RANKL-convergent osteoimmune network framework in osteoporosis: integrating macrophage activation, T-cell imbalance, and cytokine crosstalk.

Background: Osteoporosis is classically defined by reduced bone mass and microarchitectural deterioration, but osteoimmune dysregulation within the bone marrow microenvironment is increasingly recognized as an important contributor to bone loss. The RANKL/RANK/OPG axis represents a dominant pathway governing osteoclast differentiation and bone resorption, yet its activity is shaped by macrophage activation, T-cell subset imbalance, and cytokine feedback loops. Existing reviews often examine these components separately; fewer conceptualize their network-level convergence on RANKL-dependent osteoclastogenesis across osteoporosis subtypes and disease stages. Methods: Literature was searched in PubMed, Web of Science, and Scopus using combinations of "osteoporosis", "osteoimmunology", "RANKL", "macrophage polarization", "Th17", "Treg", "cytokine", and related terms. Priority was given to mechanistic studies, animal models, clinical observational studies, and recent reviews directly relevant to RANKL-dependent osteoclastogenesis and bone marrow immune regulation. Results: Pro-inflammatory M1-like macrophages, Th1/Th17 responses, and cytokines such as TNF-α, IL-1β, IL-6, and IL-17 may promote osteoclastogenesis by upregulating RANKL expression, increasing the RANKL/OPG ratio, and enhancing the responsiveness of osteoclast precursors to RANKL. Together, these mechanisms form a pro-inflammatory and pro-osteoclastogenic amplification loop. Conversely, M2-like macrophages, osteal macrophages, Treg/Th2 responses, and factors such as IL-10, TGF-β, IL-4, IL-13, and OPG may restrain excessive osteoclast formation and contribute to inflammation resolution, immune tolerance, and bone repair. Different forms of osteoporosis may share RANKL-dependent bone resorption as a common final effector process, yet differ substantially in their upstream immune drivers. Conclusion: Interpreting RANKL as a convergent effector node, rather than a RANKL-exclusive explanation, provides a framework for understanding osteoporosis heterogeneity and guiding osteoimmune-based stratification. Future studies incorporating human bone marrow samples, longitudinal cohorts, single-cell and spatial omics, immunometabolic analyses, and bone-targeted delivery technologies are needed to validate network states and translate immunomodulatory strategies into individualized osteoporosis management.