目的 運用網絡藥理學結合加權基因共表達網絡分析（WGCNA）探究黃精治療代謝性相關脂肪性肝病的作用機制。方法 利用中藥系統藥理數據分析平臺（TCMSP）檢索黃精主要活性成分，并采用Pharm Mapper平臺挖掘黃精活性成分相關靶點。在GeneCards數據庫中下載并整理了代謝性相關脂肪性肝病相關基因。通過GEO平臺下載代謝性相關脂肪性肝病相關基因芯片GSE89632，使用R軟件limma包進行差異分析，并運用WGCNA篩選出的模塊基因作為疾病靶點基因。R軟件Venn Diagram包進行交集分析并可視化。采用R軟件clusterProfiler包對交集靶點基因進行基因本體論（GO）功能富集和京都基因與基因組百科全書（KEGG）信號通路富集分析。采用Cytoscape軟件進行“藥物–活性成分–共同靶點”網絡的構建與分析。將交集靶點基因上傳至String數據庫，把結果數據導入至Cytoscape軟件構建蛋白相互作用（PPI）網絡并篩選核心靶點基因。采用MOE軟件進行分子對接。結果 共篩選出黃精活性成分12個，成分相關靶點327個；GeneCards數據庫整理獲得代謝性相關脂肪性肝病相關基因1 227個；WGCNA關聯模塊基因2 639個；最終獲得黃精治療代謝性相關脂肪性肝病靶點基因18個。富集分析發(fā)現18個靶點基因通過調控胰島素抵抗、脂質和動脈粥樣硬化、代謝性相關脂肪性肝病等信號通絡，參與細胞間信號傳導、脂質代謝、氧化應激、炎癥反應等生物過程。分子對接研究顯示核心靶點與相關黃精活性成分結合穩(wěn)定。結論 黃精具有治療代謝性相關脂肪性肝病的作用，且在治療代謝性相關脂肪性肝病中具有多靶點、多成分、協同作用的特點。

Objective To investigate the mechanism of Polygonati Rhizoma in treatment of metabolically associated fatty liver disease by network pharmacology and WGCNA. Methods The TCMSP database was used to retrieve the main active ingredients of Polygonati Rhizoma and the active ingredient-related targets were predicted by PharmMapper. The genes related to metabolically associated fatty liver disease were obtained from GeneCards, and the gene chip data (GSE89632) related to metabolically associated fatty liver disease was downloaded from the GEO platform, and the limma package of R software was used for differential analysis, and the module genes selected by WGCNA were used as disease target genes. R software Venn Diagram package for intersection analysis visualization. R software clusterProfiler package was used to perform gene ontology (GO) functional enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway enrichment analysis for intersection target genes. Cytoscape software was used to construct and analyze the "active ingredient-common target" network. The intersection target genes were uploaded to String database, and the result data were imported into Cytoscape software to construct protein interaction network (PPI) and screen the core target genes. Molecule operating environment (MOE) software was used to verify the molecular docking between active components and core targets. Results A total of 12 active ingredients and 327 related targets were screened out. A total of 1 227 genes related to metabolically associated fatty liver disease were obtained from GeneCards database. 2 639 WGCNA associated module genes. Finally, 18 target genes were obtained for the treatment of metabolically associated fatty liver disease with Polygonati Rhizoma. Enrichment analysis showed that 18 target genes were involved in cellular signaling, lipid metabolism, oxidative stress, inflammation and other biological processes by regulating insulin resistance, lipid and atherosclerosis, and metabolically associated fatty liver disease. Molecular docking studies showed that the core target was stable in binding with related active components. Conclusion Polygonati Rhizoma has an effect of treating metabolically associated fatty liver disease, and which showed the characteristics of multi-target, multi-component, and synergistic effects on the treatment of metabolically associated fatty liver disease.

R285；R975

國家自然科學基金資助項目（82100488）；陜西省重點研發(fā)計劃項目（2021SF-071）；陜西省教育廳科學研究項目（21JS012）；國家級大學生創(chuàng)新創(chuàng)業(yè)訓練計劃項目（202210716019）