Identification of a Quality Marker (Q-Marker) of Danhong Injection by the Zebrafish Thrombosis Model

Quality-marker (Q-marker) is an emerging concept to ensure the quality and batch-to-batch consistency of Chinese medicine (CM). However, significant difficulties remain in the identification of Q-markers due to the unclear relationship between complex chemical compositions and the pharmacological efficacy of CM. In the present study, we proposed a novel strategy to identify the potential Q-marker of danhong injection (DHI) by an in vivo zebrafish thrombosis model. The anti-thrombotic effects of DHI and its major constituents were evaluated by the zebrafish model of arachidonic acid (AA)-induced thrombosis. The results indicated that DHI can attenuate tail venous thrombus and recover the decrease of heart red blood cell (RBC) intensity in a dose-dependent manner. The result that DHI prevented the formulation of thrombosis in zebrafish was also validated in the zebrafish thrombosis model with green fluorescence protein (GFP)-labeled hemoglobin. The major components of DHI, namely danshen (DS) and honghua (HH), as well as the major chemical constituents of DHI, also exerted anti-thrombotic effects, among which rosmarinic acid (RA) and p-coumaric acid (pCA) showed moderate anti-thrombotic effects. This is the first time that pCA from HH has been found as an active compound exerting an anti-thrombotic effect in a dose-dependent manner, whose IC(50) value is approximately 147 μg/mL. By analyzing 10 batches of normal DHI samples and five abnormal samples by high-performance liquid chromatography (HPLC), we found the contents of pCA and RA can be positively correlated to the anti-thrombotic effect of DHI, suggesting that pCA and RA could be potential Q-markers of DHI to ensure batch-to-batch consistency. Our findings illustrated that discovering major active compounds from CM by in vivo pharmacological models can be a useful approach to identifying Q-markers of CM, and in vivo pharmacological models can be a potential tool to evaluate batch-to-batch consistency of CMs.