Identification of immune-related diagnostic genes and immune cell infiltration in aseptic loosening of prostheses after total hip arthroplasty by integrated bioinformatics analysis and experimental confirmation - Liu, Yunke; Liang, Xiaming; Qiang, Shuo; Dong, Yonghui; Zhao, Xin; Ma, Lichao; Yan, Zhihua; Yue, Songkai; Huang, Yifan; Zheng, Jia (Frontiers in Genetics, 2025)
BackgroundAseptic loosening (AL) of hip prostheses is one of the main reasons for revision total hip arthroplasty (rTHA). However, the transcriptomic characteristics of AL are scarcely understood. This study aimed to discover candidate biomarkers for the diagnosis of AL.Patients and methodsThe interface membrane from four patients with AL of hip prostheses and the synovium samples from four patients with a periprosthetic femoral fracture (PFF) after total hip arthroplasty (THA) were analyzed via RNA sequencing. Integrated bioinformatics analysis was employed to identify immune-related hub genes in AL. Immune cell infiltration analysis and correlation analysis were performed. Connectivity map analysis was utilized to predict the potential small-molecule compounds for AL treatment. Western blotting and histological staining were used to verify the expression of hub genes in AL.ResultsA total of 2,184 differentially expressed genes (DEGs) were identified in the AL samples, including 2,050 upregulated genes and 134 downregulated genes, and these DEGs were mainly enriched in immune cell-related signaling pathways and immune-related processes. Immune cell infiltration analysis showed that the proportion of M1 macrophages increased in AL. Three genes closely related to M1 macrophages were screened, namely, CD68, CD163, and SPP1, according to the results of correlation analysis. Hematoxylin–eosin staining showed that the synovitis score of AL samples was significantly higher than that of controls (average, 6.2 vs. 3.8). Western blotting and immunohistochemical analysis showed that the expression of CD68, CD163, and SPP1 in the AL group was significantly higher than that in the control group. The top 10 compounds with the highest negative scores were predicted to be potential therapeutic drugs for the treatment of AL.ConclusionPreliminary transcriptomic signatures suggested that CD68, CD163, and SPP1 may serve as potential biomarkers for AL, offering a novel research perspective for future diagnosis and therapeutic intervention of AL.