Whole genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

Ioanna Tiniakou, Cemsel Bafligil, Raúl Pérez-Moraga, Sarah Louise Harden, Sarah Harden, Sophie Ribeiro-Volturo, Alfredo Santana, Alfredo Santana Rodríguez, Roberto Notario Manzano, María Alejandra Santana Suárez, Maria Suarez, M. Tortajada Valle, Marta Tortajada Valle, María Ángeles Martínez-Zamora, Miguel A. Zamora, María Teresa Pérez Zaballos, Alicia Martin Martinez, Alicia Martín Martínez, Francisco Carmona, Cristina Fernández-Molina
Communications medicine · 2025 · doi:10.1038/s43856-026-01641-3 · PMID:42143138 · W4412673954
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Whole genome methylation profiling of menstrual stem cells identified differentially methylated regions that distinguish endometriosis patients from controls with high diagnostic performance.

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Abstract

BACKGROUND: Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological insight. Menstrual blood-derived stem cells have been implicated in disease pathogenesis, but their diagnostic potential remains unexplored. METHODS: We conducted a case-control clinical study in women (n = 42; 19 endometriosis, 23 controls). Menstrual blood samples were collected, and menstrual blood-derived stem cells were isolated for whole-genome DNA methylation sequencing. Differential methylation analysis was performed to identify disease-specific epigenetic biomarkers, and machine learning models were applied to evaluate the diagnostic performance of candidate markers. An external endometrial single-cell RNA sequencing atlas including endometriosis samples was employed to correlate RNA expression with the identified disease-specific methylation signature. RESULTS: Here we identify differentially methylated regions enriched in genes linked to hallmarks of endometriosis such as inflammation, tissue remodelling and development. These differentially methylated regions robustly distinguish cases from controls, independent of technical and clinical variables. Machine learning models trained and validated on these differentially methylated regions achieve high diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset shows that the differentially methylated regions may modulate gene expression, further supporting their biological relevance. CONCLUSIONS: These findings position menstrual blood-derived stem cell DNA methylation profiling as a promising, non-invasive approach for early endometriosis diagnosis and personalised care.
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Abstract

Background Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological insight. Menstrual blood-derived stem cells have been implicated in disease pathogenesis, but their diagnostic potential remains unexplored.

Methods

We conducted a case-control clinical study in women (n = 42; 19 endometriosis, 23 controls). Menstrual blood samples were collected, and menstrual blood-derived stem cells were isolated for whole-genome DNA methylation sequencing. Differential methylation analysis was performed to identify disease-specific epigenetic biomarkers, and machine learning models were applied to evaluate the diagnostic performance of candidate markers. An external endometrial single-cell RNA sequencing atlas including endometriosis samples was employed to correlate RNA expression with the identified disease-specific methylation signature.

Results

Here we identify differentially methylated regions enriched in genes linked to hallmarks of endometriosis such as inflammation, tissue remodelling and development. These differentially methylated regions robustly distinguish cases from controls, independent of technical and clinical variables. Machine learning models trained and validated on these differentially methylated regions achieve high diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset shows that the differentially methylated regions may modulate gene expression, further supporting their biological relevance.

Conclusions

These findings position menstrual blood-derived stem cell DNA methylation profiling as a promising, non-invasive approach for early endometriosis diagnosis and personalised care. Plain language summary Endometriosis affects about 1 in 10 women of reproductive age and can cause long-term pain and fertility problems. Yet many people wait 7 to 10 years for a diagnosis. This study explored whether menstrual-derived stem cells, which are found in menstrual blood and are linked to endometriosis, could help identify the condition earlier by providing biological markers. We analysed DNA methylation, patterns of genetic regulation in these cells. These DNA methylation patterns differed between patients with endometriosis and healthy individuals and were connected to biological processes involved in the disease. These findings suggest that menstrual blood could offer a simple, non-invasive way to detect endometriosis earlier, improve understanding of the condition and guide personalised care. Similar content being viewed by others

Acknowledgements

We thank Life & Brain GmbH for providing sequencing services. We are grateful to the physicians who contributed to the clinical study: Meritxell Gracia, Georgina Feixas, Victoria Sánchez Sánchez, Patricia Esther Escamilla, Luciana Obreros, Mariazell García Pérez, Neuda Marqués de Oliveira, José Vázquez Nuñez, Patricia Hernández Delgado, and Juan José Artazkoz Marques de Oliveira. We also acknowledge CRAnarias, Investigación y Desarrollo S.L. for clinical study management, and Teresa Galera Monge for coordinating the study internally. We thank Nilufer Rahmioglu and Altuna Akalin for their scientific support, and Pablo Arriagada and Verónica Alam for their clinical and operational guidance. This study was funded by endogene.bio, with grant support from Bpifrance. Author information Authors and Affiliations Corresponding authors Ethics declarations Competing interests C.B., R.P.M., I.T., S.H., S.R.V., R.N.M. and C.F.M. are employees of endogene.bio. M.T.P.Z. is the Chief Executive Officer of endogene.bio. All other authors declare no competing interests. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary information Rights and permissions Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. About this article Cite this article Tiniakou, I., Bafligil, C., Pérez-Moraga, R. et al. Whole genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis. Commun Med (2026). https://doi.org/10.1038/s43856-026-01641-3 Received: Accepted: Published: DOI: https://doi.org/10.1038/s43856-026-01641-3

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