Identification of potential crosstalk genes and mechanisms between periodontitis and diabetic nephropathy through bioinformatic analysis

Medicine (Baltimore). 2023 Dec 29;102(52):e36802. doi: 10.1097/MD.0000000000036802.

Abstract

Periodontitis and diabetic nephropathy are significant public health concerns globally and are closely related with each other. This study aimed to identify potential crosstalk genes, pathways, and mechanisms associated with the interaction between periodontitis and diabetic nephropathy. Expression profiles of periodontitis and diabetic nephropathy were retrieved from the Gene expression omnibus gene expression omnibus database, and differentially expressed genes (DEGs) were screened, followed by identification of co-expressed differential genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software. A protein-protein interaction network was constructed via STRING website, and key crosstalk genes were selected using Cytoscape. Subsequent gene ontology and KEGG analyses were conducted for the key genes, and a validation dataset was obtained from the gene expression omnibus database for differential gene validation. The TRRUST website was employed to identify transcription factors (TFs) associated with the key crosstalk genes between periodontitis and diabetic nephropathy, followed by differential analysis of TFs. A total of 17 crosstalk genes were obtained. Among them, SAMSN1, BCL2A1, interleukin-19, IL1B, RGS1, CXCL3, CCR1, CXCR4, CXCL1, and PTGS2 were identified as key crosstalk genes between periodontitis and diabetic nephropathy. Additionally, 16 key TFs were discovered. This bioinformatic analysis revealed potential crosstalk genes between periodontitis and diabetic nephropathy. The identified key genes participate in signaling pathways, including cytokine signaling and chemokine signaling transduction, which might collectively influence these 2 diseases. These genes may serve as potential biomarkers guiding future research in this field.

MeSH terms

  • Adaptor Proteins, Vesicular Transport / genetics
  • Computational Biology
  • Diabetes Mellitus*
  • Diabetic Nephropathies* / genetics
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Humans
  • Periodontitis* / genetics
  • Protein Interaction Maps / genetics

Substances

  • SAMSN1 protein, human
  • Adaptor Proteins, Vesicular Transport