Urinary metabolomic analysis to identify potential markers for the diagnosis of tuberculosis and latent tuberculosis

被引:13
作者
Deng, Jiaheng [1 ,2 ]
Liu, Liguo [1 ,2 ]
Yang, Qianting [3 ]
Wei, Candong [1 ,2 ]
Zhang, Haoran [1 ,2 ]
Xin, Henan [1 ,2 ]
Pan, Shouguo [4 ]
Liu, Zisen [4 ]
Wang, Dakuan [4 ]
Liu, Bo [1 ,2 ]
Gao, Lei [1 ,2 ]
Liu, Rongmei [5 ]
Pang, Yu [5 ]
Chen, Xinchun [6 ]
Zheng, Jianhua [1 ,2 ]
Jin, Qi [1 ,2 ]
机构
[1] Chinese Acad Med Sci & Peking Union Med Coll, Inst Pathogen Biol, NHC Key Lab Syst Biol Pathogens, Beijing 100730, Peoples R China
[2] Chinese Acad Med Sci & Peking Union Med Coll, Ctr TB Res, Beijing 100730, Peoples R China
[3] Southern Univ Sci & Technol, Shenzhen Peoples Hosp 3, Natl Clin Res Ctr Infect Dis, Guangdong Key Lab Diag & Treatment Emerging Infec, Shenzhen 518112, Peoples R China
[4] Ctr Dis Control & Prevent Zhongmu Cty, Zhongmu 451450, Peoples R China
[5] Capital Med Univ, Beijing Chest Hosp, Beijing TB & Thorac Tumor Res Inst, Dept TB, 97 Machang, Beijing 101149, Peoples R China
[6] Shenzhen Univ, Dept Pathogen Biol, Sch Med, Shenzhen 518060, Peoples R China
关键词
Tuberculosis; Urine; Metabolomics; Glutathione; Histamine; Biomarkers; Diagnostics; GAMMA RELEASE ASSAYS; IMMUNE REGULATION; GLUTATHIONE; INFECTION; HISTAMINE; BIOMARKERS; DISCOVERY; RESPONSES;
D O I
10.1016/j.abb.2021.108876
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Tuberculosis (TB) is a serious infectious disease with high infection and mortality rates. 5%-10% of the latent tuberculosis infections (LTBI) are likely to develop into active TB, and there are currently no clinical biomarkers that can distinguish between LTBI, active TB and other non-tuberculosis populations. Therefore, it is necessary to develop rapid diagnostic methods for active TB and LTBI. In this study, urinary metabolome of 30 active TB samples and the same number of LTBI and non-TB control samples were identified and analyzed by UPLC-Q Exactive MS. In total, 3744 metabolite components were obtained in ESI- mode and 4086 in ESI + mode. Orthogonal partial least square discriminant analysis (OPLS-DA) and hierarchical cluster analysis (HCA) showed that there were significant differences among LTBI, active TB and non-TB. Six differential metabolites were screened in positive and negative mode, 3-hexenoic acid, glutathione (GSH), glycochenodeoxycholate-3-sulfate, N-[4 '-hydroxy-(E)-cinnamoyl]-L-aspartic acid, deoxyribose 5-phosphate and histamine. The overlapping pathways differential metabolites involved were mainly related to immune regulation and urea cycle. The results showed that the urine metabolism of TB patients was disordered and many metabolic pathways changed. Multivariate statistical analysis revealed that GSH and histamine were selected as potential molecular markers, with area under curve of receiver operating characteristic curve over 0.75. Among the multiple differential metabolites, GSH and histamine changed to varying degrees in active TB, LTBI and the non-TB control group. The levels of GSH and histamine in 48 urinary samples were measured by ELISA in validation phase, and the result in our study provided the potential for non-invasive biomarkers of TB.
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页数:9
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