Biomarkers for discrimination between latent tuberculosis infection and active tuberculosis disease

doi:10.1016/j.jinf.2016.11.010

Journal of Infection

Volume 74, Issue 3, March 2017, Pages 281-293

https://doi.org/10.1016/j.jinf.2016.11.010 Get rights and content

Highlights

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Combinations of cytokine biomarkers improved the detection of Mtb-infection.
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Biomarkers improved the ability to discriminate between active TB and LTBI.
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Biomarkers improved the ability to discriminate between active TB and non-active TB.
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VEGF is a key biomarker for reflecting active TB.

Summary

Objective

We aimed to determine whether combinations of multiplex cytokine responses could differentiate Mycobacterium tuberculosis (Mtb) infection states.

Methods

Mtb-specific antigen-induced and unstimulated cytokines were measured by Luminex assay in supernatants of QuantiFERON^® Gold In-Tube assay (QFT) in 48 active pulmonary TB patients (TB), 15 latent TB infection subjects (LTBI), and 13 healthy controls (HCs).

Results

Among the 29 cytokines, eight Mtb antigen-specific biomarkers (GM-CSF, IFN-γ, IL-1RA, IL-2, IL-3, IL-13, IP-10, and MIP-1β) in the Mtb-infected group were significantly different from those of the HCs. Five Mtb-specific biomarkers (EGF, GM-CSF, IL-5, IL-10, and VEGF), two unstimulated biomarkers (TNF-α_[Nil] and VEGF_[Nil]), and one Mtb-specific biomarker ratio (IL-2/IFN-γ) showed significant differences between active TB and LTBI. Three unstimulated biomarkers (IL-8_[Nil], IL-13_[Nil], and VEGF_[Nil]) and 5 Mtb-specific biomarkers (IFN-γ, IL-2, IL-3, IP-10, and VEGF) were significantly different between active TB and non-active TB groups. Combinations of three cytokine biomarkers resulted in the accurate prediction of 92.1–93.7% of Mtb-infected cases and 92.3–100% of HCs, respectively. Moreover, combinations of five biomarkers accurately predicted 90.9–100% of active TB cases and 80–100% of LTBI subjects, respectively. In discriminating between active TB and non-active TB regardless of QFT results, combinations of six biomarkers predicted 79.2–95.8% of active TB cases and 67.9–89.3% of non-active TB subjects.

Conclusions

Taken together, our data suggest that combinations of whole blood Mtb antigen-dependent cytokines could serve as biomarkers to determine TB disease states. Especially, VEGF is highlighted as a key biomarker for reflecting active TB, irrespective of stimulation.

Introduction

Tuberculosis (TB) is a leading global public health problem with high morbidity and mortality in humans.¹ Although most individuals infected with Mycobacterium tuberculosis (Mtb) remain healthy, a state referred to as latent TB infection (LTBI), approximately 10% of these individuals will eventually develop active TB.² The development of a rapid diagnostic test that can distinguish between active TB and LTBI or active TB and non-active TB, as well as detect Mtb infection, is very important for TB control. There is no gold standard for diagnosis of Mtb infection, and, until recently, the tuberculin skin test (TST) was the only tool available for detecting LTBI. Interferon (IFN)-gamma release assays (IGRAs), which depend on the detection of a single cytokine, IFN-γ, in response to Mtb-specific antigens, have been introduced as an alternative to TST for the diagnosis of Mtb infection. However, both TST and IGRA are intrinsically unable to discriminate between active TB and LTBI.³ In addition, even with active TB patients in a high-burden setting, these assays show low sensitivity because of advanced disease, malnutrition, and immunosuppression in patients, as well as low specificity due to a high background prevalence of LTBI.⁴

To address these limitations, new techniques, including transcript microarrays, flow cytometry of intracellular cytokines, and multiplex microbead-based immunoassay (Luminex assay) of cytokines, have recently been introduced.5, 6, 7, 8, 9 In these studies, the simultaneous detection of multiple analytes rather than a single analyte has been found to be a promising approach to discriminate between active TB and LTBI. More specifically, the combination of soluble CD40 ligand (sCD40L), epidermal growth factor (EGF), IFN-α, interleukin (IL)-1α, IL-1 receptor antagonist (IL-1RA), IL-4, IL-12 (p40), IL-15, IL-17, macrophage inflammatory protein (MIP)-1β, monocyte chemotactic protein (MCP)-1, transforming growth factor (TGF)-α, tumor necrosis factor (TNF)-α, or vascular endothelial growth factor (VEGF) responses after stimulation with Mtb-specific antigens, as measured by Luminex assay, has been reported for the rapid differential diagnosis of active TB versus LTBI. However, these studies have selected different cytokines to detect active TB, and far less is known about the reliability of selected cytokines for the diagnosis of active TB. Therefore, the clinical relevance of cytokine responses remains to be clarified.

