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Aberrant Amino Acid and Lipid Metabolism Disrupts the Endometrial Transition to Receptivity in Recurrent Implantation Failure

ABSTRACT: This study comprehensively characterizes the proteomic alterations underlying endometrial dysfunction in recurrent implantation failure (RIF). Endometrial biopsies were collected longitudinally from 19 RIF patients and 19 matched controls across three critical menstrual cycle phases: mid-proliferative (MP), late-proliferative (LP), and mid-secretory (MS, LH+7). Proteins were extracted from approximately 15 mg of endometrial tissue, processed with trypsin digestion following reduction/alkylation, and analyzed using high-resolution data-independent acquisition (DIA) proteomics on a Thermo Scientific Orbitrap Astral mass spectrometer coupled with FAIMS Pro Duo interface. The dataset comprises 10,204 confidently identified proteins with high reproducibility (FDR ≤ 0.01).

ORGANISM(S): Homo Sapiens

SUBMITTER: Shen Zhang

PROVIDER: PXD072468 | iProX | Mon May 18 00:00:00 GMT+01:00 2026

REPOSITORIES: iProX

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Project description:Study question: Does a comprehensive study involving two different population cohorts and small RNA sequencing from endometrium and blood reveal new endometrial receptivity-related microRNAs (miRNAs) in healthy conditions and in women with recurrent implantation failure (RIF)? Summary answer: Several annotated miRNAs, not previously associated with endometrial receptivity, as well as one novel miRNA were found as differentially expressed between early secretory vs. mid-secretory phase samples in addition to miRNAs dysregulated in RIF patients. What is known already: The involvement of miRNAs in mid-secretory endometrial functions has been shown and aberrant expression of miRNAs in RIF has been identified in a few previous studies, but not from whole blood samples. However, as the analysis settings and platforms have been different and a small number of samples has been analysed, there is no consensus about the miRNAs involved in endometrial receptivity and dysfunction. Participants/materials, setting, methods: A total of 116 endometrial and 114 blood samples were subjected to Illumina small RNA sequencing. Identification of annotated and novel miRNAs from sequencing reads was performed by miRDeep2 algorithm. miRNAs that had significantly altered levels between the study groups in both EST and ESP datasets were considered as differentially expressed. Ingenuity Pathway Analysis was applied for identifying miRNA target genes and respective canonical pathways from the matched mRNA analysis from the same samples. Custom TaqMan Small RNA assay was used for the validation of novel miRNA (chr2_4401) levels from paired early secretory and mid-secretory endometrial samples. Main results and the role of chance: Among fertile women, 91 differentially expressed miRNAs were identified in mid-secretory vs. early secretory endometrium, while no differentially expressed miRNAs were found in the corresponding blood samples. The comparison of mid-secretory phase samples between fertile women and RIF patients revealed 21 differentially expressed miRNAs from endometrium and one from blood samples. miRNA target gene prediction analysis using our mRNA sequencing data from the matched samples detected several canonical pathways to be involved in mid-secretory endometrial functions, including JAK/STAT signalling, leptin signalling and growth hormone signalling. Moreover, JAK/STAT signalling pathway was also revealed in miRNA target analysis of mid-secretory endometrium from RIF patients when compared to fertile women. Further, our study results highlight the involvement of miR-30 and miR-200 families in endometrial receptivity, and miR-424-5p in the development of endometrial dysfunction. We identified several novel miRNAs, of which miRNA chr2_4401, being 37-fold up-regulated in mid-secretory phase, has a potential role in the mid-secretory endometrial functions. From blood samples we identified miR-30a-5p as a possible marker of infertility related to RIF.

