The potential crosstalk genes and molecular mechanisms between glioblastoma and periodontitis.

Despite clinical and epidemiological evidence suggestive of a link between glioblastoma (GBM) and periodontitis (PD), the shared mechanisms of gene regulation remain elusive. In this study, we identify differentially expressed genes (DEGs) that overlap between the GEO datasets GSE4290 [GBM] and GSE10334 [PD]. Functional enrichment analysis was conducted, and key modules were identified using protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA). The expression levels of CXCR4, LY96, and C3 were found to be significantly elevated in both the test dataset and external validation dataset, making them key crosstalk genes. Additionally, immune cell landscape analysis revealed elevated expression levels of multiple immune cells in GBM and PD compared to controls, with the key crosstalk genes negatively associated with Macrophages M2. FLI1 was identified as a potential key transcription factor (TF) regulating the three key crosstalk genes, with increased expression in the full dataset. These findings contribute to our understanding of the immune and inflammatory aspects of the comorbidity mechanism between GBM and PD.

Bioinformatics analysis revealed the potential crosstalk genes and molecular mechanisms between intracranial aneurysms and periodontitis.

OBJECTIVES: The risk of intracranial aneurysms (IAs) development and rupture is significantly higher in patients with periodontitis (PD), suggesting an association between the two. However, the specific mechanisms of association between these two diseases have not been fully investigated. MATERIALS AND METHODS: In this study, we downloaded IAs and PD data from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, and functional enrichment analysis was performed. The protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) was performed to identified key modules and key crosstalk genes. In addition, the immune cell landscape was assessed and the correlation of key crosstalk genes with each immune cell was calculated. Finally, transcription factors (TFs) regulating key crosstalk genes were explored. RESULTS: 127 overlapping DEGs were identified and functional enrichment analysis highlighted the important role of immune reflection in the pathogenesis of IAs and PD. We identified ITGAX and COL4A2 as key crosstalk genes. In addition, the expression of multiple immune cells was significantly elevated in PDs and IAs compared to controls, and both key crosstalk genes were significantly negatively associated with Macrophages M2. Finally, GATA2 was identified as a potential key transcription factor (TF), which regulates two key crosstalk gene. CONCLUSIONS: The present study identifies key crosstalk genes and TF in PD and IAs, providing new insights for further study of the co-pathogenesis of PD and IAs from an immune and inflammatory perspective. Also, this is the first study to report the above findings.