ArticleHeliyon2024
Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 5 citations in OpenAlex.
- Synovial fluid proteomic biomarkers in periprosthetic joint infection: A systematic review with gene ontology and protein network analyses.Journal of experimental orthopaedics · 2026Review
- MarkerScout: A Disease-Agnostic Machine Learning Framework for Biomarker Prediction from Multi-Scale Mechanistic Models.bioRxiv : the preprint server for biology · 2026Article
- A novel host-based strategy for detecting low-grade prosthetic joint infection using immune cell pattern in synovial fluid.Molecular medicine (Cambridge, Mass.) · 2026Article
- Continuous monitoring of serum markers for early detection of periprosthetic joint infection in osteoporotic patients undergoing hip arthroplasty: A prospective cohort study.Journal of medical biochemistry · 2026Article
- Artificial intelligence in thyroid ultrasound: clinical applications and perspectives.Frontiers in endocrinology · 2026Review
- The Application of artificial intelligence in periprosthetic joint infection.Journal of advanced research · 2026Review
- Article
- Significant alterations in peripheral lymphocyte subsets and immune-related protein profiles in patients with periprosthetic joint infection.Frontiers in immunology · 2025Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The immune response associated with periprosthetic joint infection (PJI) is an emerging but relatively unexplored topic. The aim of this study was to investigate immune cell infiltration in periprosthetic tissues and identify potential immune-related biomarkers. Methods: The GSE7103 dataset from the GEO database was selected as the data source. Differentially expressed genes (DEGs) and significant modular genes in weighted correlation network analysis (WGCNA) were identified. Functional enrichment analysis and transcription factor prediction were performed on the overlapping genes. Next, immune-related genes from the ImmPort database were matched. The protein-protein interaction (PPI) analysis was performed to identify hub genes. CIBERSORTx was used to evaluate the immune cell infiltration pattern. Spearman correlation analysis was used to evaluate the relationship between hub genes and immune cells. Results: A total of 667 DEGs were identified between PJI and control samples, and 1847 PJI-related module genes were obtained in WGCNA. Enrichment analysis revealed that the common genes were mainly enriched in immune and host defense-related terms. TFEC, SPI1, and TWIST2 were the top three transcription factors. Three hub genes, Conclusion: The present study revealed immune infiltration signatures in the periprosthetic tissues of PJI patients.
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Registered trials
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