microRNA-based signatures obtained from endometrial fluid identify implantative endometrium.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36029522", "kind": "science-record", "revision": 4, "content_hash": "sha256:aefee70dfd9add311108c2bf9eabba6c8586e4d64dbcd6d1a1338bd800a3bc52", "created_at": "2026-11-01T18:15:11Z", "updated_at": "2026-11-01T22:07:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "microRNA-based signatures obtained from endometrial fluid identify implantative endometrium.", "doi": "10.1093/humrep/deac184", "pmid": "36029522", "authors": ["Jone Ibañez-Perez", "María Díaz-Nuñez", "Marc Clos-García", "Lucía Lainz", "María Iglesias", "Miren Díez-Zapirain", "Aintzane Rabanal", "Laura Bárcena", "Monika González", "Juan J Lozano", "Urko M Marigorta", "Esperanza González", "Félix Royo", "Ana M Aransay", "Nerea Subiran", "Roberto Matorras", "Juan Manuel Falcón-Pérez"], "journal": "Human reproduction (Oxford, England)", "year": 2022, "abstract": "STUDY QUESTION: Is it possible to use free and extracellular vesicle-associated microRNAs (miRNAs) from human endometrial fluid (EF) samples as non-invasive biomarkers for implantative endometrium?\nSUMMARY ANSWER: The free and extracellular vesicle-associated miRNAs can be used to detect implantative endometrium in a non-invasive manner.\nWHAT IS KNOWN ALREADY: miRNAs and extracellular vesicles (EVs) from EF have been described as mediators of the embryo-endometrium crosstalk. Therefore, the analysis of miRNA from this fluid could become a non-invasive technique for recognizing implantative endometrium. This analysis could potentially help improve the implantation rates in ART.\nSTUDY DESIGN, SIZE, DURATION: In this prospective study, we first optimized different protocols for EVs and miRNA analyses using the EF of a setup cohort (n = 72). Then, we examined differentially expressed miRNAs in the EF of women with successful embryo implantation (discovery cohort n = 15/validation cohort n = 30) in comparison with those for whom the implantation had failed (discovery cohort n = 15/validation cohort n = 30). Successful embryo implantation was considered when pregnancy was confirmed by vaginal ultrasound showing a gestational sac 4 weeks after embryo transfer (ET).\nPARTICIPANTS/MATERIALS, SETTING, METHODS: The EF of the setup cohort was obtained before starting fertility treatment during the natural cycle, 16-21 days after the beginning of menstruation. For the discovery and validation cohorts, the EF was collected from women undergoing frozen ET on Day 5, and the samples were collected immediately before ET. In this study, we compared five different methods; two of them based on direct extraction of RNA and the other three with an EV enrichment step before the RNA extraction. Small RNA sequencing was performed to determine the most efficient method and find a predictive model differentiating between implantative and non-implantative endometrium. The models were confirmed using quantitative PCR in two sets of samples (discovery and validation cohorts) with different implantation outcomes.\nMAIN RESULTS AND THE ROLE OF CHANCE: The protocols using EV enrichment detected more miRNAs than the methods based on direct RNA extraction. The two most efficient protocols (using polymer-based precipitation (PBP): PBP-M and PBP-N) were used to obtain two predictive models (based on three miRNAs) allowing us to distinguish between an implantative and non-implantative endometrium. The first Model 1 (PBP-M) (discovery: AUC = 0.93; P-value = 0.003; validation: AUC = 0.69; P-value = 0.019) used hsa-miR-200b-3p, hsa-miR-24-3p and hsa-miR-148b-3p. Model 2 (PBP-N) (discovery: AUC = 0.92; P-value = 0.0002; validation: AUC = 0.78; P-value = 0.0002) used hsa-miR-200b-3p, hsa-miR-24-3p and hsa-miR-99b-5p. Functional analysis of these miRNAs showed strong association with key implantation processes such as in utero embryonic development or transforming growth factor-beta signaling.\nLARGE SCALE DATA: The FASTQ data are available in the GEO database (access number GSE178917).\nLIMITATIONS, REASONS FOR CAUTION: One important factor to consider is the inherent variability among the women involved in the trial and among the transferred embryos. The embryos were pre-selected based on morphology, but neither genetic nor molecular studies were conducted, which would have improved the accuracy of our tests. In addition, a limitation in miRNA library construction is the low amount of input RNA.