Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker
Abstract Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by hi...
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2020
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oai:doaj.org-article:c0ec83e3132d44ef9288c211956549d32021-12-02T12:40:40ZDiscovery and validation of an NMR-based metabolomic profile in urine as TB biomarker10.1038/s41598-020-78999-42045-2322https://doaj.org/article/c0ec83e3132d44ef9288c211956549d32020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78999-4https://doaj.org/toc/2045-2322Abstract Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by high-field nuclear magnetic resonance (NMR) spectrometry and assess whether the TB metabolic profile is also detected by a low-field benchtop NMR spectrometer. We included 189 patients with tuberculosis, 42 patients with pneumococcal pneumonia, 61 individuals infected with latent tuberculosis and 40 uninfected individuals. We acquired the urine spectra from high and low-field NMR. We characterised a TB metabolic fingerprint from the Principal Component Analysis. We developed a classification model from the Partial Least Squares-Discriminant Analysis and evaluated its performance. We identified a metabolic fingerprint of 31 chemical shift regions assigned to eight metabolites (aminoadipic acid, citrate, creatine, creatinine, glucose, mannitol, phenylalanine, and hippurate). The model developed using low-field NMR urine spectra correctly classified 87.32%, 85.21% and 100% of the TB patients compared to pneumococcal pneumonia patients, LTBI and uninfected individuals, respectively. The model validation correctly classified 84.10% of the TB patients. We have identified and characterised a metabolic profile of TB in urine from a high-field NMR spectrometer and have also detected it using a low-field benchtop NMR spectrometer. The models developed from the metabolic profile of TB identified by both NMR technologies were able to discriminate TB patients from the rest of the study groups and the results were not influenced by anti-TB treatment or TB location. This provides a new approach in the search for possible biomarkers for the diagnosis of TB.José Luis Izquierdo-GarciaPatricia Comella-del-BarrioRamón Campos-OlivasRaquel Villar-HernándezCristina Prat-AymerichMaria Luiza De Souza-GalvãoMaria Angeles Jiménez-FuentesJuan Ruiz-ManzanoZoran StojanovicAdela GonzálezMar Serra-VidalEsther García-GarcíaBeatriz Muriel-MorenoJoan Pau MilletIsrael Molina-PinargoteXavier CasasJavier SantiagoFina SabriáCarmen MartosChristian HerzmannJesús Ruiz-CabelloJosé DomínguezNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-13 (2020) |
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Medicine R Science Q |
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Medicine R Science Q José Luis Izquierdo-Garcia Patricia Comella-del-Barrio Ramón Campos-Olivas Raquel Villar-Hernández Cristina Prat-Aymerich Maria Luiza De Souza-Galvão Maria Angeles Jiménez-Fuentes Juan Ruiz-Manzano Zoran Stojanovic Adela González Mar Serra-Vidal Esther García-García Beatriz Muriel-Moreno Joan Pau Millet Israel Molina-Pinargote Xavier Casas Javier Santiago Fina Sabriá Carmen Martos Christian Herzmann Jesús Ruiz-Cabello José Domínguez Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker |
| description |
Abstract Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by high-field nuclear magnetic resonance (NMR) spectrometry and assess whether the TB metabolic profile is also detected by a low-field benchtop NMR spectrometer. We included 189 patients with tuberculosis, 42 patients with pneumococcal pneumonia, 61 individuals infected with latent tuberculosis and 40 uninfected individuals. We acquired the urine spectra from high and low-field NMR. We characterised a TB metabolic fingerprint from the Principal Component Analysis. We developed a classification model from the Partial Least Squares-Discriminant Analysis and evaluated its performance. We identified a metabolic fingerprint of 31 chemical shift regions assigned to eight metabolites (aminoadipic acid, citrate, creatine, creatinine, glucose, mannitol, phenylalanine, and hippurate). The model developed using low-field NMR urine spectra correctly classified 87.32%, 85.21% and 100% of the TB patients compared to pneumococcal pneumonia patients, LTBI and uninfected individuals, respectively. The model validation correctly classified 84.10% of the TB patients. We have identified and characterised a metabolic profile of TB in urine from a high-field NMR spectrometer and have also detected it using a low-field benchtop NMR spectrometer. The models developed from the metabolic profile of TB identified by both NMR technologies were able to discriminate TB patients from the rest of the study groups and the results were not influenced by anti-TB treatment or TB location. This provides a new approach in the search for possible biomarkers for the diagnosis of TB. |
| format |
article |
| author |
José Luis Izquierdo-Garcia Patricia Comella-del-Barrio Ramón Campos-Olivas Raquel Villar-Hernández Cristina Prat-Aymerich Maria Luiza De Souza-Galvão Maria Angeles Jiménez-Fuentes Juan Ruiz-Manzano Zoran Stojanovic Adela González Mar Serra-Vidal Esther García-García Beatriz Muriel-Moreno Joan Pau Millet Israel Molina-Pinargote Xavier Casas Javier Santiago Fina Sabriá Carmen Martos Christian Herzmann Jesús Ruiz-Cabello José Domínguez |
| author_facet |
José Luis Izquierdo-Garcia Patricia Comella-del-Barrio Ramón Campos-Olivas Raquel Villar-Hernández Cristina Prat-Aymerich Maria Luiza De Souza-Galvão Maria Angeles Jiménez-Fuentes Juan Ruiz-Manzano Zoran Stojanovic Adela González Mar Serra-Vidal Esther García-García Beatriz Muriel-Moreno Joan Pau Millet Israel Molina-Pinargote Xavier Casas Javier Santiago Fina Sabriá Carmen Martos Christian Herzmann Jesús Ruiz-Cabello José Domínguez |
| author_sort |
José Luis Izquierdo-Garcia |
| title |
Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker |
| title_short |
Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker |
| title_full |
Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker |
| title_fullStr |
Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker |
| title_full_unstemmed |
Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker |
| title_sort |
discovery and validation of an nmr-based metabolomic profile in urine as tb biomarker |
| publisher |
Nature Portfolio |
| publishDate |
2020 |
| url |
https://doaj.org/article/c0ec83e3132d44ef9288c211956549d3 |
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