The Journal of Practical Medicine ›› 2026, Vol. 42 ›› Issue (7): 1149-1157.doi: 10.3969/j.issn.1006-5725.2026.07.005

• Feature Reports:Tuberculosis • Previous Articles    

Untargeted metabolomics-based discovery of potential biomarkersfor active pulmonary tuberculosis

Yuan WANG,Zijie CHEN,Jieqing ZHONG,Yujie MO,Xiaoling QIN,Dongxu LIANG,Xiaojing GUO,Shiyi CHEN,Dan LUO()   

  1. School of Public Health and Management,Guangxi University of Chinese Medicine,Nanning 530299,Guangxi,China
  • Received:2025-08-07 Revised:2025-09-25 Accepted:2025-09-30 Online:2026-04-10 Published:2026-04-13
  • Contact: Dan LUO E-mail:luodan2005@163.com

Abstract:

Objective To analyze the fecal metabolic profile of active tuberculosis(ATB) patients in order to explore novel non-invasive diagnostic biomarkers. Methods A total of 33 treatment-naive ATB patients(TB group) and 30 healthy controls(HC group) were recruited. Fresh fecal specimens from both groups were examined using UHPLC-MS-based untargeted metabolomics. Differential metabolites were selected by partial least squares discriminant analysis(PLS-DA) with the thresholds of variable importance in projection(VIP) ≥ 1.0, |log? FC| ≥ 0.585 (1.5-fold change), and P ≤ 0.05. Potential biomarkers were recognized through KEGG pathway enrichment and clustering analyses, and their diagnostic effectiveness was assessed via receiver operating characteristic(ROC) curves. Results A total of 515 differential metabolites were identified (312 in ESI-; 203 in ESI+), which were primarily enriched in purine metabolism, bile secretion, and nicotinate/nicotinamide metabolism. In the ESI- mode, 16 out of the top 20 metabolites were significantly down-regulated in the TB group, whereas PGE?, N-{3-[(3,5-difluorophenyl)oxy]pyridin-2-yl}-4-pentylbenzenesulfonamide, N'-2-acetylpyridine-2-carbohydrazone, and 5-hydroxyindole-2-carboxylic acid were up-regulated. In the ESI+ mode, 18 out of the top 20 metabolites were up-regulated, while 3-acetyl-2,5-dimethylfuran and fumaric acid were down-regulated. Metabolic pathway analysis combined with functional prediction identified three potential biomarkers—prostaglandin E2(PGE2), trans-2-Butene-1,4-dicarboxylic Acid, and 5-hydroxyindole-2-carboxylic acid, with areas under the curve(AUC) of 0.911, 0.859, and 0.824, respectively. The logistic regression model integrating these three biomarkers achieved an AUC of 0.957 for combined diagnosis. Conclusions Differential metabolites in patients with active pulmonary tuberculosis were mainly enriched in purine metabolism, bile secretion, and nicotinate and nicotinamide metabolism pathways. Both PGE2, trans-2-Butene-1,4-dicarboxylic acid, 5-hydroxyindole-2-carboxylic acid, and their combined diagnostic model showed good diagnostic efficacy for pulmonary tuberculosis.

Key words: active tuberculosis, untargeted metabolomics, feces, biomarkers

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