Metabolomic Biomarkers for Monitoring Tuberculosis Treatment Response: A Comprehensive Literature Review

Background: Tuberculosis (TB) remains a major global cause of morbidity and mortality. Current tools for monitoring treatment response rely on sputum-based microscopy and culture, which may be insensitive, time-consuming, and impractical in extrapulmonary or pediatric TB and in individuals unable to produce sputum. Metabolomics has emerged as a promising approach to identify host-derived biomarkers reflecting treatment-associated immunometabolic changes, but evidence remains heterogeneous and incompletely synthesized. Methods: We conducted a comprehensive literature review of metabolomic biomarkers associated with TB treatment response. PubMed, Scopus, and Web of Science were searched for human studies evaluating targeted or untargeted metabolomics (NMR, LC-MS, GC-MS, CE-MS) in relation to treatment response or outcomes. Two reviewers independently screened studies, extracted data, and assessed risk of bias using QUIPS and PROBAST. Findings were synthesized using a structured framework across treatment stages and outcomes. Results: Of 218 records identified, 139 titles/abstracts were screened and 42 full texts assessed; 15 studies met inclusion criteria. Recurrent signals involved amino acid metabolism, particularly the tryptophan–kynurenine pathway, and vitamin/cofactor metabolites (pyridoxate, nicotinamide, trigonelline). Plasma studies frequently reported lipid remodeling and bile acid perturbations, while urine studies highlighted polyamine metabolism (e.g., N¹,N¹²-diacetylspermine) and fatty acid β-oxidation markers. Common limitations included inadequate adjustment for confounders and, in prediction models, small sample sizes and limited external validation. Conclusions: Metabolomic reveals reproducible but heterogeneous immunometabolic changes during TB therapy. Key pathways include tryptophan-kynurenine metabolism, vitamin/cofactor metabolism, lipid remodeling, and urine polyamine pathways. Standardization and prospective multicenter validation are needed for clinical translation.