As eloquently described by Javid Syed in a chapter of TAG’s recent pipeline report, TB diagnostics remain woefully inadequate for addressing the challenges presented by the disease. One key goal for scientists is to find ways to better discriminate active from latent infection, and two recent papers describe possible progress in this effort.
In the journal Nature, Matthew Berry and colleagues use a systems biology approach to identify a gene expression pattern associated with active TB, and speculate that this pattern may be able to identify the individuals with latent infection most likely to develop disease; however, longitudinal studies will be needed to show whether this is indeed the case. The work is encouraging in that it suggests that new technologies may be able to address previously intractable problems in TB diagnosis, but translating these advances into something usable at the health posts where most people seek TB care will still be a daunting task.
The second paper in PLoS One reports on a more traditional approach of measuring cytokine production in whole blood (as is currently done with interferon gamma-based assays) but analyzes a broader range of cytokines after 7 days of in vitro stimulation with TB antigens. The researchers report that a combined analysis of TNF-alpha, IL-12 and IL-17 production after stimulation with the TB10.4 antigen was better able to discriminate between active TB cases and latent infection than the use of interferon gamma alone.
Nature. 2010 Aug 19;466(7309):973-7.
Berry MP, Graham CM, McNab FW, Xu Z, Bloch SA, Oni T, Wilkinson KA, Banchereau R, Skinner J, Wilkinson RJ, Quinn C, Blankenship D, Dhawan R, Cush JJ, Mejias A, Ramilo O, Kon OM, Pascual V, Banchereau J, Chaussabel D, O'Garra A.
Division of Immunoregulation, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK.
Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis, is a major cause of morbidity and mortality worldwide. Efforts to control it are hampered by difficulties with diagnosis, prevention and treatment. Most people infected with M. tuberculosis remain asymptomatic, termed latent TB, with a 10% lifetime risk of developing active TB disease. Current tests, however, cannot identify which individuals will develop disease. The immune response to M. tuberculosis is complex and incompletely characterized, hindering development of new diagnostics, therapies and vaccines. Here we identify a whole-blood 393 transcript signature for active TB in intermediate and high-burden settings, correlating with radiological extent of disease and reverting to that of healthy controls after treatment. A subset of patients with latent TB had signatures similar to those in patients with active TB. We also identify a specific 86-transcript signature that discriminates active TB from other inflammatory and infectious diseases. Modular and pathway analysis revealed that the TB signature was dominated by a neutrophil-driven interferon (IFN)-inducible gene profile, consisting of both IFN-gamma and type I IFN-alphabeta signalling. Comparison with transcriptional signatures in purified cells and flow cytometric analysis suggest that this TB signature reflects changes in cellular composition and altered gene expression. Although an IFN-inducible signature was also observed in whole blood of patients with systemic lupus erythematosus (SLE), their complete modular signature differed from TB, with increased abundance of plasma cell transcripts. Our studies demonstrate a hitherto underappreciated role of type I IFN-alphabeta signalling in the pathogenesis of TB, which has implications for vaccine and therapeutic development. Our study also provides a broad range of transcriptional biomarkers with potential as diagnostic and prognostic tools to combat the TB epidemic.
PLoS One. 2010 Aug 24;5(8). pii: e12365.
Sutherland JS, de Jong BC, Jeffries DJ, Adetifa IM, Ota MO.
Bacterial Diseases Programme, Medical Research Council Laboratories, Banjul, The Gambia.
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).
RESULTS AND 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.