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Abstract：
To investigate the systemic metabolic effects of SARS-CoV-2 infection, we analyzed 1H NMR spectroscopic data on human blood plasma and co-modeled with multiple plasma cytokines and chemokines (measured in parallel). Thus, 600 MHz 1H solvent-suppressed single-pulse, spin-echo, and 2D J-resolved spectra were collected on plasma recorded from SARS-CoV-2 rRT-PCR-positive patients (n = 15, with multiple sampling timepoints) and age-matched healthy controls (n = 34, confirmed rRT-PCR negative), together with patients with COVID-19/influenza-like clinical symptoms who tested SARS-CoV-2 negative (n = 35). We compared the single-pulse NMR spectral data with in vitro diagnostic research (IVDr) information on quantitative lipoprotein profiles (112 parameters) extracted from the raw 1D NMR data. All NMR methods gave highly significant discrimination of SARS-CoV-2 positive patients from controls and SARS-CoV-2 negative patients with individual NMR methods, giving different diagnostic information windows on disease-induced phenoconversion. Longitudinal trajectory analysis in selected patients indicated that metabolic recovery was incomplete in individuals without detectable virus in the recovery phase. We observed four plasma cytokine clusters that expressed complex differential statistical relationships with multiple lipoproteins and metabolites. These included the following: cluster 1, comprising MIP-1β, SDF-1α, IL-22, and IL-1α, which correlated with multiple increased LDL and VLDL subfractions; cluster 2, including IL-10 and IL-17A, which was only weakly linked to the lipoprotein profile; cluster 3, which included IL-8 and MCP-1 and were inversely correlated with multiple lipoproteins. IL-18, IL-6, and IFN-γ together with IP-10 and RANTES exhibited strong positive correlations with LDL1-4 subfractions and negative correlations with multiple HDL subfractions. Collectively, these data show a distinct pattern indicative of a multilevel cellular immune response to SARS CoV-2 infection interacting with the plasma lipoproteome giving a strong and characteristic immunometabolic phenotype of the disease. We observed that some patients in the respiratory recovery phase and testing virus-free were still metabolically highly abnormal, which indicates a new role for these technologies in assessing full systemic recovery.
摘要：
探讨SARS-CoV-2感染的全身代谢效应,我们分析了人血浆的1HNMR光谱数据,并与多种血浆细胞因子和趋化因子共同建模(平行测量).因此，600MHz1H溶剂抑制单脉冲，自旋回波,收集SARS-CoV-2rRT-PCR阳性患者（n=15，多个采样时间点）和年龄匹配的健康对照（n=34，确认rRT-PCR阴性）的血浆的2DJ分辨光谱，以及SARS-CoV-2检测阴性的COVID-19/流感样临床症状患者(n=35)。我们将单脉冲NMR光谱数据与从原始1DNMR数据中提取的定量脂蛋白谱（112个参数）的体外诊断研究（IVDr）信息进行了比较。所有NMR方法均可对SARS-CoV-2阳性患者与对照组和SARS-CoV-2阴性患者进行高度区分。对疾病诱导的表型转化提供不同的诊断信息窗口。选定患者的纵向轨迹分析表明，在恢复期没有检测到病毒的个体中，代谢恢复不完全。我们观察到四个血浆细胞因子簇，它们与多种脂蛋白和代谢物表达了复杂的差异统计关系。这些包括以下内容：簇1，包括MIP-1β，SDF-1α,IL-22和IL-1α，与多个LDL和VLDL亚组分增加相关；第2组，包括IL-10和IL-17A，仅与脂蛋白谱弱相关；簇3，包括IL-8和MCP-1，与多种脂蛋白成反比。IL-18，IL-6和IFN-γ与IP-10和RANTES一起与LDL1-4亚组分呈强正相关，与多个HDL亚组分呈负相关。总的来说，这些数据显示了一种独特的模式，表明对SARSCoV-2感染的多水平细胞免疫应答与血浆脂蛋白组相互作用，从而为该疾病提供了强烈和特征性的免疫代谢表型。我们观察到一些处于呼吸恢复期和检测无病毒的患者在代谢上仍然高度异常，这表明这些技术在评估全面系统恢复方面的新作用。
