Imperial College London
Alternate

Emeritus ProfessorJeremyNicholson

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Emeritus Professor of Biological Chemistry
 
 
 
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Contact

 

+44 (0)20 7594 3195j.nicholson Website

 
 
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Assistant

 

Ms Wendy Torto +44 (0)20 7594 3225

 
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Location

 

Office no. 665Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Kimhofer:2020:10.1021/acs.jproteome.0c00519,
author = {Kimhofer, T and Lodge, S and Whiley, L and Gray, N and Loo, RL and Lawler, NG and Nitschke, P and Bong, S-H and Morrison, DL and Begum, S and Richards, T and Yeap, BB and Smith, C and Smith, KCG and Holmes, E and Nicholson, JK},
doi = {10.1021/acs.jproteome.0c00519},
journal = {Journal of Proteome Research},
pages = {4442--4454},
title = {Integrative modelling of quantitative plasma lipoprotein, metabolic and amino acid data reveals a multi-organ pathological signature of SARS-CoV-2 infection},
url = {http://dx.doi.org/10.1021/acs.jproteome.0c00519},
volume = {19},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 referenc
AU  - Kimhofer,T
AU  - Lodge,S
AU  - Whiley,L
AU  - Gray,N
AU  - Loo,RL
AU  - Lawler,NG
AU  - Nitschke,P
AU  - Bong,S-H
AU  - Morrison,DL
AU  - Begum,S
AU  - Richards,T
AU  - Yeap,BB
AU  - Smith,C
AU  - Smith,KCG
AU  - Holmes,E
AU  - Nicholson,JK
DO  - 10.1021/acs.jproteome.0c00519
EP  - 4454
PY  - 2020///
SN  - 1535-3893
SP  - 4442
TI  - Integrative modelling of quantitative plasma lipoprotein, metabolic and amino acid data reveals a multi-organ pathological signature of SARS-CoV-2 infection
T2  - Journal of Proteome Research
UR  - http://dx.doi.org/10.1021/acs.jproteome.0c00519
UR  - https://pubs.acs.org/doi/10.1021/acs.jproteome.0c00519
UR  - http://hdl.handle.net/10044/1/81985
VL  - 19
ER  -
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