Author Correction: A multi-cohort study of the immune factors associated with M. tuberculosis infection outcomes

Abstract

In this Letter, data from 2 out of the 17 progressors were inadvertently binned into the wrong time intervals. We have now re-analysed the entire dataset with all data points binned correctly with respect to the time intervals before tuberculosis (TB) diagnosis, and the first graph in Fig. 4b has been corrected (see Fig. 1 of this Amendment for the original figure). In the revised analysis, the time intervals are set at: >400, 201-400, 101-200 and 0-100 days before TB diagnosis (intervals in the original Fig. 4b were: 361-540, 181-360, 61-180 and 0-60 days). The comparisons between the levels of natural killer (NK) cells 1 year before TB diagnosis and at TB diagnosis, and between approximately 7 months before TB diagnosis and at TB diagnosis remain statistically significant (P = 0.0312 and P = 0.0039, respectively; P = 0.0078 and P = 0.0156 in the original Letter). The original observation of a significant decrease in the percentage of NK cells during the progression to active TB remains unchanged.In the original Letter, all non-progressors that had measurements for at least three time points were included. We have now included all non-progressors that had longitudinal measurements for at least two time points (n = 41). The second graph in Fig. 4b and the Reporting Summary have been corrected (see Fig. 1 of this Amendment for the original figure, and Supplementary Information of this Amendment for the original Reporting Summary). The revised analysis shows no significant change in the frequency of NK cells (P = 0.8828; P = 0.5202 in the original Letter) during the two-year study period.The receiver operating characteristic curves in Fig. 4c have been corrected (see Fig. 1 of this Amendment for the original figure). The new analysis shows an area under the curve (AUC) of 0.74 (95% confidence interval (CI) 0.58-0.90) in the three months (100 days) before active TB diagnosis (AUC = 0.80, CI = 0.64-0.96 in the two months (60 days) before active TB diagnosis in the original Letter), and an AUC of 0.69 (CI = 0.57-0.82) in the seven months (200 days) before active TB diagnosis (AUC = 0.74; CI = 0.63-0.85 in the 210 days before active TB diagnosis in the original Letter). These analyses do not change any of our conclusions. In addition, the name of author Qiantian Yang should have been spelled Qianting Yang, and the affiliation of author Stephanus T. Malherbe should only be 'P = 0.0078 P = 0.0156 3 6 1 -5 4 0 1 8 1 -3 6 0 6 1 -1 8 0 0 -6 0 0 5 10 15 20 25 NK cells (% of total live cells) D 0 D 1 8 0 D 3 6 0 D 5 4 0 0 5 10 15 20 25 P = 0.5202 Time points for blood draw Days before TB diagnosis Progressors Non-progressors Original Fig. 4b b Time points for blood draw Days before TB diagnosis Progressors Non-progressors NK cells (% of total live cells) D 0 D 1 8 0 D 3 6 0 D 5 4 0 0 5 10 15 20 25 P = 0.8828 > 4 0 0 2 0 1 -4 0 0 1 0 1 -2 0 0 0 -1 0 0 0 5 10 15 20 25 P = 0.0039 P = 0.0312 Corrected Fig. 4b 0 20 40 60 80 100 0 20 40 60 80 100 c 100% -speci city (%) Sensitivity (%) Days before active TB diagnosis 0-210 (AUC = 0....

Antibody Fc Glycosylation Discriminates Between Latent and Active Tuberculosis

“…Consistent with these findings, of the 193 Ab features incorporated into the model, 4 of the downselected 5 that were sufficient in discriminating latent and active tuberculosis included Fc or whole but not Fab Ab glycans ( Figure 4B ). Intriguingly, one feature also selected was Ab-mediated induction of CD107a surface expression on NK cells ( Figure 4B ), which is associated with activation and consistent with published literature linking NK cell function to latent tuberculosis in humans [ 5 , 43 ]. Thus, while there is a relative abundance of sialic acid and galactose on Fab domains, Ab glycosylation changes associated with disease resolution occur on the Fc domain and appear to impact Ab functions.…”

Impact of Mycobacterium tuberculosis Infection on Human B Cell Compartment and Antibody Responses

“…This finding was supported by gene expression and GSEA analysis, showing similar representation of B cell genes in active TB patients as compared to LTBI subjects and healthy donors. Thus, our results agree with previous studies reporting unaltered B cell frequencies in the blood of active TB patients and LTBI individuals as compared to healthy controls [ 47 ]. Conversely, other studies have shown significantly decreased or even increased [ 24 , 47 ] B cell frequencies in the peripheral blood of active TB patients [ 23 , 27 , 47 , 48 ] and LTBI [ 47 ] individuals compared to healthy controls.…”

“…Thus, our results agree with previous studies reporting unaltered B cell frequencies in the blood of active TB patients and LTBI individuals as compared to healthy controls [ 47 ]. Conversely, other studies have shown significantly decreased or even increased [ 24 , 47 ] B cell frequencies in the peripheral blood of active TB patients [ 23 , 27 , 47 , 48 ] and LTBI [ 47 ] individuals compared to healthy controls. These conflicting data likely reflect differences between study designs and groups of patients enrolled, varying by age, gender, ethnicity, form, and severity of TB disease [ 13 ].…”

Multimodal profiling of lung granulomas reveals cellular correlates of tuberculosis control

“…Data from human and animal models (including NHPs) suggest an important role for diverse lymphocyte populations in controlling Mtb infection. In addition to compelling evidence for the importance of conventional CD4+ and CD8+ T cells (Chen et al, 2009;Foreman et al, 2016;Lin and Flynn, 2015;Lin et al, 2012;Mogues et al, 2001), other lymphocyte populations have been implicated in control including gamma delta (γδ) T cells (Ogongo et al, 2020;Shen et al, 2019), iNKT cells (Arora et al, 2013;Chackerian et al, 2002;Chancellor et al, 2017), donor-unrestricted T cells such as MAITs (Joosten et al, 2019), innate lymphoid cells (ILC) (Ardain et al, 2019) and cytotoxic lymphocytes including NK cells (Lin and Flynn, 2015;Portevin et al, 2012;Roy Chowdhury et al, 2018).…”