The aims of the present study were to assess 29 background-corrected Mtb-specific antigen-stimulated cytokine/chemokine biomarker levels in supernatants from the whole blood IGRA obtained from 4 major diagnostic groups, including Mtb-uninfected healthy controls (HCs), LTBI, IGRA-negative active TB, and IGRA-positive active TB, to examine whether these biomarkers can increase the sensitivity of detecting Mtb-infected individuals, especially patients with IGRA-negative active TB, and to determine whether such biomarkers can discriminate between active TB and LTBI or between active TB and non-active TB.

Section snippets

Subjects

A total of 48 culture-confirmed active TB patients, 15 LTBI subjects, and 13 HCs were recruited at Chonnam National University Hospital, Gwangju, South Korea. All enrolled subjects were negative for anti-human immunodeficiency (HIV) antibody. All active TB were pulmonary TB and was diagnosed based on the guidelines of the American Thoracic Society and the U.S. Centers for Disease Control and Prevention.¹⁰ Active TB patients were divided into two experimental groups according to IGRA results:

Study subjects

A total of 76 subjects, including 48 active TB patients, 15 LTBI subjects, and 13 HCs were enrolled in this cohort study. According to QFT results, 48 active TB patients were subdivided into two groups: 36 patients with QFT-positive active TB (TB_QFT+) and 12 patients with QFT-negative active TB (TB_QFT−). The clinical and demographic characteristics of the study subjects are summarized in Table 1. No LTBI subjects were receiving LTBI treatment at the time of sampling.

Signatures of biomarkers in unstimulated supernatants

Of 29 total biomarkers

Discussion

To the best of our knowledge, this study determined the most extensive list of cytokine/chemokine biomarkers able to detect Mtb-infected individuals (8 biomarkers) or discriminate between active TB and LTBI (8 biomarkers) from residual QFT samples obtained from participants in HC, LTBI, and active TB populations. Importantly, combinations of these biomarkers were found to improve the potential to detect Mtb-infected individuals, particularly in active TB patients that were undetectable with

Conflict of interest

No potential conflict of interest relevant to this article was reported.

Acknowledgments

This study was supported by the National Research Foundation of Korea funded by the Korean Government (Grant 2015R1D1A1A01059762) and the Chonnam National University Hospital Biomedical Research Institute (Grant CRI15003-1 and CRI16011-1).

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IL-1RA, IFN-γ, CXCL10/IP-10, and CCL4/MIP-1β levels were higher in the active TB group than in the LTBI group in QFT-GIT antigen (GIT Ag) tubes. In QFT-plus tubes, IL-1RA was higher in TB1 and TB2 tubes, while CCL2/MCP-1 was higher only in TB2 tubes. In Nil tubes, CCL5/RANTES, TNF-α, PDGF-BB, and IL-2 levels were significantly higher in the active TB group. IL-1RA in GIT Ag tubes showed the highest area under the curve of 0.8367. The sensitivity and specificity of IL-1RA were 66.7% (95% confidence interval [CI]: 43.0–85.4) and 90.5% (95% CI: 69.6–98.8), respectively, which were the highest among the cytokines.
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^e: EJW and JHC contributed equally to this work.

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Biomarkers for discrimination between latent tuberculosis infection and active tuberculosis disease

Highlights

Summary

Objective

Methods

Results

Conclusions

Introduction

Section snippets

Subjects

Study subjects

Signatures of biomarkers in unstimulated supernatants

Discussion

Conflict of interest

Acknowledgments

Mayo Clin Proc

Chest

Exp Gerontol

J Infect

J Infect

Tuberculosis

Tuberculosis

Cell Immunol

Global tuberculosis report

Consensus statement. Global burden of tuberculosis: estimated incidence, prevalence, and mortality by country. WHO Global Surveillance and Monitoring Project

JAMA

An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis

Nature

Multifunctional CD4(+) T cells correlate with active Mycobacterium tuberculosis infection

Eur J Immunol

Host markers in QuantiFERON supernatants differentiate active TB from latent TB infection: preliminary report

BMC Pulm Med

Production of TNF-alpha, IL-12(p40) and IL-17 can discriminate between active TB disease and latent infection in a West African cohort

PLoS One

Persistence of anti-HBs among health care personnel immunized with hepatitis B vaccine

Am J Public Health