Identification of Potential Genetic Biomarkers and Target Genes of Peri-Implantitis Using Bioinformatics Tools.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34931168", "kind": "science-record", "revision": 4, "content_hash": "sha256:ea9cb1ded4b0af66ae90d90f619f790008d440f6542988906e05259ecfa1ab19", "created_at": "2026-11-01T17:36:38Z", "updated_at": "2026-11-01T22:05:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Potential Genetic Biomarkers and Target Genes of Peri-Implantitis Using Bioinformatics Tools.", "doi": "10.1155/2021/1759214", "pmid": "34931168", "authors": ["Xiaogen Zhang", "Zhifa Wang", "Li Hu", "Xiaoqing Shen", "Chundong Liu"], "journal": "BioMed research international", "year": 2021, "abstract": "OBJECTIVES: To investigate potential genetic biomarkers of peri-implantitis and target genes for the therapy of peri-implantitis by bioinformatics analysis of publicly available data.\nMETHODS: The GSE33774 microarray dataset was downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) between peri-implantitis and healthy gingival tissues were identified using the GEO2R tool. GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the DAVID database and the Metascape tool, and the results were expressed as a bubble diagram. The protein-protein interaction network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized using Cytoscape. The hub genes were screened by the cytoHubba plugin of Cytoscape. The potential target genes associated with peri-implantitis were obtained from the DisGeNET database and the Open Targets Platform. The intersecting genes were identified using the Venn diagram web tool.\nRESULTS: Between the peri-implantitis group and the healthy group, 205 DEGs were investigated including 140 upregulated genes and 65 downregulated genes. These DEGs were mainly enriched in functions such as the immune response, inflammatory response, cell adhesion, receptor activity, and protease binding. The results of KEGG pathway enrichment analysis revealed that DEGs were mainly involved in the cytokine-cytokine receptor interaction, pathways in cancer, and the PI3K-Akt signaling pathway. The intersecting genes, including IL6, TLR4, FN1, IL1β, CXCL8, MMP9, and SPP1, were revealed as potential genetic biomarkers and target genes of peri-implantitis.\nCONCLUSIONS: This study provides supportive evidence that IL6, TLR4, FN1, IL1β, CXCL8, MMP9, and SPP1 might be used as potential target biomarkers for peri-implantitis which may provide further therapeutic potentials for peri-implantitis.", "claims": [{"id": "claim-method", "statement": "The DEGs between peri-implantitis samples and healthy samples were analyzed using the GEO2R online analysis tool (http://www.ncbi.nlm.nih.gov/geo/geo2r). The DEGs with the threshold criterion of ∣log(fold change) | ≥1.0 and P value < 0.05 were considered to be significantly differentially expressed.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34931168", "locator": "sections[3] \"2.1. Data Source and Identification of DEGs\" paragraph 3", "quote": "The DEGs between peri-implantitis samples and healthy samples were analyzed using the GEO2R online analysis tool (http://www.ncbi.nlm.nih.gov/geo/geo2r). The DEGs with the threshold criterion of ∣log(fold change) | ≥1.0 and P value < 0.05 were considered to be significantly differentially expressed."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed during the current study are available in the Gene Expression Omnibus with the accession GSE33774.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34931168", "locator": "sections[15] \"Data Availability\" paragraph 2", "quote": "The datasets analyzed during the current study are available in the Gene Expression Omnibus with the accession GSE33774."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 205 DEGs between peri-implantitis and healthy gingival tissues, including 140 upregulated and 65 downregulated genes.", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "We identified 205 DEGs including 140 upregulated genes and 65 downregulated genes based on the criteria of P < 0.05 and ∣logFC | ≥1.0."}, "evidence": [{"asset": "source:pmid:34931168", "locator": "sections[8] \"3.1. Identification of DEGs\" paragraph 2", "quote": "We identified 205 DEGs including 140 upregulated genes and 65 downregulated genes based on the criteria of P < 0.05 and ∣logFC | ≥1.0."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 205 DEGs between peri-implantitis and healthy gingival tissues, including 140 upregulated and 65 downregulated genes.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34931168"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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