Chinese Journal of Antituberculosis ›› 2021, Vol. 43 ›› Issue (12): 1327-1331.doi: 10.3969/j.issn.1000-6621.2021.12.017
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CHEN Meng-meng, DONG Jing, JIA Hong-yan, ZHAGN Zong-de(), PAN Li-ping(
)
Received:
2021-08-11
Online:
2021-12-10
Published:
2021-12-01
Contact:
ZHAGN Zong-de,PAN Li-ping
E-mail:zzd417@163.com;panliping2006@163.com
CHEN Meng-meng, DONG Jing, JIA Hong-yan, ZHAGN Zong-de, PAN Li-ping. The research progress of biomarkers in cerebrospinal fluid for diagnosis of tuberculous meningitis[J]. Chinese Journal of Antituberculosis, 2021, 43(12): 1327-1331. doi: 10.3969/j.issn.1000-6621.2021.12.017
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[1] |
Jha SK, Garg RK, Jain A, et al. Definite (microbiologically confirmed) tuberculous meningitis: predictors and prognostic impact. Infection, 2015, 43(6):639-645. doi: 10.1007/s15010-015-0756-z.
doi: 10.1007/s15010-015-0756-z URL |
[2] |
Wang YY, Xie BD. Progress on diagnosis of tuberculous meningitis. Methods Mol Biol, 2018, 1754:375-386. doi: 10.1007/978-1-4939-7717-8_20.
doi: 10.1007/978-1-4939-7717-8_20 |
[3] |
Chen YZ, Sun LC, Wen YH, et al. Pooled analysis of the Xpert MTB/RIF assay for diagnosing tuberculous meningitis. Biosci Rep, 2020, 40(1):BSR20191312. doi: 10.1042/BSR20191312.
doi: 10.1042/BSR20191312 |
[4] |
Kwizera R, Cresswell FV, Mugumya G, et al. Performance of Lipoarabinomannan Assay using Cerebrospinal fluid for the diagnosis of Tuberculous meningitis among HIV patients. Wellcome Open Res, 2019, 4:123. doi: 10.12688/wellcomeopenres.15389.2.
doi: 10.12688/wellcomeopenres.15389.2 URL |
[5] |
Wu X, Wang Y, Weng T, et al. Preparation of immunochromatographic strips for rapid detection of early secreted protein ESAT-6 and culture filtrate protein CFP-10 from Mycobacterium tuberculosis. Medicine (Baltimore), 2017, 96(51):e9350. doi: 10.1097/MD.0000000000009350.
doi: 10.1097/MD.0000000000009350 URL |
[6] |
Kashyap RS, Shekhawat SD, Nayak AR, et al. Diagnosis of tuberculosis infection based on synthetic peptides from Mycobacterium tuberculosis antigen 85 complex. Clin Neurol Neurosurg, 2013, 115(6):678-683. doi: 10.1016/j.clineuro.2012.07.031.
doi: 10.1016/j.clineuro.2012.07.031 URL |
[7] |
Haldar S, Sankhyan N, Sharma N, et al. Detection of Mycobacterium tuberculosis GlcB or HspX Antigens or devR DNA impacts the rapid diagnosis of tuberculous meningitis in children. PLoS One, 2012, 7(9):e44630. doi: 10.1371/journal.pone.0044630.
doi: 10.1371/journal.pone.0044630 URL |
[8] |
Yu J, Wang ZJ, Chen LH, et al. Diagnostic accuracy of interferon-gamma release assays for tuberculous meningitis: a meta-analysis. Int J Tuberc Lung Dis, 2016, 20(4):494-499. doi: 10.5588/ijtld.15.0600.
doi: 10.5588/ijtld.15.0600 pmid: 26970159 |
[9] |
Sharma S, Goyal MK, Sharma K, et al. Cytokines do play a role in pathogenesis of tuberculous meningitis: a prospective study from a tertiary care center in India. J Neurol Sci, 2017, 379:131-136. doi: 10.1016/j.jns.2017.06.001.
