Differential mRNA expression combined with network pharmacology reveals network effects of Liangxue Tongyu Prescription for acute intracerebral hemorrhagic rats. (10th January 2020)

• Record Type: Journal Article
• Authors: Guo, Qingqing; Yang, Shijin; Yang, Dongqing; Zhang, Ning; Li, Xun; Chen, Tianli; Chen, Jiayan; Li, Guochun; Yin, Lian; Wu, Qibiao
• Is Part Of: Journal of ethnopharmacology. Volume 246(2019)
• Publication Date: 2020-01-10
• Subjects: Differential mRNA expression -- Network pharmacology -- Liangxue Tongyu Prescription (LTP) -- Acute intracerebral hemorrhage (AICH) -- Network effects -- Traditional Chinese medicine; Ethnopharmacology -- Periodicals; Pharmacognosy -- Periodicals; Herbs -- Periodicals; Herbs -- Periodicals; Pharmacognosy -- Periodicals; Pharmacognosie -- Périodiques; Herbes -- Périodiques; 615.1
• DOI: 10.1016/j.jep.2019.112231
• Languages: English
• ISSNs: 0378-8741

Abstract

Abstract: Ethnopharmacological relevance: Liangxue Tongyu Prescription (LTP) is a traditional Chinese medicine formula composed of 8 crude drugs that is widely used to treat acute intracerebral hemorrhage (AICH). Aim of the study: To verify the efficacy of LTP on the survival time in the treatment of acute intracerebral hemorrhagic rats (AICHs), and to elucidate its network pharmacodynamic mechanism of multi-component, multi-target, and multi-signaling pathways. Materials and methods: Survival analysis was used to evaluate the survival time of AICH rats induced by different doses of collagenase and the efficacy of three doses of LTP in the treatment of AICH rats. The Kaplan-Meier curves for survival time were produced and compared with the Log-rank test and Wilcoxon (Gehan) χ 2 . Differential mRNA-seq combined with network pharmacology was used to disclose the network effect mechanism of LTP on AICH, and the obtained differential genes were mapped into the predictive empirical compound-target network model (ECT network model) and the empirical compound-target-pathogenesis (disease) network model (ECTP network model). Results: The median survival time of four different doses of LTP-treated groups (0.00 g/kg, 5.78 g/kg, 11.55 g/kg, 23.10 g/kg) for adult AICH rats by 0.18 U collagenase was 14 h, 37 h, 150 h, and 51 h respectively, and the 7-day survival rates were 33.3%, 41.7%, 50.0%, and 38.5%, of which the medium-dose group (MD) had a longer survival time and higher survival rate. Through further validation experiments, the MD group had a better efficacy trend with a median survival time of 168 h vs 23 h in the model control group (MC) (Wilcoxon Gehan Test, χ 2 = 3.478, P = 0.062). The transcriptomic analysis of mRNA showed that 583 significant differential genes were found between the MC and MD group and 7 key therapeutic targets regulated by 29 compounds in LTP on AICH were screened out by VCT and VCTP network model. These targets were involved in 5 regulatory models or pathways. Conclusion: Our study confirmed the exact efficacy of the LTP in the treatment of AICH and revealed the potential pharmacodynamic components and mode of action of the LTP on AICH. Using differential transcriptome of mRNA combined with network pharmacology, we screened out 29 chemical compounds as the potential effective ingredients of LTP which acted on 7 targets of AICH involving 5 pathological pathways, mainly including repairing the brain function defect, improving neural function, protecting blood-brain barrier from damage, reducing inflammatory factors, and inhibiting apoptosis. The present study not only provides a new explanation for the 'multi-component, multi-target, multi-pathway' effects of the LTP on AICH but also screened out some major compounds of LTP and their potential targets which will facilitate the development of new drugs for AICH.