ArticleMedical science monitor : international medical journal of experimental and clinical research2024
Comprehensive Analysis of Immune Infiltration and Key Genes in Peri-Implantitis Using Bioinformatics and Molecular Biology Approaches.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Transcriptomic and Metagenomic Biomarkers in Peri-Implantitis: A Systematic Review, Diagnostic Meta-Analysis, and Functional Meta-Synthesis.Medical sciences (Basel, Switzerland) · 2025Pooled it
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Peri-implantitis is the main cause of failure of implant treatment, and there is little research on its molecular mechanism. This study aimed to identify key biomarkers and immune infiltration of peri-implantitis using a bioinformatics method. MATERIAL AND METHODS Three Gene Ontology (GO) gene expression profiles were selected from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified by the LIMMA package, and functional correlations of DEGs were analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Information on immune-related genes was obtained from ImmPort (https://www.immport.org) and InnateDB (http://www.innatedb.com). Immune-related DEGs were screened by least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE). The single-sample Gene Set Enrichment Analysis algorithm was used to analyze immune cell infiltration in gingival tissue between peri-implantitis and normal controls. Finally, results of bioinformatics analysis were verified by qPCR. RESULTS A total of 398 DEGs were identified, of which 96 were immune-related. Enrichment analysis showed these genes were enriched in inflammatory response, leucocyte chemotaxis, immune response-regulating signaling pathway, and cell activation. Seven key genes were selected by LASSO and SVM-RFE. Receiver operating characteristic curve results showed these genes had excellent diagnostic efficacy. Results of qPCR showed significant differences in the expression of these genes. CONCLUSIONS Differences in key genes and immune infiltration between peri-implantitis and gingival tissues of normal controls may provide new insights into the development of peri-implantitis. Elucidating the difference in immune infiltration between peri-implantitis tissues and normal tissues will help to understand the development of peri-implantitis.
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