Identification of cross-talk pathways and PANoptosis-related genes in periodontitis and atherosclerosis by bioinformatics analysis and machine learning.

BACKGROUND AND OBJECTIVES

Periodontitis(PD) is a chronic inflammatory disease that poses a serious threat to oral health and is one of the risk factors for atherosclerosis(AS). A growing body of evidence suggests that the two diseases are closely related. However, current studies have yet to fully understand the common genes and common mechanisms between PD and AS. This study aimed to screen the tandem genes of PD and AS and the potential relationship between the tandem genes and pan-apoptosis-related genes. By analyzing the relationship between the core genes and immune cells, it will provide new targets for clinical treatment.

MATERIALS AND METHODS

The PD and AS datasets were downloaded from the GEO database and differential expression analysis was performed to obtain DEGs. AS-related genes were downloaded from the GeneCards database, and PANoptosis-related genes were obtained through literature review. AS-related genes were merged into AS DEGs, and overlapping DEGs were cross-talk genes for PD and AS. Protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape software. Pearson coefficients were used to calculate the correlation between cross-talk genes and PANoptosis-related genes in the PD and AS datasets. The intersection of cross-talk genes and PANoptosis-related genes was defined as cross-talk-PANoptosis genes. Core genes were screened using ROC analysis and XGBoost. PPI sub-network, gene-biological processes and gene-pathway networks were constructed based on the core genes. In addition, immune infiltration on the PD and AS datasets was analyzed using the CIBERSORT algorithm.

RESULTS

285 cross-talk genes overlapped between PD DEGs and AS DEGs. The intersection of cross-talk genes with 109 PANoptosis-related genes was defined as cross-talk-PAoptosis genes. ROC and XGBoost showed that MLKL, ZBP1, CD14, and IL6 were more accurate than the other cross-talk-PAoptosis genes in predicting the diseases, and were better in terms of the overall characteristics. GO and KEGG analyses showed that these four core genes were involved in the immune and inflammatory response of the organism. The results of immune infiltration showed that Monocytes and Mast cells resting were altered to a greater extent in PD and AS patients. Finally, 24 drugs related to the core genes were retrieved from the DGIDB database.

CONCLUSIONS

This study reveals the joint mechanism between PD and AS associated with PANoptosis. Analyzing the four core genes and immune cells may provide new therapeutic directions for the pathogenesis of PD combined with AS.