Identification of Key Genes Underlying the Effects of Obesity on Knee Osteoarthritis
Osteoarthritis (OA) is a debilitating disease characterized by high morbidity and disability. Obesity, defined as a body mass index (BMI) of 30 kg/m² or higher, is a well-established risk factor for the onset and progression of OA. While the association between obesity and OA is widely recognized, the underlying molecular mechanisms linking these two conditions remain poorly understood. This study aimed to identify key genes and molecular pathways that mediate the effects of obesity on knee OA, using a combination of bioinformatics approaches, including weighted gene co-expression network analysis (WGCNA), differential expression analysis, and protein-protein interaction (PPI) network analysis.
The study utilized the GSE98460 dataset from the Gene Expression Omnibus (GEO) database, which contains gene expression profiles of knee cartilage samples from 23 end-stage OA patients. The dataset includes 46 samples, with 23 from the lateral tibial plateau and 23 from the medial tibial plateau. After quality control and outlier removal, 45 samples were retained for further analysis. The top 50% of genes with the highest median absolute deviation (MAD) values, totaling 7439 genes, were selected for WGCNA analysis.
The WGCNA approach was employed to construct a gene co-expression network and identify modules of genes that are highly correlated with clinical traits, such as BMI. A soft-thresholding power of 18 was chosen to ensure a scale-free network, resulting in the identification of ten distinct gene modules. Among these, three modules (light-green, salmon, and steel-blue) showed significant associations with BMI, with absolute correlation coefficients greater than 0.5 and p-values less than 0.05. These three modules contained 458 genes, which were considered key candidates for further analysis.
To understand the biological functions and pathways associated with these genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. The GO analysis revealed that the genes in the three modules were significantly enriched in biological processes such as ossification, connective tissue development, cartilage development, reactive oxygen species metabolic process, and osteoblast differentiation. The KEGG pathway analysis highlighted enrichment in pathways related to glutathione metabolism, MAPK signaling, PI3K-Akt signaling, and the cell cycle, particularly in the ribosome.
Next, the OA samples were stratified into non-obese (BMI <30 kg/m²) and obese (BMI ≥30 kg/m²) groups to identify differentially expressed genes (DEGs). Using the R package "limma," 289 DEGs were identified, comprising 146 upregulated and 143 downregulated genes. GO and KEGG analyses of the DEGs revealed their involvement in processes such as negative regulation of cell migration, regulation of leukocyte migration, and negative regulation of cellular component movement. KEGG pathway analysis further implicated the DEGs in apoptosis, glutathione metabolism, and fatty acid metabolism.
To identify key genes, a PPI network was constructed using the 458 genes from the three significant modules and the 289 DEGs. The network, generated using the STRING database, consisted of 378 nodes (proteins) and 895 interactions (edges). Thirty genes with a degree of connectivity greater than 20 were identified as hub genes. Further analysis using the MCC algorithm narrowed down the list to ten key genes: RPS5, RPL8, RPL17, RPL36, RPL18, RPL18A, RPL22L1, MRPL3, RPS19, and RPS9. These genes encode ribosomal proteins, which are essential for ribosome biogenesis—a process not previously implicated in OA pathology.
The study hypothesized that the upregulation of ribosomal protein genes in obese individuals may represent a compensatory response to stress stimuli, such as obesity. This stress-induced alteration in ribosomal protein expression could contribute to the pathogenesis of OA by promoting endochondral ossification, a process that leads to cartilage degeneration. The findings suggest that obesity-induced changes in ribosomal protein genes may play a critical role in the onset and progression of OA.
The study also highlighted the enrichment of genes involved in ossification, reactive oxygen species metabolic processes, and osteoblast differentiation in the three key modules. These processes have been previously linked to OA progression, further supporting the hypothesis that obesity exacerbates OA through genetic alterations in these pathways.
In conclusion, this study identified ribosomal protein genes as potential mediators of obesity-induced knee OA. The findings provide new insights into the molecular mechanisms underlying the relationship between obesity and OA, suggesting that ribosomal protein genes may serve as novel therapeutic targets. Future research will focus on validating these findings through additional experiments to further elucidate the role of ribosomal proteins in OA pathogenesis.
doi.org/10.1097/CM9.0000000000001670
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