Study On Potential New Molecular Markers For Tuberculosis Cure Based On Metabolomics

Background: Pulmonary tuberculosis(TB)is a chronic pulmonary infection caused by Mycobacterium tuberculosis(Mtb).China has the second largest number of TB cases in the world.However,there is a lack of standard clinical diagnostic laboratory methods for the detection of cured TB.Generally,the recommended TB treatment plan by the World Health Organization(WHO)is for six months including,the intensive phase of TB treatment with isoniazid,rifampicin,pyrazinamide,and ethambutol for the first two months followed by the continuation phase with isoniazid and rifampicin for the next four months.At present,the hospital discharge criteria for TB patients are based on the evaluation of symptoms,sputum smear or sputum culture results,chest CT manifestations,and medication course to determine whether the patients are cured.Due to the lack of uniform laboratory evaluation standards for cured TB,the subjective judgment of doctors can result in hospital discharge of some uncured TB patients,thereby increasing the risk of TB transmission and accelerating Mtb resistance.For this reason,there is an urgent need to identify biomarkers for the evaluation of cured TB in order to establish a fast,sensitive and specific method for cured TB diagnosis.Methods: High performance liquid chromatography coupled with mass spectrometry(LC-MS)was used to detect metabolites in heparin anticoagulated plasma in the healthy control group,the untreated TB group,the 2-month treated TB group,and the cured TB group.The data was filtered by baseline,peak identification,integration,retention time correction,peak alignment and normalization,and finally a data matrix of retention time,mass-to-charge ratio and peak intensity was obtained.The mass-to-charge ratios were obtained in both positive and negative ion mode.The combination of multi-dimensional analysis(OPLS-DA)and single-dimensional analysis(Student's t-test)was used to screen the differential metabolites between groups(VIP>1,p<0.05).For the screened differential metabolites in the healthy control group,the untreated TB group,the 2-month treated TB group and the cured TB group,a combined model of TB plasma metabolites was established and its clinical diagnostic value was evaluated.Results: Differential metabolites were screened between the healthy control group,the untreated TB group,the 2-month treated TB group and the cured TB group.After pretreatment,3861 peaks in positive ion mode and 3975 peaks in negative ion mode were retained.The results of multivariate statistical analysis showed that the model was well established,and the healthy control group,the untreated TB group,the 2-month treated TB group and the cured TB group could be well distinguished.A total of 32 differential metabolites were identified between the 2-month treated TB group and the untreated TB group(15 down-regulated and 17 up-regulated differential metabolites).The differential metabolites were mainly enriched in metabolism of alanine,aspartic acid,glutamic acid and pathway of glutathione metabolism.Between the cured TB group and the untreated TB group,19 differential metabolites were identified(8 down-regulated and 11 up-regulated differential metabolites).The differential metabolites were mainly enriched in phenylalanine metabolism,arachidonic acid metabolism,and phenylalanine,tyrosine and tryptophan biosynthesis.Finally,four differential metabolites such as,L-Histidine,Arachidonic acid(AA),Biliverdin,and L-Cysteine-glutathione disulfide were identified after six months of TB treatment.Among them,L-Cysteine-glutathione disulfide and AA could be identified after 2 months of TB treatment.The changes in Biliverdin,L-Cysteine-glutathione disulfide,and AA could reflect the body's defense ability against Mtb,while,the changes in L-Histidine could reflect the coagulation function.We established a cured TB model with an area under the curve(AUC)of 0.909(95% CI,0.802 to 0.970),86.2% sensitivity,and 85.2% specificity.Conclusion: The established combined diagnostic model can be used as a potential biomarker for the diagnosis of cured TB.Our results may provide laboratory standards for hospital discharge of TB patients,as well as experimental basis for the efficacy of anti-TB drugs.