TY - JOUR
T1 - NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines
AU - Lodge, Samantha
AU - Nitschke, Philipp
AU - Kimhofer, Torben
AU - Coudert, Jerome D.
AU - Begum, Sofina
AU - Bong, Sze How
AU - Richards, Toby
AU - Edgar, Dale
AU - Raby, Edward
AU - Spraul, Manfred
AU - Schaefer, Hartmut
AU - Lindon, John C.
AU - Loo, Ruey Leng
AU - Holmes, Elaine
AU - Nicholson, Jeremy K.
N1 - Funding Information:
We thank the Spinnaker Health Foundation, WA, The McCusker Foundation, WA, the Western Australian State Government, and the MRFF for funding the Australian National Phenome Centre for this and related work. We thank the UK MRC for funding (S.B.), and the Department of Jobs, Tourism, Science and Innovation, Government of Western Australian Premier’s Fellowship for funding R.-L.L. and E.H.; and ARC Laureate Fellowship funding for E.H. We would also like to acknowledge the Western Australian COVID Research Response team ( https://research-au.net/covid-research-response/ ), Giuliana D’Aulerio, Kelly Beer, Rolee Kumar, Doug Robb, Joseph Miocevich, Dominic Mallon, Michael Epis, Merrilee Needham, Daniel Fatovich, Aron Chakera, Thomas Gilbert, Nathanael Foo, @STRIVE WA, Candice Peel, Sheeraz Mohd, and Ali Alishum for the coordination, sampling, and biobanking of patient samples and clinical metadata. We would also like to acknowledge Darren McKee and David Morrison for support in the establishment of infrastructure for cytokine analysis. We would like to thank Anuradha Sooda and Emily McLeish for their technical assistance with cytokine analysis. a
Publisher Copyright:
© 2021 The Authors. Published by American Chemical Society.
PY - 2021/2/5
Y1 - 2021/2/5
N2 - 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-γtogether 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.
AB - 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-γtogether 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.
KW - biomarkers
KW - COVID-19
KW - diagnostic modeling
KW - IVDr
KW - lipoproteins
KW - metabolic phenotyping
KW - NMR spectroscopy
KW - plasma
KW - SARS-CoV-2
KW - single-pulse
KW - spin-echo
UR - http://www.scopus.com/inward/record.url?scp=85100051439&partnerID=8YFLogxK
U2 - 10.1021/acs.jproteome.0c00876
DO - 10.1021/acs.jproteome.0c00876
M3 - Article
C2 - 33426894
AN - SCOPUS:85100051439
SN - 1535-3893
VL - 20
SP - 1382
EP - 1396
JO - Journal of Proteome Research
JF - Journal of Proteome Research
IS - 2
ER -