Multifunctional Analysis of CD4⁺T-Cell Response as Immune-Based Model for Tuberculosis Detection

Abstract

Mono- and multifunctional specific CD4+ and CD8+ T-cell responses were evaluated to improve the immune-based detection of active tuberculosis (TB) and latent infection (LTBI). We applied flow cytometry to investigate cytokines profile (IFN-γ, TNF-α, and IL-2) of T cells after stimulation with TB antigens in 28 TB-infected subjects (18 active TB and 10 LTBI) and 10 uninfected controls. Cytokines production by CD4+ T cells at single-cell levels was higher in TB-infected subjects than uninfected controls (P < 0.0001). Assigning to activated CD4+ T cells, producing any of the three cytokines, a cut-off >0.45%, it was possible to differentiate TB-infected (>0.45%) by uninfected subjects (<0.45%). Among TB-infected subjects, the frequencies of multifunctional CD4+ T cells, simultaneously producing all 3 cytokines, are lower in active TB than LTBI subjects (P = 0.003). Thus, assigning to triple-positive CD4+ T cells a cut-off <0.182%, TB-infected individuals could be classified as active TB subjects (<0.182%) or LTBI subjects (>0.182%). The magnitude of CD8+ T-cell responses showed no differences between active TB and LTBI. Multifunctional CD4+ T-cell responses could have the potential to identify at single time point subjects without TB infection and patients having active or latent TB.

Immunological diagnosis as an adjunctive tool for an early diagnosis of tuberculous meningitis of an immune competent child in a low tuberculosis endemic country: a case report

“…Intracellular response in peripheral blood showed firstly a TB infection, revealed by neither TST nor Quantiferon. Moreover the polyfunctional CD4 profile suggested a pattern associated to active TB, according to the previously proposed algorithm [10]. The same test performed in CSF confirmed a M. tuberculosis infection with a high local immune specificity.…”

Treatment of latent tuberculosis infection induces changes in multifunctional Mycobacterium tuberculosis-specific CD4+ T cells

“…The TB antigens are pools of overlapping peptides and pooled together as a single stimulation condition. Whole blood was co-stimulated with anti-CD28 plus anti-CD49d (5 μl/ml, BD Bioscience, Pharmingen, Italy) as indicated by several authors [11,12,24], and Brefeldin A (10 μg/ml, Sigma-Aldrich) was immediately added to each tube, as previously described [16,20]. In brief, after 18 h of incubation, the cell surface staining was performed with the following markers: anti-CD45-VioBlue, anti-CD4 PE-Vio770, and anti-CD8 PerCP (Miltenyi Biotec, Germany) and the red cells were lysed with 1 ml FACS Lysing Solution (BD Bioscience).…”

“…First and foremost, we analysed a relatively small number of patients within each clinical group, even if the number of subjects enrolled is comparable to those described in similar reports [10,16,20,29]. Secondly, this is a cross-sectional study, and determining the clinical utility of cytokine profiles of Mtb-specific T cells for treatment monitoring will require a longitudinal study.…”

“…With a view of improving discrimination between active TB and LTBI, alternative immunological methods have also been investigated in recent years [10][11][12][13][14][15][16]. In particular, the determination of multifunctional Mtb-specific T cells secreting a range of cytokines (IFN-γ, IL-2, and TNF-α) by multiparameter intracellular cytokine flow cytometry (ICCFC) appears to show a better diagnostic yield than Abstract To ascertain whether multiparametric flow cytometry assessment of multifunctional Mycobacterium tuberculosis (Mtb)-specific CD4 + and CD8 + T cells can distinguish between untreated and treated patients with latent tuberculosis infection (LTBI), we enrolled 14 LTBI subjects treated with isoniazid (INH) therapy, 16 untreated LTBI patients, and 25 healthy controls.…”

“…The significant changes in the cytokine profiles of Mtb-specific T cells after INH therapy suggest that analysis IGRA to detect TB infection [17][18][19][20]. Indeed, ICCFC has been reported to improve discrimination between active TB and LTBI [10][11][12][13][14][15][16] and to enable more reliable monitoring of responses to TB treatment [11-13, 21, 22].…”