Biomarkers on patient T cells diagnose active tuberculosis and monitor treatment response
Toidi Adekambi, … , Susan M. Ray, Jyothi Rengarajan
Toidi Adekambi, … , Susan M. Ray, Jyothi Rengarajan
Published March 30, 2015
Citation Information: J Clin Invest. 2015;125(5):1827-1838. https://doi.org/10.1172/JCI77990.
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Clinical Medicine Immunology Infectious disease Microbiology

Biomarkers on patient T cells diagnose active tuberculosis and monitor treatment response

Abstract

BACKGROUND. The identification and treatment of individuals with tuberculosis (TB) is a global public health priority. Accurate diagnosis of pulmonary active TB (ATB) disease remains challenging and relies on extensive medical evaluation and detection of Mycobacterium tuberculosis (Mtb) in the patient’s sputum. Further, the response to treatment is monitored by sputum culture conversion, which takes several weeks for results. Here, we sought to identify blood-based host biomarkers associated with ATB and hypothesized that immune activation markers on Mtb-specific CD4+ T cells would be associated with Mtb load in vivo and could thus provide a gauge of Mtb infection.

METHODS. Using polychromatic flow cytometry, we evaluated the expression of immune activation markers on Mtb-specific CD4+ T cells from individuals with asymptomatic latent Mtb infection (LTBI) and ATB as well as from ATB patients undergoing anti-TB treatment.

RESULTS. Frequencies of Mtb-specific IFN-γ+CD4+ T cells that expressed immune activation markers CD38 and HLA-DR as well as intracellular proliferation marker Ki-67 were substantially higher in subjects with ATB compared with those with LTBI. These markers accurately classified ATB and LTBI status, with cutoff values of 18%, 60%, and 5% for CD38+IFN-γ+, HLA-DR+IFN-γ+, and Ki-67+IFN-γ+, respectively, with 100% specificity and greater than 96% sensitivity. These markers also distinguished individuals with untreated ATB from those who had successfully completed anti-TB treatment and correlated with decreasing mycobacterial loads during treatment.

CONCLUSION. We have identified host blood-based biomarkers on Mtb-specific CD4+ T cells that discriminate between ATB and LTBI and provide a set of tools for monitoring treatment response and cure.

TRIAL REGISTRATION. Registration is not required for observational studies.

FUNDING. This study was funded by Emory University, the NIH, and the Yerkes National Primate Center.

Authors

Toidi Adekambi, Chris C. Ibegbu, Stephanie Cagle, Ameeta S. Kalokhe, Yun F. Wang, Yijuan Hu, Cheryl L. Day, Susan M. Ray, Jyothi Rengarajan

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Figure 3

CD38, HLA-DR, and Ki-67 expression on IFN-γ+CD4+ T cells discriminates between ATB and LTBI in the test cohort.

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CD38, HLA-DR, and Ki-67 expression on IFN-γ+CD4+ T cells discriminates b...
PBMCs from individuals with LTBI (black circles, n = 25) and ATB (white squares, n = 24) were stimulated with Mtb-CW antigens and ESAT6-CFP10 peptide pools or nonstimulated (NS). The frequencies of activated Mtb-specific CD4+ T cells were analyzed by flow cytometry. Representative flow plots and summary of the data are shown for frequencies of CD38+IFN-γ+ T cells (A and D), HLA-DR+IFN-γ+ T cells (B and E), and Ki-67+IFN-γ+ T cells (C and F) in LTBI and ATB groups. The percentages represent the frequencies of Mtb-specific IFN-γ+CD4+ T cells that express CD38, HLA-DR, or Ki-67. ROC analysis to determine the predictive value of each marker for classifying ATB and LTBI (Supplemental Figure 2) resulted in AUC values of 1.0. The red, dashed lines represent the discrimination threshold for each marker and show cutoff values of 18%, 60%, and 5% for CD38+IFN-γ+, HLA-DR+IFN-γ+, and Ki-67+IFN-γ+, respectively. Mann-Whitney U test was used to compare the 2 groups. Bars represent medians. P < 0.05 was considered statistically significant.