ArticleCombinatorial chemistry & high throughput screening2023
Identification of Key Diagnostic Markers and Immune Infiltration in Osteoarthritis.
Article in Combinatorial chemistry & high throughput screening, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Genetic Biomarkers and Circulating White Blood Cells in Osteoarthritis: A Bioinformatics and Mendelian Randomization Analysis.Biomedicines · 2025Article
- Bioinformatics analysis of hub genes as osteoarthritis prognostic biomarkers.Scientific reports · 2023Article
- Single-cell RNA sequencing reveals distinct chondrocyte states in femoral cartilage under weight-bearing load in Rheumatoid arthritis.Frontiers in immunology · 2023Article
- Spatial transcriptomics of the lacrimal gland features macrophage activity and epithelium metabolism as key alterations during chronic inflammation.Frontiers in immunology · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOsteoarthritis (OA) is a worldwide chronic disease of the articulating joints. An increasing body of data demonstrates the immune system's involvement in osteoarthritis. The molecular mechanisms of OA are still unclear. This study aimed to search for OA immunerelated hub genes and determine appropriate diagnostic markers to help the detection and treatment of the disease.
methodsGene expression data were downloaded from the GEO database. Firstly, we analyzed and identified the differentially expressed genes (DEGs) using R packages. Meanwhile, ssGSEA was used to determine the activation degree of immune-related genes (IRGs), and WGCNA analysis was applied to search for co-expressed gene modules associated with immune cells. Then, critical networks and hub genes were found in the PPI network. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analyzed the biological functions of genes. The ability of the hub genes to differentiate OA from controls was assessed by the area under the ROC curve. A miRNA and transcription factor (TF) regulatory network was constructed according to their relationship with hub genes. Finally, the validation of hub genes was carried out by qPCR.
resultsIn total, 353 DEGs were identified in OA patients compared with controls, including 222 upregulated and 131 downregulated genes. WGCNA successfully identified 34 main functional modules involved in the pathogenesis of OA. The most crucial functional module involved in OA included 89 genes. 19 immune-related genes were obtained by overlapping DEGs with the darkgrey module. The String database was constructed using the protein-protein interaction (PPI) network of 19 target genes, and 7 hub genes were identified by MCODE. ROC curve showed that 7 hub genes were potential biomarkers of OA. The expression levels of hub genes were validated by qPCR, and the results were consistent with those from bioinformatic analyses.
conclusionImmune-related hub genes, including TYROBP, ITGAM, ITGB2, C1QC, MARCO, C1QB, and TLR8, may play critical roles in OA development. ITGAM had the highest correction on immune cells.
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