Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis - Cai, Yisheng; Zuo, Xuemei; Zuo, Yuyang; Wu, Shuang; Pang, Weiwei; Ma, Keqiang; Yi, Qiaorong; Tan, Lijun; Deng, Hongwen; Qu, Xiaochao; Chen, Xiangding (Frontiers in Immunology, 2023)
Both obesity (OB) and periodontitis (PD) are chronic non-communicable diseases, and numerous epidemiological studies have demonstrated the association between these two diseases. However, the molecular mechanisms that could explain the association between OB and PD are largely unclear. This study aims to investigate the common gene signatures and biological pathways in OB and PD through bioinformatics analysis of publicly available transcriptome datasets. Differentially expressed analysis was performed and a total of 147 common differentially expressed genes (DEGs) (38 down-regulated and 109 up-regulated) in OB and PD were identified. Protein-protein interaction (PPI) network was built using Cytoscape software. Receiver operating characteristic (ROC) curves were plotted to verify the predictive accuracy of the hub genes and 14 genes (FGR, MNDA, NCF2, FYB1, EVI2B, LY86, IGSF6, CTSS, CXCR4, LCK, FCN1, CXCL2, P2RY13, MMP7) were screened as hub genes with an area under the curve > 0.7. which may be potential targets for diagnosis and treatment. Immune infiltration analysis was performed using single sample gene set enrichment analysis (ssGSEA) algorithm to quantify the relative immune infiltration levels, the results of which showed that immune cells including activated CD4 T cell, activated dendritic cell, central memory CD8 T cell, immune B cell, macrophage, MDSC, natural killer T cell and plasmacytoid dendritic cell showed higher infiltration levels both in OB and PD samples. Spearman’s coefficient was used to analyze the correlation of hub gene expression and immune infiltration levels, from which 5 hub genes including FGR, LCK, FYB1, LY86 and P2RY13 were found to be highly positively associated with macrophage infiltration, and GSEA analysis showed that high expression of the 5 genes was significantly correlated with macrophage-related pathways. Besides, a TF-miRNA-mRNA regulatory network consisting of 233 transcription factors (TFs), 8 miRNAs and 14 mRNAs was built based on validated information obtained from databases. To our knowledge, the present work is the first to identify co-DEGs, reveal common molecular mechanisms, demonstrate the immune microenvironment, and construct a validated TF-miRNA‒mRNA network shared in OB and PD, which provides new insights into the relationship between the two diseases and the treatment of PD patients with OB.