Abstract:

Objective

To identify shared hub genes between periodontitis（PD）and nonalcoholic steatohepatitis （NASH） using bioinformatics methods，and to explore potential common pathogenic mechanisms of the two diseases.

Methods

Gene expression datasets related to the diseases were obtained from the gene expression omnibus（GEO）database between 2008 and 2016.GSE16134 and GSE89632 were selected as training datasets for PD and NASH，respectively. Differentially expressed genes（DEGs）were identified，and overlapping DEGs were extracted by intersecting the two datasets.Gene ontology（GO）and Kyoto encyclopedia of genes and genomes（KEGG）enrichment analyses were performed on the overlapping DEGs.Hub genes were further screened through weighted gene co-expression network analysis（WGCNA）and the least absolute shrinkage and selection operator（LASSO）regression analysis. Subsequently，the expression levels of hub genes were validated in independent datasets（PD：GSE10334；NASH：GSE33814），and their diagnostic performance was evaluated using receiver operating characteristic（ROC）curve analysis.

Results

A total of 36 overlapping DEGs were identified from GSE16134 and GSE89632，including 19 upregulated and 17 downregulated genes. GO and KEGG enrichment analysis indicated that these genes were associated with cell adhesion，cytokine and chemokine signaling pathway. By intersecting overlapping DEGs with module genes from WGCNA，eight candidate hub genes were identified：ANXA6，CD48，GIMAP2，GPR34，HAL，ITGAL，PTPRCAP，SLC19A2. Among them，ANXA6，CD48，GIMAP2，GPR34，ITGAL and PTPRCAP were significantly upregulated in disease groups（P＜0.05），while HAL and SLC19A2 were significantly downregulated（P＜0.05）. Further LASSO regression analysis identified four potential shared hub genes（ANXA6，GIMAP2，HAL and SLC19A2）. Among these genes，ANXA6，GIMAP2 and SLC19A2 consistently exhibited stable differential expression and considerable diagnostic performance（AUC＞0.7）across multiple datasets，and were ultimately identified as shared hub genes between PD and NASH.

Conclusions

This study identified three potential shared hub genes between PD and NASH based on bioinformatics analyses，providing novel insights into their common pathogenic mechanisms and offering potential targets for future therapeutic strategies.

Key words: Periodontitis, Non-alcoholic fatty liver disease, Bioinformatics, Weighted gene coexpression network analysis(WGCNA), Least absolute shrinkage and selection operator(LASSO)regression