Identification of Pulpitis-Related Potential Biomarkers Using Bioinformatics Approach

Inflammatory reaction of pulp tissue plays a role in the pathogen elimination and tissue repair. The evaluation of severity of pulpitis can serve an instructive function in therapeutic scheme. However, there are many limitations in the traditional evaluation methods for the severity of pulpitis. Based on the Gene Expression Omnibus (GEO) database, our study discovered 843 differentially expressed genes (DEGs) related to pulpitis. Afterwards, we constructed a protein-protein interaction (PPI) network of DEGs and used MCODE plugin to determine the key functional subset. Meanwhile, genes in the key functional subset were subjected to GO and KEGG enrichment analyses. The result showed that genes were mainly enriched in inflammatory reaction-related functions. Next, we screened out intersections of PPI network nodes and pulpitis-related genes. Then, 20 genes were obtained as seed genes. In the PPI network, 50 genes that had the highest correlation with seed genes were screened out using random walk with restart (RWR). Furthermore, 4 pulpitis-related hub genes were obtained from the intersection of the top 50 genes and genes in the key functional subset. Finally, GeneMANIA was utilized to predict genes coexpressed with hub genes, and expression levels of the 4 hub genes in normal and pulpitis groups were analyzed based on GEO data. The result demonstrated that the 4 hub genes were mainly coexpressed with chemokine-related genes and were remarkably upregulated in the pulpitis group. In short, we eventually determined 4 potential biomarkers of pulpitis.