Metabolic phenotyping and global functional analysis facilitate metabolic signature discovery for tuberculosis treatment monitoring

• Published in: Biochimica et biophysica acta. Molecular basis of disease 2024-04, Vol.1870 (4), p.167064, Article 167064
• Main Authors: Anh, Nguyen Ky, Yen, Nguyen Thi Hai, Tien, Nguyen Tran Nam, Phat, Nguyen Ky, Park, Young Jin, Kim, Ho-Sook, Vu, Dinh Hoa, Oh, Jee Youn, Kim, Dong Hyun, Long, Nguyen Phuoc
• Format: Article
• Language: English
• Subjects: Biomarker; Diagnosis; Metabolomics; Treatment monitoring; Tuberculosis
• ISSN: 0925-4439; 1879-260X; 1879-260X
• DOI: 10.1016/j.bbadis.2024.167064

Tracking alterations in polar metabolite and lipid levels during anti-tuberculosis (TB) interventions is an emerging biomarker discovery and validation approach due to its sensitivity in capturing changes and reflecting on the host status. Here, we employed deep plasma metabolic phenotyping to explore the TB patient metabolome during three phases of treatment: at baseline, during intensive phase treatment, and upon treatment completion. Differential metabolites (DMs) in each period were determined, and the pathway-level biological alterations were explored by untargeted metabolomics-guided functional interpretations that bypassed identification. We identified 41 DMs and 39 pathways that changed during intensive phase completion. Notably, levels of certain amino acids including histidine, bile acids, and metabolites of purine metabolism were dramatically increased. The altered pathways included those involved in the metabolism of amino acids, glycerophospholipids, and purine. At the end of treatment, 44 DMs were discovered. The levels of glutamine, bile acids, and lysophosphatidylinositol significantly increased compared to baseline; the levels of carboxylates and hypotaurine declined. In addition, 37 pathways principally associated with the metabolism of amino acids, carbohydrates, and glycan altered at treatment completion. The potential of each DM for diagnosing TB was examined using a cohort consisting of TB patients, those with latent infections, and controls. Logistic regression revealed four biomarkers (taurine, methionine, glutamine, and acetyl-carnitine) that exhibited excellent performance in differential diagnosis. In conclusion, we identified metabolites that could serve as useful metabolic signatures for TB management and elucidated underlying biological processes affected by the crosstalk between host and TB pathogen during treatment. •Metabolome at three representative phases of tuberculosis treatment were investigated.•Deep phenotyping explored metabolic signatures for treatment monitoring.•Global pathway analysis revealed immunometabolism altered during treatment.•Taurine, methionine, glutamine, and acetyl-carnitine can be biomarkers for diagnosis.