Identification and Validation of Signature Genes and Potential Therapy Targets of Inflammatory Bowel Disease and Periodontitis

Abstract

Background

Inflammatory bowel disease (IBD) and periodontitis (PD) are correlated, although the pathogenic mechanism behind their correlation has not been clarified. This study aims to explore the common signature genes and potential therapeutic targets of IBD and PD using transcriptomic analysis.

Methods

The GEO database was used to download datasets of IBD and PD, and differential expression analysis was used to identify DEGs. We then conducted GO and KEGG enrichment analyses of the shared genes. Next, we applied 4 machine learning (ML) algorithms (GLM, RF, GBM, and SVM) to select the best prediction model for diagnosing the disease and obtained the hub genes of IBD and PD. The diagnostic value of the signature genes was verified by a validation set and qRT‒PCR experiments. Subsequently, immune cell infiltration in IBD samples and PD samples was analyzed by ssGSEA. Finally, we investigated and validated the response of hub genes to infliximab therapy.

Results

We identified 43 upregulated genes as shared genes by intersecting the DEGs of IBD and PD. Functional enrichment analysis suggested that the shared genes were closely associated with immunity and inflammation. The ML algorithm and qRT‒PCR results indicated that IGKC and COL4A1 were the hub genes with the most diagnostic value for IBD and PD. Subsequently, through immune infiltration analysis, CD4 T cells, NK cells and neutrophils were identified to play crucial roles in the pathogenesis of IBD and PD. Finally, through in vivo and in vitro experiments, we found that IGKC and COL4A1 were significantly downregulated during the treatment of patients with IBD using infliximab.

Conclusion

We investigated the potential association between IBD and PD using transcriptomic analysis. The IGKC and COL4A1 genes were identified as characteristic genes and novel intervention targets for these two diseases. Infliximab may be used to treat or prevent IBD and PD.

Keywords:

• Inflammatory bowel disease
• periodontitis
• machine learning
• ssGSEA
• infliximab
• IGKC
• COL4A1

Acknowledgments

This work was supported by the Fund of Nanjing Medical University (NMUC2021026A).

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.