ArticleBMC musculoskeletal disorders2024
Identification of HTRA1, DPT and MXRA5 as potential biomarkers associated with osteoarthritis progression and immune infiltration.
Article in BMC musculoskeletal disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Single-Cell and Mendelian Randomization Analyses Identify Macrophage Polarization and Efferocytosis Biomarkers in Osteoarthritis and Reveal Their Regulatory Mechanisms.Iranian journal of biotechnology · 2026Article
- Transcriptomics in the Study of Bone and Cartilage.Current osteoporosis reports · 2026Review
- The oral-gut-joint axis in osteoarthritis: a multiomics case-control study.Frontiers in cellular and infection microbiology · 2026Observational
- Insights into Vascular Changes in Hip Degenerative Disorders: An Observational Study.Journal of clinical medicine · 2025Article
- Identification of MEG3 and MAPK3 as potential therapeutic targets for osteoarthritis through multiomics integration and machine learning.Scientific reports · 2025Article
- Identification and Validation of Fibroblast-Associated Genes in Osteoarthritis Based on High-Dimensional Weighted Gene Coexpression Network Analysis.Journal of immunology research · 2025Article
- The Causal Effects Between Circulating Inflammatory Proteins and Osteoarthritis: A Mendelian Randomization and Transcriptomic Analysis.Journal of pain research · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundOur study aimed to identify potential specific biomarkers for osteoarthritis (OA) and assess their relationship with immune infiltration.
methodsWe utilized data from GSE117999, GSE51588, and GSE57218 as training sets, while GSE114007 served as a validation set, all obtained from the GEO database. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed to identify hub modules and potential functions of genes. We subsequently screened for potential OA biomarkers within the differentially expressed genes (DEGs) of the hub module using machine learning methods. The diagnostic accuracy of the candidate genes was validated. Additionally, single gene analysis and ssGSEA was performed. Then, we explored the relationship between biomarkers and immune cells. Lastly, we employed RT-PCR to validate our results.
resultsWGCNA results suggested that the blue module was the most associated with OA and was functionally associated with extracellular matrix (ECM)-related terms. Our analysis identified ALB, HTRA1, DPT, MXRA5, CILP, MPO, and PLAT as potential biomarkers. Notably, HTRA1, DPT, and MXRA5 consistently exhibited increased expression in OA across both training and validation cohorts, demonstrating robust diagnostic potential. The ssGSEA results revealed that abnormal infiltration of DCs, NK cells, Tfh, Th2, and Treg cells might contribute to OA progression. HTRA1, DPT, and MXRA5 showed significant correlation with immune cell infiltration. The RT-PCR results also confirmed these findings.
conclusionsHTRA1, DPT, and MXRA5 are promising biomarkers for OA. Their overexpression strongly correlates with OA progression and immune cell infiltration.
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