Early diagnosis of osteoarthritis (OA) is critical for effective cartilage repair. However, lack of blood vessels in articular cartilage poses a barrier to contrast agent delivery and subsequent diagnostic imaging. To address this challenge, we proposed to develop ultra-small superparamagnetic iron oxide nanoparticles (SPIONs, 4 nm) that can penetrate into the matrix of articular cartilage, and further modified with the peptide ligand WYRGRL (particle size, 5.9 nm), which allows SPIONs to bind to type II collagen in the cartilage matrix and increase the retention of probes. Type II collagen in the cartilage matrix is gradually lost with the progression of OA, consequently, the binding of peptide-modified ultra-small SPIONs to type II collagen in the OA cartilage matrix is less, thus presenting different magnetic resonance (MR) signals in OA group from the normal ones. By introducing the AND logical operation, damaged cartilage can be differentiated from the surrounding normal tissue on T1 and T2 AND logical map of MR images, and this was also verified in histology studies. Overall, this work provides an effective strategy for delivering nanosized imaging agents to articular cartilage, which could potentially be used to diagnosis joint-related diseases such as osteoarthritis.

OBJECTIVE: This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue.
METHODS: The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.
RESULTS: A total of 88 DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that DEGs were significantly enriched in leucocyte migration and interleukin (IL)-17 signalling pathways. Disease ontology (DO) indicated that DEGs were mostly enriched in rheumatoid arthritis. Six hub genes including FosB proto-oncogene, AP-1 transcription factor subunit (FOSB); C-X-C motif chemokine ligand 2 (CXCL2); CXCL8; IL-6; Jun proto-oncogene, AP-1 transcription factor subunit (JUN); and Activating transcription factor 3 (ATF3) were identified and verified by GEO datasets. ATF3 (area under the curve = 0.975) turned out to be a potential biomarker for the diagnosis of early OA. Several infiltrating immune cells varied significantly between early-stage OA and end-stage OA, such as resting NK cells (p = 0.016), resting dendritic cells (p = 0.043), and plasma cells (p = 0.043). Additionally, ATF3 was significantly correlated with resting NK cells (p = 0.034), resting dendritic cells (p = 0.026), and regulatory T cells (Tregs, p = 0.018).
CONCLUSIONS: ATF3 may be a potential diagnostic marker for early diagnosis and treatment of OA, and immune cell infiltration provides new perspectives for understanding the mechanism during OA progression.Cite this article: Bone Joint Res 2022;11(9):679-689.