Background Qilong capsule (QLC) is a well-known traditional Chinese medicine compound extensively used in clinical practice. It has been approved by the China's FDA for the treatment of ischemic stroke (IS). In our clinical trial involving QLC (ClinicalTrials.gov identifier NCT03174535), we observed the potential of QLC to improve neurological function in IS patients at the 24th week, while ensuring their safety. However, the effectiveness of QLC beyond the initial 12-week period remains uncertain, and the precise mechanisms underlying its action in IS have not been fully elucidated. Purpose In order to further explore the clinical efficacy of QLC in treating IS beyond the initial 12-week period and systematically elucidate its underlying mechanisms. Study Design This study employed an interdisciplinary integration strategy that combines post hoc analysis of clinical trials, transcriptome sequencing, integrated bioinformatics analysis, and animal experiments. Methods In this study, we conducted a post-hoc analysis with 2302 participants to evaluate the effectiveness of QLC at the 12th week. The primary outcome was the proportion of patients achieving functional independence at the 12th week, defined as a score of 0-2 on the modified Rankin Scale (mRS), which ranges from 0 (no symptoms) to 6 (death). Subsequently, we employed RNA sequencing (RNA-Seq) and quantitative reverse transcription polymerase chain reaction (RT-qPCR) techniques in the QLC trial to investigate the potential molecular mechanisms underlying the therapeutic effect of QLC in IS. Simultaneously, we utilized integrated bioinformatics analyses driven by external multi-source data and algorithms to further supplement the exploration and validation of QLC's therapeutic mechanism in treating IS. This encompassed network pharmacology analysis and analyses at the mRNA, cellular, and pathway levels focusing on core targets. Additionally, we developed a disease risk prediction model using machine learning. By identifying differentially expressed core genes (DECGs) between the normal and IS groups, we quantitatively predicted IS occurrence. Furthermore, to assess its protective effects and determine the key regulated pathway, we conducted experiments using a middle cerebral artery occlusion and reperfusion (MACO/R) rat model. Results Our findings demonstrated that the combination of QLC and conventional treatment (CT) significantly improved the proportion of patients achieving functional independence (mRS score 0-2) at the 12th week compared to CT alone (n = 2,302, 88.65 % vs 87.33 %, p = 0.3337; n = 600, 91.33 % vs 84.67 %, p = 0.0165). Transcriptome data revealed that the potential underlying mechanism of QLC for IS is related to the regulation of the NF-κB inflammatory pathway. The RT-qPCR results demonstrated that the regulatory trends of key genes, such as MD-2, were consistent with those observed in the RNA-Seq analysis. Integrated bioinformatics analysis elucidated that QLC regulates the NF-κB signaling pathway by identifying core targets, and machine learning was utilized to forecast the risk of IS onset. The MACO/R rat model experiment confirmed that QLC exerts its anti-CIRI effects by inhibiting the MD-2/TLR-4/NF-κB signaling axis.

Conclusion:

Our interdisciplinary integration study has demonstrated that the combination of QLC with CT exhibits significant superiority over CT alone in improving functional independence in patients at the 12th week. The potential mechanism underlying QLC's therapeutic effect in IS involves the inhibition of the MD-2/TLR4/NF-κB inflammatory signaling pathway, thereby attenuating cerebral ischemia/reperfusion inflammatory injury and facilitating neurofunctional recovery. The novelty and innovative potential of this study primarily lie in the novel finding that QLC significantly enhances the proportion of patients achieving functional independence (mRS score 0-2) at the 12th week. Furthermore, employing a "multilevel-multimethod" integrated research approach, we elucidated the potential mechanism underlying QLC's therapeutic effect in IS.