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Exploration of potential shared gene signatures between periodontitis and multiple sclerosis

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Abstract Background Although periodontitis has previously been reported to be linked with multiple sclerosis (MS), but the molecular mechanisms and pathological interactions between the two remain unclear. This study aims to explore potential crosstalk genes and pathways between periodontitis and MS. Methods Periodontitis and MS data were obtained from the Gene Expression Omnibus (GEO) database. Shared genes were identified by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Then, enrichment analysis for the shared genes was carried out by multiple methods. The least absolute shrinkage and selection operator (LASSO) regression was used to obtain potential shared diagnostic genes. Furthermore, the expression profile of 28 immune cells in periodontitis and MS was examined using single-sample GSEA (ssGSEA). Finally, real-time quantitative fluorescent PCR (qRT-PCR) and immune histochemical staining were employed to validate Hub gene expressions in periodontitis and MS samples. Results FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ genes were the shared genes between periodontitis, and MS. GO analysis revealed that the shared genes exhibited the greatest enrichment in response to molecules of bacterial origin. LASSO analysis indicated that CFI, DDIT4L, and FAM46C were the most effective shared diagnostic biomarkers for periodontitis and MS, which were further validated by qPCR and immunohistochemical staining. ssGSEA analysis revealed that T and B cells significantly influence the development of MS and periodontitis. Conclusions FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ were the most important crosstalk genes between periodontitis, and MS. Further studies found that CFI, DDIT4L, and FAM46C were potential biomarkers in periodontitis and MS.
Title: Exploration of potential shared gene signatures between periodontitis and multiple sclerosis
Description:
Abstract Background Although periodontitis has previously been reported to be linked with multiple sclerosis (MS), but the molecular mechanisms and pathological interactions between the two remain unclear.
This study aims to explore potential crosstalk genes and pathways between periodontitis and MS.
Methods Periodontitis and MS data were obtained from the Gene Expression Omnibus (GEO) database.
Shared genes were identified by differential expression analysis and weighted gene co-expression network analysis (WGCNA).
Then, enrichment analysis for the shared genes was carried out by multiple methods.
The least absolute shrinkage and selection operator (LASSO) regression was used to obtain potential shared diagnostic genes.
Furthermore, the expression profile of 28 immune cells in periodontitis and MS was examined using single-sample GSEA (ssGSEA).
Finally, real-time quantitative fluorescent PCR (qRT-PCR) and immune histochemical staining were employed to validate Hub gene expressions in periodontitis and MS samples.
Results FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ genes were the shared genes between periodontitis, and MS.
GO analysis revealed that the shared genes exhibited the greatest enrichment in response to molecules of bacterial origin.
LASSO analysis indicated that CFI, DDIT4L, and FAM46C were the most effective shared diagnostic biomarkers for periodontitis and MS, which were further validated by qPCR and immunohistochemical staining.
ssGSEA analysis revealed that T and B cells significantly influence the development of MS and periodontitis.
Conclusions FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ were the most important crosstalk genes between periodontitis, and MS.
Further studies found that CFI, DDIT4L, and FAM46C were potential biomarkers in periodontitis and MS.

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