Zhu Guizhen, Luo Yuan, Su Nan, Zheng Xiangyi, Mei Zhusong, Ye Qiao, Peng Jie, An Peiyu, Song Yangqian, Luo Weina, Li Hongxia, Wang Guangyun, Zhang Haitao
Laboratory of Clinical Medicine, Air Force Medical Center, Air Force Medical University, People's Liberation Army of China, Beijing 100142, China.
Military Medical Center, Air Force Medical Center, Air Force Medical University, People's Liberation Army of China, Beijing 100142, China.
Metabolites. 2025 Aug 29;15(9):580. doi: 10.3390/metabo15090580.
Gout, a complex metabolic disorder of increasing global incidence, remains incompletely understood in its pathogenesis. Current diagnostic approaches exhibit significant limitations, including insufficient specificity and the requirement for invasive joint aspiration, highlighting the need for non-invasive, sensitive biomarkers for early detection. Urine metabolites were extracted from 28 healthy controls, 13 asymptomatic hyperuricemia (HUA) patients, and 29 acute gouty arthritis (AGA) patients. The extracted metabolites were analyzed by UHPLC-MS/MS for untargeted metabolomics. Differential metabolites were screened by partial least squares discriminant analysis (PLS-DA) and volcano plot analysis. Pathway analysis determined the core disorder pathway of gout progression. A total of 278 differential metabolites associated with gout progression were identified. The most pronounced metabolic alterations were observed between the AGA and control groups, indicative of substantial metabolic reprogramming during disease transition. Metabolic pathway analysis revealed four significantly dysregulated pathways: histidine metabolism, nicotinate and nicotinamide metabolism, phenylalanine metabolism, and tyrosine metabolism. Receiver operating characteristic (ROC) curve analysis revealed that three urine markers with high diagnostic efficacy-oxoamide, 3-methylindole, and palmitic acid-exhibited progressive alterations across the disease continuum. This metabolomics study identified core regulatory metabolites and newly discovered metabolic pathways underlying gout pathogenesis, along with novel urinary biomarkers capable of predicting HUA-to-AGA progression. The aberrant levels of key metabolites in the disordered pathway implicate neuroimmune dysregulation, energy metabolism disruption, and oxidative stress in gout pathogenesis. These findings provide new foundations and strategies for the daily monitoring and prevention of gout.
痛风是一种全球发病率不断上升的复杂代谢紊乱疾病,其发病机制仍未完全明确。目前的诊断方法存在显著局限性,包括特异性不足以及需要进行侵入性关节穿刺,这凸显了对用于早期检测的非侵入性、敏感生物标志物的需求。从28名健康对照者、13名无症状高尿酸血症(HUA)患者和29名急性痛风性关节炎(AGA)患者中提取尿液代谢物。提取的代谢物通过超高效液相色谱-串联质谱(UHPLC-MS/MS)进行非靶向代谢组学分析。通过偏最小二乘判别分析(PLS-DA)和火山图分析筛选差异代谢物。通路分析确定了痛风进展的核心紊乱通路。共鉴定出278种与痛风进展相关的差异代谢物。在AGA组和对照组之间观察到最明显的代谢改变,表明在疾病转变过程中存在大量代谢重编程。代谢通路分析揭示了四条显著失调的通路:组氨酸代谢、烟酸和烟酰胺代谢、苯丙氨酸代谢和酪氨酸代谢。受试者工作特征(ROC)曲线分析显示,三种具有高诊断效能的尿液标志物——草酰胺、3-甲基吲哚和棕榈酸——在整个疾病连续体中呈现出渐进性变化。这项代谢组学研究确定了痛风发病机制的核心调节代谢物和新发现的代谢通路,以及能够预测HUA向AGA进展的新型尿液生物标志物。紊乱通路中关键代谢物的异常水平表明痛风发病机制中存在神经免疫失调、能量代谢紊乱和氧化应激。这些发现为痛风的日常监测和预防提供了新的基础和策略。