The changes in tongue coating metabolites in patients with chronic gastritis (CG) under different gastroscopy indicators were analyzed, and these metabolites were screened for potential non-invasive biomarkers to assist in the diagnosis of chronic gastritis. The technology of gas chromatography and liquid chromatography combined with mass spectrometry has been used to more comprehensively detect tongue coating metabolites of 350 CG patients. Spearman correlation analysis and random forest algorithm were used to screen metabolites that can serve as potential biomarkers. Compared with healthy individuals, CG group showed significant changes in the content of 101 metabolites, with an increase in the content of 54 metabolites and a decrease in the content of 47 metabolites. These differential metabolites are mainly composed of 47 lipids and lipid like substances. 1 metabolite was associated with bile reflux, 1 metabolite was associated with gastric mucosal erosion, 10 metabolites were associated with atrophy, 10 metabolites were associated with intestinal metaplasia, and 3 metabolites were associated with Helicobacter pylori infection. The ROC model composed of 5 metabolites can distinguish between CG group and healthy individuals, with an accuracy of 95.4%. The ROC model composed of 5,6-Dihydroxyindole can distinguish between chronic superficial gastritis group and chronic atrophic gastritis group, with an accuracy of 75.3%. The lipids and lipid like metabolites were the main abnormal metabolites in patients with chronic gastritis. It was worth noting that the content of Sphinganine 1-phase, 4-Ipomenol, and Nervonic acid in tongue coating increased, and the content of 1-Methyladenosine and 3-Hydroxycapric acid decreased, which helped to identify CG patients. The decrease in the content of 5,6-dihydroxyindole reminded patients that the development trend of CG was shifting from superficial to atrophic or even intestinal metaplasia. The detection of these metabolic markers of tongue coating was expected to be developed as a non-invasive and convenient technology in the future to assist us in monitoring and diagnosing the occurrence and development of CG.
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