4.7 Article

Urine NMR-based TB metabolic fingerprinting for the diagnosis of TB in children

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SCIENTIFIC REPORTS
卷 11, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-021-91545-0

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资金

  1. Isolana Foundation
  2. Maria Francesca Roviralta Foundation
  3. Spanish Ministry of Economy, Industry, and Competitiveness (MEIC-AEI) [SAF2017-84494-C2-1-R]
  4. Instituto de Salud Carlos III [PI13/01546, PI16/01912, DTS18/0092]
  5. Plan Nacional de I+D+I
  6. ISCIII Subdireccion General de Evaluacion
  7. European Reginal Development Fund (ERDF)
  8. Spanish Ministry of Science and Innovation [PID2019-10656RJ-I00]
  9. Sociedad Espanola de Neumologia y Cirugia Toracica (SEPAR
  10. Barcelona, Spain) [052/2011]
  11. Fundacion para la Innovacion y la Prospectiva en Salud en Espana (FIPSE) [02730-16, 3307-17]
  12. Comunidad de Madrid [B2017/BMD3875]
  13. Gobierno Vasco, Dpto. Industria, Innovacion, Comercio y Turismo, under the ELKARTEK programme [KK-2019/bmG19]
  14. European Respiratory Society-ERS Short-Term Research Fellowship [STRTF201810-00467]
  15. European Union [823854]
  16. BBVA Foundation
  17. La Caixa Foundation [2020/HR20-00075]
  18. Maria de Maeztu Units of Excellence Programme from the Spanish State Research Agency [MDM-2017-0720]
  19. Marie Curie Actions (MSCA) [823854] Funding Source: Marie Curie Actions (MSCA)

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In this study, differences in metabolic response in children with different diagnostic certainty of TB were identified using urine nuclear magnetic resonance-based metabolomics. This could help improve the accuracy of TB diagnosis and prediction in pediatric populations.
Tuberculosis (TB) is a major cause of morbidity and mortality in children, and early diagnosis and treatment are crucial to reduce long-term morbidity and mortality. In this study, we explore whether urine nuclear magnetic resonance (NMR)-based metabolomics could be used to identify differences in the metabolic response of children with different diagnostic certainty of TB. We included 62 children with signs and symptoms of TB and 55 apparently healthy children. Six of the children with presumptive TB had bacteriologically confirmed TB, 52 children with unconfirmed TB, and 4 children with unlikely TB. Urine metabolic fingerprints were identified using high- and low-field proton NMR platforms and assessed with pattern recognition techniques such as principal components analysis and partial least squares discriminant analysis. We observed differences in the metabolic fingerprint of children with bacteriologically confirmed and unconfirmed TB compared to children with unlikely TB (p=0.041 and p=0.013, respectively). Moreover, children with unconfirmed TB with X-rays compatible with TB showed differences in the metabolic fingerprint compared to children with non-pathological X-rays (p=0.009). Differences in the metabolic fingerprint in children with different diagnostic certainty of TB could contribute to a more accurate characterisation of TB in the paediatric population. The use of metabolomics could be useful to improve the prediction of TB progression and diagnosis in children.

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