Urinary metabolic profiles during Helicobacter pylori eradication in chronic gastritis

Abstract

Background: Helicobacter pylori (H. pylori) infection is a major risk factor for chronic gastritis, affecting approximately half of the global population. H. pylori eradication is a popular treatment method for H. pylori-positive chronic gastritis, but its mechanism remains unclear. Urinary metabolomics has been used to elucidate the mechanisms of gastric disease treatment. However, no clinical study has been conducted on urinary metabolomics of chronic gastritis.

Aim: To elucidate the urinary metabolic profiles during H. pylori eradication in patients with chronic gastritis.

Methods: We applied LC-MS-based metabolomics and network pharmacology to investigate the relationships between urinary metabolites and H. pylori-positive chronic gastritis via a clinical follow-up study.

Results: Our study revealed the different urinary metabolic profiles of H. pylori-positive chronic gastritis before and after H. pylori eradication. The metabolites regulated by H. pylori eradication therapy include cis-aconitic acid, isocitric acid, citric acid, L-tyrosine, L-phenylalanine, L-tryptophan, and hippuric acid, which were involved in four metabolic pathways: (1) Phenylalanine metabolism; (2) phenylalanine, tyrosine, and tryptophan biosynthesis; (3) citrate cycle; and (4) glyoxylate and dicarboxylate metabolism. Integrated metabolomics and network pharmacology revealed that MPO, COMT, TPO, TH, EPX, CMA1, DDC, TPH1, and LPO were the key proteins involved in the biological progress of H. pylori eradication in chronic gastritis.

Conclusion: Our research provides a new perspective for exploring the significance of urinary metabolites in evaluating the treatment and prognosis of H. pylori-positive chronic gastritis patients.

Keywords: Helicobacter pylori; LC-MS; chronic gastritis; metabolomics; urinary metabolites.

Figure 1

Schematic of patient enrollment and sample collection and analysis. Fasting morning urine samples were collected from enrolled patients and subjected to metabolomics using LC–MS/MS analysis. Data were analyzed using One-Map, SIMCA, and MetaboAnalyst. HP(+): Helicobacter pylori-positive; HP(−): Helicobacter pylori-negative.

Figure 2

Principal component analysis and partial least square discriminant analysis score scatter plots from urine analysis data. A, B: Principal component analysis (PCA) model score scatter plots; C, D: Partial least square discriminant analysis (PLS–DA) model score scatter plots; and (E and F) PLS-DA validation plot; A, C, E: Negative electronspray ionization (ESI) mode; B, D, F: Positive ESI mode. HP(+): Helicobacter pylori-positive; HP(−): Helicobacter pylori-negative.

Figure 3

Orthogonal partial least square discriminant analysis and pathway enrichment analysis of the health and Helicobacter pylori-positive samples. A, B: Orthogonal partial least square (OPLS) score plots; C, D: S-plots; A, C: Negative electronspray ionization (ESI) mode; B, D: Positive ESI mode. Model parameters of the negative ESI mode: R2X = 0.537, R2Y = 0.935, and Q2 = −0.33. Model parameters of the positive ESI mode: R2X = 0.467, R2Y = 0.955, and Q2 = −0.0553; E: Pathway enrichment analysis of differential metabolites between Helicobacter pylori-negative and health samples. Differential metabolites were obtained from OPLS–discriminant analysis and subjected to Kyoto encyclopedia of genes and genomes analysis using MetaboAnalyst software. Helicobacter pylori-positive; HP(−): Helicobacter pylori-negative.

Figure 4

Orthogonal partial least square discriminant analysis and pathway enrichment analysis between the Helicobacter pylori-positive and -negative samples. A, B: Orthogonal partial least square (OPLS) score plots; C, D: S-plots; A, C: Negative electronspray ionization (ESI) mode; B, D: Positive ESI mode. Model parameters of the negative ESI mode: R2X = 0.472, R2Y = 0.944, and Q2 = 0.119; model parameters of the positive ESI mode: R2X = 0.424, R2Y = 0.985, and Q2 = −0.109; E: Pathway enrichment analysis of differential metabolites between the Helicobacter pylori-negative and -positive samples. Differential metabolites were obtained from the OPLS–discriminant analysis and subjected to Kyoto encyclopedia of genes and genomes analysis using MetaboAnalyst. Helicobacter pylori-positive; HP(−): Helicobacter pylori-negative.

Figure 5

Metabolites involved in Helicobacter pylori elimination. A: Peak intensity of the significant urinary metabolites associated with chronic gastritis management during Helicobacter pylori (H. pylori) elimination. Data presented as the mean ± SD (n = 20). P < 0.05 was considered to represent significance. Health group vs H. pylori-positive [HP(+)] group: ^aP < 0.05, ^bP < 0.01, ^cP < 0.001, and ^dP < 0.0001; HP(+) group vs H. pylori-negative group: ^eP < 0.05, ^fP < 0.01, and ^gP < 0.0001; B: Receiver operating characteristic curve analysis of seven identified biomarkers. Helicobacter pylori-positive; HP(−): Helicobacter pylori-negative.

Figure 6

The metabolite-reaction-enzyme-gene networks of the key metabolites and targets. The hexagons, diamonds, rounded rectangles, and circles represent the metabolites, reactions, metabolic enzymes, and regulatory genes of metabolic enzymes, respectively. The differential metabolites and differential metabolite-related metabolites are shown as dark and bright red hexagons, respectively. The yellow circles represent the potential proteins involved in the regulation of the identified differential metabolites in Helicobacter pylori-positive chronic gastritis.