Longitudinal Metabolomics Reveals Ornithine Cycle Dysregulation Correlates With Inflammation and Coagulation in COVID-19 Severe Patients.
Longitudinal Metabolomics Reveals Ornithine Cycle Dysregulation Correlates With Inflammation and Coagulation in COVID-19 Severe Patients.
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纵向代谢组学揭示鸟氨酸循环失调与 COVID-19 重症患者的炎症和凝血相关
DOI：
10.3389/fmicb.2021.723818
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发表时间：
2021
影响因子：
5.2
通讯作者：
Wang H
中科院分区：
文献类型：
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作者：
Li T;Ning N;Li B;Luo D;Qin E;Yu W;Wang J;Yang G;Nan N;He Z;Yang N;Gong S;Li J;Liu A;Sun Y;Li Z;Jia T;Gao J;Zhang W;Huang Y;Hou J;Xue Y;Li D;Wei Z;Zhang L;Li B;Wang H
新冠肺炎是一种严重的人类疾病，当前的全球大流行突显了这一点。几项关于新冠肺炎患者代谢组的研究揭示了代谢紊乱和疾病进展过程中的一些潜在诊断标志物。然而，新冠肺炎患者代谢组学的纵向变化，特别是与疾病进展的关系仍不清楚。在这里，我们系统地分析了新冠肺炎患者血清代谢物的动态变化，发现大多数代谢物在出院前1-3天仍未恢复。新冠肺炎患者的显著特征是由氨基酸、肽和类似物组成的代谢物，涉及9种必需氨基酸、10种二肽和4种N-乙酰化氨基酸。重型患者氨基酸代谢中的12种代谢物，尤其是鸟氨酸周期的3种代谢物水平明显高于轻型者，主要发生在发病后1~3天或4~6天。结合血液代谢学、生化和细胞因子数据，我们发现了一个高度相关的网络，包括6种细胞因子、13个生化参数和49种代谢物。值得注意的是，5种与鸟氨酸循环相关的代谢物(鸟氨酸、N-乙酰鸟氨酸、3-氨基-2-哌啶酮、天冬氨酸和天冬氨酸)与“细胞因子风暴”和凝血指数高度相关。我们发现重症患者的鸟氨酸循环紊乱与炎症和凝血状态密切相关，这可能是新冠肺炎致病的一个潜在机制。本研究为详细探讨新冠肺炎患者的代谢因素，指导代谢恢复，了解其致病机制，开发抗SARS-CoV-2感染的药物提供了有价值的资源。
COVID-19 is a severe disease in humans, as highlighted by the current global pandemic. Several studies about the metabolome of COVID-19 patients have revealed metabolic disorders and some potential diagnostic markers during disease progression. However, the longitudinal changes of metabolomics in COVID-19 patients, especially their association with disease progression, are still unclear. Here, we systematically analyzed the dynamic changes of the serum metabolome of COVID-19 patients, demonstrating that most of the metabolites did not recover by 1–3 days before discharge. A prominent signature in COVID-19 patients comprised metabolites of amino acids, peptides, and analogs, involving nine essential amino acids, 10 dipeptides, and four N-acetylated amino acids. The levels of 12 metabolites in amino acid metabolism, especially three metabolites of the ornithine cycle, were significantly higher in severe patients than in mild ones, mainly on days 1–3 or 4–6 since onset. Integrating blood metabolomic, biochemical, and cytokine data, we uncovered a highly correlated network, including 6 cytokines, 13 biochemical parameters, and 49 metabolites. Significantly, five ornithine cycle-related metabolites (ornithine, N-acetylornithine, 3-amino-2-piperidone, aspartic acid, and asparagine) highly correlated with “cytokine storms” and coagulation index. We discovered that the ornithine cycle dysregulation significantly correlated with inflammation and coagulation in severe patients, which may be a potential mechanism of COVID-19 pathogenicity. Our study provided a valuable resource for detailed exploration of metabolic factors in COVID-19 patients, guiding metabolic recovery, understanding the pathogenic mechanisms, and creating drugs against SARS-CoV-2 infection.