Computational protocol: T-Cell Immunophenotyping Distinguishes Active From Latent Tuberculosis

Similar protocols

Protocol publication

[…] The data were analyzed on FlowJo version 9.4.4,TreeStar, Inc. Events were gated on live cells, singlets, and lymphocytes using forward and side scatter properties. CD3+CD4+ and CD3+ CD8+ subsets were defined. Gating controls were used to define IFN-γ, IL-2, and TNF-α responses and surface marker expression.For phenotypic analysis of M. tuberculosis-specific cells, only participants with a positive response were included. Positive responders were defined as those with a response that was ≥2 times the background (in unstimulated but fully stained samples) and >0.001% of CD3+CD4+ or CD3+CD8+ cells. This cutoff was used because we did not use costimulation to enhance responses, and we normalized to background (unstimulated) data before applying the cutoff (rather than classifying background as negligible). A strict cutoff meant only antigen-specific cells were included in the phenotypic analysis. [...] Statistical analysis was conducted using IBM SPSS Statistics version 20 and GraphPad Prism version 5.00 for Mac OS X, GraphPad Software, California. Tuberculosis disease stage compared all tuberculosis (n = 13) vs all latent tuberculosis infection (n = 21) regardless of HIV status, the impact of HIV compared all HIV-infected (n = 17) vs uninfected (n = 17) regardless of tuberculosis disease stage and across all 4 subgroups. The 2-tailed Mann–Whitney U test was used for nonparametric 2-sample comparisons. Spearman rank correlation coefficients were used to test correlations. Receiver operator characteristic (ROC) curve defined the sensitivity and specificity of the diagnostic approach. […]

Pipeline specifications

Software tools FlowJo, SPSS
Applications Miscellaneous, Flow cytometry
Organisms Mycobacterium tuberculosis
Diseases Neoplasms, Tuberculosis, HIV Infections, Latent Tuberculosis