Liquid chromatography-tandem mass spectrometry technology revealed differences in serum metabolites between rheumatoid arthritis patients in different seasons

Objective: Using liquid chromatography-tandem mass spectrometry (LC-MS/MS) technology, we investigated differences in serum metabolites among rheumatoid arthritis (RA) patients in different seasons. Methods: Serum samples were collected from 60 patients meeting the diagnostic criteria for RA and divided into four groups based on different seasons. Metabolites in the serum samples were analyzed using a liquid chromatography-mass spectrometry (LC-MS) system comprising the Waters ACQUITY UPLC I-Class plus/Thermo QE plus ultra-high-performance liquid chromatography and high-resolution mass spectrometry instruments. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify seasonally differential metabolites and investigate their metabolic pathways and enrichment patterns. Results: A total of 3,787 metabolites were detected in serum, with the majority of differentially expressed metabolites classified as "Lipids and Lipid-Like Molecules." Metabolites in the serum of RA patients across the four seasons exhibited varying degrees of differences. The significantly different metabolites identified between groups were 223 (C1_vs_C2), 977 (C1_vs _C3), and 778 (C1_vs_C4), with 62 common different metabolites among them. These differential metabolites were primarily found in the "Lipids and Lipid-Like Molecules" and "Organic acids and derivatives" categories. We also identified key differentially expressed metabolites. C1_vs_C2 includes Behenic acid (d3), Stizolamine, and Cyanidin 7-arabinoside; C1_vs_C3 includes Phosphatidylinositol-3,4,5-trisphosphate, N-Docosahexaenoyl Threonine, and Alginic acid; C1_vs_C4 includes 9,10-DiHOME, Perfluorotridecanoic acid, and 3,4-Dehydro-gamma,chi-carotene. KEGG metabolic pathway enrichment analysis showed that the differential metabolites were enriched in metabolic pathways such as Carbohydrate metabolism and Lipid metabolism. Conclusion: This study elucidates the regulatory role of seasonal factors in serum metabolic profiles of RA patients. The identified seasonally variable metabolites may provide potential reference points for seasonal monitoring of RA and optimization of personalized treatment regimens, opening new metabolomics perspectives for disease diagnosis and management.