[Endometriosis pain research in Germany : ENDO-PAIN and StEPP-UPP-two new research consortia on endometriosis pain]

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Two German research consortia, StEPP-UPP and ENDO-PAIN, utilize diverse clinical and preclinical approaches to investigate endometriosis pain mechanisms, stratify patients, and identify therapeutic targets.

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This article outlines two new German research consortia, StEPP-UPP and ENDO-PAIN, designed to address the insufficiently defined mechanisms and predictors of chronic pelvic pain in endometriosis. StEPP-UPP utilizes prospective cohorts, multi-omics, and machine learning to stratify patients and predict persistent pain trajectories, while ENDO-PAIN investigates neuroinflammation and fibrosis using patient samples and organoids to identify novel therapeutic targets. Both initiatives integrate patient advocacy and aim to standardize data collection for a more personalized, mechanistically grounded approach to endometriosis pain management. This paper is centrally about endometriosis — specifically focusing on establishing research frameworks to understand and treat endometriosis-associated pain.

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Abstract

Endometriosis is one of the most common causes of chronic pelvic or lower-abdominal pain, yet mechanisms, predictors, and patient-centered treatment pathways remain insufficiently defined. This article summarizes the situation in Germany and presents two complementary research consortia: StEPP-UPP and ENDO-PAIN.StEPP-UPP addresses the clinical heterogeneity of endometriosis pain via a prospective multicenter cohort, standardized patient-reported outcomes, quantitative sensory testing, and multi-omics from blood, stool, and lesions. Explainable artificial intelligence and machine-learning models aim to estimate risk and trajectories of persistent pain, define mechanism-informed subgroups, and support treatment decisions. Preclinical mouse models with non-evoked behavioral metrics plus multiparametric MRI and single-cell analyses provide mechanistic anchoring for clinical signatures.ENDO-PAIN focuses on neuroinflammation and fibrosis as drivers of pain and chronification. Using patient samples, cell cultures, and 3D organoids, it maps immune-stroma interactions, syndecan signaling, and hormone-inflammation axes (for example P4-TGFβ-NFκB-COX-2) to derive biomarker networks and therapeutic targets.Both consortia integrate patient advocacy structurally to ensure patient-relevant endpoints and accessible information. Together they point to three priorities: standardization of data collection and biobanking; stratification along bio-psycho-social profiles and molecular signatures; and interdisciplinary shared decision-making across research, clinics, and people with endometriosis, aiming for mechanistically grounded, data-driven, patient-centered pain medicine.
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Zusammenfassung Endometriose ist eine der häufigsten Ursachen chronischer Becken‑/Unterbauchschmerzen; Mechanismen, Prädiktoren und patientinnenzentrierte Therapiepfade sind jedoch unzureichend definiert. Dieser Beitrag bündelt den Status quo in Deutschland und stellt zwei komplementäre Verbünde vor: StEPP-UPP und ENDO-PAIN. StEPP-UPP adressiert die klinische Heterogenität des Endometrioseschmerzes mit einer prospektiven Kohorte (prä- und postoperativ), standardisierten „patient-reported outcomes“, quantitativer sensorischer Testung (QST) und Multi-Omics. Erklärbare KI/ML-Modelle (künstliche Intelligenz/maschinelles Lernen) sollen Risiko und Verlauf persistierender Schmerzen abschätzen, Subgruppen definieren und Therapieentscheidungen unterstützen. Präklinische Mausmodelle mit nichtevozierten Verhaltensmetriken, multiparametrischer MRT und Single-Cell-Analysen verankern klinische Signaturen mechanistisch. ENDO-PAIN fokussiert auf Neuroinflammation und Fibrose als Treiber von Schmerz und Chronifizierung. Mit Patientinnenproben, Zellkulturen und 3D-Organoiden werden Immun- und Stromazell-Interaktionen, Syndecan-Signalwege und hormon-entzündliche Achsen (z. B. P4–TGFβ–NFκB–COX-2) kartiert, um Biomarker-Netzwerke und neue Zielstrukturen abzuleiten. Beide Verbünde integrieren Patientinnenvertretungen (Advisory, Material-Feedback, Dissemination), um patientinnenrelevante Endpunkte und verständliche Materialien zu sichern. Daraus ergibt sich ein Quo vadis: 1) Standardisierung von Erhebung und Biobanking (u. a. WERF-ePHect, FAIR); 2) Stratifizierung entlang bio-psycho-sozialer