Rheumatoid arthritis (RA) is a systemic autoimmune disease dominated by chronic inflammatory lesions of peripheral synovial joints. Growing evidence suggests that abnormal lipid metabolism levels contribute to the progression of RA. Although several metabolomics studies have shown abnormality in the RA lipidome, the relationship between the overall lipid metabolites and RA has not been systematically evaluated. In this study, an untargeted lipidomics method based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the serum and urine lipidomes of adjuvant-induced arthritis rats to study the characteristics of lipid metabolism changes in the rats and search lipid markers for diagnosing RA. By combining with orthogonal partial least squares discriminant analysis, a total of 52 potential lipid markers were identified, mainly involved in sphingolipid metabolism, glycerophospholipid metabolism, sterol lipid metabolism, glycerolipid metabolism and fatty acid metabolism, which provided crucial insight into lipid metabolism disturbances in RA. Further receiver operating characteristic analysis revealed that the areas under the curve of PC(22:4/16:0), PI(18:1/16:0) and LacCer(d18:1/12:0) from serum and 25-hydroxycholesterol from urine were 0.94, 1.00, 1.00 and 1.00, respectively, indicating the high predictive ability of this method for RA. In this study, our results indicated that a combination of serum and urine analysis can provide a more comprehensive and reliable assessment of RA, and a UPLC-MS-based lipidomics strategy is a powerful tool to search for potential lipid markers associated with RA and explore the pathogenesis of RA.
Keywords: UPLC-MS; adjuvant-induced arthritis; lipidomics; rheumatoid arthritis; serum; urine.
© 2023 John Wiley & Sons Ltd.