Production of TNF-alpha, IL-12(p40) and IL-17 can discriminate between active TB disease and latent infection in a West African cohort.
BACKGROUND
Mycobacterium tuberculosis (MTb) infects approximately 2 billion people world-wide resulting in almost 2 million deaths per year. Determining biomarkers that distinguish different stages of tuberculosis (TB) infection and disease will provide tools for more effective diagnosis and ultimately aid in the development of new vaccine candidates. The current diagnostic kits utilising production of IFN-gamma in response to TB antigens can detect MTb infection but are unable to distinguish between infection and disease. The aim of this study was to assess if the use of a longer term assay and the analysis of multiple cytokines would enhance diagnosis of active TB in a TB-endemic population.


METHODS
We compared production of multiple cytokines (TNF-alpha, IFN-gamma, IL-10, IL-12(p40), IL-13, IL-17 and IL-18) following long-term (7 days) stimulation of whole-blood with TB antigens (ESAT-6/CFP-10 (EC), PPD or TB10.4) from TB cases (n = 36) and their Mycobacterium-infected (TST+; n = 20) or uninfected (TST-; n = 19) household contacts (HHC).


CONCLUSIONS
We found that TNF-alpha production following EC stimulation and TNF-alpha and IL-12(p40) following TB10.4 stimulation were significantly higher from TB cases compared to TST+ HHC, while production of IFN-gamma and IL-13 were significantly higher from TST+ compared to TST- HHC following PPD or EC stimulation. Combined analysis of TNF-alpha, IL-12(p40) and IL-17 following TB10.4 stimulation resulted in 85% correct classification into TB cases or TST+ HHC. 74% correct classification into TST+ or TST- HHC was achieved with IFN-gamma alone following TB10.4 stimulation (69% following EC) and little enhancement was seen with additional cytokines. We also saw a tendency for TB cases infected with M. africanum to have increased TNF-alpha and IL-10 production compared to those infected with M. tuberculosis. Our results provide further insight into the pathogenesis of tuberculosis and may enhance the specificity of the currently available diagnostic tests, particularly for diagnosis of active TB.
Sutherland
Jayne S
JS
Bacterial Diseases Programme, Medical Research Council Laboratories, Banjul, The Gambia. jsutherland@mrc.gm
de Jong
Bouke C
BC
Jeffries
David J
DJ
Adetifa
Ifedayo M
IM
Ota
Martin O C
MO
D000293:Adolescent; D000354:Africa, Western; D000942:Antigens, Bacterial / Q000276:immunology; D015331:Cohort Studies; D017077:Culture Media, Conditioned / Q000378:metabolism; D003937:Diagnosis, Differential; D006801:Humans; D018664:Interleukin-12 / Q000096:biosynthesis*; D020381:Interleukin-17 / Q000096:biosynthesis*; D055985:Latent Tuberculosis / Q000175:diagnosis* / Q000276:immunology / Q000378:metabolism*; D008297:Male; D015999:Multivariate Analysis; D009169:Mycobacterium tuberculosis / Q000502:physiology; D011993:Recombinant Fusion Proteins / Q000276:immunology; D013997:Time Factors; D014373:Tuberculin / Q000276:immunology; D014374:Tuberculin Test; D014409:Tumor Necrosis Factor-alpha / Q000096:biosynthesis*; D055815:Young Adult
D000942:Antigens, Bacterial; D017077:Culture Media, Conditioned; C505464:ESAT-6-CFP10 fusion protein; D020381:Interleukin-17; D011993:Recombinant Fusion Proteins; C501710:TB10.4 antigen, Mycobacterium tuberculosis; D014373:Tuberculin; D014409:Tumor Necrosis Factor-alpha; D018664:Interleukin-12
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