ArticleAmerican journal of respiratory and critical care medicine2015
Combinatorial Immunoprofiling in Latent Tuberculosis Infection. Toward Better Risk Stratification.
Article in American journal of respiratory and critical care medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed.
- Multiparameter antigen-specific immunoprofiling in subjects with negative IGRA and TST results with potentialFrontiers in cellular and infection microbiology · 2026Article
- Peptide MegaPools Approach to Evaluate the Dengue-Specific CD4 and CD8 T-Cell Response.Pathogens (Basel, Switzerland) · 2025Article
- Multiplexed cytokine profiling identifies diagnostic signatures for latent tuberculosis and reactivation risk stratification.PloS one · 2025Article
- Article
- Specific immune response toFrontiers in immunology · 2024Article
- Convalescent Adaptive Immunity Is Highly Heterogenous after SARS-CoV-2 Infection.Journal of clinical medicine · 2023Article
- T-cell activation-induced marker assays in health and disease.Immunology and cell biology · 2023Review
- Challenges and the Way forward in Diagnosis and Treatment of Tuberculosis Infection.Tropical medicine and infectious disease · 2023Review
- Article
- Diagnostic Value of CD25, CD69, and CD134 on Tuberculosis-Specific Antigen-Stimulated CD4+ T Cells for Tuberculous Pleurisy.Journal of immunology research · 2023Article
- Risk assessment of latent tuberculosis infection through a multiplexed cytokine biosensor assay and machine learning feature selection.Scientific reports · 2021Article
- New Diagnostics to Infer Risk in Tuberculosis: Is the Term "Latent Tuberculosis Infection" Obsolete?American journal of respiratory and critical care medicine · 2021Article
- Diagnostic performance in active TB of QFT-Plus assay and co-expression of CD25/CD134 in response to new antigens of Mycobacterium tuberculosis.Medical microbiology and immunology · 2019Article
- A quartz crystal microbalance modified with antibody-coated silver nanoparticles acting as mass signal amplifiers for real-time monitoring of three latent tuberculosis infection biomarkers.Mikrochimica acta · 2019Article
- Comparison of the QuantiFERON-TB Gold Plus and QuantiFERON-TB Gold In-Tube Interferon Gamma Release Assays in Patients at Risk for Tuberculosis and in Health Care Workers.Journal of clinical microbiology · 2018Article
- Stratification of Latent Mycobacterium tuberculosis Infection by Cellular Immune Profiling.The Journal of infectious diseases · 2017Article
- Flow Cytometric Immune Profiling in Infliximab-Associated Tuberculosis.Clinical medicine insights. Case reports · 2017Article
- Severe Tuberculosis in Humans Correlates Best with Neutrophil Abundance and Lymphocyte Deficiency and Does Not Correlate with Antigen-Specific CD4 T-Cell Response.Frontiers in immunology · 2017Article
- A Cytokine-Independent Approach To Identify Antigen-Specific Human Germinal Center T Follicular Helper Cells and Rare Antigen-Specific CD4+ T Cells in Blood.Journal of immunology (Baltimore, Md. : 1950) · 2016Article
- Update in Tuberculosis/Pulmonary Infections 2015.American journal of respiratory and critical care medicine · 2016Review
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Abstract
rationaleMost immunocompetent patients diagnosed with latent tuberculosis infection (LTBI) will not progress to tuberculosis (TB) reactivation. However, current diagnostic tools cannot reliably distinguish nonprogressing from progressing patients a priori, and thus LTBI therapy must be prescribed with suboptimal patient specificity. We hypothesized that LTBI diagnostics could be improved by generating immunomarker profiles capable of categorizing distinct patient subsets by a combinatorial immunoassay approach.
objectivesA combinatorial immunoassay analysis was applied to identify potential immunomarker combinations that distinguish among unexposed subjects, untreated patients with LTBI, and treated patients with LTBI and to differentiate risk of reactivation.
methodsIFN-γ release assay (IGRA) was combined with a flow cytometric assay that detects induction of CD25(+)CD134(+) coexpression on TB antigen-stimulated T cells from peripheral blood. The combinatorial immunoassay analysis was based on receiver operating characteristic curves, technical cut-offs, 95% bivariate normal density ellipse prediction, and statistical analysis. Risk of reactivation was estimated with a prediction formula. MEASUREMENTS AND MAIN
resultsSixty-five out of 150 subjects were included. The combinatorial immunoassay approach identified at least four different T-cell subsets. The representation of these immune phenotypes was more heterogeneous in untreated patients with LTBI than in treated patients with LTBI or unexposed groups. Patients with IGRA(+) CD4(+)CD25(+)CD134(+) T-cell phenotypes had the highest estimated reactivation risk (4.11 ± 2.11%).
conclusionsThese findings suggest that immune phenotypes defined by combinatorial assays may potentially have a role in identifying those at risk of developing TB; this potential role is supported by risk of reactivation modeling. Prospective studies will be needed to test this novel approach.
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