doi: S0022-510X(17)30375-1 pmid: 28716226 |
[10] |
Kwon JS, Park JH, Kim JY, et al. Diagnostic Usefulness of Cytokine and Chemokine Levels in the Cerebrospinal Fluid of Patients with Suspected Tuberculous Meningitis. Am J Trop Med Hyg, 2019, 101(2):343-349. doi: 10.4269/ajtmh.18-0947.
doi: 10.4269/ajtmh.18-0947 URL |
[11] |
Manyelo CM, Solomons RS, Snyders CI, et al. Application of cerebrospinal fluid host protein biosignatures in the diagnosis of tuberculous meningitis in children from a high burden setting. Mediators Inflamm, 2019, 2019:7582948. doi: 10.1155/2019/7582948.
doi: 10.1155/2019/7582948 |
[12] |
Shekhawat SD, Jain RK, Gaherwar HM, et al. Heat shock proteins: possible biomarkers in pulmonary and extrapulmonary tuberculosis. Hum Immunol, 2014, 75(2):151-158. doi: 10.1016/j.humimm.2013.11.007.
doi: 10.1016/j.humimm.2013.11.007 pmid: 24269695 |
[13] |
Shekhawat SD, Purohit HJ, Taori GM, et al. Evaluation of host Hsp (s) as potential biomarkers for the diagnosis of tuberculous meningitis. Clin Neurol Neurosurg, 2016, 140:47-51. doi: 10.1016/j.clineuro.2015.11.008.
doi: 10.1016/j.clineuro.2015.11.008 URL |
[14] |
Yang Y, Mu J, Chen G, et al. iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid reveals NELL2 as a potential diagnostic biomarker of tuberculous meningitis. Int J Mol Med, 2015, 35(5):1323-1332. doi: 10.3892/ijmm.2015.2131.
doi: 10.3892/ijmm.2015.2131 URL |
[15] |
Chen Y, Zhang J, Wang X, et al. HMGB1 level in cerebrospinal fluid as a complimentary biomarker for the diagnosis of tuberculous meningitis. Springerplus, 2016, 5(1):1775. doi: 10.1186/s40064-016-3478-5.
doi: 10.1186/s40064-016-3478-5 pmid: 27795917 |
[16] |
Peng T, Zhou Y, Li J, et al. Detection of Delta-like 1 ligand for the diagnosis of tuberculous meningitis: an effective and rapid diagnostic method. J Int Med Res, 2014, 42(3):728-736. doi: 10.1177/0300060513498669.
doi: 10.1177/0300060513498669 pmid: 24651996 |
[17] |
谭燕. 中枢神经系统感染患者脑脊液和血清中 MMP-2, MMP-9, MCP-1表达的研究. 中国微生态学杂志, 2015, 27(4):424-428. doi: 10.13381/j.cnki.cjm.201504015.
doi: 10.13381/j.cnki.cjm.201504015 |
[18] |
Sabir N, Hussain T, Shah SZA, et al. miRNAs in tuberculosis: new avenues for diagnosis and host-directed therapy. Front Microbiol, 2018, 9:602. doi: 10.3389/fmicb.2018.00602.
doi: 10.3389/fmicb.2018.00602 URL |
[19] |
Pan D, Pan M, Xu YM. Mir-29a expressions in peripheral blood mononuclear cell and cerebrospinal fluid: diagnostic value in patients with pediatric tuberculous meningitis. Brain Res Bull, 2017, 130:231-235. doi: 10.1016/j.brainresbull.2017.01.013.
doi: 10.1016/j.brainresbull.2017.01.013 URL |
[20] |
Pan L, Liu F, Zhang J, et al. Genome-wide miRNA analysis identifies potential biomarkers in distinguishing tuberculous and viral meningitis. Front Cell Infect Microbiol, 2019, 9:323. doi: 10.3389/fcimb.2019.00323.
doi: 10.3389/fcimb.2019.00323 URL |
[21] |
Panganiban RP, Wang Y, Howrylak J, et al. Circulating microRNAs as biomarkers in patients with allergic rhinitis and asthma. J Allergy Clin Immunol, 2016, 137(5):1423-1432. doi: 10.1016/j.jaci.2016.01.029.
