hrvatski jezikClear Cookie - decide language by browser settings

Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine

Kopriva, Ivica; Jerić, Ivanka; Popović Hadžija, Marijana; Hadžija, Mirko; Vučić Lovrenčić, Marijana (2021) Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine. Analytical Chemistry, 93 (2). pp. 745-751. ISSN 0003-2700

PDF - Published Version - article
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview


Due to its quantitative character and capability for high throughput screening, 1H nuclear magnetic resonance (NMR) spectroscopy is used extensively in the profiling of biofluids such as urine and blood plasma. However, the narrow frequency bandwidth of 1H NMR spectroscopy leads to a severe overlap of the spectra of components present in the complex mixtures such as biofluids. Therefore, 1H NMR-based metabolomics analysis is focused on targeted studies related to concentrations of the small number of metabolites. Here, we propose a library-based approach to quantify proportions of overlapping metabolites from 1H NMR mixture spectra. The method boils down to the linear nonnegative least squares (NNLS) problem, whereas proportions of the pure components contained in the library stand for the unknowns. The method is validated on an estimation of the proportions of: (i) the 78 pure spectra, presumably related to type 2 diabetes mellitus (T2DM), from their synthetic linear mixture; (ii) metabolites present in 62 1H NMR spectra of urine of subjects with T2DM and 62 1H NMR spectra of urine of control subjects. In both cases, the in-house library of 210 pure components 1H NMR spectra represented the design matrix in related NNLS problem. The proposed method pinpoints 63 metabolites that in a statistically significant way discriminate T2DM group from the control group, and 46 metabolites discriminating control from the T2DM group. For several T2DM-discriminative metabolites, we prove their presence by an independent analytical determination or by pointing out the corresponding findings in the published literature.

Item Type: Article
Uncontrolled Keywords: 1H nuclear magnetic resonance spectroscopy; nonnegative least squares; human urine; metabolic profiling
Subjects: NATURAL SCIENCES > Mathematics > Applied Mathematics and Mathematical Modeling
NATURAL SCIENCES > Chemistry > Analytic Chemistry
TECHNICAL SCIENCES > Computing > Data Processing
BIOMEDICINE AND HEALTHCARE > Basic Medical Sciences > Human Physiology
Divisions: Division of Electronics
Division of Molecular Medicine
Division of Organic Chemistry and Biochemistry
Project titleProject leaderProject codeProject type
Strukturne dekompozicije empirijskih podataka za računalno potpomognutu dijagnostiku bolesti-DEDADIvica KoprivaIP-2016-06-5235HRZZ
Depositing User: Ivica Kopriva
Date Deposited: 22 Jan 2021 09:14
DOI: 10.1021/acs.analchem.0c02837

Actions (login required)

View Item View Item


Downloads per month over past year

Increase Font
Decrease Font
Dyslexic Font