College & Hospital of Stomatology, Key Lab. of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, 230032, China.
First Clinical Medical College (First Affiliated Hospital), Anhui Medical University, Hefei, 230032, China.
BMC Oral Health. 2024 Jan 13;24(1):75. doi: 10.1186/s12903-023-03846-7.
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.
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.
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.
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.
尽管先前有研究报道牙周炎与多发性硬化症(MS)之间存在关联,但两者之间的分子机制和病理相互作用尚不清楚。本研究旨在探讨牙周炎和 MS 之间潜在的串扰基因和途径。
从基因表达综合(GEO)数据库中获取牙周炎和 MS 数据。通过差异表达分析和加权基因共表达网络分析(WGCNA)确定共享基因。然后,通过多种方法对共享基因进行富集分析。使用最小绝对收缩和选择算子(LASSO)回归获得潜在的共享诊断基因。进一步,使用单样本 GSEA(ssGSEA)检测牙周炎和 MS 中 28 种免疫细胞的表达谱。最后,通过实时定量荧光 PCR(qRT-PCR)和免疫组织化学染色验证牙周炎和 MS 样本中 Hub 基因的表达。
FAM46C、SLC7A7、LY96、CFI、DDIT4L、CD14、C5AR1 和 IGJ 是牙周炎和 MS 之间的共享基因。GO 分析表明,共享基因在对细菌来源的分子的反应中表现出最大的富集。LASSO 分析表明,CFI、DDIT4L 和 FAM46C 是牙周炎和 MS 最有效的共享诊断生物标志物,进一步通过 qPCR 和免疫组织化学染色进行验证。ssGSEA 分析表明 T 和 B 细胞显著影响 MS 和牙周炎的发展。
FAM46C、SLC7A7、LY96、CFI、DDIT4L、CD14、C5AR1 和 IGJ 是牙周炎和 MS 之间最重要的串扰基因。进一步的研究发现,CFI、DDIT4L 和 FAM46C 是牙周炎和 MS 的潜在生物标志物。