Gene Correlation Network Analysis to Identify Biomarkers of Peri-Implantitis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36013591", "kind": "science-record", "revision": 5, "content_hash": "sha256:010afe6051811b6f4743da68f2415def2bf447d3abb7404db0bd549716630560", "created_at": "2026-11-01T18:15:10Z", "updated_at": "2026-11-01T22:49:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Gene Correlation Network Analysis to Identify Biomarkers of Peri-Implantitis.", "doi": "10.3390/medicina58081124", "pmid": "36013591", "authors": ["Binghuan Sun", "Wei Zhang", "Xin Song", "Xin Wu"], "journal": "Medicina (Kaunas, Lithuania)", "year": 2022, "abstract": "Background and Objectives: The histopathological and clinical conditions for transforming peri-implant mucositis into peri-implantitis (PI) are not fully clarified. We aim to uncover molecular mechanisms and new potential biomarkers of PI. Materials and Methods: Raw GSE33774 and GSE57631 datasets were obtained from the Gene Expression Omnibus (GEO) database. The linear models for microarray data (LIMMA) package in R software completes differentially expressed genes (DEGs). We conducted a weighted gene co-expression network analysis (WGCNA) on the top 25% of altered genes and identified the key modules associated with the clinical features of PI. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the R software. We constructed a protein-protein interaction (PPI) network through the STRING database. After that we used Cytohubba plug-ins of Cytoscape to screen out the potential hub genes, which were subsequently verified via receiver operating characteristic (ROC) curves in another dataset, GSE178351, and revalidation of genes through the DisGeNET database. Results: We discovered 632 DEGs (570 upregulated genes and 62 downregulated genes). A total of eight modules were screened by WGCNA, among which the turquoise module was most correlated with PI. The Cytohubba plug-ins were used for filtering hub genes, which are highly linked with PI development, from the candidate genes in the protein-protein interaction (PPI) network. Conclusions: We found five key genes from PI using WGCNA. Among them, ICAM1, CXCL1, and JUN are worthy of further study of new target genes, providing the theoretical basis for further exploration of the occurrence and development mechanism of PI.", "claims": [{"id": "claim-method", "statement": "We applied the LIMMA package [16] and the robust multi-array average (RMA) technique in the R software for normalizing the data and analyzing differentially expressed genes (DEGs) based on the dataset GSE57631 raw data files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36013591", "locator": "sections[4] \"2.2. Identification of DEGs\" paragraph 2", "quote": "We applied the LIMMA package [16] and the robust multi-array average (RMA) technique in the R software for normalizing the data and analyzing differentially expressed genes (DEGs) based on the dataset GSE57631 raw data files."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data Availability StatementNot applicable.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36013591", "locator": "sections[21] \"notes\" paragraph 1", "quote": "Data Availability StatementNot applicable."}], "state": "complete"}, {"id": "claim-target-result", "statement": "There were 632 DEGs between PI and healthy controls, between them, there were 570 identified genes with an increase in expression and 62 identified genes with a decrease in expression.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36013591", "locator": "sections[10] \"3.1. Identification of DEGs\" paragraph 2", "quote": "There were 632 DEGs between PI and healthy controls, between them, there were 570 identified genes with an increase in expression and 62 identified genes with a decrease in expression."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "There were 632 DEGs between PI and healthy controls, between them, there were 570 identified genes with an increase in expression and 62 identified genes with a decrease in expression.", "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:36013591"], "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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