A study on the screening of potential biomarkers for rheumatoid arthritis based on nontarget metabolomics.

Abstract

To explore changes in blood metabolites with rheumatoid arthritis (RA) using non-targeted metabolomics techniques, to identify potential metabolic biomarkers in RA patients. Twenty patients with rheumatoid arthritis (RA group) who attended the Sichuan Province Orthopaedic Hospital between July and December 2023 were recruited, and twenty healthy controls were included. Serum candidate metabolites were analysed using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Variable Importance in Projection (VIP) value > 1 and p 0.8 as a criterion, four potential biomarkers for RA were identified, including PE(22:0/15:0) (AUC = 0.8333, 95% CI: 0.6244-1), PE-NMe(18:4(6Z,9Z,12Z,15Z)/18:4(6Z,9Z,12Z,15Z))(AUC = 0.9722, 95% CI: 0.6571-1), Sphinganine (AUC = 0.9167, 95% CI: 0.7143-1), GPEtn(16:1/22:4)(AUC = 0.8889, 95% CI: 0.7429-1). The AUC for the combined diagnosis of RA using the four differentially expressed candidate metabolites was 0.961 (95% CI: 0.9463-0.9757). Glycerophospholipid metabolism was the most significantly altered pathway in RA, according to pathway enrichment analysis. Our research identified four potential biomarkers: PE(22:0/15:0), PE-NMe(18:4(6Z,9Z,12Z,15Z)/18:4(6Z,9Z,12Z,15Z)), Sphinganine, and GPEtn(16:1/22:4). Glycerophospholipid metabolism may be involved in RA. This study was entirely exploratory research and framed as hypothesis-generating only, which will require further validation in subsequent research.

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