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Minimal immune cell subset differences in a cohort of close contacts of tuberculosis index cases

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ABSTRACT Understanding the perturbations in immune response across the spectrum of TB infection is still unclear. In this study, we followed a cohort of close contacts of pulmonary TB patients with serial QFT testing at 0, 3, 6, and 12 months, and stratified them into six subgroups: QFT-increasing (low/high), QFT converters (QFT- to QFT+), QFT+ stable, and QFT- individuals. Despite these distinct QFT trajectories, we observed minimal differences in immune cell frequencies, activation profiles, and T helper subset distributions among the QFT subgroups, suggesting limited immunological stratification based on QFT dynamics alone. Ex vivo immune phenotyping, including analysis of CD4, CD8, and NKT cell frequencies, memory T cell subsets, and activated T cells (HLA-DR⁺CD38⁺), failed to distinguish between QFT subgroups. Antigen-specific CD4 T cell responses assessed by the activation-induced marker (AIM) assay were elevated in QFT+ compared to QFT- individuals. These findings suggest that blood-based immune profiling may not capture subtle immunological transitions among QFT converters or individuals with increasing QFT responses. In contrast, individuals with active TB (ATB) showed clear immune perturbations. ATB patients at diagnosis exhibited significantly elevated frequencies of antigen-specific CD4 T cells, increased activated T cells, and higher frequencies of intermediate monocytes and NK cells compared to QFT+/QFT- contacts. Many of these immune features declined with treatment, indicating therapy-associated immune resolution. Additionally, shifts in T helper subsets and effector memory populations were observed over the course of treatment. These results suggest that while ex vivo immune profiling can robustly distinguish active TB from non-diseased states, it lacks the resolution to differentiate QFT subgroups based on QFT dynamics alone. This could reflect either immunological similarity among close contacts regardless of QFT status or limitations of blood-based phenotyping in detecting early or subclinical immune shifts. Our study highlights the challenge of immunologically distinguishing QFT-defined subgroups within close contacts using conventional ex vivo profiling approaches.
Title: Minimal immune cell subset differences in a cohort of close contacts of tuberculosis index cases
Description:
ABSTRACT Understanding the perturbations in immune response across the spectrum of TB infection is still unclear.
In this study, we followed a cohort of close contacts of pulmonary TB patients with serial QFT testing at 0, 3, 6, and 12 months, and stratified them into six subgroups: QFT-increasing (low/high), QFT converters (QFT- to QFT+), QFT+ stable, and QFT- individuals.
Despite these distinct QFT trajectories, we observed minimal differences in immune cell frequencies, activation profiles, and T helper subset distributions among the QFT subgroups, suggesting limited immunological stratification based on QFT dynamics alone.
Ex vivo immune phenotyping, including analysis of CD4, CD8, and NKT cell frequencies, memory T cell subsets, and activated T cells (HLA-DR⁺CD38⁺), failed to distinguish between QFT subgroups.
Antigen-specific CD4 T cell responses assessed by the activation-induced marker (AIM) assay were elevated in QFT+ compared to QFT- individuals.
These findings suggest that blood-based immune profiling may not capture subtle immunological transitions among QFT converters or individuals with increasing QFT responses.
In contrast, individuals with active TB (ATB) showed clear immune perturbations.
ATB patients at diagnosis exhibited significantly elevated frequencies of antigen-specific CD4 T cells, increased activated T cells, and higher frequencies of intermediate monocytes and NK cells compared to QFT+/QFT- contacts.
Many of these immune features declined with treatment, indicating therapy-associated immune resolution.
Additionally, shifts in T helper subsets and effector memory populations were observed over the course of treatment.
These results suggest that while ex vivo immune profiling can robustly distinguish active TB from non-diseased states, it lacks the resolution to differentiate QFT subgroups based on QFT dynamics alone.
This could reflect either immunological similarity among close contacts regardless of QFT status or limitations of blood-based phenotyping in detecting early or subclinical immune shifts.
Our study highlights the challenge of immunologically distinguishing QFT-defined subgroups within close contacts using conventional ex vivo profiling approaches.

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