ArticleBMC oral health2015
Genes related to inflammation and bone loss process in periodontitis suggested by bioinformatics methods.
Article in BMC oral health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 43 citations in OpenAlex.
- Identifying omic biomarkers for chronic inflammatory diseases associated with periodontitis using percolation on multi-disease gene co-expression networks.Communications medicine · 2026Article
- Obesity and cathepsin S in periodontal health and disease: A prospective clinical observational study.Acta odontologica Scandinavica · 2025Observational
- Using weighted gene co-expression network analysis to identify key genes related to preeclampsia.Frontiers in immunology · 2025Article
- Evaluation of Periodontitis andHealthcare (Basel, Switzerland) · 2024Article
- Microbiological and functional traits of peri-implant mucositis and correlation with disease severity.mSphere · 2024Article
- AmSystems · 2024Article
- OralExplorer: a web server for exploring the mechanisms of oral inflammatory diseases.Journal of translational medicine · 2024Article
- Distinctive genes and signaling pathways associated with type 2 diabetes-related periodontitis: Preliminary study.PloS one · 2024Article
- Genomic Medicine in Canine Periodontal Disease: A Systematic Review.Animals : an open access journal from MDPI · 2023Review
- Cathepsins in oral diseases: mechanisms and therapeutic implications.Frontiers in immunology · 2023Review
- The relationship between FOSB and SOCS3 gene polymorphisms and the susceptibility to periodontitis and osteopenia in the Chinese population.Odontology · 2022Article
- Autophagy-Related Genes Predict the Progression of Periodontitis Through the ceRNA Network.Journal of inflammation research · 2022Article
- Construction of artificial neural network diagnostic model and analysis of immune infiltration for periodontitis.Frontiers in genetics · 2022Article
- Selected using bioinformatics and molecular docking analyses, PHA-793887 is effective against osteosarcoma.Aging · 2021Article
- Association of type 2 diabetes mellitus and periodontal disease susceptibility with genome-wide association-identified risk variants in a Southeastern Brazilian population.Clinical oral investigations · 2021Article
- Pleckstrin Levels Are Increased in Patients with Chronic Periodontitis and RegulatedFrontiers in immunology · 2021Article
- Emerging Roles of Pleckstrin-2 Beyond Cell Spreading.Frontiers in cell and developmental biology · 2021Review
- Neuropeptides as the Shared Genetic Crosstalks Linking Periodontitis and Major Depression Disorder.Disease markers · 2021Article
- Cytokines and Their Genetic Polymorphisms Related to Periodontal Disease.Journal of clinical medicine · 2020Review
- The Association between Periodontitis and Human Colorectal Cancer: Genetic and Pathogenic Linkage.Life (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite of numerous studies on periodontitis, the mechanism underlying the progression of periodontitis still remains largely unknown. This study aimed to have an expression profiling comparison between periodontitis and normal control and to identify more candidate genes involved in periodontitis and to gain more insights into the molecular mechanisms of periodontitis progression.
methodsThe gene expression profile of GSE16134, comprising 241 gingival tissue specimens and 69 healthy samples as control which were obtained from 120 systemically healthy patients with periodontitis (65 with chronic and 55 with aggressive periodontitis), was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in periodontitis samples were screened using the limma package in R compared with control samples. Gene Ontology (GO) and pathway enrichment analysis upon the DEGs were carried out using Hypergeometric Distribution test. Protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape, followed by module selection from the PPI network using MCODE plugin. Moreover, transcription factors (TFs) of these DEGs were identified based on TRANSFAC database and then a regulatory network was constructed.
resultsTotally, 762 DEGs (507 up- and 255 down-regulated) in periodontitis samples were identified. DEGs were enriched in different GO terms and pathways, such as immune system process, cell activation biological processes, cytokine-cytokine receptor interaction, and metabolic pathways. Cathepsin S (CTSS) and pleckstrin (PLEK) were the hub proteins in the PPI network and 3 significant modules were selected. Moreover, 19 TFs were identified including interferon regulatory factor 8 (IRF8), and FBJ murine osteosarcoma viral oncogene homolog B (FOSB).
conclusionThis study identified genes (CTSS, PLEK, IRF-8, PTGS2, and FOSB) that may be involved in the development and progression of periodontitis.
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