ArticleFrontiers in endocrinology2021
Identification of Shared Genes and Pathways in Periodontitis and Type 2 Diabetes by Bioinformatics Analysis.
Article in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Bioinformatics analyses of comorbid mechanisms between psoriasis and type 2 diabetes mellitus.Scientific reports · 2025Article
- Cytokine-Related Genes and Inflammatory Profiles as Potential Biomarkers in Major Depressive Disorder.Psychiatry investigation · 2025Article
- Identification of key signaling pathways and novel computational drug target for oral cancer, metabolic disorders and periodontal disease.Journal, genetic engineering & biotechnology · 2024Article
- Comparison of genetic and epigenetic profiles of periodontitis according to the presence of type 2 diabetes.MedComm · 2024Article
- The Bidirectional Relationship between Periodontal Disease and Diabetes Mellitus-A Review.Diagnostics (Basel, Switzerland) · 2023Review
- Gene Interaction Network Analysis Reveals IFI44L as a Drug Target in Rheumatoid Arthritis and Periodontitis.Molecules (Basel, Switzerland) · 2022Article
- Diagnostic accuracy of salivary hemoglobin, lactate dehydrogenase and Interleukin-6 to determine chronic periodontitis and tooth loss in type 2 diabetics.Journal of oral biology and craniofacial researchArticle
Corrections and comments
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Authors and funding
14 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: It is well known that the presence of diabetes significantly affects the progression of periodontitis and that periodontitis has negative effects on diabetes and diabetes-related complications. Although this two-way relationship between type 2 diabetes and periodontitis could be understood through experimental and clinical studies, information on common genetic factors would be more useful for the understanding of both diseases and the development of treatment strategies. Materials and Methods: Gene expression data for periodontitis and type 2 diabetes were obtained from the Gene Expression Omnibus database. After preprocessing of data to reduce heterogeneity, differentially expressed genes (DEGs) between disease and normal tissue were identified using a linear regression model package. Gene ontology and Kyoto encyclopedia of genes and genome pathway enrichment analyses were conducted using R package ' Results: We identified 152 commonly DEGs, including 125 upregulated and 27 downregulated genes. Through common DEGs, we constructed a protein-protein interaction and identified highly connected hub genes. The hub genes were up-regulated in both diseases and were most significantly enriched in the Fc gamma R-mediated phagocytosis pathway. Discussion: We have identified three up-regulated genes involved in Fc gamma receptor-mediated phagocytosis, and these genes could be potential therapeutic targets in patients with periodontitis and type 2 diabetes.
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