目的 建立基于高分辨质谱、全球天然产物分子网络（global natural products social molecular networking，GNPS）和网络药理学的中药治疗共病物质基础研究策略，并对开心散治疗抑郁症-阿尔茨海默病的物质基础进行系统分析。方法 采用超高效液相色谱-轨道阱串联质谱（ultra-performance liquid chromatography-orbitrap tandem mass spectrometry，UPLC-Orbitrap-MS/MS）对开心散提取物及其血浆和脑组织暴露样品进行非靶向二级质谱分析。然后，利用GNPS平台，基于开心散提取物和血浆样品所得质谱数据构建分子网络，结合化合物的精确质量数、保留时间、碎片信息、质谱裂解规律，快速鉴定开心散血浆暴露成分。基于血浆暴露成分，结合脑组织样品的高分辨质谱数据，鉴定开心散入脑成分。结合脑组织暴露成分和网络药理学技术探究开心散治疗抑郁症-阿尔茨海默病共病物质基础。结果 从血浆中鉴定出开心散暴露成分共34个，从脑组织中鉴定出开心散暴露成分共21个，并筛选出开心散中具有治疗抑郁症-阿尔茨海默病共病活性的成分共19个，涉及皂苷类成分9个、寡糖酯类成分9个、𠮿酮类成分1个。结论 建立了中药共病物质基础快速发现的新策略，为中药“异病同治”研究提供方法支撑，且为开心散治疗抑郁症-阿尔茨海默病共病的物质基础阐释及其临床应用提供数据支撑。

Objective To establish a research strategy for the material basis of traditional Chinese medicine treatment of comorbidities based on high-resolution mass spectrometry, the global natural products social molecular networking (GNPS), and network pharmacology, and conduct a systematic analysis of the material basis of Kaixinsan (开心散) treatment for depression and Alzheimer’s disease. Methods First, ultra-high-performance liquid chromatography-orbitrap tandem mass spectrometry (UPLC-Orbitrap-MS/MS) was used to perform non-targeted secondary mass spectrometry analysis on the extracts of Kaixinsan and its plasma and brain tissue exposure samples. Then, using the GNPS platform, molecular networks were constructed based on the mass spectrometry data obtained from the Kaixinsan extract and plasma samples. Combining the precise mass numbers, retention times, fragmentation information, and mass spectrometry fragmentation patterns of the compounds, the plasma exposure components of Kaixinsan were rapidly identified. Subsequently, based on the plasma exposure components, combined with the high-resolution mass spectrometry data from the brain tissue samples, the brain-penetrating components of Kaixinsan were identified. Finally, the material basis for treatment of depression-Alzheimer’s disease comorbidity by the Kaixinsan was explored by combining brain tissue exposure components and network pharmacology techniques. Results A total of 34 components exposed to Kaixinsan were identified in plasma, and a total of 21 components exposed to Kaixinsan were identified in brain tissue. A total of 19 components with therapeutic activity for depression-Alzheimer’s disease comorbidity were screened from Kaixinsan, including 9 saponins, 9 oligosaccharide esters, and 1 xanthone. Conclusion This study established a new strategy for rapidly identifying the material basis of concomitant diseases in traditional Chinese medicine, providing methodological support for research on treatment of different diseases with the same treatment in traditional Chinese medicine. It also provided data support for explaining the material basis of the treatment of depression and Alzheimer’s disease concomitant diseases with Kaixinsan and its clinical application.

R284.1

中国中医科学院科技创新工程项目资助（CI2023E002）；中央级公益性科研院所基本科研业务费专项资金资助（ZXKT25014）；四大慢病重大专项（2023ZD0509300）