ArticleJournal of cellular and molecular medicine2023
Classification and characterisation of extracellular vesicles-related tuberculosis subgroups and immune cell profiles.
Article in Journal of cellular and molecular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Extracellular Vesicles of Mycobacterium tuberculosis Serve as a Virulence Factor - Current Research Applications.Current microbiology · 2026Review
- Single-Cell Immune Atlases to Map Small Extracellular Vesicle Cargo in Tuberculosis-Diabetes Comorbidity: A Narrative Review and Conceptual Roadmap.International journal of molecular sciences · 2026Review
- Machine learning for extracellular vesicles enables diagnostic and therapeutic nanobiotechnology.Journal of nanobiotechnology · 2026Review
- The recent progression of extracellular vesicles application in osteoporosis.Frontiers in pharmacology · 2026Review
- Single-cell sequencing: Current applications in various tuberculosis specimen types.Cell proliferation · 2024Review
- Article
- Classification and characterisation of extracellular vesicles-related tuberculosis subgroups and immune cell profiles.Journal of cellular and molecular medicine · 2023Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Around the world, tuberculosis (TB) remains one of the most common causes of morbidity and mortality. The molecular mechanism of Mycobacterium tuberculosis (Mtb) infection is still unclear. Extracellular vesicles (EVs) play a key role in the onset and progression of many disease states and can serve as effective biomarkers or therapeutic targets for the identification and treatment of TB patients. We analysed the expression profile to better clarify the EVs characteristics of TB and explored potential diagnostic markers to distinguish TB from healthy control (HC). Twenty EVs-related differentially expressed genes (DEGs) were identified, and 17 EVs-related DEGs were up-regulated and three DEGs were down-regulated in TB samples, which were related to immune cells. Using machine learning, a nine EVs-related gene signature was identified and two EVs-related subclusters were defined. The single-cell RNA sequence (scRNA-seq) analysis further confirmed that these hub genes might play important roles in TB pathogenesis. The nine EVs-related hub genes had excellent diagnostic values and accurately estimated TB progression. TB's high-risk group had significantly enriched immune-related pathways, and there were substantial variations in immunity across different groups. Furthermore, five potential drugs were predicted for TB using CMap database. Based on the EVs-related gene signature, the TB risk model was established through a comprehensive analysis of different EV patterns, which can accurately predict TB. These genes could be used as novel biomarkers to distinguish TB from HC. These findings lay the foundation for further research and design of new therapeutic interventions aimed at treating this deadly infectious disease.
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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 Socratic graph.