4.7 Article

Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis

Journal

SCIENTIFIC REPORTS
Volume 10, Issue 1, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41598-020-64413-6

Keywords

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Funding

  1. National Institute for Health Research (NIHR) Biomedical Research Centre at Imperial College
  2. Medical Research Council
  3. National Institute for Health Research UK [MC-PC-12025]
  4. Department of Paediatrics
  5. Institute for Translational Medicine and Therapeutics
  6. MRC Program grant [MR/K007602/1, MR/K011944/1, MC_UP_A900/1122]
  7. NIHR [SRF-2009-02-07]
  8. Clinical Research Training Fellowship - UK Medical Research Council (MRC) [MR/K023446/1]
  9. Clinical Research Training Fellowship - UK Department for International Development (DFID) under the MRC/DFID [MR/K023446/1]
  10. European Union
  11. NIHR Academic Clinical Lectureship
  12. European Society for Paediatric Infectious Diseases
  13. Steinberg Global Health Fellowship by McGill Global Health Program
  14. MRC [MC_PC_12025, MR/K023446/1] Funding Source: UKRI

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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 H-1 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 H-1 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.

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