Crosstalk between Venous Thromboembolism and Periodontal Diseases: A Bioinformatics Analysis

Background. This current study applied bioinformatics analysis to reveal the crosstalk between venous thromboembolism (VTE) and periodontitis, as well as the potential role of immune-related genes in this context. Methods. Expression data were downloaded from the GEO database. Blood samples from venous thromboembolism (VTE) were used (GSE19151), while for periodontal disease, we used gingival tissue samples (GSE10334, GSE16134, and GSE23586). After batch correction, we used “limma” packages of R language for differential expression analysis ( p value < 0.05, ∣ logFC ∣ ≥ 0.5 ). We used Venn diagrams to extract the differentially expressed genes common to VTE and periodontitis as potential crosstalk genes and applied functional enrichment analysis (GO biological process and KEGG pathway). The protein-protein interaction (PPI) network of crosstalk genes was constructed by Cytoscape software. The immune-related genes were downloaded from the literature. The Wilcoxon test was used to test the scores of immune infiltrating cells. The crosstalk genes were further screened by LASSO Logistic Regression. Results. For periodontitis, 427 case and 136 control samples, and for VTE, 70 case and 63 control samples were included. The obtained PPI network had 1879 nodes and 2257 edges. Moreover, 782 immune genes and 28 cell types were included in the analysis. Over 90% of immune cells had different expressions in VTE and periodontitis. We obtained 12 significant pathways corresponding to crosstalk genes. CD3D, CSF3R, and CXCR4 acted as an immune gene and a crosstalk gene. We obtained a total of 12 shared biomarker crosstalk genes. Among those 12 biomarker crosstalk genes, 4 were immune genes (LGALS1, LSP1, SAMSN1, and WIPF1). Conclusion. Four biomarker crosstalk genes between periodontitis and VTE were also immune genes, i.e., LGALS1, LSP1, SAMSN1, and WIPF1. The findings of the current study need further validation and are a basis for development of biomarkers.