| 摘要: |
| 目的：通过生物信息学手段识别慢性萎缩性胃炎（chronic atrophic gastritis ，CAG）的差异表达基因及其与舒胃方活性成分的潜在关联，以探索新的治疗靶点。方法：基于GEO数据库数据集GSE27411和GSE153224，进行差异基因分析、基因本体（gene ontology， GO）功能注释和京都基因与基因组数据库（Kyoto Encyclopedia of Genes and Genomes， KEGG）通路富集分析、最小绝对收缩和选择算子（least absolute shrinkage and selection operator，LASSO）回归模型、受试者工作特征曲线（receiver operating characteristic，ROC）分析，筛选出关键基因并验证其诊断潜力。通过斯皮尔曼（Spearman）分析评估基因间的相关性，使用分子对接探究舒胃方活性成分与关键基因编码蛋白质的结合亲和力。结果：在CAG中鉴定到6个具有诊断价值的关键基因（MDM2、COL1A1、HMOX1、CYP3A4、MAOB、SLC6A4），关键基因之间存在显著的表达相关性。舒胃方的活性成分与上述关键基因编码的蛋白质具有较强的结合能力。结论：本研究为CAG的早期诊断和靶向治疗提供了潜在的生物标志物及干预策略。 |
| 关键词: 慢性萎缩性胃炎 舒胃方 生物标志物 生物信息学 分子对接 |
| DOI： |
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| Effect of Shuwei prescription in treatment of chronic atrophic gastritis: A study based on bioinformatics |
| RAO Wenjuan,HONG Haiyan,MI Yanhong |
| (Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Changsha 410006, Hunan, China;Community Health Service Center of Qingzhuhu Street in Kaifu District, Changsha 410201, Hunan, China) |
| Abstract: |
| Objective: To identify differentially expressed genes in chronic atrophic gastritis （CAG） using bioinformatics methods, to investigate their potential association with the active components of Shuwei prescription, and to explore new therapeutic targets. Methods: GEO datasets GSE27411 and GSE153224 were used to perform the analysis of differentially expressed genes, gene ontology functional annotation, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, the least absolute shrinkage and selection operator （LASSO） regression analysis, and the receiver operating characteristic （ROC） curve analysis. Key genes were identified, and their diagnostic potential was evaluated. The Spearman analysis was used to investigate the correlation between genes, and molecular docking was used to observe the binding affinity between the active components of Shuwei prescription and the proteins encoded by the key genes. Results: Six key genes with a diagnostic value were identified in CAG, i.e., MDM2, COL1A1, HMOX1, CYP3A4, MAOB, and SLC6A4, and there was a significant correlation between the expression of these key genes. The active components of Shuwei prescription had strong binding affinity to the proteins encoded by the above key genes. Conclusion: This study systematically analyzes the differentially expressed genes in CAG, identifies six key genes with good diagnostic potential based on the LASSO regression model and the ROC curve analysis, and reveals the potential molecular mechanism of Shuwei prescription in the treatment of CAG. |
| Key words: chronic atrophic gastritis Shuwei prescription biomarker bioinformatics molecular docking |
