1.中国中医科学院中医临床基础医学研究所,北京市东城区东直门内南小街16号,100700
2.中国中医科学院广安门医院
wlxing@126.com
收稿:2024-06-19,
修回:2024-09-15,
纸质出版:2024-11-17
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杨硕,栾相佳,王连心.中药药物性急性肾损伤的网络毒理学及免疫机制研究[J].中医杂志,2024,65(22):2347-2357.
YANG Shuo,LUAN Xiangjia,WANG Lianxin.Studies on the Network Toxicology and Immunological Mechanism of Chinese Herbal Medicine-Induced Acute Kidney Injury[J].Journal of Traditional Chinese Medicine,2024,65(22):2347-2357.
杨硕,栾相佳,王连心.中药药物性急性肾损伤的网络毒理学及免疫机制研究[J].中医杂志,2024,65(22):2347-2357. DOI: 10.13288/j.11-2166/r.2024.22.011.
YANG Shuo,LUAN Xiangjia,WANG Lianxin.Studies on the Network Toxicology and Immunological Mechanism of Chinese Herbal Medicine-Induced Acute Kidney Injury[J].Journal of Traditional Chinese Medicine,2024,65(22):2347-2357. DOI: 10.13288/j.11-2166/r.2024.22.011.
目的
2
挖掘导致药物性急性肾损伤(DI-AKI)的潜在中药成分/中药并分析其致DI-AKI的可能机制,进一步探索中药导致DI-AKI与免疫系统的相关性。
方法
2
采用网络毒理学研究方法,通过DisGeNET、MalaCards、TTD、OMIM数据库收集DI-AKI相关靶点,再通过本草组鉴数据库、中国知网、万方数据知识服务平台、维普资讯中文期刊服务平台、PubMed进行中药导致DI-AKI成分筛选,选择口服生物利用度(OB)值≥20%的致DI-AKI中药成分,通过中药系统毒理学数据库筛选致DI-AKI的中药。使用Cytoscape v3.9.1构建DI-AKI靶点-中药成分-中药网络,计算该网络的拓扑属性得到关键的靶点、致DI-AKI中药成分及对应中药,对核心子网络靶点进行GO功能和KEGG通路富集分析,并使用免疫浸润分析及孟德尔随机化分析探索中药导致的DI-AKI与免疫系统的相关性。
结果
2
筛选出OB≥20%的致DI-AKI中药成分22个,其中生物碱类成分最多有5个,其次为蒽醌类和二萜类成分各3个。最终共收集到21味潜在的致DI-AKI中药,其中含马兜铃酸/马兜铃内酰胺类中药成分如朱砂莲、关木通、广防己、青木香等是导致DI-AKI的主要中药。TNF、TP53、IL6、HIF1A、BCL2等10个基因是DI-AKI发生发展过程中的枢纽基因。对核心子网络29个靶点GO功能富集发现上皮细胞增殖、凋亡信号通路的调控、血管生成、缺氧和氧化应激、血管生成等显著富集。KEGG通路中信号转导通路富集到了23个靶点和17条通路。免疫浸润分析结果显示,致DI-AKI中药与常规树突状细胞、巨噬细胞、中性粒细胞等呈正相关,而与CD4
+
初始T细胞、CD8
+
初始T细胞、未成熟的树突状细胞等呈负相关。孟德尔随机化分析结果显示,CD14
+
、CD16
+
单核细胞上的CD64可能成为急性肾损伤的危险因素,T细胞依赖性的CD4
+
T细胞上的抗原受体为急性肾损伤的保护因素。
结论
2
通过网络毒理学研究逆向推导出了21个潜在的致DI-AKI中药,其机制可能与氧化应激、自噬、凋亡等激活免疫系统导致炎症反应密切相关。中药导致DI-AKI的免疫机制可能与常规树突状细胞、巨噬细胞、中性粒细胞等免疫细胞的升高和自然杀伤T细胞、辅助性T细胞等免疫细胞的下降有关,单核细胞与急性肾损伤也有因果关系。
Objective
2
To explore potential herbal components/Chinese herbal medicines (CHM) leading to drug-induced acute kidney injury (DI-AKI) and analyse the possible mechanisms of DI-AKI, and to further explore the correlation between DI-AKI caused by Chinese herbal medicines and the immune system.
Methods
2
Using network toxicology research methods, DI-AKI-related targets were collected through DisGeNET, MalaCards, TTD, and OMIM databases, and then screened CHM components that caused DI-AKI through HERB database, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform, Wikipedia Chinese Journal Service Platform, and PubMed, selected with an oral bioavailability (OB) value ≥20%, and screened CHM caused DI-AKI through traditional Chinese medicine system toxicology database. Cytoscape v3.9.1 was used to construct a DI-AKI target-CHM component-CHM network, and the topological properties of the network were calculated to obtain the key targets, DI-AKI-causing CHM components and the corresponding CHM, and the core sub-network targets were subjected to GO function and KEGG pathway enrichment analyses were conducted. The correlation between DI-AKI caused by CHM and the immune system was also explored using immune infiltration analysis and Mendelian randomisation analysis.
Results
2
There are 22 CHM components causing DI-AKI with OB ≥ 20% were identified, among which alkaloids are the most abundant contained in 5 CHM components, followed by anthraquinones and diterpenes contained in 3 CHM components each. A total of 21 CHMs causing DI-AKI were finally collected, among which CHMs containing components of aristolochic acid/aristolactam such as Zhusha (
Cinnabaris
), Guanmutong (
Isotrema manshuriense
), Guangfangji (
Isotrema fangchi
) and Qingmuxiang (
Inula helenium L.
) were the main CHMs leading to DI-AKI. Ten genes including TNF, TP53, IL6, HIF1A, and BCL2 were the pivotal genes in the development of DI-AKI. GO functional enrichment of 29 targets in the core sub-network revealed significant enrichment in epithelial cell proliferation, regulation of apoptotic signalling pathways, angiogenesis, hypoxia and oxidative stress, and angiogenesis. Signal transduction pathways in the KEGG pathway were enriched to 23 targets and 17 pathways. The results of immune infiltration analysis showed that CHMs causing DI-AKI were positively correlated with
conventional dendritic cells, macrophages, and neutrophils, and negatively correlated with CD4
+
initial T cells, CD8
+
initial T cells, and immature dendritic cells. Mendelian randomisation analysis showed that CD64 on CD14
+
and CD16
+
monocytes may be a risk factor for acute kidney injury, and T-cell-dependent antigen receptor on CD4
+
T cells is a protective factor for acute kidney injury.
Conclusion
2
Network toxicology studies identified 21 potential CHMs associated with DI-AKI, suggesting that their mechanisms may be closely linked to immune system activation through oxidative stress, autophagy, and apoptosis, which lead to inflammatory responses. The immune mechanism of DI-AKI induced by CHMs may involve elevated levels of immune cells, such as conventional dendritic cells, macrophages, and neutrophils, alongside a decline in natural killer T cells, helper T cells (types I and II), and monocytes, which have shown a causal relationship with acute kidney injury.he study provide a theoretical support for the study of CHM causing DI-AKI and also offer references for the CHM safety precise study and pharmacovigilance.
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