期刊
JOURNAL OF PROTEOME RESEARCH
卷 20, 期 2, 页码 1382-1396出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00876
关键词
plasma; COVID-19; SARS-CoV-2; NMR spectroscopy; single-pulse; spin-echo; IVDr; metabolic phenotyping; biomarkers; diagnostic modeling; lipoproteins
资金
- Spinnaker Health Foundation, WA
- McCusker Foundation, WA
- Western Australian State Government
- MRFF
- UK MRC
- Department of Jobs, Tourism, Science and Innovation, Government of Western Australian Premier's Fellowship
- ARC Laureate Fellowship
The study investigated the systemic metabolic effects of SARS-CoV-2 infection by analyzing H-1 NMR spectroscopic data on human blood plasma. The findings revealed that some patients in the respiratory recovery phase, with no detectable virus, still exhibited highly abnormal metabolism, indicating a new role for these technologies in assessing full systemic recovery.
To investigate the systemic metabolic effects of SARS-CoV-2 infection, we analyzed H-1 NMR spectroscopic data on human blood plasma and co-modeled with multiple plasma cytokines and chemokines (measured in parallel). Thus, 600 MHz H-1 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-1 beta, SDF-1 alpha, IL22, and IL-1 alpha, 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-gamma 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.
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