A Metabolic Biosignature of Early Response to Anti-tuberculosis Treatment

Overview

Journal BMC Infect Dis

Publisher Biomed Central

Specialty Infectious Diseases

Date 2014 Feb 4

PMID 24484441

Citations 35

Authors

Sebabrata Mahapatra

Ann M Hess

John L Johnson

Kathleen D Eisenach

Mary A DeGroote

Phineas Gitta

Moses L Joloba

Gilla Kaplan

Gerhard Walzl

W Henry Boom

John T Belisle

Affiliations

Soon will be listed here.

Abstract

Background: The successful treatment of tuberculosis (TB) requires long-term multidrug chemotherapy. Clinical trials to evaluate new drugs and regimens for TB treatment are protracted due to the slow clearance of Mycobacterium tuberculosis (Mtb) infection and the lack of early biomarkers to predict treatment outcome. Advancements in the field of metabolomics make it possible to identify metabolic profiles that correlate with disease states or successful chemotherapy. However, proof-of-concept of this approach has not been provided for a TB-early treatment response biosignature (TB-ETRB).

Methods: Urine samples collected at baseline and during treatment from 48 Ugandan and 39 South African HIV-seronegative adults with pulmonary TB were divided into discovery and qualification sets, normalized to creatinine concentration, and analyzed by liquid chromatography-mass spectrometry to identify small molecule molecular features (MFs) in individual patient samples. A biosignature that distinguished baseline and 1 month treatment samples was selected by pairwise t-test using data from two discovery sample sets. Hierarchical clustering and repeated measures analysis were applied to additional sample data to down select molecular features that behaved consistently between the two clinical sites and these were evaluated by logistic regression analysis.

Results: Analysis of discovery samples identified 45 MFs that significantly changed in abundance at one month of treatment. Down selection using an extended set of discovery samples and qualification samples confirmed 23 MFs that consistently changed in abundance between baseline and 1, 2 and 6 months of therapy, with 12 MFs achieving statistical significance (p < 0.05). Six MFs classified the baseline and 1 month samples with an error rate of 11.8%.

Conclusions: These results define a urine based TB-early treatment response biosignature (TB-ETRB) applicable to different parts of Africa, and provide proof-of-concept for further evaluation of this technology in monitoring clinical responses to TB therapy.

Citing Articles

Combined urine proteomics and metabolomics analysis for the diagnosis of pulmonary tuberculosis.

Yu J, Yuan J, Liu Z, Ye H, Lin M, Ma L Clin Proteomics. 2024; 21(1):66.

PMID: 39695396 PMC: 11657435. DOI: 10.1186/s12014-024-09514-4.

Untargeted Metabolomics of Feces Reveals Diagnostic and Prognostic Biomarkers for Active Tuberculosis and Latent Tuberculosis Infection: Potential Application for Precise and Non-Invasive Identification.

Luo D, Yang B, Qin K, Shi C, Wei N, Li H Infect Drug Resist. 2023; 16:6121-6138.

PMID: 37719654 PMC: 10505020. DOI: 10.2147/IDR.S422363.

Untargeted metabolomics of pulmonary tuberculosis patient serum reveals potential prognostic markers of both latent infection and outcome.

Wang X, Wu Z, Zeng J, Zhao Y, Zhang C, Yu M Front Public Health. 2022; 10:962510.

PMID: 36457328 PMC: 9705731. DOI: 10.3389/fpubh.2022.962510.

Circulating metabolites associated with tumor hypoxia and early response to treatment in bevacizumab-refractory glioblastoma after combined bevacizumab and evofosfamide.

Lodi A, Pandey R, Chiou J, Bhattacharya A, Huang S, Pan X Front Oncol. 2022; 12:900082.

PMID: 36226069 PMC: 9549210. DOI: 10.3389/fonc.2022.900082.

Identification of Prognostic Metabolomic Biomarkers at the Interface of Mortality and Morbidity in Pre-Existing TB Cases Infected With SARS-CoV-2.

Diboun I, Cyprian F, Anwardeen N, Yassine H, Elrayess M, Rahmoon S Front Cell Infect Microbiol. 2022; 12:929689.

PMID: 35937683 PMC: 9354137. DOI: 10.3389/fcimb.2022.929689.

