الملخص
Background: Mycobacterium tuberculosis (Mtb) adapts many strategies to persist and replicate inside human tissue. One such strategy is the manipulation of CD4+ TH cells for subset interconversion to regulatory subsets. The aim of the present study is to get an insight of dynamic changes of CD4+ TH cells to regulatory subsets, CD4+ CD25+ forkhead box P3 (Foxp3)+ T-cells and CD4+ CD25+ Foxp3+ programmed death molecule-1 (Foxp3+) T-cells, in peripheral blood in Mtb-infected individuals and healthy contacts in a high-burden setting from Assam, Northeast India. Materials and Methods: A case–control study was conducted in newly diagnosed active pulmonary tuberculosis (APTBs) patients and 2 sets of controls: (i) individuals infected with latent tuberculosis infection (LTBI) and (ii) healthy close tuberculosis healthy contacts (HCs). The frequencies of different subsets of CD4+ cells with regulatory markers were measured in peripheral blood in 3 groups of study participants. Results and Observations: Frequencies of CD4+ CD25+ Foxp3+ T-cells (1.84 ± 1.40 vs. 4.32 ± 1.82 vs. 11.30 ± 3.66), CD4+ CD25+ Foxp3+ PD1+ T-cells (0.37 ± 1.28 vs. 2.99 ± 3.69 vs. 14.54 ± 5.10) and ligand (PD-L1)-positive CD4+ TH cells (0.80 ± 0.45 vs. 2.28 ± 0.95 vs. 7.13 ± 2.02) were significantly increased from HCs to LTBIs to APTB patients, respectively (P < 0.0001). No significant changes in frequencies of total CD4+ cells were observed between APTBs (29.51 ± 11.93), LTBIs (29.23 ± 8.16) and HCs (28.16 ± 9.73) whereas the mean ratios of CD4+ to CD4+ CD25+ FoxP3+ were significantly decreased from 34.34 ± 47.56 in HCs to 7.96 ± 5.8 in LTBIs to 3.12 ± 2.58 in APTBs (P < 0.0001). Significant decrease in mean ratios of CD4+ CD25+ FoxP3+ to CD4+ CD25+ FoxP3+ PD1+ were also observed from 4.97 ± 1.09 in HCs to 1.44 ± 0.49 in LTBIs to 0.78 ± 0.72 in APTBs. Conclusion: CD4+ TH cells change dynamically to regulatory subsets depending on the status of infection and a shift of response towards excessive regulatory T-cells, and PD-1/PD-L1 production may help in the development of active infection in latently infected individuals. These immunological parameters may be used, as potential biomarkers to see the changing dynamics of Mtb infection.