Dong Lingqiu, Tan Jiaxing, Zhong Zhengxia, Tang Yi, Qin Wei
Department of Nephrology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Division of Nephrology, Department of Medicine, Affiliated Hospital of Zunyi Medical College, Zunyi, Guizhou, China.
Clin Chim Acta. 2023 Sep 1;549:117561. doi: 10.1016/j.cca.2023.117561. Epub 2023 Sep 16.
We investigated alterations in the serum metabolomic profile of IgA nephropathy (IgAN) patients and screen biomarkers of IgA nephropathy based on ultra-performance liquid chromatography-mass spectrometry (UPLC-MS).
Serum samples from 65 IgAN patients and 31 healthy controls were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Univariate and multivariate analysis were performed to screen the differential metabolites. Differential metabolites should meet both the following two criteria: adjusted P < 0.05 in the univariate analysis and VIP value > 1 in the multivariate model. Pathway analysis was performed to reveal the metabolic pathways that were significantly influenced in IgAN. Spearman correlation analysis was applied to explore the correlation between metabolites and between the metabolites and clinicopathological features of IgAN. A random forest model and Logistics regression analysis were conducted to evaluate the predictive ability of the metabolites.
The metabolic profile was significantly altered in IgAN patients compared with healthy controls. Thirty-nine metabolites were identified, including glycerophospholipids, sphingolipids, vitamin K1, vitamin K2, bile acids and amino acids. Sphingolipid metabolism, ubiquinone and other terpenoid-quinone biosynthesis, and glycerophospholipid metabolism were found to be significantly disturbed in the pathway analysis. Differential metabolites were found to be associated with the clinical and pathological features of IgAN patients. Lanosterol, vitamin K1, vitamin K2, and β-elemonic acid were found to have promising predictive ability for IgAN.
We confirmed the differences in the metabolic profiles of IgAN patients and healthy controls and identified the differential metabolites of IgAN, which may help with the further exploration of the pathogenesis and treatment of IgAN.
我们基于超高效液相色谱-质谱联用技术（UPLC-MS）研究了IgA肾病（IgAN）患者血清代谢组学谱的变化，并筛选IgA肾病的生物标志物。
采用超高效液相色谱-质谱联用技术（UPLC-MS）分析65例IgAN患者和31例健康对照者的血清样本。进行单变量和多变量分析以筛选差异代谢物。差异代谢物应同时满足以下两个标准：单变量分析中校正P<0.05且多变量模型中VIP值>1。进行通路分析以揭示IgAN中受到显著影响的代谢通路。应用Spearman相关性分析来探索代谢物之间以及代谢物与IgAN临床病理特征之间的相关性。进行随机森林模型和逻辑回归分析以评估代谢物的预测能力。
与健康对照相比，IgAN患者的代谢谱有显著改变。鉴定出39种代谢物，包括甘油磷脂、鞘脂、维生素K1、维生素K2、胆汁酸和氨基酸。在通路分析中发现鞘脂代谢、泛醌和其他萜类醌生物合成以及甘油磷脂代谢受到显著干扰。发现差异代谢物与IgAN患者的临床和病理特征相关。发现羊毛甾醇、维生素K1、维生素K2和β-榄香烯酸对IgAN具有良好的预测能力。
我们证实了IgAN患者与健康对照者代谢谱的差异，并鉴定出IgAN的差异代谢物，这可能有助于进一步探索IgAN的发病机制和治疗方法。
