ArticleScientific reports2020
Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- Urine-based diagnostic tests for tuberculosis: a scoping review highlighting unmet diagnostic needs.Frontiers in microbiology · 2026Pooled it
- NMR Metabolomics in Veterinary Medicine: From Biomarker Discovery to Clinical Implementation.Veterinary sciences · 2026Review
- Benchtop NMR as a clinical tool for acute respiratory illness: metabolic signatures associated with disease severity.Respiratory research · 2026Article
- Potential urine NMR Metabolomic signatures for early diagnosis of paediatric tuberculosis.Scientific reports · 2026Article
- Effect of PKM2 onFrontiers in cellular and infection microbiology · 2026Article
- Benchtop NMR in Biomedicine: An Updated Literature Overview.Metabolites · 2025Review
- Metabolomic signatures of tuberculosis and paratuberculosis in goats revealed by high-resolution and benchtop NMR spectroscopy.Veterinary research · 2025Article
- NMR based human gut metabolomic profiling reveals altered metabolites associated with pulmonary and extra-pulmonary tuberculosis.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Benchtop NMR urine metabolomics for diagnosing pulmonary tuberculosis.Scientific reports · 2025Article
- A nuclear magnetic resonance spectroscopy metabolomic approach to renal dysfunction in canine leishmaniasis.Veterinary and animal science · 2025Article
- Benchtop Proton NMR Spectroscopy for High-Throughput Lipoprotein Quantification in Human Serum and Plasma.Analytical chemistry · 2025Article
- Genome-wide expression in human whole blood for diagnosis of latent tuberculosis infection: a multicohort research.Frontiers in microbiology · 2025Article
- Combined urine proteomics and metabolomics analysis for the diagnosis of pulmonary tuberculosis.Clinical proteomics · 2024Article
- Non-targeted metabolomics and pseudo-targeted lipidomics combined with gut microbes reveal the protective effects ofFrontiers in cellular and infection microbiology · 2024Article
- Benchtop NMR-Based Metabolomics: First Steps for Biomedical Application.Metabolites · 2023Review
- Application of Benchtop NMR for Metabolomics Study Using Feces of Mice with DSS-Induced Colitis.Metabolites · 2023Article
- Small molecule metabolites: discovery of biomarkers and therapeutic targets.Signal transduction and targeted therapy · 2023Review
- NMR Metabolomics Methods for Investigating Disease.Analytical chemistry · 2023Review
- Biomarker discovery for tuberculosis using metabolomics.Frontiers in molecular biosciences · 2023Review
- Untargeted Metabolomics of Feces Reveals Diagnostic and Prognostic Biomarkers for Active Tuberculosis and Latent Tuberculosis Infection: Potential Application for Precise and Non-Invasive Identification.Infection and drug resistance · 2023Article
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Authors and funding
22 authors at 8 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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