ArticleFrontiers in cellular and infection microbiology2019
Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis.
Article in Frontiers in cellular and infection microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Investigating Blood Biomarkers That Can Facilitate the Diagnosis of Meningitis-A Systematic Literature Review.International journal of molecular sciences · 2025Pooled it
- Integrated Characterization of ceRNA (circRNA/lncRNA/miRNA/mRNA) Regulatory Networks in aAnimals : an open access journal from MDPI · 2026Article
- The pathway of autophagy in the epigenetic landscape ofAutophagy · 2025Review
- Recent advances in the development and clinical application of miRNAs in infectious diseases.Non-coding RNA research · 2025Review
- Development and validation of a diagnostic model for tuberculous meningitis based on laboratory data.Frontiers in cellular and infection microbiology · 2025Article
- Utility of microRNA analysis in exhaled breath condensate of sarcoidosis and mediastinal tuberculosis patients: a pilot study.ERJ open research · 2024Article
- ZebrafishLife science alliance · 2024Article
- Tuberculous meningitis diagnosis and treatment: classic approaches and high-throughput pathways.Frontiers in immunology · 2024Review
- Development and validation of a new model for the early diagnosis of tuberculous meningitis in adults based on simple clinical and laboratory parameters.BMC infectious diseases · 2023Article
- MiR-25 blunts autophagy and promotes the survival ofiScience · 2022Article
- MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features.BMC medical informatics and decision making · 2021Article
- Tuberculous Meningitis: Pathogenesis, Immune Responses, Diagnostic Challenges, and the Potential of Biomarker-Based Approaches.Journal of clinical microbiology · 2021Review
- Composition and Clinical Significance of Exosomes in Tuberculosis: A Systematic Literature Review.Journal of clinical medicine · 2021Review
- Systematic evaluation, verification and comparison of tuberculosis-related non-coding RNA diagnostic panels.Journal of cellular and molecular medicine · 2021Article
- Diagnostic Model for Discrimination Between Tuberculous Meningitis and Bacterial Meningitis.Frontiers in immunology · 2021Article
- Principal component analysis of blood microRNA datasets facilitates diagnosis of diverse diseases.PloS one · 2020Article
Corrections and comments
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Authors and funding
15 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tuberculous meningitis (TBM) is the most common and severe form of central nervous system tuberculosis. Due to the non-specific clinical presentation and lack of efficient diagnosis methods, it is difficult to discriminate TBM from other frequent types of meningitis, especially viral meningitis (VM). In order to identify the potential biomarkers for discriminating TBM and VM and to reveal the different pathophysiological processes between TBM and VM, a genome-wide miRNA screening of PBMCs from TBM, VM, and healthy controls (HCs) using microarray assay was performed (12 samples). Twenty-eight differentially expressed miRNAs were identified between TBM and VM, and 11 differentially expressed miRNAs were identified between TBM and HCs. The 6 overlapping miRNAs detected in both TBM vs. VM and TBM vs. HCs were verified by qPCR analysis and showed a 100% consistent expression patterns with that in microarray test. Statistically significant differences of 4 miRNAs (miR-126-3p, miR-130a-3p, miR-151a-3p, and miR-199a-5p) were further confirmed in TBM compared with VM and HCs in independent PBMCs sample set (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.