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Screening differential circular RNA expression profiles reveals the regulatory role of circMARS in anti-tuberculosis drug-induced liver injury.

ABSTRACT: Tuberculosis (TB) treatment is plagued by liver damage, which often leads to treatment interruptions. Circular RNAs (circRNAs) are a special class of non-coding RNAs abundant in body fluids with important biological functions. However, the role of circRNA in anti-tuberculosis drug-induced liver injury (ADLI) is unclear. We explored ADLI-specific circRNAs in TB patients using circRNA microarrays and verified circMARS in a cohort of 300 individuals. In addition to the value assessment of circMARS in patients using a receiver operating characteristic (ROC) curve, cell experiments were also performed under the guidance of bioinformatics analyses. In particular, we found that circMARS acts as a miRNA sponge by binding to miRNAs. Compared with the blank group, the expressions of circMARS, KMT2C gene, and EGFR protein in the ADLI group were increased, while miR-6808-5p, miR-6874-3p, and miR-3157-5p were decreased. Furthermore, when si-circMARS was used in the ADLI groups, circMARS demotion manifested the opposite results. Subsequently, a self-controlled cohort of 35 participants was used to verify the circMARS-miR-6808-5p/-6874-3p/-3157-5p-KMT2C-EGFR function axis. Therefore, circMARS may participate in the compensatory repair mechanism of ADLI through the function axis, and may be a potential biomarker for ADLI diagnosis in TB patients.

SUBMITTER: Li B

PROVIDER: S-EPMC8831982 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Screening differential circular RNA expression profiles reveals the regulatory role of circMARS in anti-tuberculosis drug-induced liver injury.

Li Biao B Ren Qi Q Li Yuhong Y Tian Shenqian S Chong Yingzhi Y Sun Shufeng S Feng Fumin F

Journal of cellular and molecular medicine 20220114 4

Tuberculosis (TB) treatment is plagued by liver damage, which often leads to treatment interruptions. Circular RNAs (circRNAs) are a special class of non-coding RNAs abundant in body fluids with important biological functions. However, the role of circRNA in anti-tuberculosis drug-induced liver injury (ADLI) is unclear. We explored ADLI-specific circRNAs in TB patients using circRNA microarrays and verified circMARS in a cohort of 300 individuals. In addition to the value assessment of circMARS ...[more]

PMID: 35032098

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Project description:Background: Anti-tuberculosis drug-induced liver injury (ATB-DILI) is an adverse reaction with a high incidence and the greatest impact on tuberculosis treatment. However, there is a lack of effective biomarkers for the early prediction of ATB-DILI. Herein, this study uses UPLC‒MS/MS to reveal the plasma metabolic profile and lipid profile of ATB-DILI patients before drug administration and screen new biomarkers for predicting ATB-DILI. Methods: A total of 60 TB patients were enrolled, and plasma was collected before antituberculosis drug administration. The untargeted metabolomics and lipidomics analyses were performed using UPLC‒MS/MS, and the high-resolution mass spectrometer Q Exactive was used for data acquisition in both positive and negative ion modes. The random forest package of R software was used for data screening and model building. Results: A total of 60 TB patients, including 30 ATB-DILI patients and 30 non-ATB-DILI subjects, were enrolled. There were no significant differences between the ATB-DILI and control groups in age, sex, smoking, drinking or body mass index (p > 0.05). Twenty-two differential metabolites were selected. According to KEGG pathway analysis, 9 significantly enriched metabolic pathways were found, and both drug metabolism-other enzymes and niacin and nicotinamide metabolic pathways were found in both positive and negative ion models. A total of 7 differential lipid molecules were identified between the two groups. Ferroptosis and biosynthesis of unsaturated fatty acids were involved in the occurrence of ATB-DILI. Random forest analysis showed that the model built with the top 30 important variables had an area under the ROC curve of 0.79 (0.65-0.93) for the training set and 0.79 (0.55-1.00) for the validation set. Conclusion: This study demonstrated that potential markers for the early prediction of ATB-DILI can be found through plasma metabolomics and lipidomics. The random forest model showed good clinical predictive value for ATB-DILI.

Dataset Information

Screening differential circular RNA expression profiles reveals the regulatory role of circMARS in anti-tuberculosis drug-induced liver injury.

Publications

Screening differential circular RNA expression profiles reveals the regulatory role of circMARS in anti-tuberculosis drug-induced liver injury.

Similar Datasets

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