Imperial College London
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Peter Openshaw - Professor of Experimental Medicine

Faculty of Medicine, National Heart & Lung Institute

Proconsul, Professor of Experimental Medicine
 
 
 
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Contact

 

+44 (0)20 7594 3854p.openshaw Website CV

 
 
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Assistant

 

Ms Gale Lewis +44 (0)20 7594 0944

 
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Location

 

353Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Correia:2022:10.1021/acs.analchem.2c00466,
author = {Correia, GDS and Takis, PG and Sands, CJ and Kowalka, AM and Tan, T and Turtle, L and Ho, A and Semple, MG and Openshaw, PJM and Baillie, JK and Takáts, Z and Lewis, MR},
doi = {10.1021/acs.analchem.2c00466},
journal = {Analytical Chemistry},
pages = {6919--6923},
title = {1H NMR Signals from urine excreted protein are a source of bias in probabilistic quotient normalization},
url = {http://dx.doi.org/10.1021/acs.analchem.2c00466},
volume = {94},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Normalization to account for variation in urinary dilution is crucial for interpretation of urine metabolic profiles. Probabilistic quotient normalization (PQN) is used routinely in metabolomics but is sensitive to systematic variation shared across a large proportion of the spectral profile (>50%). Where 1H nuclear magnetic resonance (NMR) spectroscopy is employed, the presence of urinary protein can elevate the spectral baseline and substantially impact the resulting profile. Using 1H NMR profile measurements of spot urine samples collected from hospitalized COVID-19 patients in the ISARIC 4C study, we determined that PQN coefficients are significantly correlated with observed protein levels (r2 = 0.423, p < 2.2 × 10–16). This correlation was significantly reduced (r2 = 0.163, p < 2.2 × 10–16) when using a computational method for suppression of macromolecular signals known as small molecule enhancement spectroscopy (SMolESY) for proteinic baseline removal prior to PQN. These results highlight proteinuria as a common yet overlooked source of bias in 1H NMR metabolic profiling studies which can be effectively mitigated using SMolESY or other macromolecular signal suppression methods before estimation of normalization coefficients.
AU  - Correia,GDS
AU  - Takis,PG
AU  - Sands,CJ
AU  - Kowalka,AM
AU  - Tan,T
AU  - Turtle,L
AU  - Ho,A
AU  - Semple,MG
AU  - Openshaw,PJM
AU  - Baillie,JK
AU  - Takáts,Z
AU  - Lewis,MR
DO  - 10.1021/acs.analchem.2c00466
EP  - 6923
PY  - 2022///
SN  - 0003-2700
SP  - 6919
TI  - 1H NMR Signals from urine excreted protein are a source of bias in probabilistic quotient normalization
T2  - Analytical Chemistry
UR  - http://dx.doi.org/10.1021/acs.analchem.2c00466
UR  - https://pubs.acs.org/doi/10.1021/acs.analchem.2c00466
UR  - http://hdl.handle.net/10044/1/96567
VL  - 94
ER  -
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