Integrative modelling of quantitative plasma lipoprotein, metabolic and amino acid data reveals a multi-organ pathological signature of SARS-CoV-2 infection

File Description SizeFormat 
COVID-19JPRpreproof.pdfAccepted version3.36 MBAdobe PDFView/Open
Title: Integrative modelling of quantitative plasma lipoprotein, metabolic and amino acid data reveals a multi-organ pathological signature of SARS-CoV-2 infection
Authors: Kimhofer, T
Lodge, S
Whiley, L
Gray, N
Loo, RL
Lawler, NG
Nitschke, P
Bong, S-H
Morrison, DL
Begum, S
Richards, T
Yeap, BB
Smith, C
Smith, KCG
Holmes, E
Nicholson, JK
Item Type: Journal Article
Abstract: The metabolic effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on human blood plasma were characterized using multi-platform metabolic phenotyping with Nuclear Magnetic Resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Quantitative measurements of lipoprotein sub-fractions, alpha-1-acid glycoprotein, glucose and biogenic amines were made on samples from symptomatic coronavirus disease 19 (COVID-19) patients who had tested positive for the SARS-CoV-2 virus (n = 17) and from age and gender-matched controls (n = 25). Data were analyzed using an orthogonal-projections to latent structures (O-PLS) method and used to construct an exceptionally strong (AUROC=1) hybrid NMR-MS model that enabled detailed metabolic discrimination between the groups and their biochemical relationships. Key discriminant metabolites included markers of inflammation including elevated alpha-1 acid glycoprotein and an increased kynurenine/tryptophan ratio. There was also an abnormal lipoprotein, glucose and amino acid signature consistent with diabetes and coronary artery disease (low total and HDL Apolipoprotein A1, low HDL triglycerides, high LDL and VLDL triglycerides). Plus, multiple highly significant amino acid markers of liver dysfunction (including the elevated glutamine/glutamate and Fischer’s ratios) that present themselves as part of a distinct SARS-CoV-2 infection pattern. A multivariate training-test set model was validated using independent samples from additional SARS-CoV-2 positive patients and controls. The predictive model showed a sensitivity of 100% for SARS-CoV-2 positivity. The breadth of the disturbed pathways indicates a systemic signature of SARS-CoV-2 positivity that includes elements of liver dysfunction, dyslipidaemia, diabetes, and coronary heart disease risk that are consistent with recent reports that COVID-19 is a systemic disease affecting multiple organs and systems. Metabolights study reference: MTBLS2014.
Issue Date: 17-Aug-2020
Date of Acceptance: 1-Aug-2020
URI: http://hdl.handle.net/10044/1/81985
DOI: 10.1021/acs.jproteome.0c00519
ISSN: 1535-3893
Publisher: American Chemical Society (ACS)
Start Page: 4442
End Page: 4454
Journal / Book Title: Journal of Proteome Research
Volume: 19
Issue: 11
Copyright Statement: © 2020 American Chemical Society. This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Proteome Research (JPR), after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jproteome.0c00519
Keywords: COVID-19
NMR spectroscopy
SARS-CoV-2
amino acids
biomarkers
lipoproteins
mass spectrometry
metabolic phenotyping
mosaic disease
multiorgan damage
systems model
03 Chemical Sciences
06 Biological Sciences
Biochemistry & Molecular Biology
Publication Status: Published
Online Publication Date: 2020-08-17
Appears in Collections:Department of Metabolism, Digestion and Reproduction
Department of Surgery and Cancer
Faculty of Medicine
Imperial College London COVID-19