most studies of endometrial transcriptomics where whole-transcriptome analysis considers nearly 22 000 variables in a relatively small population. Yet, our study includes a main sample set and subsequent validation set that enhances reproducibility of our results and provides reasonable evidence for concluding that age affects endometrial gene expression. A larger study prospectively controlling for patient characteristics is needed to accurately describe changes related to age, with a higher sample size and across a wide age range. Additional studies also are necessary to determine the endometrial ageing contribution to infertility for ultimate translation to a clinical setting. WIDER IMPLICATIONS OF THE FINDINGS Our findings support an influence of age on the endometrium in a genome-wide functional approach, breaking the endometrial ageing paradigm in human reproduction. To our knowledge, this work is the first to identify, using a genome-wide functional non-targeted approach, ciliary processes as the primary dysregulated function associated with maternal age. These results should guide the research community to control for age as a potential confounding variable in endometrial gene expression studies and to consider endometrial ageing in further studies as a potential cause of infertility in the clinical setting. The reported functional dysregulations could contribute to diminished embryo implantation with age and further studies will demonstrate if such dysregulation underlies some cases of implantation failure. Additionally, the discovery of these functional alterations could enable mechanistic studies, particularly around the age-related increase in uterine pathologies. STUDY FUNDING/COMPETING INTEREST(S) This research was funded by the Instituto de Salud Carlos III through Miguel Servet programme (CP20/00118) granted to Patricia Diaz-Gimeno (Spanish Government) co-funded by FEDER; and by IVI Foundation (1706-FIVI-041-PD). A.D.-P. (FPU/15/01398) and A.P.-L. (FPU18/01777) are granted by the pre-doctoral programme fellowship from the Ministry of Science, Innovation and Universities (Spanish Government). The authors do not have any competing interests to declare. TRIAL REGISTRATION NUMBER N/A

The human endometrium is a dynamic tissue that only is receptive to host the embryo during a brief time in the middle secretory phase, called the window of implantation (WOI). Despite its importance, regulation of the menstrual cycle remains incompletely understood. The aim of this study was to characterize the gene cooperation and regulation of menstrual cycle progression, in order to dissect the molecular complexity underlying acquisition of endometrial receptivity for a successful pregnancy; and to provide the scientific community with detailed gene co-expression information throughout the menstrual cycle on a user-friendly web-tool database. A retrospective gene co-expression analysis was performed based on the endometrial receptivity array (ERarray) gene signature from 523 human endometrial samples collected across the menstrual cycle, including during the WOI. Gene co-expression analysis revealed the WOI as having the significantly smallest proportion of negative correlations for transcriptional profiles associated with successful pregnancies compared to other cycle stages, pointing to a global transcriptional derepression being involved in acquisition of endometrial receptivity. Regulation was greatest during the transition between proliferative and secretory endometrial phases. Further, we prioritized nuclear hormone receptors as major regulators of this derepression and proved that some genes and transcription factors involved in this process were dysregulated in patients with recurrent implantation failure. We also compiled the wealth of gene co-expression data to stimulate hypothesis-driven single-molecule endometrial studies in a user-friendly database: Menstrual Cycle Gene Co-expression Network (www.menstrualcyclegcn.com). This study revealed a global transcriptional repression across the menstrual cycle, which relaxes when the WOI opens for transcriptional profiles associated with successful pregnancies. These findings suggest that a global transcriptional derepression is needed for embryo implantation and early development.

Study question Is there a most represented group of approved drugs that can revert the impaired endometrial expression pattern associated with endometrial failure to improve reproductive outcomes? Summary answer Transcriptomics-based drug repurposing strategy identifies drugs currently used for nervous system diseases as repurposing candidates for endometrial therapies in infertility. What is known already Endometrium is a dynamic tissue with a key role in human reproduction whose alterations lead to infertility problems. Transcriptomic studies have been performed to understand molecular bases of endometrial failure, but effective treatments remain unknown. Transcriptomics-based drug repurposing strategy identifies approved drugs with a reversed disease gene expression profile, where genes up-regulated in a condition are down-regulated with the drug therapy and vice-versa, having a predicted therapeutic effect. Encouraging results for conditions such as preterm birth or cancer have already been shown using this methodology. In this study, we applied this approach to obtain treatment predictions for endometrial failure. Study design, size, duration A prospective multicenter study was performed between January 2019 and December 2021. A total of 192 women (18-50 years old) undergoing IVF with good-quality embryos were included and an endometrial sample in mid-secretory phase was collected to study their gene expression. Through artificial intelligence algorithms, we identified transcriptomic patterns with different endometrial prognoses. Expression changes among good or poor prognosis profiles were used to identify potential approved therapies to treat infertility leveraging drug expression databases. Participants/materials, setting, methods Gene signatures associated with poor prognosis were identified (FDR<0.05) and queried against the Connectivity Map database, containing gene expression profiles for 1,309 drugs in 5 different cell lines. Statistical analyses were performed to evaluate the drugs selected and obtain a score based on the drug expression reversal of the disease signatures. Significant drugs (adj. p-value) inversely associated with the gene signatures were highlighted. Finally, approved drugs were classified according to Anatomical Therapeutic Chemical codes. Main results and the role of chance We identified four transcriptomic profiles significantly (p-value<0.05) associated with different reproductive outcomes in the first embryo transfer after biopsy collection. Two poor prognosis profiles, one of them more related to clinical miscarriage, P1 (implantation rate = 30.4%, live birth rate = 42.9%, clinical miscarriage rate = 50%), and another to biochemical miscarriage, P2 (implantation rate = 20.0%, live birth rate = 33.3%, biochemical miscarriage rate = 66.7%) were compared with the best prognosis profile (implantation rate = 64.6%, live birth rate = 95.2%, biochemical miscarriage rate = 0.0%, clinical miscarriage rate = 4.8%), obtaining a total of 439 and 4,984 differential expressed genes, respectively for P1 and P2. After applying the drug repurposing methodology, we selected 50 and 32 significant approved drugs (adj. p-value<0.05) for P1 and P2. A total of 14 and 11 different drugs categories were obtained for each poor prognosis profile highlighting Nervous System (26%) and Alimentary tract and metabolism (12%) for P1, and Nervous System (23%), Antineoplastic and Immune modulating agents (15%) and Antiparasitic products (15%) for P2. Moreover, when both nervous system categories were compared, a total of 15 drugs were found in common, making possible the use of a unique drug for both profiles. Limitations, reasons for caution Since the Connectivity Map database does not include endometrial tissue, the action of these drugs should be validated experimentally in endometrial cell culture. Afterwards, to prioritize the best drug, side effects and approved doses reported in drug databases should be taken into consideration in further analyses. Wider implications of the findings The use of drug repurposing generates hypotheses for finding suitable drugs for endometrial failure, not requiring preclinical trials and going directly to Phase II clinical trials. These potential treatments will improve reproductive outcomes. Nervous system drugs seem to have a considerable effect on endometrium revealing possible causes of endometrial failure. Trial registration number Not Applicable