Profile und molekularer Signaturen; 3) interdisziplinäres Shared Decision-Making zwischen Forschung, Klinik und Betroffenen. Ziel ist eine mechanistisch fundierte, datengetriebene, patientinnenzentrierte Schmerzmedizin mit früherer Diagnose und passenderen Therapien. Abstract Endometriosis is one of the most common causes of chronic pelvic or lower-abdominal pain, yet mechanisms, predictors, and patient-centered treatment pathways remain insufficiently defined. This article summarizes the situation in Germany and presents two complementary research consortia: StEPP-UPP and ENDO-PAIN. StEPP-UPP addresses the clinical heterogeneity of endometriosis pain via a prospective multicenter cohort, standardized patient-reported outcomes, quantitative sensory testing, and multi-omics from blood, stool, and lesions. Explainable artificial intelligence and machine-learning models aim to estimate risk and trajectories of persistent pain, define mechanism-informed subgroups, and support treatment decisions. Preclinical mouse models with non-evoked behavioral metrics plus multiparametric MRI and single-cell analyses provide mechanistic anchoring for clinical signatures. ENDO-PAIN focuses on neuroinflammation and fibrosis as drivers of pain and chronification. Using patient samples, cell cultures, and 3D organoids, it maps immune–stroma interactions, syndecan signaling, and hormone–inflammation axes (for example P4–TGFβ–NFκB–COX-2) to derive biomarker networks and therapeutic targets. Both consortia integrate patient advocacy structurally to ensure patient-relevant endpoints and accessible information. Together they point to three priorities: standardization of data collection and biobanking; stratification along bio-psycho-social profiles and molecular signatures; and interdisciplinary shared decision-making across research, clinics, and people with endometriosis, aiming for mechanistically grounded, data-driven, patient-centered pain medicine. Similar content being viewed by others Datenverfügbarkeit Alle dieser Arbeit zugrunde liegenden Daten sind in diesem Artikel enthalten. Literatur Becker CM, Bokor A, Heikinheimo O et al (2022) ESHRE guideline: endometriosis. 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Fertil Steril 102:1223–1232. https://doi.org/10.1016/J.FERTNSTERT.2014.07.1244 Vollert J, Egert VM, Segelcke D et al (2026) Minimal Clinically Important Changes of Patient-reported Outcome Measures for Acute Postsurgical Pain. Anesthesiology 144:143–153. https://doi.org/10.1097/ALN.0000000000005792 Vollert J, Segelcke D, Weinmann C et al (2024) Responsiveness of multiple patient-reported outcome measures for acute postsurgical pain: primary results from the international multi-centre PROMPT NIT‑1 study. Br J Anaesth 132:96–106. https://doi.org/10.1016/j.bja.2023.10.020 Wang Z, Ouyang Y, Xue Z et al (2025) Global, regional, and national burden and trends of endometriosis, 1990–2021: an analysis of the global burden of disease study 2021 and forecast to 2050. BMC Womens Health. https://doi.org/10.1186/s12905-025-04043-0 Wilkinson MD, Dumontier M, Aalbersberg IjJ et al (2016) The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3(1):160018. https://doi.org/10.1038/sdata.2016.18 Endometriose-Vereinigung Deutschland e. V. https://www.endometriose-vereinigung.de/. Zugegriffen: 15. Dezember 2025 SHG Aufgefangen Münster. https://www.aufgefangen-muenster.de/home/. Zugegriffen: 15. Dezember 2025 Funding BP und EP haben gemeinsam Förderung erhalten: BMFTR (01EJ2404). SM hat Förderung erhalten: BMFTR (01EJ2402A). Author information Authors and Affiliations Corresponding author Ethics declarations Interessenkonflikt R. Voltolini Velho, B. Pradier, F. Werner, E. Pogatzki-Zahn und S. Mechsner geben an, dass kein Interessenkonflikt besteht. Für diesen Beitrag wurden von den Autor/-innen keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien. Additional information Hinweis des Verlags Der Verlag bleibt in Hinblick auf geografische Zuordnungen und Gebietsbezeichnungen in veröffentlichten Karten und Institutsadressen neutral. QR-Code scannen & Beitrag online lesen Rights and permissions About this article Cite this article Velho, R.V., Pradier, B., Werner, F. et al. Endometrioseschmerz-Forschung in Deutschland. Schmerz 40, 264–269 (2026). https://doi.org/10.1007/s00482-026-00958-1 Received: Accepted: Published: Version of record: Issue date: DOI: https://doi.org/10.1007/s00482-026-00958-1

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Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

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