Integrative metabolomics and genomics analysis reveals chronic gastritis associated metabolites

Metabolomics plays a crucial role in understanding disease mechanisms by identifying biomarkers that reflect biochemical alterations. In chronic gastritis (CG), these metabolic shifts may serve as key contributors, and their investigation could offer profound insights into the underlying mechanisms of the disease's pathogenesis. We conducted a study with genomic and metabolomic profiling of Han Chinese participants from the Zhejiang Metabolic Syndrome Cohort in Zhoushan, Zhejiang, China. Using liquid chromatography-mass spectrometry, we measured 1912 serum metabolites. Logistic regression analysis was performed to identify metabolites associated with CG. Additionally, we conducted a genome-wide association study to explore genetic determinants of these metabolites, and then applied genetic-based association test to examine the potential causal effects of metabolites on CG, using CG-related genome-wide association study summary statistics from a publicly available database. After adjusting for covariates, we identified 103 metabolites significantly associated with CG. Genetic-based analysis (by both the regular inverse variance weighting and weak instrument robust approach Mendelian randomization robust adjusted profile scoring) revealed 54 genetically predicted metabolites that were found to be associated with CG. Consistent results were observed for both kynurenic acid (has a role in anti-inflammation) and (±)12-hydroxyeicosatetraenoic acid, which exhibited negative associations with CG in both cross-sectional and genetically informed analyses. This study highlights the metabolomic characteristics of CG and provides valuable insights into its potential pathophysiological mechanisms.