doi: 10.1016/j.jaci.2016.01.029 pmid: 27025347 |
[22] |
尹慧敏, 贾永林, 李燕飞, 等. 结核性脑膜炎患者脑脊液外泌体中 let-7d 表达的研究. 中国实用神经疾病杂志, 2017, 20(6):9-12. doi: 10.3969/j.issn.1673-5110.2017.06.003.
doi: 10.3969/j.issn.1673-5110.2017.06.003 |
[23] |
路雁惠, 郭斌, 张锐毅, 等. 结核性脑膜炎患者脑脊液外泌体中 Let-7b 的表达水平及临床意义. 中风与神经疾病杂志, 2018, 35(12):1107-1110. doi: 10.19845/j.cnki.zfysjjbzz.2018.12.013.
doi: 10.19845/j.cnki.zfysjjbzz.2018.12.013 |
[24] |
Hu X, Liao S, Bai H, et al. Integrating exosomal microRNAs and electronic health data improved tuberculosis diagnosis. EBioMedicine, 2019, 40:564-573. doi: 10.1016/j.ebiom.2019.01.023.
doi: 10.1016/j.ebiom.2019.01.023 URL |
[25] |
Rohlwink UK, Figaji A, Wilkinson KA, et al. Tuberculous meningitis in children is characterized by compartmentalized immune responses and neural excitotoxicity. Nat Commun, 2019, 10(1):3767. doi: 10.1038/s41467-019-11783-9.
doi: 10.1038/s41467-019-11783-9 pmid: 31434901 |
[26] |
van Rensburg IC, Wagman C, Stanley K, et al. Successful TB treatment induces B-cells expressing FASL and IL5RA mRNA. Oncotarget, 2017, 8(2):2037-2043. doi: 10.18632/oncotarget.12184.
doi: 10.18632/oncotarget.12184 pmid: 27682872 |
[27] |
D’Attilio L, Díaz A, Santucci N, et al. Levels of inflammatory cytokines, adrenal steroids, and mRNA for GRα, GRβ and 11βHSD1 in TB pleurisy. Tuberculosis (Edinb), 2013, 93(6):635-641. doi: 10.1016/j.tube.2013.07.008.
doi: 10.1016/j.tube.2013.07.008 URL |
[28] |
Yang X, Yang J, Wang J, et al. Microarray analysis of long noncoding RNA and mRNA expression profiles in human macrophages infected with Mycobacterium tuberculosis. Sci Rep, 2016, 6:38963. doi: 10.1038/srep38963.
doi: 10.1038/srep38963 URL |
[29] |
He J, Ou Q, Liu C, et al. Differential expression of long non-coding RNAs in patients with tuberculosis infection. Tuberculosis (Edinb), 2017, 107:73-79. doi: 10.1016/j.tube.2017.08.007.
doi: 10.1016/j.tube.2017.08.007 URL |
[30] |
Li Z, Du B, Li J, et al. Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: screening potential markers for differential diagnosis. Clin Chim Acta, 2017, 466:38-45. doi: 10.1016/j.cca.2017.01.002.
doi: 10.1016/j.cca.2017.01.002 URL |
[31] |
Zhang P, Zhang W, Lang Y, et al. 1H nuclear magnetic resonance-based metabolic profiling of cerebrospinal fluid to identify metabolic features and markers for tuberculosis meningitis. Infect Genet Evol, 2019, 68:253-264. doi: 10.1016/j.meegid.2019.01.003.
doi: 10.1016/j.meegid.2019.01.003 URL |
[32] |
Dai YN, Huang HJ, Song WY, et al. Identification of potential metabolic biomarkers of cerebrospinal fluids that differentiate tuberculous meningitis from other types of meningitis by a metabolomics study. Oncotarget, 2017, 8(59):100095-100112. doi: 10.18632/oncotarget.21942.
doi: 10.18632/oncotarget.21942 URL |
[33] |
Van Zyl CW, Loots DT, Solomons R, et al. Metabolic characterization of tuberculous meningitis in a South African paediatric population using 1 HNMR metabolomics. J Infect, 2020, 81(5):743-752. doi: 10.1016/j.jinf.2020.06.078.
doi: 10.1016/j.jinf.2020.06.078 URL |
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