Lymphocyte-Related Immunological Indicators for Stratifying Mycobacterium tuberculosis Infection

Abstract

BackgroundEasily accessible tools that reliably stratify Mycobacterium tuberculosis (MTB) infection are needed to facilitate the improvement of clinical management. The current study attempts to reveal lymphocyte-related immune characteristics of active tuberculosis (ATB) patients and establish immunodiagnostic model for discriminating ATB from latent tuberculosis infection (LTBI) and healthy controls (HC).MethodsA total of 171 subjects consisted of 54 ATB, 57 LTBI, and 60 HC were consecutively recruited at Tongji hospital from January 2019 to January 2021. All participants were tested for lymphocyte subsets, phenotype, and function. Other examination including T-SPOT and microbiological detection for MTB were performed simultaneously.ResultsCompared with LTBI and HC, ATB patients exhibited significantly lower number and function of lymphocytes including CD4+ T cells, CD8+ T cells and NK cells, and significantly higher T cell activation represented by HLA-DR and proportion of immunosuppressive cells represented by Treg. An immunodiagnostic model based on the combination of NK cell number, HLA-DR+CD3+ T cells, Treg, CD4+ T cell function, and NK cell function was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.920 (95% CI, 0.867-0.973) in distinguishing ATB from LTBI, while the cut-off value of 0.676 produced a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and specificity of 91.23% (95% CI, 81.06%-96.20%). Meanwhile, AUC analysis between ATB and HC according to the diagnostic model was 0.911 (95% CI, 0.855-0.967), with a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and a specificity of 90.00% (95% CI, 79.85%-95.34%).ConclusionsOur study demonstrated that the immunodiagnostic model established by the combination of lymphocyte-related indicators could facilitate the status differentiation of MTB infection.

Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

“…Results from blood examination, biochemical tests, coagulation detection, and T-SPOT assay showed mediocre value in identifying Mtb infection status [ 18 , 19 ]. In addition, the value of the detection targeting lymphocyte number and function for TB diagnostics was also confirmed by two recent reports [ 20 , 21 ]. Although these tests were of limited discriminatory value when they were used separately, the diagnostic performance of these data could be effectively improved when the data is integrated with appropriate algorithm.…”

Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection

“…Although many advances have been achieved, especially in omics field (60-62), there were some practical limitations for their clinical application, including expensive laboratory facilities and sophisticated operating procedures. Meanwhile, immunodiagnostics has received considerable attention as an alternative for discrimination of MTB infection status in recent years (63)(64)(65)(66)(67)(68)(69)(70). Nevertheless, the identified biomarkers including proteins and cytokines in serum or plasma for diagnostic aim may not be specific for TB due to the influence brought by other immune related diseases such as infection and autoimmune diseases (71)(72)(73)(74)(75)(76)(77).…”

Differential activation of innate and adaptive lymphocytes during latent or active infection with Mycobacterium tuberculosis

“…The active TB patients included in this study had lymphopenia, which was caused by reduced numbers of Th cells, Tγδ cells, and ILC1s. Previous studies have reported reduced numbers of these three lymphocyte subsets in active TB patients 13,45–47 . The decreased numbers of peripheral blood lymphocytes in active TB patients could be caused by migration of these cells to the infected organs, the lungs.…”

“…Previous studies have reported reduced numbers of these three lymphocyte subsets in active TB patients. 13,[45][46][47] The decreased numbers of peripheral blood lymphocytes in active TB patients could be caused by migration of these cells to the infected organs, the lungs. In the BAL cell suspensions from the active TB patients included in this study, ILC1s were the most abundant ILC subset, which is consistent with reports that intranasal immunization of mice with M. bovis BCG, 12 or with a subunit vaccine against Mtb (ESAT-6 with c-di-AMP as an adjuvant), 48 increases the number of ILC1s in mice lungs.…”