目的 基于專利數據挖掘與轉錄組學分析,探索中藥復方治療肌萎縮側索硬化癥(amyotrophic lateral sclerosis,ALS)的配伍規(guī)律及精準治療策略。方法 從中國專利數據庫篩選ALS中藥復方專利,通過頻次統(tǒng)計與關聯分析挖掘核心藥物及配伍規(guī)律;利用中藥系統(tǒng)藥理學數據庫(traditional Chinese medicine systems pharmacology,TCMSP)和中藥高通量實驗和參考數據庫(a high-throughput experiment and reference-guided database of TCM,HERB)構建復方-靶點網絡,通過模塊劃分識別核心靶點模塊;基于轉錄組數據集,采用非負矩陣分解(non-negative matrix factorization,NMF)對ALS患者進行轉錄組分型;運用網絡相似性分析(Vertex/Edge Overlap,VEO算法)篩選各亞組優(yōu)勢復方,結合重啟隨機游走(random walk with restart,RWR)和SymMap平臺預測證候特征。結果 通過對中國專利數據庫中11項治療ALS的中藥復方專利(含101味中藥)進行配伍規(guī)律分析,發(fā)現黃芪、茯苓、人參、淫羊藿和當歸為高頻核心藥物。關聯規(guī)則分析進一步揭示關鍵藥對組合,其中白術-淫羊藿、白術-茯苓的配伍關聯性最強?；贕SE16989數據集的轉錄組NMF分析,ALS患者被劃分為4個亞組:組1顯著富集白細胞介素-17(interleukin 17,IL-17)信號通路;組2未富集顯著通路;組3與組4共同富集病毒-細胞因子互作通路。通過VEO算法計算復方蛋白質相互作用(protein-protein interaction,PPI)網絡與各亞組的相似性,篩選出亞組特異性優(yōu)勢復方:復方11匹配組1;復方9匹配組2;復方8匹配組3、4。RWR算法結合SymMap平臺進行亞組證候分型。結論 研究揭示了ALS的潛在優(yōu)勢中藥復方,將轉錄組亞型與中醫(yī)證候關聯,為ALS“病證結合”精準治療提供科學依據。

Objective To explore the compatibility patterns and precision treatment strategies of traditional Chinese medicine (TCM) prescriptions for amyotrophic lateral sclerosis (ALS) using patent data mining and transcriptomic analysis. Methods TCM prescriptions patents for ALS were screened from the Chinese Patent Database. Frequency statistics and association analysis were applied to identify core herbs and compatibility patterns. The traditional Chinese medicine systems pharmacology (TCMSP) and a high-throughput experiment- and reference-guided database of TCM (HERB) databases were utilized to construct prescriptions-target networks, and module partitioning was employed to identify core target modules. ALS patients were classified into transcriptional subgroups via non-negative matrix factorization (NMF) based on the GSE16989 transcriptomic dataset. Vertex/Edge Overlap (VEO) algorithm was used to screen subgroups-specific optimal prescriptions, while restart random walk (RWR) and the SymMap platform were applied to predict syndrome characteristics. Results Analysis of 11 ALS TCM prescriptions patents (containing 101 herbs) revealed Astragali Radix, Poria, Ginseng Radix et Rhizoma, Epimedii Folium, and Angelicae Sinensis Radix as high-frequency core herbs. Association rule mining identified key herb pairs, with Atractylodis Macrocephalae Rhizoma-Epimedii Folium and Atractylodis Macrocephalae Rhizoma-Poria showing the strongest compatibility correlations. NMF analysis classified ALS patients into four molecular subgroups: group 1 was significantly enriched in the interleukin-17 (IL-17) signaling pathway, group 2 showed no significant pathway enrichment; group 3 and group4 were co-enriched in the viral protein-cytokine receptor interaction pathway. Subgroups-specific optimal prescriptions were identified via VEO similarity: prescriptions 11 for group1, prescriptions 9 for group 2, and prescriptions 8 for group 3 and group 4. Syndrome stratification was performed using RWR and SymMap. Conclusion This study elucidates the precision treatment potential of TCM prescriptions for ALS by integrating transcriptomic subgroups with TCM syndrome characteristics, providing a scientific foundation for “disease-syndrome combination” therapy in ALS.

TP18;R285

國家自然科學基金面上項目（82474682）；國家“重大新藥創(chuàng)制”科技重大專項（2017ZX09031059）