Unknown

Dataset Information

0

Combined Analysis of IFN-γ, IL-2, IL-5, IL-10, IL-1RA and MCP-1 in QFT Supernatant Is Useful for Distinguishing Active Tuberculosis from Latent Infection.


ABSTRACT: The QuantiFERON®-TB Gold In-Tube test (QFT), an interferon-γ release assay, is used to diagnose Mycobacterium tuberculosis, but its inaccuracy in distinguishing active tuberculosis from latent infection is a major concern. There is thus a need for an easy and accurate tool for achieving that goal in daily clinical settings. This study aimed to identify candidate cytokines for specifically differentiating active tuberculosis from latent infection. Our study population consisted of 31 active TB (tuberculosis) patients, 29 LTBI (latent tuberculosis infection) patients and 10 healthy control subjects. We assayed for 27 cytokines in QFT supernatants of both specific antigen-stimulated blood samples (TBAg) and negative-control samples (Nil). We analyzed their specificities and sensitivities by creating receiver operating characteristic (ROC) curves and measuring the area under those curves (AUCs). In TBAg-Nil supernatants, IL-10, IFN-γ, MCP-1 and IL-1RA showed high AUCs of 0.8120, 0.7842, 0.7419 and 0.7375, respectively. Compared with each cytokine alone, combined assay for these top four cytokines showed positive rates in diagnosing active TB, and GDA analysis revealed that MCP-1 and IL-5 are potent in distinguishing active TB from LTBI, with Wilk's lambda = 0.718 (p < 0.001). Furthermore, utilizing the unique characteristic of IL-2 that its TBAg-Nil supernatant levels are higher in LTBI compared to active TB, the difference between IFN-γ and IL-2 showed a large AUC of 0.8910. In summary, besides IFN-γ, IL-2, IL-5, IL-10, IL-1RA and MCP-1 in QFT supernatants may be useful for distinguishing active TB from LTBI. Those cytokines may also help us understand the difference in pathogenesis between active TB and LTBI.

SUBMITTER: Suzukawa M 

PROVIDER: S-EPMC4817970 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC2679252 | biostudies-literature
| S-EPMC10331420 | biostudies-literature
| S-EPMC6788090 | biostudies-other
| S-EPMC3914637 | biostudies-literature
| S-EPMC7885875 | biostudies-literature
| S-EPMC2556346 | biostudies-literature
| S-EPMC4718545 | biostudies-literature
| S-EPMC3062297 | biostudies-literature
| S-EPMC5220308 | biostudies-literature
| S-EPMC4543906 | biostudies-literature