THU0405 SERUM METABOLIC PROFILING ANALYSIS OF GOUT PATIENTS BASED ON UHPLC-Q-TOF/MS

Background: Gout is a common kind of inflammatory arthritis with metabolic disorders. The detailed pathogenesis of gout remains largely unknown. Metabolomics has become an important tool in detecting the new pathogenesis and biomarkers. However, few studies have focused on the serum metabolic profiling of gout. Objectives: The study aims to investigate the metabolic profiling of gout patients with ultra-performance liquid chromatograph quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), and explore the potential pathological mechanisms and biomarkers. Methods: Serum samples from 31 gout patients and 31 healthy controls were analyzed by UPLC-Q-TOF-MS. Principal components analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA) and Hierarchical clustering analysis were performed to detect different compounds between the two groups. Receiver operating characteristic (ROC) curve analysis and pathway analysis of the different metabolites were conducted. Results: A total of 9192 compounds were detected, of which 138 significantly different compounds were selected, according to the criteria of (Variable importance in projection (VIP)>3, P <0.05). Eventually, 96 reliable metabolites matched the HMDB database were confirmed. ROC curve results showed that the area under the curve (AUC) value of 4-hydroxytriazolam for gout was 0.933 (CI95%: 0.875-0.992), yielding a highest AUC value, with the sensitivity of 83.9% and specificity of 93.5%. The pathway analysis results indicated that the significantly different metabolites were mainly involved in “primary bile acid biosynthesis”, “purine metabolism” and “glycerophospholipid metabolism”. Conclusion: The serum metabolic profiling in gout patients were significantly different from healthy subjects. 4-hydroxytriazolam was the potential biomarkers. Primary bile acid biosynthesis may be a novel metabolic pathway of gout. References: [1]Banoei MM, et al. Metabolomics and Biomarker Discovery in Traumatic Brain Injury. J Neurotrauma, 2018. 35(16): p. 1831-1848. Disclosure of Interests: : None declared