Immunological correlates of mycobacterial growth inhibition describe a spectrum of tuberculosis infection

Abstract

A major contribution to the burden of Tuberculosis (TB) comes from latent Mycobacterium tuberculosis infections (LTBI) becoming clinically active. TB and LTBI probably exist as a spectrum and currently there are no correlates available to identify individuals with LTBI most at risk of developing active disease. We set out to identify immune parameters associated with ex vivo mycobacterial growth control among individuals with active TB disease or LTBI to define the spectrum of TB infection. We used a whole blood mycobacterial growth inhibition assay to generate a functional profile of growth control among individuals with TB, LTBI or uninfected controls. We subsequently used a multi-platform approach to identify an immune signature associated with this profile. We show, for the first time, that patients with active disease had the greatest control of mycobacterial growth, whilst there was a continuum of responses among latently infected patients, likely related to the degree of immune activation in response to bacillary load. Control correlated with multiple factors including inflammatory monocytes, activated and atypical memory B cells, IgG1 responses to TB-specific antigens and serum cytokines/chemokines. Our findings offer a method to stratify subclinical TB infections and the future potential to identify individuals most at risk of progressing to active disease and benefit from chemoprophylaxis.

Figure 1

Ex vivo differential mycobacterial control is associated with disease state in pre-treatment whole blood. Samples were collected from volunteers before starting anti-TB treatment. Whole blood MGIT using BCG Pasteur (A) and M.tb H37Rv (B) was performed and data meeting the inclusion criteria (duplicate ΔTTP < 6 hours) are shown (BCG: n = 11, n = 93, n = 35; H37Rv: n = 19, n = 101, n = 51; for active TB, LTBI and healthy controls, respectively). The association between BCG and H37Rv pre-treatment MGIT results was evaluated by Pearson’s correlation (C). Points represent the mean of duplicates; bars represent mean values with SD. A one-way multiple comparison ANOVA with Tukey’s post-test correction was performed between the groups. *Represents a p-value of <0.05, **a p-value of <0.005, ***a p-value of <0.0005 and ****a p-value of <0.0001.

Figure 2

Enhanced mycobacterial control decreases following TB treatment. Samples were collected from volunteers with active TB and LTBI between 1 to 6 months following completion of anti-TB treatment. Whole blood MGIT using BCG Pasteur (A) and M.tb H37Rv (B) was performed. Data meeting the inclusion criteria (duplicate ΔTTP < 6 hours) are shown. For MGIT data, points represent the mean of duplicates; bars represent mean values with SD. A paired t- test was performed to assess net growth before and after treatment. *Represents a p-value of <0.05, **a p-value of <0.01 and ****a p-value of <0.0001. Red circles = active TB and black = LTBI.

Figure 3

Altered proportions of intermediate and non-classical monocyte subsets are associated with differential mycobacterial control. Monocyte subsets were characterized among patients with active TB disease (n = 17), LTBI (n = 17) and healthy controls (n = 10) before starting anti-TB treatment. The proportions of classical (A), intermediate (B), and non-classical (C) monocytes were calculated from the total monocyte population. A negative correlation between intermediate monocytes and net growth (D), and a positive correlation between non-classical monocytes and net growth (E) of BCG were seen. The latter was also seen with M.tb H37Rv (data not shown). Monocyte subsets were then characterized after completion of treatment among active TB (n = 11) and LTBI (n = 14) patients. The proportions of intermediate (F) and non-classical (G) monocytes are shown. Points are single values and bars represent the mean with SD. After testing for normality, an ordinary one-way ANOVA with Tukey’s correction (A,C,G) or a Kruskal-Wallis test with Dunn’s correction for multiple comparisons (B,F) was performed. *Represents a p-value of <0.05, **a p-value of <0.005, ***a p-value of <0.0005 and ****a p-value of <0.0001. For correlations Spearman’s rho and associated p-values are shown.

Figure 4

Increases in activated and atypical memory B cells occur in M.tb infection and correlate with improved mycobacterial control. B cell subsets were characterised among patients with active TB disease (n = 19), LTBI (n = 18) and healthy controls (n = 9) before starting anti-TB treatment. The proportions of mature (A), naïve (B), classical (C), activated (D) and atypical (E) B cells are shown. Negative correlations between the proportion of activated (F) and atypical (G) B cells and BCG net growth were seen. Points are single values and bars represent the median with interquartile range. After testing for normality a Kruskal-Wallis test with Dunn’s correction for multiple comparisons was performed. *Represents a p-value of <0.05, **a p-value of <0.005, ***a p-value of <0.0005 and ****a p-value of <0.0001. Spearman’s rho and associated p-values are shown.

Figure 5

IgG1 responses to RD1 restricted M.tb-specific antigens are negatively correlated with mycobacterial net growth. Antigen-specific IgG2 (A) and IgG1 (B) responses in pre-treatment samples from active TB (n = 21), LTBI (n = 30) and healthy control individuals (n = 20) were determined by ELISA. Negative correlations between IgG1 responses to ESAT-6/CFP-10 and BCG (C) and M.tb H37Rv (D) net growth were seen. Antigens used were M.tb H37Rv-derived LAM, cell membrane fraction, culture filtrate and ESAT-6/CFP-10. Optical densities (ODs) are reported following subtraction of the background and plotted on a Log₁₀ scale. Points represent the mean of duplicates and bars are the median values with the interquartile range. After normality testing a Kruskal-Wallis test with Dunn’s correction for multiple comparisons was performed for each antigen. *Represents a p-value of <0.05, **a p-value of <0.01, ***a p-value of <0.005 and ****a p-value of <0.0001. Spearman’s rho and associated p-values are shown. Red circles = active TB, grey squares = LTBI and blue triangles = healthy controls.

Figure 6

Serum cytokine analysis reveals discrete clusters, which delineate the spectrum of M.tb infection and strong negative correlations with ex vivo mycobacterial growth. Serum cytokine/chemokine responses in pre-treatment samples from active TB (n = 20), LTBI (n = 83) and healthy control individuals (n = 30) were investigated by Luminex assay. A heatmap of cytokine/chemokine levels (log, row scaled, pg/ml) is shown. Samples were clustered according to Spearman correlation distance and the four most distinct clusters were coloured in black, grey, blue and red. For clustering of cytokines/chemokines into three clusters, k-means clustering was applied to the rows.

Figure 7

A spectrum of M.tb infection and associated immune profiles. We propose that the delineation of the spectrum of M.tb infection identified by the MGIT MGIA, and the underlying immunological profiles associated with this spectrum, is biologically plausible and may have value in identifying subclinical active TB disease and possibly in determining reactivation risk of LTBI.