ArticlePloS one2011
Novel biomarkers distinguishing active tuberculosis from latent infection identified by gene expression profile of peripheral blood mononuclear cells.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
49 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.
- Pooled it
- Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis.Frontiers in immunology · 2019Trial
- Detection for New Biomarkers of Tuberculosis Infection Activity Using Machine Learning Methods.Diseases (Basel, Switzerland) · 2026Review
- Artificial intelligence in medicine: Current applications in cardiology, oncology, and radiology.World journal of methodology · 2025Review
- TRAIL and IP-10 dynamics in pregnant women post COVID-19 vaccination: associations with neutralizing antibody potency.Frontiers in cellular and infection microbiology · 2024Article
- Novel RNA biomarkers improve discrimination of children with tuberculosis disease from those with non-TB pneumonia afterFrontiers in immunology · 2024Article
- From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning.Military Medical Research · 2023Review
- Review
- Identification of immune biomarkers in recent active pulmonary tuberculosis.Scientific reports · 2023Article
- Management of Tuberculosis Infection: Current Situation, Recent Developments and Operational Challenges.Pathogens (Basel, Switzerland) · 2023Review
- Evaluation of theFrontiers in cellular and infection microbiology · 2023Article
- MOVER approximated CV: A tool for quantifying precision in ratiometric droplet digital PCR assays.Journal of pharmaceutical and biomedical analysis · 2022Article
- The Biological and Clinical Aspects of a Latent Tuberculosis Infection.Tropical medicine and infectious disease · 2022Review
- In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlyingFrontiers in microbiology · 2022Article
- Diagnostic Performance of a NovelFrontiers in microbiology · 2022Article
- Exaggerated IL-17A activity in human in vivo recall responses discriminates active tuberculosis from latent infection and cured disease.Science translational medicine · 2021Article
- Infected juvenile salmon can experience increased predation during freshwater migration.Royal Society open science · 2021Article
- Biomarkers for Detecting Resilience against Mycobacterial Disease in Animals.Infection and immunity · 2019Review
- Observational
- Host Transcriptomics as a Tool to Identify Diagnostic and Mechanistic Immune Signatures of Tuberculosis.Frontiers in immunology · 2019Review
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHumans infected with Mycobacterium tuberculosis (MTB) can delete the pathogen or otherwise become latent infection or active disease. However, the factors influencing the pathogen clearance and disease progression from latent infection are poorly understood. This study attempted to use a genome-wide transcriptome approach to identify immune factors associated with MTB infection and novel biomarkers that can distinguish active disease from latent infection. METHODOLOGY/PRINCIPAL
findingsUsing microarray analysis, we comprehensively determined the transcriptional difference in purified protein derivative (PPD) stimulated peripheral blood mononuclear cells (PBMCs) in 12 individuals divided into three groups: TB patients (TB), latent TB infection individuals (LTBI) and healthy controls (HC) (n = 4 per group). A transcriptional profiling of 506 differentially expressed genes could correctly group study individuals into three clusters. Moreover, 55- and 229-transcript signatures for tuberculosis infection (TB<BI) and active disease (TB) were identified, respectively. The validation study by quantitative real-time PCR (qPCR) performed in 83 individuals confirmed the expression patterns of 81% of the microarray identified genes. Decision tree analysis indicated that three genes of CXCL10, ATP10A and TLR6 could differentiate TB from LTBI subjects. Additional validation was performed to assess the diagnostic ability of the three biomarkers within 36 subjects, which yielded a sensitivity of 71% and specificity of 89%. CONCLUSIONS/SIGNIFICANCE: The transcription profiles of PBMCs induced by PPD identified distinctive gene expression patterns associated with different infectious status and provided new insights into human immune responses to MTB. Furthermore, this study indicated that a combination of CXCL10, ATP10A and TLR6 could be used as novel biomarkers for the discrimination of TB from LTBI.
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Registered trials
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