{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T10:07:59Z","timestamp":1790071679525,"version":"4.0.1"},"reference-count":113,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:p>Osteoarthritis (OA) is a heterogeneous whole-joint disorder in which pain, structural progression and treatment response often diverge from radiographic severity. This mismatch has limited disease-modifying OA drug development and highlights the need for biologically informed patient stratification. Chronic low-grade inflammation contributes to OA progression, but it is embedded within mechanical loading, metabolic dysfunction, synovitis, osteochondral remodeling, cellular senescence and pain sensitization rather than acting as a single-cytokine process. Here, we propose a Node-Edge-Boundary-Emergent (NEBE) inflammatory ecosystem framework that organizes current OA evidence around cellular nodes, communication edges, boundary conditions and emergent disease states. We summarize evidence from human tissue studies, imaging-linked biomarker work, single-cell and spatial analyses, preclinical models and clinical trials. Mechanisms are organized around three translational processes: damage sensing, multicellular network amplification and failed inflammatory resolution. We then discuss candidate biological states, including inflammatory-dominant, metabolic, senescence-associated, osteochondral-remodeling and mechanical-structural OA, and map therapeutic strategies to the ecosystem level they primarily target. Prior failures of cytokine blockade and several disease-modifying approaches may reflect ecosystem mismatch involving the wrong target level, patient population, disease stage or endpoint rather than simple irrelevance of inflammation. Routine phenotyping and MRI may provide first-level stratification, biomarkers may support exploratory trial enrichment and high-cost omics should be reserved for discovery, validation and selected complex cases. Prospective human cohorts and biomarker-guided trials are required to determine whether NEBE-informed stratification improves target engagement, progression prediction or treatment selection beyond existing OA frameworks.<\/jats:p>","DOI":"10.3389\/fmed.2026.1976217","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T09:44:25Z","timestamp":1790070265000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The osteoarthritis inflammatory ecosystem: a node-edge-boundary-emergent framework toward precision stratification and therapeutic hypothesis generation"],"prefix":"10.3389","volume":"13","author":[{"given":"Zhiwen","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Orthopedics and Traumatology, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine","place":["Harbin, Heilongjiang, 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