中医药干预抗结核药致肝损伤核心方药的筛选研究

DILI caused by anti-tuberculosis drugs is an important factor for tuberculosis patients to fail in regular drug use and treatment. TCM therapy has unique advantages in intervening liver injury caused by anti-tuberculosis drugs. There are many clinical reports, flexible and abundant treatment strategies, but lack of systematic collation and excavation. Entropy clustering algorithm of complex system is good at processing and mining non-linear and complex data of TCM. This project intends to systematically collate and evaluate the clinical reports on DILI caused by anti-tuberculosis drug intervention in recent years, and construct the literature database of Baogan formulas and herbs. The data were analyzed by complex system entropy clustering and other unsupervised data mining methods, and then the core formulas and herbs for interfering with DILI caused by anti-tuberculosis drugs were obtained preliminarily by combining with the evaluation of experts. At the same time, the zebrafish liver injury model was constructed. By examining the biochemical indicators of liver damage, liver morphology, liver damage specific proteins and so on, the drug efficacy of the core formulas and herbs excavated from the data was screened efficiently. On the basis of the preliminary screening, the rat liver injury model was used to further validate the drug efficacy. Finally, the core formulas and herbs were determined, and the differentiation and treatment of TCM for interfering with DILI caused by anti-tuberculosis drugs were summarized. Regularity can provide reference for clinical medication. Combining data mining screening with experimental validation screening, a new drug screening model was explored.

抗结核药导致的肝损伤是结核患者无法规律用药、治疗失败的重要因素。中医药疗法对于干预抗结核药致肝损伤具有独特的优势，临床报道众多，治疗策略灵活而丰富，但缺乏系统整理与挖掘。复杂系统熵聚类算法善于处理挖掘非线性、复杂性的中医数据。本项目拟对近年来国内外中药干预抗结核药导致肝损伤的临床报道文献进行系统整理与评价，构建保肝方药文献数据库。采用复杂系统熵聚类等多种无监督数据挖掘方法对数据进行分析，再结合多名专家评定意见，初步获得干预抗结核药致肝损伤的核心方药。同时构建斑马鱼肝损伤模型，通过检验肝损生化指标、肝脏形态、肝损特异性蛋白等，对数据挖掘出的核心方药药效进行高效初筛，在初筛的基础上利用大鼠肝损模型进行进一步药效验证，最终确定核心方药，总结中医药疗法干预抗结核药致肝损伤的中医辨治规律，为临床用药提供参考。将数据挖掘筛选与实验验证筛选相结合，探索构建药物筛选新模式。

背景: 结核病至今仍是严重的公共卫生问题。抗结核化学疗法是干预结核病的有效手段，但多数一线化疗药物都有潜在肝毒性，易产生抗结核化疗肝损伤（ATDILI, antituberculosis drug-induced liver injury），最终导致化疗中断，甚则治疗失败。中医药疗法干预ATDILI具有明显优势，自上世纪90年代以来，临床报道多，但治法各异，令人莫衷一是，急需运用新方法、新思路进行系统整理与挖掘。目的: 基于数据挖掘与斑马鱼模型，分析中医药干预ATDILI的用药规律，筛选核心方药。继而采用小鼠模型探索核心方缓解ATDILI的潜在机制。方法: 收集相关文献，运用中医传承辅助系统建立方剂数据库进行数据挖掘，将核心方药在斑马鱼模型进行药效验证。继而将先期数据挖掘与斑马鱼药效筛选出的核心方——逍遥散（XYS），在小鼠ATDILI模型上进一步验证，通过小鼠肝脏病理切片的苏木精-伊红染色(HE)、油红O染色(oil red O)、生化指标和活性氧(ROS)水平观察XYS对ATDILI的作用。用Western blotting检测线粒体合成相关蛋白和铁死亡相关蛋白的表达。结果: 筛选方剂 342首，分析得到 41味常用药物，17种常用药对，1组核心方，以及 6个新处方。核心方药干预下的ATDILI斑马鱼模型，斑马鱼幼鱼的畸形率、死亡率均显著下降，形态学改善，肝脏荧光面积显著上升，荧光光密度显著增强。此外，核心方XYS对ATDILI小鼠的作用研究结果显示，XYS能改善肝损伤小鼠肝脏组织的病理改变，降低氧化应激水平。XYS增加了线粒体合成相关蛋白的表达，逆转了铁死亡相关蛋白的表达。通过shRNA介导的基因敲低技术，抑制富含鸟嘌呤的序列结合因子1（Grsf1）的表达，可阻断XYS对肝损伤的保护作用。结论: 中医药干预ATDILI以补虚、清热、利湿为总原则，注重肝脾同治。数据挖掘得到的核心方与高频单药，在斑马鱼ATDILI模型上均显示出一定的保肝作用，验证了数据挖掘技术的可靠与适用。核心方XYS通过介导线粒体氧化应激通路中的Grsf1来缓解AT药物诱导的肝损伤。本研究将数据挖掘与药理实验验证相结合，探索构建了一种药物筛选新模式。