Developing A Baseline Metabolomic Signature Associated with COVID-19 Severity: Insights from Prospective Trials Encompassing 13 U.S. Centers.
Developing A Baseline Metabolomic Signature Associated with COVID-19 Severity: Insights from Prospective Trials Encompassing 13 U.S. Centers.
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DOI：
10.3390/metabo13111107
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发表时间：
2023-10-24
期刊：
影响因子：
4.1
通讯作者：
Safo SE
中科院分区：
文献类型：
--
作者：
Yang K;Kang Z;Guan W;Lotfi-Emran S;Mayer ZJ;Guerrero CR;Steffen BT;Puskarich MA;Tignanelli CJ;Lusczek E;Safo SE
代谢性疾病是COVID-19严重感染的重要危险因素，但其影响途径尚未完全阐明。使用来自13个美国学术中心的两项随机对照试验的数据，我们的目标是表征预测严重COVID-19的代谢特征，并定义新的基线代谢组学特征。根据WHO的顺序量表，将133名患者分为轻度或中度/重度COVID-19疾病。使用Biocrates平台分析血液样本，提供630种目标代谢物进行分析。重新采样技术和机器学习模型用于确定与严重疾病相关的代谢组学特征。独创性途径分析（Ingenuity Pathway Analysis， IPA）用于功能富集分析。为了帮助临床决策，我们创建了低相关分子的基线代谢组学特征。多变量逻辑回归模型拟合将这些特征与训练数据上的严重疾病相关联。以溶血磷脂酰胆碱A C17:0、二氢神经酰胺（d18:0/24:1）和甘油三酯（20:43 - 36:4）为3种代谢物，鉴定效果最佳，平均AUROC为0.978，F1分数为0.942。IPA分析显示，氨基酸相关通路显著富集，有丝分裂原激活的蛋白激酶激酶5 （MAP2K5）在两组之间存在差异激活。总之，与脂质代谢相关的代谢物可以有效地区分轻度与中度/重度疾病。SDMA和GABA也显示了区分这两组的潜力。有丝分裂原激活的蛋白激酶激酶5 （MAP2K5）调节因子在两组之间的激活存在差异，这表明进一步研究可能是一种潜在的治疗途径。
Metabolic disease is a significant risk factor for severe COVID-19 infection, but the contributing pathways are not yet fully elucidated. Using data from two randomized controlled trials across 13 U.S. academic centers, our goal was to characterize metabolic features that predict severe COVID-19 and define a novel baseline metabolomic signature. Individuals (n = 133) were dichotomized as having mild or moderate/severe COVID-19 disease based on the WHO ordinal scale. Blood samples were analyzed using the Biocrates platform, providing 630 targeted metabolites for analysis. Resampling techniques and machine learning models were used to determine metabolomic features associated with severe disease. Ingenuity Pathway Analysis (IPA) was used for functional enrichment analysis. To aid in clinical decision making, we created baseline metabolomics signatures of low-correlated molecules. Multivariable logistic regression models were fit to associate these signatures with severe disease on training data. A three-metabolite signature, lysophosphatidylcholine a C17:0, dihydroceramide (d18:0/24:1), and triacylglyceride (20:4_36:4), resulted in the best discrimination performance with an average test AUROC of 0.978 and F1 score of 0.942. Pathways related to amino acids were significantly enriched from the IPA analyses, and the mitogen-activated protein kinase kinase 5 (MAP2K5) was differentially activated between groups. In conclusion, metabolites related to lipid metabolism efficiently discriminated between mild vs. moderate/severe disease. SDMA and GABA demonstrated the potential to discriminate between these two groups as well. The mitogen-activated protein kinase kinase 5 (MAP2K5) regulator is differentially activated between groups, suggesting further investigation as a potential therapeutic pathway.
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