Transcriptomics-based analysis revealed the functional pattern of Radix Paeoniae Alba

Radix Paeoniae Alba (RPA) and other natural medicines have remarkable curative effects and are widely used. However, due to their multicomponent and multitarget characteristics, relevant effective research methods are lacking. The present study was designed to integrate the results of transcriptomics and metabolomics determined by RNA sequencing and serum NMR spectroscopy, respectively, after RPA consumption. A variety of dimension-reduction algorithms and classifier models were applied to the processing of high-throughput data. Based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, differential analysis showed that the liver was the site where RPA exerted a significant effect, which confirmed the rationality of "meridian tropism" in the theory of traditional Chinese medicine (TCM). In addition, RPA played a role in lipid metabolism by regulating genes encoding key enzymes of the glycerolipid metabolism pathway, such as Agpat, Lpin and Lipg. Meanwhile, it was found that RPA could regulate several substance addiction pathways in the brain, such as the cocaine addiction pathway, and related targets were predicted based on the pathological model sequencing data in the GEO database. By examining the common changes in molecular levels between organs, it was speculated that the potency of drugs composed of complex components may be based on the synergistic effect of the hypothalamic pituitary adrenal (HPA) axis or liver-brain axis. The overall effective pattern of RPA was intuitively presented with a multidimensional radar map through a self-designed model. In essence, this study used modern tools to interpret the theories of TCM, expanded the potential application of RPA, and provided some possible targets and directions for further mechanism research to provide a valuable reference model for the modernization of TCM research.