\nWIDER IMPLICATIONS OF THE FINDINGS: We describe new non-invasive protocols to analyze miRNAs from small volumes of EF. These protocols could be implemented in clinical practice to assess the status of the endometrium before attempting ET. Such evaluation could help to avoid the loss of embryos transferred to a non-implantative endometrium.\nSTUDY FUNDING/COMPETING INTEREST(S): J.I.-P. was supported by a predoctoral grant from the Basque Government (PRE_2017_0204). This study was partially funded by the Grant for Fertility Innovation (GFI, 2011) from Merck (Darmstadt, Germany). It was also supported by the Spanish Ministry of Economy and Competitiveness MINECO within the National Plan RTI2018-094969-B-I00, the European Union's Horizon 2020 research and innovation program (860303), the Severo Ochoa Centre of Excellence Innovative Research Grant (SEV-2016-0644) and the Instituto de Salud Carlos III (PI20/01131). The funding entities did not play any role in the study design, collection, analysis and interpretation of data, writing of the report or the decision to submit the article for publication. The authors declare no competing interests.", "claims": [{"id": "claim-method", "statement": "A subset of miRNAs was used to generate two linear regression models with k-fold cross-validations, one for each miRNA extraction protocol assessed.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36029522", "locator": "sections[28] \"Regression study\" paragraph 2", "quote": "A subset of miRNAs was used to generate two linear regression models with k-fold cross-validations, one for each miRNA extraction protocol assessed."}], "state": "complete"}, {"id": "claim-data-access", "statement": "FASTQ data are available in GEO with the access number GSE178917 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178917).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36029522", "locator": "sections[39] \"Data Availability\" paragraph 2", "quote": "FASTQ data are available in GEO with the access number GSE178917 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178917)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Two three-miRNA models derived from extracellular-vesicle-enriched endometrial fluid distinguished implantative from non-implantative endometrium, with the PBP-N model showing stronger validation performance (AUC = 0.78).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36029522", "locator": "sections[0] \"Abstract\" paragraph 6", "quote": "The two most efficient protocols (using polymer-based precipitation (PBP): PBP-M and PBP-N) were used to obtain two predictive models (based on three miRNAs) allowing us to distinguish between an implantative and non-implantative endometrium."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Two three-miRNA models derived from extracellular-vesicle-enriched endometrial fluid distinguished implantative from non-implantative endometrium, with the PBP-N model showing stronger validation performance (AUC = 0.78).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36029522"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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Small RNA sequencing was performed to determine the most efficien", "As than the PBP-N procedure (Fig. 3A). Small RNA-Seq analysis of the RNA obtained using PBP-N and", "e two methods (Fig. 3B). Moreover, the small RNA-Seq analysis of fractions F3 and F4 detected 204", "number of unique miRNAs detected using small RNA-Seq for each method and the number of miRNAs com"], "order_basis": "paper_text_order:1855", "id": "assay:1"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["13 miRNAs suitable for further validation by qPCR in the same samples. In the case of PBP-N, f", "= 30), obtained using the small RNA-Seq and qPCR. The miRNAs selected as internal normalizers", "hree miRNA-based predictive models tested by qPCR in the discovery cohort. The performance of", "microRNAs; PBP, polymer-based precipitation; qPCR, quantitative PCR; RNA-Seq, RNA-sequencing;"], "order_basis": "paper_text_order:18845", "id": "assay:2"}, {"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["ols_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["A subset of miRNAs was used to generate two linear regression models with k-fold cross-validations, one for each miRNA extraction protocol assessed."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}