No abstract

BackgroundHumans infected with Mycobacterium tuberculosis (MTB) can delete the pathogen or otherwise become latent infection or active disease. However, the factors influencing the pathogen clearance and disease progression from latent infection are poorly understood. This study attempted to use a genome-wide transcriptome approach to identify immune factors associated with MTB infection and novel biomarkers that can distinguish active disease from latent infection.Methodology/Principal FindingsUsing microarray analysis, we comprehensively determined the transcriptional difference in purified protein derivative (PPD) stimulated peripheral blood mononuclear cells (PBMCs) in 12 individuals divided into three groups: TB patients (TB), latent TB infection individuals (LTBI) and healthy controls (HC) (n = 4 per group). A transcriptional profiling of 506 differentially expressed genes could correctly group study individuals into three clusters. Moreover, 55- and 229-transcript signatures for tuberculosis infection (TB<BI) and active disease (TB) were identified, respectively. The validation study by quantitative real-time PCR (qPCR) performed in 83 individuals confirmed the expression patterns of 81% of the microarray identified genes. Decision tree analysis indicated that three genes of CXCL10, ATP10A and TLR6 could differentiate TB from LTBI subjects. Additional validation was performed to assess the diagnostic ability of the three biomarkers within 36 subjects, which yielded a sensitivity of 71% and specificity of 89%.Conclusions/SignificanceThe transcription profiles of PBMCs induced by PPD identified distinctive gene expression patterns associated with different infectious status and provided new insights into human immune responses to MTB. Furthermore, this study indicated that a combination of CXCL10, ATP10A and TLR6 could be used as novel biomarkers for the discrimination of TB from LTBI.

BackgroundThe Mycobacterium tuberculosis (Mtb)-specific T-cell interferon gamma release assays (IGRAs) are useful in detecting Mtb infection but perform poorly at distinguishing active tuberculosis disease (ATB) and latent tuberculosis infection (LTBI). This study is aimed at evaluating additional cytokines as biomarkers besides interferon-gamma (IFN-γ) to improve the identification of ATB and LTBI.Methodology/Principal FindingsSixty-six patients with ATB, 73 household contacts (HHC) of ATB patients and 76 healthy controls (HC) were recruited to undergo QuantiFERON TB GOLD in-tube assay (QFT) and the enzyme-linked immunosorbent assay (ELISA) where the release of IFN-γ, IFN-γ inducible protein 10 (IP-10), Interleukin 2 (IL-2) and Tumor Necrosis Factor-α (TNF-α) was determined in the whole blood with or without antigen-stimulation. The positive rates of the QFT, IP-10 and IL-2 tests were 86.4%, 89.4% and 86.4% for the ATB group with no difference between them (p>0.05). However, QFT in combination with IP-10 and IL-2 significantly increased the detection rate to 95.5% in the ATB group (p = 0.03) and the indeterminate rate of all samples decreased from 2.3% (5/215) to 0.4% (1/215). The un-stimulated level of IP-10 was significantly higher in the HHC than the ATB and HC groups. The IP-10 responses were strongly associated with extended Mtb exposure time and the degree of smear-positivity of the index cases. The IL-2/IFN-γ ratio in the antigen-stimulated plasma could discriminate LTBI from ATB with a sensitivity of 77.2% and a specificity of 87.2%.ConclusionThe increased Mtb-specific antigen-stimulated expression of IP-10 and IL-2 may be useful for detecting both ATB and LTBI. Combining the QFT with IP-10 and IL-2 could increase the detection accuracy of active TB over the QFT alone.