Metabolomics Markers of COVID-19 Are Dependent on Collection Wave.
Metabolomics Markers of COVID-19 Are Dependent on Collection Wave.
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DOI：
10.3390/metabo12080713
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发表时间：
2022-07-30
期刊：
影响因子：
4.1
通讯作者：
中科院分区：
文献类型：
--
作者：
COVID-19感染对人体代谢组的影响已被广泛报道，但迄今为止，所有此类研究都集中在单波感染上。COVID-19已经产生了许多具有不同临床表现的疾病波，因此，探索代谢紊乱是否相应变化，以更好地了解其对宿主代谢的影响并实现更好的治疗是相关的。这项工作使用靶向代谢组学平台（Biocrates Life Sciences）分析了164名住院患者的血清，其中123名患者在两波感染中确认为COVID-19 RT-PCR检测阳性，41名患者提供阴性检测。7名COVID-19阳性患者也提供了感染后2-7个月的纵向样本。阳性和阴性患者的代谢物和脂质的变化被发现依赖于收集波。机器学习模型确定了在两波感染中诊断阳性患者的六种代谢物：TG（22：1_32：5），TG（18：0_36：3），谷氨酸（Glu），乙醇石胆酸（GLCA），天冬氨酸（Asp）和甲硫氨酸亚砜（Met-SO），准确率为91%。虽然一些代谢产物（TG（18：0_36：3）和Asp）在感染后恢复正常，但在纵向样品中谷氨酸仍然失调。这项工作首次表明，代谢失调在大流行过程中发生了部分变化，反映了变异、临床表现和治疗方案的变化。它还表明，一些代谢变化在不同的波中是稳健的，这些变化可以将COVID-19阳性个体与医院环境中的对照个体区分开来。这项研究也支持了一种假设，即一些代谢途径在COVID-19感染后几个月被破坏。
The effect of COVID-19 infection on the human metabolome has been widely reported, but to date all such studies have focused on a single wave of infection. COVID-19 has generated numerous waves of disease with different clinical presentations, and therefore it is pertinent to explore whether metabolic disturbance changes accordingly, to gain a better understanding of its impact on host metabolism and enable better treatments. This work used a targeted metabolomics platform (Biocrates Life Sciences) to analyze the serum of 164 hospitalized patients, 123 with confirmed positive COVID-19 RT-PCR tests and 41 providing negative tests, across two waves of infection. Seven COVID-19-positive patients also provided longitudinal samples 2–7 months after infection. Changes to metabolites and lipids between positive and negative patients were found to be dependent on collection wave. A machine learning model identified six metabolites that were robust in diagnosing positive patients across both waves of infection: TG (22:1_32:5), TG (18:0_36:3), glutamic acid (Glu), glycolithocholic acid (GLCA), aspartic acid (Asp) and methionine sulfoxide (Met-SO), with an accuracy of 91%. Although some metabolites (TG (18:0_36:3) and Asp) returned to normal after infection, glutamic acid was still dysregulated in the longitudinal samples. This work demonstrates, for the first time, that metabolic dysregulation has partially changed over the course of the pandemic, reflecting changes in variants, clinical presentation and treatment regimes. It also shows that some metabolic changes are robust across waves, and these can differentiate COVID-19-positive individuals from controls in a hospital setting. This research also supports the hypothesis that some metabolic pathways are disrupted several months after COVID-19 infection.
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影响因子：
24.5
作者：
Ren Z;Wang H;Cui G;Lu H;Wang L;Luo H;Chen X;Ren H;Sun R;Liu W;Liu X;Liu C;Li A;Wang X;Rao B;Yuan C;Zhang H;Sun J;Chen X;Li B;Hu C;Wu Z;Yu Z;Kan Q;Li L
通讯作者：
Li L
影响因子：
4.4
作者：
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通讯作者：
Nicholson, Jeremy K.
影响因子：
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作者：
Asvold, Bjorn O.;Grill, Valdemar;Bjorgaas, Marit R.
通讯作者：
Bjorgaas, Marit R.
影响因子：
1.6
作者：
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通讯作者：
Niu, Junqi
影响因子：
6.1
作者：
Galvao, RKH;Araujo, MCU;Saldanha, TCB
通讯作者：
Saldanha, TCB