中国药学(英文版) ›› 2023, Vol. 32 ›› Issue (10): 796-812.DOI: 10.5246/jcps.2023.10.065
魏东升1,3, 刘孝生1, 李路珍1, 齐佳杰1, 王雨轩1, 张哲1,2,3,4,*()
收稿日期:
2023-04-25
修回日期:
2023-05-18
接受日期:
2023-06-05
出版日期:
2023-11-04
发布日期:
2023-11-04
通讯作者:
张哲
作者简介:
基金资助:
Dongsheng Wei1,3, Xiaosheng Liu1, Luzhen Li1, Jiajie Qi1, Yuxuan Wang1, Zhe Zhang1,2,3,4,*()
Received:
2023-04-25
Revised:
2023-05-18
Accepted:
2023-06-05
Online:
2023-11-04
Published:
2023-11-04
Contact:
Zhe Zhang
摘要:
本文基于生物信息学、网络药理学与单细胞测序探讨红花-丹参治疗冠心病(CAD)的机制。采用Comparative Toxicogenomics Database、Swiss target prediction、Binding Database Home、TargetNet四个数据库筛选出羟基红花黄色素、丹参酮、丹酚酸、丹参素的靶向基因。基于GEO数据库所筛选的3个CAD数据集, 通过差异分析及加权基因共表达网络(WGCNA)筛选与CAD相关的基因。融合药物与疾病基因, 通过cytoscape中mcode插件筛选出药物-疾病调控网络核心亚群。使用ssGSEA算法分析38种免疫细胞与mcode核心亚群基因的浸润情况。使用单细胞RNA测序明确mcode核心亚群所分布的细胞亚群。最后, 分别对药物靶点基因、疾病基因以及mcode核心亚群基因进行GO、KEGG富集分析。结果发现, 四个数据库共得到485个药物靶点基因。通过差异分析及WGCNA得到617个疾病基因。mcode插件获得1个药物-疾病的核心调控亚群, 包括99个基因。ssGSEA算法结果表明TGFβ家族成员、趋化因子、白介素受体可能是红花-丹参治疗CAD核心调控的免疫细胞。单细胞RNA测序结果表明巨噬细胞与单核细胞可能是核心细胞亚群。GO、KEGG富集分析结果表明内膜结合的细胞器与细胞核可能是核心细胞成分。红花-丹参可能通过调控TGFβ家族成员、趋化因子、白介素受体、巨噬细胞、单核细胞、内膜结合的细胞器与细胞核发挥治疗CAD的作用。
Supporting:
魏东升, 刘孝生, 李路珍, 齐佳杰, 王雨轩, 张哲. 基于综合生物信息学和单细胞测序方法揭示红花-丹参治疗冠心病的生物学和免疫学机制[J]. 中国药学(英文版), 2023, 32(10): 796-812.
Dongsheng Wei, Xiaosheng Liu, Luzhen Li, Jiajie Qi, Yuxuan Wang, Zhe Zhang. Unraveling the biological and immunological mechanisms of safflower-danshen in the treatment of coronary atherosclerotic heart disease: a comprehensive bioinformatics and single-cell sequencing approach[J]. Journal of Chinese Pharmaceutical Sciences, 2023, 32(10): 796-812.
Figure 2. Plots of drug DO enrichment analysis results. (A) A bar graph of DO enrichment analysis results sorted by P-value; (B) A bubble graph of DO enrichment analysis results sorted by the number of enriched genes.
Figure 3. Differential gene volcano map and heat map. (A) Volcano plot for DEGs. Red dots indicate upregulated DEGs, and blue dots express downregulated DEGs; (B) Heatmap for DEGs. Each line symbolizes one DEG, and each row represents one specimen. The yellow and blue swatches represent upregulated and downregulated DEGs, respectively.
Figure 4. A plot of CAD plus cluster gene coexpression results. (A) Gene tree of the gene coexpression modules; (B) Heat map of the association of the modules with CAD. The blue module was significantly associated with CAD; numbers in and out of brackets indicate P-values and correlation coefficients, respectively; (C) Correlation plot of genes contained in the blue module MM (X-axis) versus GS (Y-axis); (D) Venn diagram of overlapping genes between DEGs and genes in the blue module.
Figure 5. Drug-disease mcode network map and keycluster gene differential box plot. (A) Mcode network of CGs fused to drug-targeted genes; purple represents disease genes, blue represents drug-targeted genes; (B) Core subgroups of the mcode network; purple represents disease genes, blue represents drug-targeted genes; (C) Variability of keycluster genes in normal and CAD samples, ns represents P > 0.05, *Represents P < 0.05, **Represents P < 0.01, ***Represents P < 0.001.
Figure 6. ssGSEA immune infiltration results. (A) Box plot of the difference in infiltration of 38 immune cells between CAD samples and normal samples; (B) Heat map of the correlation between keycluster genes and 38 immune cells; Yellow represents high correlation, blue represents correlation is low, white represents no correlation; ***Represents P < 0.001, **Represents P < 0.01, *Represents P < 0.05.
Table 2. Keycluster gene to immune cell correlation ratios, "–" represents negative correlation, "+" represents positive correlation. The number of correlations was limited to regions where the difference was significant (P < 0.05).
Figure 7. A plot of CAD SCS results. (A) 20 cell clusters labeled by Uniform Manifold Approximation and Projection (UMAP); (B) Six cell types clustered by 20 cell clusters; (C) Degree of aggregation of keycluster genes in cell subpopulations.
Figure 8. GO and KEGG enrichment analysis histogram, from top to bottom, drug targeted genes, disease genes, and keycluster genes. (A) BP enrichment histogram; (B) CC enrichment histogram; (C) MF enrichment histogram; (D) KEGG enrichment histogram.
Figure 9. RORA, FN1, and FYN levels in the control, model, and TCM groups. ###Represents P < 0.001 compared to the blank group; ***Represents P < 0.001 compared to the model group; nsRepresents P > 0.05 compared to the model group.
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