Trial reportScientific reports2020
Whole blood mRNA expression-based targets to discriminate active tuberculosis from latent infection and other pulmonary diseases.
Trial report in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 30 citations in OpenAlex.
- Novel RT‒qPCR-based blood signatures for the diagnosis of pulmonary tuberculosis.Scientific reports · 2026Article
- Advances in functional transcriptome analysis of Mycobacterium tuberculosis: a review.Molecular genetics and genomics : MGG · 2026Review
- Evaluation of TST/C-TST combination for latent tuberculosis infection screening: diagnostic performance and cost-effectiveness compared to TST/IGRAs.BMC infectious diseases · 2026Article
- Functional analysis of distinct factors linked to the development of latent to active tuberculosis.Frontiers in cellular and infection microbiology · 2026Review
- Exploration of common immune mechanisms and hub genes in latent and active tuberculosis infection.Frontiers in cellular and infection microbiology · 2026Article
- Advancement in diagnostic approaches for latent tuberculosis: distinguishing recent from remote infections.One health outlook · 2025Review
- Long non-coding RNA transcripts inNon-coding RNA research · 2025Review
- Identification and assessment of hub genes and miRNAs coregulatory associated with immune infiltrations and drug interactions in latent tuberculosis based on MicroarrayData analysis, molecular docking, and dynamic simulation.Biochemistry and biophysics reports · 2025Article
- Targeting CCRL2 enhances therapeutic outcomes in a tuberculosis mouse model.Frontiers in immunology · 2025Article
- Inhibitory leukocyte immunoglobulin-like receptors, subfamily B (LILRBs) in human diseases: structure, roles, mechanisms, and clinical applications.Theranostics · 2025Review
- Integration and validation of host transcript signatures, including a novel 3-transcript tuberculosis signature, to enable one-step multiclass diagnosis of childhood febrile disease.Journal of translational medicine · 2024Article
- Article
- Identification of immune biomarkers in recent active pulmonary tuberculosis.Scientific reports · 2023Article
- Assessment of ferroptosis-associated gene signatures as potential biomarkers for differentiating latent from active tuberculosis in children.Microbial genomics · 2023Article
- Challenges and the Way forward in Diagnosis and Treatment of Tuberculosis Infection.Tropical medicine and infectious disease · 2023Review
- Transcriptomics for child and adolescent tuberculosis.Immunological reviews · 2022Review
- Article
- In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlyingFrontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 3 countries.
Funding
Abstract
Current diagnostic tests for tuberculosis (TB) are not able to predict reactivation disease progression from latent TB infection (LTBI). The main barrier to predicting reactivation disease is the lack of our understanding of host biomarkers associated with progression from latent infection to active disease. Here, we applied an immune-based gene expression profile by NanoString platform to identify whole blood markers that can distinguish active TB from other lung diseases (OPD), and that could be further evaluated as a reactivation TB predictor. Among 23 candidate genes that differentiated patients with active TB from those with OPD, nine genes (CD274, CEACAM1, CR1, FCGR1A/B, IFITM1, IRAK3, LILRA6, MAPK14, PDCD1LG2) demonstrated sensitivity and specificity of 100%. Seven genes (C1QB, C2, CCR2, CCRL2, LILRB4, MAPK14, MSR1) distinguished TB from LTBI with sensitivity and specificity between 82 and 100%. This study identified single gene candidates that distinguished TB from OPD and LTBI with high sensitivity and specificity (both > 82%), which may be further evaluated as diagnostic for disease and as predictive markers for reactivation TB.
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What OpenQuestion holds
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.