Literature DB >> 31931167

Screening and identification of plasma lncRNAs uc.48+ and NR_105053 as potential novel biomarkers for cured pulmonary tuberculosis.

Zhi-Bin Li1, Yu-Shuai Han1, Li-Liang Wei2, Li-Ying Shi3, Wen-Jing Yi1, Jing Chen1, Huai Huang1, Ting-Ting Jiang1, Ji-Cheng Li4.   

Abstract

BACKGROUND: Tuberculosis (TB) treatment takes a long time, and a gold standard test to define TB cure is lacking. This may lead to early discharge of TB patients, resulting in an increased risk of disease transmission and drug resistance. Plasma lncRNAs might act as potential biomarkers to evaluate TB cure in an efficient and precise manner.
METHODS: A lncRNA microarray assay was used to screen differentially expressed plasma lncRNAs in untreated TB and cured TB subjects. The expression levels of lncRNAs were verified by qPCR. Target genes of lncRNAs were predicted using a coding-non-coding gene co-expression network and mRNA-lncRNA-miRNA interaction network analysis.
RESULTS: The expression levels of lncRNAs uc.48+ (p < 0.001) and NR_105053 (p = 0.03) were found to differ significantly between the untreated TB group and the cured TB group. The predicted target genes of uc.48+ were EP300, BAI1 and NR_105053 were TLR9, MYD88, BAI1, respectively. A predictive model for cured TB was established by the combination of uc.48+ and NR_105053 expression, with a sensitivity of 90.00% and specificity of 86.36%, and an area under the curve (AUC) value of 0.945.
CONCLUSIONS: lncRNAs uc.48+ and NR_105053 may serve as potential biomarkers to distinguish between untreated TB patients and cured TB subjects. This study provides an experimental basis to evaluate the effect of TB treatment and may also provide new clues to the pathological mechanisms of TB.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Biomarker; Macrophage; T-UCR; Tuberculosis; lncRNA

Year:  2020        PMID: 31931167     DOI: 10.1016/j.ijid.2020.01.005

Source DB:  PubMed          Journal:  Int J Infect Dis        ISSN: 1201-9712            Impact factor:   3.623


  4 in total

Review 1.  Long Non-coding RNAs in Tuberculosis: From Immunity to Biomarkers.

Authors:  Xianyi Zhang; Chan Chen; Yuzhong Xu
Journal:  Front Microbiol       Date:  2022-05-11       Impact factor: 6.064

2.  Novel Long Non-coding RNA and LASSO Prediction Model to Better Identify Pulmonary Tuberculosis: A Case-Control Study in China.

Authors:  Zirui Meng; Minjin Wang; Shuo Guo; Yanbing Zhou; Mengyuan Lyu; Xuejiao Hu; Hao Bai; Qian Wu; Chuanmin Tao; Binwu Ying
Journal:  Front Mol Biosci       Date:  2021-05-25

3.  Screening and identification of differentially expressed long non-coding RNAs in multidrug-resistant tuberculosis.

Authors:  Junwei Zhao; ShuHui Gao; Chunguang Chen; Hui Li; Shaohua Wang; Yongmin Yu; Liang Ming
Journal:  PeerJ       Date:  2022-01-17       Impact factor: 2.984

4.  Identification of potential lipid biomarkers for active pulmonary tuberculosis using ultra-high-performance liquid chromatography-tandem mass spectrometry.

Authors:  Yu-Shuai Han; Jia-Xi Chen; Zhi-Bin Li; Jing Chen; Wen-Jing Yi; Huai Huang; Li-Liang Wei; Ting-Ting Jiang; Ji-Cheng Li
Journal:  Exp Biol Med (Maywood)       Date:  2020-11-11
  4 in total

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