title: Whole-blood flow-cytometric analysis of antigen-specific CD4 T-cell cytokine profiles distinguishes active tuberculosis from non-active states.
abstract: T-cell based IFN-γ release assays do not permit distinction of active tuberculosis (TB) from successfully treated disease or latent M. tuberculosis infection. We postulated that IFN-γ and IL-2 cytokine profiles of antigen-specific T cells measured by flow-cytometry ex vivo might correlate with TB disease activity in vivo. Tuberculin (PPD), ESAT-6 and CFP-10 were used as stimuli to determine antigen-specific cytokine profiles in CD4 T cells from 24 patients with active TB and 28 patients with successfully treated TB using flow-cytometry. Moreover, 25 individuals with immunity consistent with latent M. tuberculosis infection and BCG-vaccination, respectively, were recruited. Although the frequency of cytokine secreting PPD reactive CD4 T cells was higher in patients with active TB compared to patients with treated TB (median 0.81% vs. 0.39% of CD4 T cells, p = 0.02), the overlap in frequencies precluded distinction between the groups on an individual basis. When assessing cytokine profiles, PPD specific CD4 T cells secreting both IFN-γ and IL-2 predominated in treated TB, latent infection and BCG-vaccination, whilst in active TB the cytokine profile was shifted towards cells secreting IFN-γ only (p<0.0001). Cytokine profiles of ESAT-6 or CFP-10 reactive CD4 T cells did not differ between the groups. Receiver operator characteristics (ROC) analysis revealed that frequencies of PPD specific IFN-γ/IL-2 dual-positive T cells below 56% were an accurate marker for active TB (specificity 100%, sensitivity 70%) enabling effective discrimination from non-active states. In conclusion, a frequency lower than 56% IFN-γ/IL-2 dual positive PPD-specific circulating CD4 T-cells is strongly indicative of active TB.
authors.affiliation: Department of Internal Medicine IV, Saarland University, Homburg, Germany.
authors.forename: Urban
authors.initials: U
authors.lastname: Sester
authors.forename: Mathias
authors.initials: M
authors.lastname: Fousse
authors.forename: Jan
authors.initials: J
authors.lastname: Dirks
authors.forename: Ulrich
authors.initials: U
authors.lastname: Mack
authors.forename: Antje
authors.initials: A
authors.lastname: Prasse
authors.forename: Mahavir
authors.initials: M
authors.lastname: Singh
authors.forename: Ajit
authors.initials: A
authors.lastname: Lalvani
authors.forename: Martina
authors.initials: M
authors.lastname: Sester
mesh_terms: D000942:Antigens, Bacterial / Q000097:blood* / Q000276:immunology; D001426:Bacterial Proteins / Q000276:immunology; D015496:CD4-Positive T-Lymphocytes / Q000276:immunology*; D003710:Demography; D003937:Diagnosis, Differential; D005260:Female; D005434:Flow Cytometry; D006801:Humans; D007371:Interferon-gamma / Q000097:blood*; D007376:Interleukin-2 / Q000097:blood*; D008297:Male; D008875:Middle Aged; D014376:Tuberculosis / Q000097:blood* / Q000175:diagnosis / Q000276:immunology*
chemical_list: D000942:Antigens, Bacterial; D001426:Bacterial Proteins; C117940:CFP-10 protein, Mycobacterium tuberculosis; C093276:ESAT-6 protein, Mycobacterium tuberculosis; D007376:Interleukin-2; D007371:Interferon-gamma