Predictive markers of endometriosis: a future perspective

Alexandre Vallée, Ayoubi JM, Jean-Marc Ayoubi
Archives of gynecology and obstetrics · 2026 · vol. 313(1) · doi:10.1007/s00404-026-08499-9 · PMID:42406164 · PMC13616853 · W7167510312
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This review synthesizes evidence on emerging genetic, epigenetic, and clinical factors as predictive markers for endometriosis, highlighting their potential for risk stratification and preventive strategies.

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This narrative review examines emerging predictive markers for endometriosis, focusing on how genetic and epigenetic alterations and clinical features such as dysmenorrhea, migraine, autoimmune and endocrine disorders, and stress or early-life adversity have been linked to disease initiation, lesion development, and symptom severity. The authors describe endometriosis as a multifactorial condition with shared genetic and molecular pathways with other chronic pain and inflammatory disorders, and they synthesize evidence supporting the need for multimodal risk stratification that considers interactions among candidate markers. A key limitation acknowledged is that, despite progress, large prospective studies are still required to validate these biomarkers and enable targeted interventions. This paper is centrally about endometriosis — it synthesizes current evidence on predictive biomarkers and future validation needs for risk stratification in endometriosis.

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Abstract

Endometriosis is a chronic gynecological disorder affecting up to 10% of women of reproductive age and is characterized by the presence of endometrial-like tissue outside the uterus. The condition is associated with chronic pelvic pain, dysmenorrhea, dyspareunia, and infertility, and remains difficult to diagnose at early stages. Recent evidence suggests that endometriosis shares genetic and molecular pathways with other chronic pain and inflammatory disorders. Identifying reliable biomarkers is therefore essential to improve risk stratification and support earlier evaluation. Multiple domains have emerged as candidate markers for risk stratification, including genetic and epigenetic alterations, dysmenorrhea, migraine, autoimmune and endocrine disorders, and stress and early-life adversity. These factors have been associated with disease initiation, lesion development, and symptom severity. Understanding their interactions could support multimodal risk stratification approaches and guide preventive strategies. This narrative review highlights the multifactorial nature of endometriosis and synthesizes current evidence on emerging predictive markers. Although progress has been made, large prospective studies are still needed to validate these markers and facilitate the development of targeted interventions.
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Abstract

Endometriosis is a chronic gynecological disorder affecting up to 10% of women of reproductive age and is characterized by the presence of endometrial-like tissue outside the uterus. The condition is associated with chronic pelvic pain, dysmenorrhea, dyspareunia, and infertility, and remains difficult to diagnose at early stages. Recent evidence suggests that endometriosis shares genetic and molecular pathways with other chronic pain and inflammatory disorders. Identifying reliable biomarkers is therefore essential to improve risk stratification and support earlier evaluation. Multiple domains have emerged as candidate markers for risk stratification, including genetic and epigenetic alterations, dysmenorrhea, migraine, autoimmune and endocrine disorders, and stress and early-life adversity. These factors have been associated with disease initiation, lesion development, and symptom severity. Understanding their interactions could support multimodal risk stratification approaches and guide preventive strategies. This narrative review highlights the multifactorial nature of endometriosis and synthesizes current evidence on emerging predictive markers. Although progress has been made, large prospective studies are still needed to validate these markers and facilitate the development of targeted interventions. Similar content being viewed by others

Acknowledgements

Not applicable. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author information Authors and Affiliations Corresponding author Ethics declarations Conflict of interest The authors declare no competing interests. Ethical approval Not applicable. Consent to publish Not applicable. Additional information Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 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 Vallée, A., Ayoubi, JM. Predictive markers of endometriosis: a future perspective. Arch Gynecol Obstet (2026). https://doi.org/10.1007/s00404-026-08499-9 Received: Accepted: Published: DOI: https://doi.org/10.1007/s00404-026-08499-9

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MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Biomarkers Biomarkers Biomarkers Biomarkers Biomarkers Biomarkers Biomarkers Biomarkers Female Female

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