Evidence map›Paper›PMID 42381032›Full record

ArticleBMC medicine2026

Single-nucleus analysis of menstrual fluid highlights gene expression differences in epithelial cells of endometriosis donors.

Katie Leap, Anthony Lepelletier, Eulalie Liorzou, Ludivine Doridot, Axelle Brulport, Camille Berthelot

Abstract read
In one paragraph

Article in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Katie LeapInstitut Pasteur, Université Paris Cité, CNRS UMR 3525, INSERM ERL1351, Comparative Functional Genomics group, F-75015, Paris, France.
Anthony LepelletierInstitut Pasteur, Université Paris Cité, CNRS UMR 3525, INSERM ERL1351, Comparative Functional Genomics group, F-75015, Paris, France.
Eulalie LiorzouInstitut Pasteur, Université Paris Cité, CNRS UMR 3525, INSERM ERL1351, Comparative Functional Genomics group, F-75015, Paris, France.
Ludivine DoridotUniversité Paris Cité, Institut Cochin, INSERM, CNRS, F-75014 PARIS, France, Paris, France.
Axelle Brulport *Institut Pasteur, Université Paris Cité, CNRS UMR 3525, INSERM ERL1351, Comparative Functional Genomics group, F-75015, Paris, France. axelle.brulport@inserm.fr.
Camille Berthelot *Institut Pasteur, Université Paris Cité, CNRS UMR 3525, INSERM ERL1351, Comparative Functional Genomics group, F-75015, Paris, France. camille.berthelot@pasteur.fr.

Funding

European Research Council (ERC) 101078556European Research Council (ERC) No 851360Fondation pour la Recherche sur l'Endométriose, Endofrance FRE202112014887Institut Pasteur G5 package
6 · The paper itself

Abstract

backgroundEndometriosis is a common complex gynecological condition that is difficult to efficiently diagnose and remains poorly understood. Menstrual fluid provides a non-invasive source of disease-relevant tissue and has been identified as promising for endometriosis diagnostics. Peripheral blood-based assays have yielded few clinically relevant targets, thus we hypothesize that cells specific to the uterus will exhibit more disease-related differences and may lead to insights into disease development and potential diagnostic markers.

methodsWe profiled 10 menstrual fluid samples, from 5 donors with endometriosis and 5 donors without, using both single-nucleus RNA sequencing and bulk RNA sequencing. We tested for differential abundance of cell types, differential gene expression within cell types, and differential cell communication between cell types by disease status. Finally, we compared the results of both single-nucleus and bulk RNA sequencing analyses to identify potential diagnostic targets.

resultsWe identified endometrial and immune cell types present in menstrual fluid, with large inter-individual heterogeneity in cell type representation. While most cells were immune, the cell types with the greatest number of differentially expressed genes were endometrial epithelial cells followed by stromal cells. Epithelial cells in particular recapitulated some gene expression differences previously described in the context of endometriosis, although most identified differences were novel. Cell-cell communication in endometriosis was characterized by a loss of interactions between epithelial and stromal cells related to developmental and growth genes WNT2B, IGF2 and TGFB2, but a gain of cell-cell communications between dendritic cells and other cell types, especially within the BMP signaling pathway. Bulk RNA sequencing revealed that some of the differentially expressed genes found in epithelial cells could be replicated in the whole tissue, highlighting the following genes as biomarker candidates: TIMP2, AKR1C2, DMBT1, FERMT1, and KCNK5.

conclusionsWe identified a set of promising genes that may contribute to endometriosis pathophysiology understanding and have potential as diagnosis biomarkers in whole menstrual blood. Further assessment of their stability over time within each patient and in a larger cohort will confirm whether this represents a viable non-invasive strategy to reduce diagnostic delays.

Indexed as

Cell NucleusEndometriosisEpithelial CellsMenstruationAdultFemaleGene Expression ProfilingHumansSequence Analysis, RNASingle-Cell Gene Expression AnalysisBulk RNA sequencingDiagnosis biomarkersEndometriosisMenstrual fluidSingle-nucleus RNA sequencing

Identifiers

PMID42381032
PMCPMC13587483

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