Analysis of Lymphocyte Immunologic Indexes in the Early Diagnosis of Active Pulmonary Tuberculosis of Adolescents in China.

Introduction: The aim of this study was to detect lymphocyte subpopulations to discover potential immunologic indicators to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and healthy controls (HC) and to predict the risk of progression of LTBI to ATB. Methodology: Flow cytometry was used to detect lymphocyte subsets in ATB, LTBI and HC to compare the differences in lymphocyte subpopulation levels between groups, and Logistic regression was used to screen ATB-related immune indices, development of a novel nomogram model to predict the risk of progression to ATB in individuals with LTBI. Results: Compared to the LTBI group, the ATB group had significantly higher CD3+CD4+T cell percentage, whereas CD3-CD16+CD56+NK cell percentage, lymphatic cell, CD3+T cell number, CD3+CD8+T cell number, and CD3-CD16+CD56+NK cell number were significantly lower (P<0.05). Compared with the HC group, the ATB group had significantly higher CD3+T cell percentage and CD3+CD4+T cell percentage, whereas CD3-CD16+CD56+NK cell percentage, lymphatic cell, CD3+T cell number, and CD3-CD16+CD56+NK cell number were significantly lower (P<0.05); logistic regression analysis showed that CD3+CD4+T cell percentage, CD3+T cell number, and CD3+CD8+T cell number were all independent indicators for the diagnosis of ATB (P<0.05), and based on these three immune indicators, we constructed diagnostic feature to distinguish ATB and LTBI, ATB from HC, and successfully developed a novel nomogram model to predict the risk of progression to ATB in individuals with LTBI. Conclusion: A combined assay of lymphocyte-associated immune markers serves as a biomarker for early ATB diagnosis in adolescents, and established a predictive model to evaluate the risk of progression of LTBI to ATB.