Imperial College London
Alternate

ProfessorElaineHolmes

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Professor of Chemical Biology
 
 
 
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Contact

 

+44 (0)20 7594 3220elaine.holmes

 
 
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Location

 

661Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Gray:2021:10.3390/metabo11070467,
author = {Gray, N and Lawler, NG and Zeng, AX and Ryan, M and Bong, SH and Boughton, BA and Bizkarguenaga, M and Bruzzone, C and Embade, N and Wist, J and Holmes, E and Millet, O and Nicholson, JK and Whiley, L},
doi = {10.3390/metabo11070467},
journal = {Metabolites},
pages = {1--17},
title = {Diagnostic potential of the plasma lipidome in infectious disease: application to acute SARS-CoV-2 infection},
url = {http://dx.doi.org/10.3390/metabo11070467},
volume = {11},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management.
AU  - Gray,N
AU  - Lawler,NG
AU  - Zeng,AX
AU  - Ryan,M
AU  - Bong,SH
AU  - Boughton,BA
AU  - Bizkarguenaga,M
AU  - Bruzzone,C
AU  - Embade,N
AU  - Wist,J
AU  - Holmes,E
AU  - Millet,O
AU  - Nicholson,JK
AU  - Whiley,L
DO  - 10.3390/metabo11070467
EP  - 17
PY  - 2021///
SN  - 2218-1989
SP  - 1
TI  - Diagnostic potential of the plasma lipidome in infectious disease: application to acute SARS-CoV-2 infection
T2  - Metabolites
UR  - http://dx.doi.org/10.3390/metabo11070467
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000676377500001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.mdpi.com/2218-1989/11/7/467
UR  - http://hdl.handle.net/10044/1/91211
VL  - 11
ER  -
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