Abstract
Chronic gastritis (CG) is a common inflammatory disease of chronic inflammatory lesion of gastric mucosa and in the diagnosis of gastritis in traditional Chinese medicine (TCM), CG can be classified into Cold ZHENG (syndrome in TCM) and Hot ZHENG. However, the molecular features of Cold/Hot ZHENG in CG and the mechanism of Cold/Hot herbs in formulae for CG remained unclear. In this study, we collected a transcriptomics data including 35 patients of Cold/Hot ZHENG CG and 3 scRNA-seq CG samples. And 25 formulae for CG and 89 herbs recorded in these formulae were also collected. We conduct a comprehensive analysis based on the combination of transcriptomics datasets and machine learning algorithms, to discover biomarkers for Cold/Hot ZHENG CG. Then the target profiles of the collected formulae and Cold/Hot herbs were predicted to uncover the features and biomarkers of them against Cold/Hot ZHENG CG. These biomarkers suggest that Hot ZHENG CG might be characterized by over-inflammation and exuberant metabolism, and Cold ZHENG CG showed a trend of suppression in immune regulation and energy metabolism. Biomarkers and specific pathways of Hot herbs tend to regulate immune responses and energy metabolism, while those of Cold herbs are more likely to participate in anti-inflammatory effects. Finally, the findings were verified based on public transcriptomics datasets, as well as transcriptomics and ELISA detection, taking Jin Hong tablets as a case study. Biomarkers like leptin and IL-6 together with proportions of immune cells showed significant changes after the intervention. These findings might reflect the mechanism and build a bridge between macro and micro views of Cold/Hot ZHENG as well as Cold/Hot herbs.