Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker.

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.

Diagnostic Accuracy of Interferon Gamma-Induced Protein 10 mRNA Release Assay for Tuberculosis.

Interferon gamma (IFN-γ) release assays (IGRAs) are increasingly used to test for latent tuberculosis (TB) infection. Although highly specific, IGRAs have a relatively high false-negative rate in active TB patients. A more sensitive assay is needed. IFN-γ-induced protein 10 (IP-10) is an alternative biomarker with a 100-fold-higher expression level than IFN-γ, allowing for different analysis platforms, including molecular detection. The PCR technique is already an integrated tool in most TB laboratories and, thus, an obvious platform to turn to. In this case-control study, we investigated the diagnostic sensitivity and specificity of a molecular assay detecting IP-10 mRNA expression following antigen stimulation of a blood sample. We included 89 TB patients and 99 healthy controls. Blood was drawn in QuantiFeron-TB gold in-tube (QFT) assay tubes. Eight hours poststimulation, IP-10 mRNA expression was analyzed, and 20 h poststimulation, IP-10 and IFN-γ protein plasma levels were analyzed using an in-house IP-10 enzyme-linked immunosorbent assay (ELISA) and the official QFT ELISA, respectively. The IP-10 mRNA assay provided high specificity (98%), sensitivity (80%), and area under the concentration-time curve (AUC) (0.97); however, the QFT assay provided a higher overall diagnostic potential, with specificity of 100%, sensitivity of 90%, and AUC of 0.99. The IP-10 protein assay performed on par with the QFT assay, with specificity of 98%, sensitivity of 87%, and AUC of 0.98. We have provided proof of high technical performance of a molecular assay detecting IP-10 mRNA expression. As a diagnostic tool, this assay would gain from further optimization, especially on the kinetics of IP-10 mRNA expression.