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. 2024 Aug 27:16:1430290.
doi: 10.3389/fnagi.2024.1430290. eCollection 2024.

Identification of cross-talk pathways and PANoptosis-related genes in periodontitis and Alzheimer's disease by bioinformatics analysis and machine learning

Xiantao Chen  1   2 , Yifei Dai  1   2 , Yushen Li  1   2 , Jiajun Xin  1   2 , Jiatong Zou  1   2 , Rui Wang  1   2 , Hao Zhang  1   2 , Zhihui Liu  1   2
Affiliations

Identification of cross-talk pathways and PANoptosis-related genes in periodontitis and Alzheimer's disease by bioinformatics analysis and machine learning

Xiantao Chen et al. Front Aging Neurosci. .

Abstract

Background and objectives: Periodontitis (PD), a chronic inflammatory disease, is a serious threat to oral health and is one of the risk factors for Alzheimer's disease (AD). A growing body of evidence suggests that the two diseases are closely related. However, current studies have not provided a comprehensive understanding of the common genes and common mechanisms between PD and AD. This study aimed to screen the crosstalk genes of PD and AD and the potential relationship between cross-talk and PANoptosis-related genes. The relationship between core genes and immune cells will be analyzed to provide new targets for clinical treatment.

Materials and methods: The PD and AD datasets were downloaded from the GEO database and differential expression analysis was performed to obtain DEGs. Overlapping DEGs had cross-talk genes linking PD and OP, and PANoptosis-related genes were obtained from a literature review. Pearson coefficients were used to compute cross-talk and PANoptosis-related gene correlations in the PD and AD datasets. Cross-talk genes were obtained from the intersection of PD and AD-related genes, protein-protein interaction(PPI) networks were constructed and cross-talk genes were identified using the STRING database. The intersection of cross-talk and PANoptosis-related genes was defined as cross-talk-PANoptosis genes. Core genes were screened using ROC analysis and XGBoost. PPI subnetwork, gene-biological process, and gene-pathway networks were constructed based on the core genes. In addition, immune infiltration on the PD and AD datasets was analyzed using the CIBERSORT algorithm.

Results: 366 cross-talk genes were overlapping between PD DEGs and AD DEGs. The intersection of cross-talk genes with 109 PANoptosis-related genes was defined as cross-talk-PANoptosis genes. ROC and XGBoost showed that MLKL, DCN, IL1B, and IL18 were more accurate than the other cross-talk-PANoptosis genes in predicting the disease, as well as better in overall characterization. GO and KEGG analyses showed that the four core genes were involved in immunity and inflammation in the organism. Immune infiltration analysis showed that B cells naive, Plasma cells, and T cells gamma delta were significantly differentially expressed in patients with PD and AD compared with the normal group. Finally, 10 drugs associated with core genes were retrieved from the DGIDB database.

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

Keywords: Alzheimer’s disease; PANoptosis; common genes; immune infiltration; periodontitis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Flow-chart of datasets analysis in this paper.
FIGURE 2
FIGURE 2
(A) PCA analysis results of PD datasets before batch correction; (B) PCA analysis results of PD datasets after batch correction; (C) PCA analysis results of AD datasets before batch correction; (D) PCA analysis results of AD datasets after batch correction.
FIGURE 3
FIGURE 3
(A) The volcano plots of PD DEGs; (B) the heatmap of PD up-regulated and down-regulated genes; PD present the samples of the monocytes from osteoporosis patient and PD_control present the samples of the monocytes from non-osteoporotic patients; (C) the volcano plots of AD DEGs; (D) the heatmap of AD up-regulated and down-regulated genes; AD present the samples of the monocytes from osteoporosis patient and AD_control present the samples of the monocytes from non-osteoporotic patients.
FIGURE 4
FIGURE 4
(A) TOP20 GO BP terms of PD DEGs; (B) TOP20 GO BP terms of AD DEGs; (C) TOP20 KEGG pathways of PD DEGs; (D) TOP20 KEGG pathways of AD DEGs.
FIGURE 5
FIGURE 5
Venn diagram of the intersection of PD DEGs,OP DEGs and AD-disgenet.
FIGURE 6
FIGURE 6
(A) TOP20 GO BP terms of cross-talk genes; (B) TOP20 KEGG pathways of cross-talk genes.
FIGURE 7
FIGURE 7
(A) PPI network of cross-talk genes; (B) CytoHubba analysis of PPI network with Cytoscape; (C) TOP9 GO BP terms of hub genes; (D) TOP7 KEGG pathways of hub genes.
FIGURE 8
FIGURE 8
(A) Heatmap of PANoptosis-related genes expression in PD samples; (B) Heatmap of PANoptosis-related genes expression in AD samples.
FIGURE 9
FIGURE 9
(A) Heatmap of the correlation between cross-talk and PANoptosis-related genes in PD samples; (B) Heatmap of the correlation between cross-talk and PANoptosis-related genes in AD samples.
FIGURE 10
FIGURE 10
(A) ROC curve analysis of cross-talk-PANoptosis genes in PD samples; (B) ROC curve analysis of cross-talk-PANoptosis genes in AD samples; (C) the ROC of XGBoost in PD samples. The AUC is 0.849; (D) the ROC of XGBoost in AD samples. The AUC is 0.669; (E) the importance of features in PD samples; (F) the importance of features in OP samples.
FIGURE 11
FIGURE 11
PPI subnetwork of core genes.
FIGURE 12
FIGURE 12
(A) Immune infiltration of each sample in PD; (B) Boxplots of each immune cell’s expression in PD (*P-value < 0.05, **P-value < 0.01, ***P-value < 0.001, ****P-value < 0.0001); (C) correlation between immune cells and core genes in PD.
FIGURE 13
FIGURE 13
(A) Immune infiltration of each sample in AD; (B) Boxplots of each immune cell’s expression in AD (**P-value < 0.01, ***P-value < 0.001, ****P-value < 0.0001); (C) correlation between immune cells and core genes in AD.
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