Multi-omic profiling reveals age-specific blood biomarkers and aging-driven B cell remodeling in osteoarthritis

Clinical Snapshot

Key Findings

• P Value: Not reported in abstract

• Effect Size: AUC = 0.966 for overall OA diagnosis; AUC = 0.8 for elderly knee OA vs 0.7 for younger knee OA

• Primary Outcome: Five-biomarker panel (MAPK1, MAP3K8, ING1, LDLR, NUP153) for OA diagnosis

• Nnt Or Sensitivity: Age-specific biomarker expression patterns with ING1, NUP153, MAP3K8 elevated and MAPK1 reduced in elderly vs younger OA patients

• Confidence Interval: Not reported in abstract

Clinical Application

Blood-based biomarkers offer practical non-invasive diagnostic approach suitable for primary care and specialist settings Could complement existing RACGP osteoarthritis guidelines by providing objective diagnostic support, particularly valuable given PBS restrictions on imaging and specialist referrals for OA management Adults with suspected osteoarthritis, particularly elderly patients with knee OA where diagnostic accuracy appears superior

Abstract

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.

References

1. 1.Tu, B., Fang, R., Lu, P., Liu, M., Yang, S., Hu, D., Ruan, R., & Ning, R. (2025). Multi-omic profiling reveals age-specific blood biomarkers and aging-driven B cell remodeling in osteoarthritis. International Journal of Surgery. https://doi.org/10.1097/JS9.0000000000003076