Exploration of rhubarb Q-marker based on smart data processing techniques and AUC cluster method


This article was originally published here

Before Pharmacol. 2022 Mar 21;13:865066. doi: 10.3389/fphar.2022.865066. eCollection 2022.


Rhubarb, as a traditional Chinese medicine, has several positive therapeutic effects, such as purging and attacking buildup, clearing heat and purging fire, cooling blood, and detoxifying. Recently, rhubarb has been used in prescriptions for the prevention and treatment of COVID-19, with good efficacy. However, exploring an effective quantitative approach to ensure consistency in the therapeutic efficacy of rhubarb remains a challenge. In this case, this study aims to use untargeted and targeted data mining technologies for its exploration and has comprehensively identified 72 rhubarb-related components in human plasma for the first time. In details, the area under the concentration-time curve (AUC) pooling method was used to quickly screen high-exposure components, and the main components were analyzed using the correlation of Pearson and other statistical analyses. Interestingly, the prototype component (rhein) at high exposure could be selected as a Q-marker, which could also reflect changes in metabolic status of rhubarb anthraquinone in humans. Moreover, after comparing the metabolism of different species, mice were selected as animal models to verify the pharmacodynamics of rhein. the live experimental results showed that rhein has a positive therapeutic effect on pneumonia, significantly reducing the concentration of pro-inflammatory factors [interleukin (IL)-6 and IL-1β] and improve lung disease. Briefly, based on the perspective of human exposure, this study comprehensively used intelligent data post-processing technologies and AUC pooling method to establish that rhein can be chosen as a marker. Q for rhubarb, the content of which must be monitored individually.

PMID:35387347 | PMC: PMC8979112 | DOI:10.3389/fphar.2022.865066


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