Targeted metabolomics analysis for serum Helicobacter pylori-positive based on liquid chromatography-tandem mass spectrometry

Helicobacter pylori (H. pylori), as a harmful bacteria associated with gastric cancer, can have adverse effects on human normal flora and metabolism. However, the effects of H. pylori on human metabolism have not been fully elucidated. The C-13 breathing test was used as the basis for distinguishing negative and positive groups. Serum samples were collected from the two groups for targeted quantitative metabolomics detection; multidimensional statistics were used, including partial least squares discriminant analysis (PLS-DA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and differential metabolites were screened. Unidimensional statistics combined with multidimensional statistics were used to further screen potential biomarkers, and finally pathway analysis was performed. SPSS 21.0 software package was used for statistical analysis of experimental data. Multivariate statistical analysis such as PLS-DA, PCA, and OPLS-DA was performed using Simca-P 13.0 to search for differential metabolites. This study confirmed that H. pylori caused significant changes in human metabolism. In this experiment, 211 metabolites were detected in the serum of the two groups. Multivariate statistical analysis showed that PCA of metabolites was not significantly different between the two groups. PLS-DA indicated that the serum of the two groups was well clustered. There were significant differences in metabolites between OPLS-DA groups. By setting the variable importance in projection (VIP) threshold as one and the corresponding P-value <0.05, a total of 40 metabolites were screened in this study. P 0 (where FC is the fold change) were used together as a unidimensional statistical filter condition. The analysis found that the expression of 15 metabolites such as propionic acid, acetic acid, adipic acid increased, and the metabolism of six products such as deoxycholic acid (DCA), 4-hydroxyphenylpyruvic acid, pyruvic acid decreased. P <0.05, false discovery rate <0.5, divide log2FC divide >1, and OPLSDA_VIP>1 were used together as a condition for filter screening potential biomarkers. Four potential biomarkers were screened, which were sebacic acid, isovaleric acid, DCA, and indole-3-carboxylic acid. Finally, the different metabolites were added to the pathway-associated metabolite sets (SMPDB) library for the corresponding pathway enrichment analysis. The significant abnormal metabolic pathways were taurine and subtaurine metabolism, tyrosine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, etc. This study shows that H. pylori has an impact on human metabolism. Not only a variety of metabolites have significant changes, but also metabolic pathways are abnormal, which may be the reason for the high risk of H. pylori causing gastric cancer.