References

Bollard M, Stanley E, Lindon J, Nicholson J, Holmes E . NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition. NMR Biomed. 2005; 18(3):143-62. DOI: 10.1002/nbm.935. View

Weiner 3rd J, Parida S, Maertzdorf J, Black G, Repsilber D, Telaar A . Biomarkers of inflammation, immunosuppression and stress with active disease are revealed by metabolomic profiling of tuberculosis patients. PLoS One. 2012; 7(7):e40221. PMC: 3402490. DOI: 10.1371/journal.pone.0040221. View

Theodoridis G, Gika H, Want E, Wilson I . Liquid chromatography-mass spectrometry based global metabolite profiling: a review. Anal Chim Acta. 2011; 711:7-16. DOI: 10.1016/j.aca.2011.09.042. View

Garcia-Zamalloa A, Taboada-Gomez J . Diagnostic accuracy of adenosine deaminase and lymphocyte proportion in pleural fluid for tuberculous pleurisy in different prevalence scenarios. PLoS One. 2012; 7(6):e38729. PMC: 3377686. DOI: 10.1371/journal.pone.0038729. View

Zhu M, Burman W, Starke J, Stambaugh J, Steiner P, Bulpitt A . Pharmacokinetics of ethambutol in children and adults with tuberculosis. Int J Tuberc Lung Dis. 2004; 8(11):1360-7. View

Vinayavekhin N, Homan E, Saghatelian A . Exploring disease through metabolomics. ACS Chem Biol. 2009; 5(1):91-103. DOI: 10.1021/cb900271r. View

Wishart D, Knox C, Guo A, Eisner R, Young N, Gautam B . HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 2008; 37(Database issue):D603-10. PMC: 2686599. DOI: 10.1093/nar/gkn810. View

Nicol M, Wilkinson R . The clinical consequences of strain diversity in Mycobacterium tuberculosis. Trans R Soc Trop Med Hyg. 2008; 102(10):955-65. DOI: 10.1016/j.trstmh.2008.03.025. View

Patti G . Separation strategies for untargeted metabolomics. J Sep Sci. 2011; 34(24):3460-9. DOI: 10.1002/jssc.201100532. View

10.

Richeldi L . An update on the diagnosis of tuberculosis infection. Am J Respir Crit Care Med. 2006; 174(7):736-42. DOI: 10.1164/rccm.200509-1516PP. View

11.

Walzl G, Ronacher K, Djoba Siawaya J, Dockrell H . Biomarkers for TB treatment response: challenges and future strategies. J Infect. 2008; 57(2):103-9. DOI: 10.1016/j.jinf.2008.06.007. View

12.

du Preez I, Loots D . New sputum metabolite markers implicating adaptations of the host to Mycobacterium tuberculosis, and vice versa. Tuberculosis (Edinb). 2013; 93(3):330-7. DOI: 10.1016/j.tube.2013.02.008. View

13.

Prasad B, Singh S . In vitro and in vivo investigation of metabolic fate of rifampicin using an optimized sample preparation approach and modern tools of liquid chromatography-mass spectrometry. J Pharm Biomed Anal. 2009; 50(3):475-90. DOI: 10.1016/j.jpba.2009.05.009. View

14.

Bowen B, Northen T . Dealing with the unknown: metabolomics and metabolite atlases. J Am Soc Mass Spectrom. 2010; 21(9):1471-6. DOI: 10.1016/j.jasms.2010.04.003. View

15.

Alsleben N, Ruhwald M, Russmann H, Marx F, Wahn U, Magdorf K . Interferon-gamma inducible protein 10 as a biomarker for active tuberculosis and latent tuberculosis infection in children: a case-control study. Scand J Infect Dis. 2011; 44(4):256-62. DOI: 10.3109/00365548.2011.632644. View

16.

Hesseling A, Walzl G, Enarson D, Carroll N, Duncan K, Lukey P . Baseline sputum time to detection predicts month two culture conversion and relapse in non-HIV-infected patients. Int J Tuberc Lung Dis. 2010; 14(5):560-70. View

17.

Rhee E, Gerszten R . Metabolomics and cardiovascular biomarker discovery. Clin Chem. 2011; 58(1):139-47. PMC: 4402975. DOI: 10.1373/clinchem.2011.169573. View

18.

Beisel W . Metabolic response to infection. Annu Rev Med. 1975; 26:9-20. DOI: 10.1146/annurev.me.26.020175.000301. View

19.

Kim K, Aronov P, Zakharkin S, Anderson D, Perroud B, Thompson I . Urine metabolomics analysis for kidney cancer detection and biomarker discovery. Mol Cell Proteomics. 2008; 8(3):558-70. PMC: 2649817. DOI: 10.1074/mcp.M800165-MCP200. View

20.

Riou C, Perez Peixoto B, Roberts L, Ronacher K, Walzl G, Manca C . Effect of standard tuberculosis treatment on plasma cytokine levels in patients with active pulmonary tuberculosis. PLoS One. 2012; 7(5):e36886. PMC: 3351475. DOI: 10.1371/journal.pone.0036886. View