目的

采用生物信息学方法筛选牙周炎（PD）和非酒精性脂肪性肝炎（NASH）的共同关键基因，探索两种疾病潜在的共同致病机制。

方法

从基因表达数据库（GEO）中获取2008—2016年相关疾病数据集，选择GSE16134和GSE89632分别作为PD和NASH的训练数据集，筛选差异表达基因（DEG）并取交集得到重叠DEG。对重叠DEG 进行基因本体（GO）和京都基因与基因组百科全书（KEGG）富集分析。结合加权基因共表达网络分析（WGCNA），以及最小绝对收缩和选择算子（LASSO）回归分析进一步筛选关键基因。分析关键基因在训练和验证数据集（PD：GSE10334；NASH：GSE33814）中的差异表达水平，并通过受试者工作特征（ROC）曲线评估其诊断价值。

结果

从GSE16134 和GSE89632 中得到36 个重叠DEG，其中包含19 个上调基因和17 个下调基因。GO 和KEGG富集分析表明这些重叠DEG主要与细胞间黏附、细胞因子和趋化因子相关信号通路等有关。将重叠DEG 与WGCNA 获取的重叠模块基因取交集后得到8 个候选关键基因（ANXA6、CD48、GIMAP2、GPR34、HAL、ITGAL、PTPRCAP 和SLC19A2）。其中ANXA6、CD48、GIMAP2、GPR34、ITGAL和PTPRCAP在疾病组中表达显著上调（P＜0.05），HAL和SLC19A2则显著下调（P＜0.05）。在此基础上，通过LASSO回归分析进一步筛选出4个候选共同关键基因（ANXA6、GIMAP2、HAL和SLC19A2），其中ANXA6、GIMAP2和SLC19A2在多数据集验证中表现出稳定的表达差异和良好的诊断效能［曲线下面积（AUC）＞0.7］，最终被确定为PD和NASH的共同关键基因。

结论

本研究利用公共数据集挖掘出了3个PD和NASH的潜在共同关键基因，为PD和NASH共同致病机制研究、治疗策略提供了新的线索和方向。

Objective

To identify shared hub genes between periodontitis（PD）and nonalcoholic steatohepatitis （NASH） using bioinformatics methods，and to explore potential common pathogenic mechanisms of the two diseases.

Methods

Gene expression datasets related to the diseases were obtained from the gene expression omnibus（GEO）database between 2008 and 2016.GSE16134 and GSE89632 were selected as training datasets for PD and NASH，respectively. Differentially expressed genes（DEGs）were identified，and overlapping DEGs were extracted by intersecting the two datasets.Gene ontology（GO）and Kyoto encyclopedia of genes and genomes（KEGG）enrichment analyses were performed on the overlapping DEGs.Hub genes were further screened through weighted gene co-expression network analysis（WGCNA）and the least absolute shrinkage and selection operator（LASSO）regression analysis. Subsequently，the expression levels of hub genes were validated in independent datasets（PD：GSE10334；NASH：GSE33814），and their diagnostic performance was evaluated using receiver operating characteristic（ROC）curve analysis.

Results

A total of 36 overlapping DEGs were identified from GSE16134 and GSE89632，including 19 upregulated and 17 downregulated genes. GO and KEGG enrichment analysis indicated that these genes were associated with cell adhesion，cytokine and chemokine signaling pathway. By intersecting overlapping DEGs with module genes from WGCNA，eight candidate hub genes were identified：ANXA6，CD48，GIMAP2，GPR34，HAL，ITGAL，PTPRCAP，SLC19A2. Among them，ANXA6，CD48，GIMAP2，GPR34，ITGAL and PTPRCAP were significantly upregulated in disease groups（P＜0.05），while HAL and SLC19A2 were significantly downregulated（P＜0.05）. Further LASSO regression analysis identified four potential shared hub genes（ANXA6，GIMAP2，HAL and SLC19A2）. Among these genes，ANXA6，GIMAP2 and SLC19A2 consistently exhibited stable differential expression and considerable diagnostic performance（AUC＞0.7）across multiple datasets，and were ultimately identified as shared hub genes between PD and NASH.

Conclusions

This study identified three potential shared hub genes between PD and NASH based on bioinformatics analyses，providing novel insights into their common pathogenic mechanisms and offering potential targets for future therapeutic strategies.