Introduction: Chronic erosive gastritis (CEG) is closely related to gastric cancer, which requires early diagnosis and intervention. The invasiveness and discomfort of electronic gastroscope have limited its application in the large-scale screening of CEG. Therefore, a simple and noninvasive screening method is needed in the clinic.
Objectives: The aim of this study is to screen potential biomarkers that can identify diseases from the saliva samples of CEG patients using metabolomics.
Methods: Saliva samples from 64 CEG patients and 30 healthy volunteers were collected, and metabolomic analysis was performed using UHPLC-Q-TOF/MS in the positive and negative ion modes. Statistical analysis was performed using both univariate (Student's t-test) and multivariate (orthogonal partial least squares discriminant analysis) tests. Receiver operating characteristic (ROC) analysis was conducted to determine significant predictors in the saliva of CEG patients.
Results: By comparing the saliva samples from CEG patients and healthy volunteers, 45 differentially expressed metabolites were identified, of which 37 were up-regulated and 8 were down-regulated. These differential metabolites were related to amino acid, lipid, phenylalanine metabolism, protein digestion and absorption, and mTOR signaling pathway. In the ROC analysis, the AUC values of 7 metabolites were greater than 0.8, among which the AUC values of 1,2-dioleoyl-sn-glycoro-3-phosphodylcholine and 1-stearoyl-2-oleoyl-sn-glycoro-3-phospholine (SOPC) were greater than 0.9.
Conclusions: In summary, a total of 45 metabolites were identified in the saliva of CEG patients. Among them, 1,2-dioleoyl-sn-glycoro-3-phosphorylcholine and 1-stearoyl-2-oleoyl-sn-glycoro-3-phosphorine (SOPC) might have potential clinical application value.
Keywords: Biomarker; Chronic erosive gastritis; Metabolomics; Saliva; UHPLC-Q-TOF/MS.
© 2023. The Author(s).