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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.
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BP und EP haben gemeinsam Förderung erhalten: BMFTR (01EJ2404). SM hat Förderung erhalten: BMFTR (01EJ2402A).
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R. Voltolini Velho, B. Pradier, F. Werner, E. Pogatzki-Zahn und S. Mechsner geben an, dass kein Interessenkonflikt besteht.
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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
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DOI: https://doi.org/10.1007/s00482-026-00958-1
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