Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study

Junqi Liu; Bo Zhang; Guanyin Zhu; Chenlu Liu; Shuangcheng Wang; Zhihe Zhao

doi:10.3389/fgene.2023.1147819

Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study

Front Genet. 2023 Mar 27:14:1147819. doi: 10.3389/fgene.2023.1147819. eCollection 2023.

Authors

Junqi Liu^{1

2}, Bo Zhang^{1

2}, Guanyin Zhu^{1

2}, Chenlu Liu^{1

2}, Shuangcheng Wang¹, Zhihe Zhao^{1

2}

Affiliations

¹ State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
² Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China.

Abstract

Background: Relationship between periodontitis (PD) and type 1 diabetes (T1D) has been reported, but the detailed pathogenesis requires further elucidation. This study aimed to reveal the genetic linkage between PD and T1D through bioinformatics analysis, thereby providing novel insights into scientific research and clinical treatment of the two diseases. Methods: PD-related datasets (GSE10334, GSE16134, GSE23586) and T1D-related datasets(GSE162689)were downloaded from NCBI Gene Expression Omnibus (GEO). Following batch correction and merging of PD-related datasets as one cohort, differential expression analysis was performed (adjusted p-value <0.05 and ∣log₂ fold change| > 0.5), and common differentially expressed genes (DEGs) between PD and T1D were extracted. Functional enrichment analysis was conducted via Metascape website. The protein-protein interaction (PPI) network of common DEGs was generated in The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Hub genes were selected by Cytoscape software and validated by receiver operating characteristic (ROC) curve analysis. Results: 59 common DEGs of PD and T1D were identified. Among these DEGs, 23 genes were commonly upregulated, and 36 genes were commonly downregulated in both PD- and T1D-related cohorts. Functional enrichment analysis indicated that common DEGs were mainly enriched in tube morphogenesis, supramolecular fiber organization, 9 + 0 non-motile cilium, plasma membrane bounded cell projection assembly, glomerulus development, enzyme-linked receptor protein signaling pathway, endochondral bone morphogenesis, positive regulation of kinase activity, cell projection membrane and regulation of lipid metabolic process. After PPI construction and modules selection, 6 hub genes (CD34, EGR1, BBS7, FMOD, IGF2, TXN) were screened out and expected to be critical in linking PD and T1D. ROC analysis showed that the AUC values of hub genes were all greater than 70% in PD-related cohort and greater than 60% in T1D-related datasets. Conclusion: Shared molecular mechanisms between PD and T1D were revealed in this study, and 6 hub genes were identified as potential targets in treating PD and T1D.

Keywords: bioinformatics; genetic linkage; hyperglycaemia; periodontitis; type 1 diabetes.

Grants and funding

This study was supported by the National Natural Science Foundation of China (81771048), Sichuan province Science and technology program (2022ZDZX0031).