AQuA: An Automated Quantification Algorithm for High-Throughput NMR-Based Metabolomics and Its Application in Human Plasma

A key limiting step for high-throughput NMR-based metabolomics is the lack of rapid and accurate tools for absolute quantification of many metabolites. We developed, implemented, and evaluated an algorithm, AQuA (Automated Quantification Algorithm), for targeted metabolite quantification from comple...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2018-02, Vol.90 (3), p.2095-2102
Main Authors: Röhnisch, Hanna E, Eriksson, Jan, Müllner, Elisabeth, Agback, Peter, Sandström, Corine, Moazzami, Ali A
Format: Article
Language:English
Subjects:
Algorithms
Analytical Chemistry
Analytisk kemi
Blood - metabolism
Blood Chemical Analysis - methods
Blood plasma
Calibration
Chemistry
Data processing
Experiments
Goodness of fit
High-Throughput Screening Assays - methods
Humans
Indicators
Male
Metabolites
Metabolomics
Metabolomics - methods
NMR
Nuclear magnetic resonance
Plasma
Plasma spectra
Proton Magnetic Resonance Spectroscopy - statistics & numerical data
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Summary:A key limiting step for high-throughput NMR-based metabolomics is the lack of rapid and accurate tools for absolute quantification of many metabolites. We developed, implemented, and evaluated an algorithm, AQuA (Automated Quantification Algorithm), for targeted metabolite quantification from complex 1H NMR spectra. AQuA operates based on spectral data extracted from a library consisting of one standard calibration spectrum for each metabolite. It uses one preselected NMR signal per metabolite for determining absolute concentrations and does so by effectively accounting for interferences caused by other metabolites. AQuA was implemented and evaluated using experimental NMR spectra from human plasma. The accuracy of AQuA was tested and confirmed in comparison with a manual spectral fitting approach using the ChenomX software, in which 61 out of 67 metabolites quantified in 30 human plasma spectra showed a goodness-of-fit (r 2) close to or exceeding 0.9 between the two approaches. In addition, three quality indicators generated by AQuA, namely, occurrence, interference, and positional deviation, were studied. These quality indicators permit evaluation of the results each time the algorithm is operated. The efficiency was tested and confirmed by implementing AQuA for quantification of 67 metabolites in a large data set comprising 1342 experimental spectra from human plasma, in which the whole computation took less than 1 s.
ISSN:0003-2700
1520-6882
1520-6882
DOI:10.1021/acs.analchem.7b04324