Lipidomics coupled with pathway analysis characterizes serum metabolic changes in response to potassium oxonate induced hyperuricemic rats

BACKGROUND: Hyperuricemia as a metabolic disease is usually associated with lipid metabolic disorder. The purpose of this study is to identify potential lipid biomarkers and provide the evidence for the relationship between hyperuricemia and lipid-related diseases. METHODS: Lipidomics-a specialized study of lipid metabolites-has become a highly sensitive and powerful tool for biomarker discovery. In this work, an ultra-performance liquid chromatography-quadruole-time-of-flight tandem mass spectrometry (UPLC-Q-TOF/MS)-based on Lipidomics approach was employed to investigate serum samples from potassium oxonate-treated rats to find potential biomarkers. Principal component analysis (PCA) was used to analyze the MS data to assess the establishment of hyperuricemia model. Orthogonal partial least-squares discriminant analysis (OPLS-DA) in combination with independent samples t-test was performed for biomarker selection and identification. RESULTS: Thirteen potential biomarkers in rat serum were identified in the screen, and two abnormal metabolism pathways were found, namely glycerolphospholipid metabolism and glycosylphosphatidylinositol-anchored protein biosynthesis. CONCLUSIONS: In this work, the Lipidomics approach based on UPLC-Q-TOF/MS was employed to investigate serum metabolic changes in the rat model, 13 potential biomarkers related to hyperuricemia were identified, primarily involved in glycerolphospholipid metabolism and glycosylphosphatidylinositol-anchored protein biosynthesis. Abnormal glycerophospholipid metabolism pathway may be associated with lipid metabolism disorder caused by hyperuricemia, while the relationship between hyperuricemia and glycosylphosphatidylinositol-anchored protein biosynthesis needs further study.