ArticleFrontiers in immunology2023
Identification of immune-associated genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 27 citations in OpenAlex.
- Identification of Diagnostic Biomarkers Among Metabolism-related Genes in Rheumatoid Arthritis: Insights into Immune Landscape and Molecular Subtype Characterization.Applied biochemistry and biotechnology · 2026Article
- Mifepristone ameliorates osteoporosis & hyperlipidemia comorbidity through SPNS3-S1P-S1PR1 axis via regulating BMSCs differentiation.Journal of pharmaceutical analysis · 2026Article
- Interleukin-1 Receptor-Associated Kinase 3 Attenuates Chondrocyte Senescence and Osteoarthritis via Inhibition of the TLR7/9-NF-κB Axis.Journal of molecular histology · 2026Article
- Immune cells with senescence-related transcriptional signatures orchestrate the inflammatory continuum in osteoarthritis synovium: a single-cell and machine learning study.Frontiers in immunology · 2026Article
- From algorithm to verification: based on network toxicology and machine learning, the immunomodulatory role of IGFBP1/MKI67/C9 in perfluorooctanoic acid-induced osteoarthritis was discovered, and a diagnostic model was constructed.Frontiers in immunology · 2026Article
- Unveiling novel potential drug targets for lung cancer through Mendelian randomization analysis.Scientific reports · 2025Article
- Advancing osteoarthritis research: the role of AI in clinical, imaging and omics fields.Bone research · 2025Review
- Screening necroptosis genes influencing osteoarthritis development based on machine learning.Scientific reports · 2025Article
- A multidimensional approach reveals the function of lactylation related genes in osteoarthritis.Scientific reports · 2025Article
- Decoding Alzheimer's Disease With Depression: Molecular Insights and Therapeutic Target.Journal of cellular and molecular medicine · 2025Article
- Identification and Validation of Fibroblast-Associated Genes in Osteoarthritis Based on High-Dimensional Weighted Gene Coexpression Network Analysis.Journal of immunology research · 2025Article
- IRAK3 is upregulated in rheumatoid arthritis synovium and delays the onset of experimental arthritis.Frontiers in immunology · 2025Article
- Identification and Experimental Validation of Biomarkers Associated With Mitochondria and Macrophage Polarization in Sepsis.Emergency medicine international · 2025Article
- Integrated Transcriptome Analysis Reveals Novel Molecular Signatures for Schizophrenia Characterization.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Uncovering the shared neuro-immune-related regulatory mechanisms between spinal cord injury and osteoarthritis.Heliyon · 2024Article
- Unveiling the bioinformatic genes and their involved regulatory mechanisms in type 2 diabetes combined with osteoarthritis.Frontiers in immunology · 2024Article
- Identification of diagnostic genes and drug prediction in metabolic syndrome-associated rheumatoid arthritis by integrated bioinformatics analysis, machine learning, and molecular docking.Frontiers in immunology · 2024Article
- Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head.Frontiers in immunology · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: In the pathogenesis of osteoarthritis (OA) and metabolic syndrome (MetS), the immune system plays a particularly important role. The purpose of this study was to find key diagnostic candidate genes in OA patients who also had metabolic syndrome. Methods: We searched the Gene Expression Omnibus (GEO) database for three OA and one MetS dataset. Limma, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms were used to identify and analyze the immune genes associated with OA and MetS. They were evaluated using nomograms and receiver operating characteristic (ROC) curves, and finally, immune cells dysregulated in OA were investigated using immune infiltration analysis. Results: After Limma analysis, the integrated OA dataset yielded 2263 DEGs, and the MetS dataset yielded the most relevant module containing 691 genes after WGCNA, with a total of 82 intersections between the two. The immune-related genes were mostly enriched in the enrichment analysis, and the immune infiltration analysis revealed an imbalance in multiple immune cells. Further machine learning screening yielded eight core genes that were evaluated by nomogram and diagnostic value and found to have a high diagnostic value (area under the curve from 0.82 to 0.96). Conclusion: Eight immune-related core genes were identified (
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