Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis.
Nicholas J AndreasRobindra Basu RoyMaria Gomez-RomeroVerena Horneffer-van der SluisMatthew R LewisStephane S M CamuzeauxBeatriz JiménezJoram M PosmaLeopold TientcheuUzochukwu EgereAbdou K SillahToyin TogunElaine HolmesBeate KampmannPublished in: Scientific reports (2020)
We applied a metabonomic strategy to identify host biomarkers in serum to diagnose paediatric tuberculosis (TB) disease. 112 symptomatic children with presumptive TB were recruited in The Gambia and classified as bacteriologically-confirmed TB, clinically diagnosed TB, or other diseases. Sera were analysed using 1H nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Multivariate data analysis was used to distinguish patients with TB from other diseases. Diagnostic accuracy was evaluated using Receiver Operating Characteristic (ROC) curves. Model performance was tested in a validation cohort of 36 children from the UK. Data acquired using 1H NMR demonstrated a sensitivity, specificity and Area Under the Curve (AUC) of 69% (95% confidence interval [CI], 56-73%), 83% (95% CI, 73-93%), and 0.78 respectively, and correctly classified 20% of the validation cohort from the UK. The most discriminatory MS data showed a sensitivity of 67% (95% CI, 60-71%), specificity of 86% (95% CI, 75-93%) and an AUC of 0.78, correctly classifying 83% of the validation cohort. Amongst children with presumptive TB, metabolic profiling of sera distinguished bacteriologically-confirmed and clinical TB from other diseases. This novel approach yielded a diagnostic performance for paediatric TB comparable to that of Xpert MTB/RIF and interferon gamma release assays.
Keyphrases
- mycobacterium tuberculosis
- data analysis
- mass spectrometry
- pulmonary tuberculosis
- magnetic resonance
- emergency department
- intensive care unit
- young adults
- multiple sclerosis
- high resolution
- ms ms
- electronic health record
- cross sectional
- machine learning
- immune response
- hepatitis c virus
- capillary electrophoresis
- human immunodeficiency virus
- tandem mass spectrometry
- antiretroviral therapy