Project description:Study question : Are there changes in transcript levels as endometrial receptivity changes in patients with recurrent implantation failure (RIF), particularly in alternative splicing events (ASEs), differential expression genes (DEGs) and immune cells levels? Summary answer: Changes in endometrial receptivity affect alternative splicing (AS), differential gene expression and immune cells, and the RNA-binding protein (RBP) KHDRBS3 likelymaybe？ Likely？ is involved in the dysregulation of alternative splicing. What is known already: Endometrial receptivity is critical for RIF patients. Researchers have developed transcript level-based models to predict personalized endometrial assessment at WOI. Investigating alternative splicing dysregulation, immune cells and other transcriptional biomarkers in RIF patients may further help to predict endometrial receptivity and improve embryo implantation success. Study design, size, duration: 90 endometrial samples were collected from fertile healthy controls (HC) during the menstrual cycle, including pre-receptive (PR) (luteinising hormone (LH)+3 days/LH+5 days), receptive (R) (LH+7 days) and post-receptive (PS) (LH+9 days) phases. 73 endometrial samples were taken from RIF patients on hormone replacement therapy (HRT) cycles, including PR (progesterone (P)+3 days), R (P+5 days) and PS (P+7 days) phases. Participants/materials, setting, methods: Total RNA was extracted and sequenced for all 163 endometrial samples . Bioinformatic analysis was used to comprehensively investigate the endometrial transcriptome at different stages of receptivity. We elucidated the biological significance of the universal alteration of alternative splicing in endometrial receptivity and further analyzed the role of immune cells and gene expression in this process. In addition, an ASEs-RBPs correlation network was constructed in the endometrial receptive period to evaluate the dysregulation of AS by RBPs. Main results and the role of chance: Global splicing profiling of the four subgroups (HC: PR vs. R; HC: PS vs. R; RIF: PR vs. R; RIF: PS vs. R) consistently showed that skipped exons (SE) and mutually exclusive exons (MXE) were the most common changes in splicing events. These different ASEs occurred at high frequency and some of them could affect the coding potential of a transcript. A greater number of genes with different alternative splicing events (ASEGs) were identified between PR and R phases than between PS and R phases, and the same trend was observed for differentially expressed genes (DEGs). Both ASEGs and DEGs showed enrichment for pathways associated with cell function and adhesion, while DEGs were also enriched for cytokine and immune-related pathways. Immune cell prediction shows that changes in endometrial receptivity phases result in differences in the levels of CD8 T cells, resting NK cells and other immune cells. During the R phase, there was a significant decrease in CD8 T cells and resting NK cells, whereas monocytes and M0 macrophages were significantly increased compared to the endometrial PR phase in RIF patients. Similarly, analysis of immune cells showed a significant increase in CD8 T cells, M1 and M2 macrophages and a significant decrease in activated NK cells in the R phase compared to the PS phase of the endometrium in RIF patients. Some of these immune cells, such as NK cells and monocytes, are highly correlated with certain ASEs. Investigation of ASEs-RBPs networks suggested that KHDRBS3 may be a key regulator of splicing events. Limitations, reasons for caution: The sample size needs to be increased and cover a variety of situations, such as different age, pathology, dietary habits, etc., and alsothe molecular experimental validation needs to be considered. The lack of direct comparisons between natural and HRT cycles in the same sample and molecular experimental validation need to be considered. Wider implications of the findings: Comprehensive transcriptional analysis of the endometrium provide valuable insight into potential biomarkers related to endometrial receptivity and potential treatments for RIF patients. Study funding/competing interest(s): This study was supported by Supported by the Program of National Natural Science of China (Grant No. 81701409). All authors declared that they have no conflicts of interest.

Project description:This study addresses the need for non-invasive methods to assess the human endometrium, which is critical for successful pregnancy and is implicated in unexplained infertility. The primary biological relevance lies in determining if extracellular vesicles in uterine fluid (UF-EVs) can serve as a proxy for the cellular state of the endometrial tissue. The intent is to validate a deep learning-based deconvolution approach that uses the transcriptomic profile of UF-EVs to accurately delineate the cellular composition of the endometrium throughout the menstrual cycle. Success in this area would enable detailed endometrial assessment without requiring invasive biopsies. The experimental workflow was designed to compare cellular profiles derived from UF-EVs against those from paired endometrial tissue. The primary dataset consisted of paired endometrial tissue and UF-EV transcriptomes collected from 19 fertile, healthy women across four menstrual cycle phases: proliferative (n=4), early-secretory (n=5), mid-secretory (n=5), and late-secretory (n=5). Two additional unpaired UF-EV samples were also included (phenotypes mapped in main_pheno.csv). For this cohort, small EVs were isolated using size-exclusion chromatography and RNA libraries were prepared with the TruSeq exome RNA library preparation kit. Raw sequencing data was processed with the nf-core/rnaseq pipeline (v3.14) and the RSEM outputs are provided. To map the spatial origin of EVs, the analysis also incorporated endometrial tissue Visium slides from two proliferative (n=2) and two early-secretory (n=2) phase samples (E-MTAB-9260). A deep learning deconvolution model, BulkTrajBlend, was trained on a human endometrial single-cell RNA-seq reference atlas. The trained model was then used to infer cell type proportions in the bulk transcriptomes and to generate pseudo-single-cell (pSC) data (weights in pseudosc_bio.pth and pseudosc_ev.pth), which was subsequently projected onto the spatial transcriptomic slides to visualize the potential tissue origins of the cells secreting EVs.

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Aberrant Amino Acid and Lipid Metabolism Disrupts the Endometrial Transition to Receptivity in Recurrent Implantation Failure

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