The objective of this study is to utilize metabolomics to analyze saliva samples from chronic erosive gastritis (CEG) patients and identify potential biomarkers capable of detecting diseases.

A total of 64 CEG-affected subjects and 30 healthy subjects were recruited. Saliva samples were collected and analyzed in both negative and positive ion modes utilizing ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS).

Using multivariate (orthogonal partial least squares discriminant analysis) along with univariate (Student's t-test) tests, statistical assessment was executed. To identify predictors in the saliva of CEG subjects, receiver operating characteristic (ROC) assessment was carried out.

A comparative analysis of saliva samples from CEG volunteers and healthy people revealed 45 metabolites that exhibited differential expression. Among these metabolites, 37 were up-regulated while 8 were down-regulated. The differentially expressed metabolites were found to be associated with the mTOR signaling pathway, protein digestion and absorption, phenylalanine metabolism, lipid, and amino acid. In the ROC analysis, seven metabolites displayed area under the curve (AUC) values exceeding 0.8, with 1,2-dioleoyl-sn-glycoro-3-phosphorylcholine and 1-stearoyl-2-oleoyl-sn-glycoro-3-phosphorine exhibiting AUC values surpassing 0.9.

In the saliva of individuals diagnosed with CEG, a set of 45 metabolites was discovered. Notably, two specific metabolites, namely 1,2-dioleoyl-sn-glycoro-3-phosphorylcholine and 1-stearoyl-2-oleoyl-sn-glycoro-3-phosphorine, exhibited promising indications of having valuable clinical applications.