Background: Osteoarthritis (OA) pathogenesis involves age-related immune dysregulation, yet non-invasive diagnostic tools and mechanistic insights remain limited. Methods: We integrated transcriptomic profiling of four OA-affected joint tissues with machine learning to identify potential peripheral blood biomarkers. Weighted gene co-expression network analysis was employed to explore gene modules and pathways associated with OA. Single-cell RNA sequencing was performed on 217 983 joint cells to delineate B cell differentiation trajectories. Flow cytometry was used to validate age-associated B cell imbalances in peripheral blood. Results: We identified five peripheral blood biomarkers: MAPK1, MAP3K8, ING1, LDLR, and NUP153 in distinguishing OA patients from controls (the area under the curve [AUC] = 0.966). Importantly, these markers exhibited age-specific expression profiles; ING1, NUP153, and MAP3K8 were elevated, while MAPK1 was reduced in elderly compared to younger OA patients. A refined predictive model based on these age-specific markers demonstrated superior performance specifically for elderly Knee OA (KOA, AUC: 0.8 vs. 0.7 for younger KOA). These biomarkers correlated with immune cell infiltration and inflammatory cytokines. In osteoarthritic joint tissues, B cells predominantly originated from subchondral bone and synovium. Single-cell analysis identified age-specific B cell differentiation patterns, with elderly KOA patients enriched in an activated B cell cluster (C1). Furthermore, B cells from elderly KOA patients showed altered energy metabolism and increased proportions in peripheral blood, and functionally promoted chondrocyte damage. Conclusion: Our findings establish a novel blood-based diagnostic framework for OA and uncover aging-driven B cell remodeling as a key contributor to elderly OA pathogenesis. These findings offer non-invasive diagnostics and immunomodulatory targets for age-specific OA therapy.

Total knee arthroplasty (TKA) is an effective treatment for end-stage knee osteoarthritis (KOA). Previous studies have found that KOA patients commonly experience sleep disorders during the perioperative period of TKA, which can significantly affect postoperative recovery, pain management, and quality of life. Sleep disturbances during the perioperative period of TKA are a complex issue influenced by multiple factors. Although clinical interventions have shown promising efficacy, the underlying mechanisms remain unclear and require further research. This article reviews the specific causes of sleep disturbances in TKA patients during the perioperative period, aiming to provide a reference for personalized sleep regulation interventions to improve postoperative outcomes. The article begins by searching public databases using selected keywords to identify recent studies on the management of sleep dysfunction during the perioperative period of TKA. Through a summary of the relevant literature, the review focuses on the incidence, influencing factors, interventions, and potential mechanisms of sleep dysfunction during the perioperative period of TKA. It aims to optimize perioperative management and support the future development of high-quality clinical intervention randomized controlled trials, ultimately contributing to the optimization of postoperative sleep management strategies and enhancing rapid recovery and long-term satisfaction in TKA patients.