Benchtop NMR-based metabolomic analysis as a diagnostic tool for tuberculosis in clinical urine samples

This study aimed at developing a Nuclear Magnetic Resonance (NMR)-based metabolomic approach for the differential diagnosis of TB from urine samples. Translational potential has been also proved by the use of an affordable and portable low-field (LF) NMR spectrometer.Methods: Urine samples from adult patients diagnosed of TB (n=19), other respiratory infection (n=25) and healthy controls (n=29) were examined using a Bruker Avance high-field (HF) (16.4T) spectrometer and a Magritek Spinsolve LF (1.4T) spectrometer. Principal Component Analysis (PCA) was applied to identify metabolic differences between groups. Classificatory models of partial least squares discriminant analysis (PLS-DA) was developed for the diagnosis of TB.Results: The urine HF NMR spectra provide a high discrimination between the three groups. We identified 31 metabolic signals significantly diferent between groups. PLS-DA classification models, TB vs control and TB vs respiratory infection, provided a diagnosis accuracy of about 100% by test samples. A similar PLS-DA classification model was developed based on LF NMR spectra, providing a diagnosis accuracy of about 100% by test samples. As conclusions, we have shown that the metabolomic profile obtained by both high- and low-field NMR is sensitive to identify TB. The high diagnostic accuracy archive by LF NMR is of particular interest because it opens the door to an easy translation to a clinical environment.
Source: European Respiratory Journal - Category: Respiratory Medicine Authors: Tags: Tuberculosis Source Type: research