Identification of plasma biomarkers for discrimination between tuberculosis infection/disease and pulmonary non tuberculosis disease.

Juraj Ivanyi,Marco Pio La Manna,Nadia Caccamo,Guido Sireci,Francesco Dieli,Paolo Li Donni,Paola Di Carlo,Antonio Cascio,Valentina Orlando

doi:10.1371/journal.pone.0192664

Juraj Ivanyi, Marco Pio La Manna + Show 7 more

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https://doi.org/10.1371/journal.pone.0192664

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Abstract

We used the Luminex Bead Array Multiplex Immunoassay to measure cytokines, chemokines and growth factors responses to the same antigens used for RD1-based Interferon γ Release Assay (IGRA) test. Seventy-nine individuals, 27 active TB, 32 latent infection subsets, 20 individuals derivative purified protein (PPD) negative (subjects that do not have any indurative cutaneous reaction after 72 hrs of intradermal injection of PPD) and with other pulmonary disease were retrospectively studied. Forty-eight analytes were evaluated by Luminex Assay in plasma obtained from whole blood stimulated cells. The diagnostic accuracies of the markers detected were evaluated by ROC curve analysis and by the combination of multiple biomarkers to improve the potential to discriminate between infection/disease and non infection. Among 48 cytokines, 13 analytes, namely IL-3, IL-12-p40, LIF, IFNα2, IL-2ra, IL-13, b-NGF, SCF, TNF-β, TRAIL, IL-2, IFN-γ, IP-10, and MIG, were significantly higher in the active TB and LTBI groups, compared to NON-TB patients, while MIF was significantly lower in active TB patients compared to NON-TB and LTBI groups. The diagnostic accuracies of the markers detected in the culture supernatants evaluated by ROC curve analysis revealed that 11 analytes (IL2, IP10, IFN-γ, IL13, MIG, SCF, b-NGF, IL12-p40, TRAIL, IL2 Ra, LIF) discriminated between NON-TB and LTBI groups, with AUC for all analytes ≥0.73, while 14 analytes (IL2, IP10, IFN-γ, MIG, SCF, b-NGF, IL12-p40, TRAIL, IL2Ra, MIF, TNF-β, IL3, IFN-α2, LIF) discriminated between NON-TB and active TB groups, with AUC ≥0.78, that is a moderate, value in terms of accuracy of a diagnostic test. Finally, the combinations of seven biomarkers resulted in the accurate prediction of 88.89% of active TB patients, 82.35% of subjects with latent infection and 90% of non-TB patients, respectively. Taken together, our data suggest that combinations of whole blood Mycobacterium tuberculosis (Mtb) antigen dependent cytokines production could be useful as biomarkers to determine tuberculosis disease states when compared to non TB cohort.

Highlights

Tuberculosis (TB) continues to be the cause of death of 4000 people per day [1], and the World Health Organization (WHO) and all the people that are involved in the field are still searching solutions able to control and prevent the socio-economic and medical problems caused by this pathology
On the basis of the WHO End TB strategy, we have evaluated the levels of different cytokines and chemokines from plasma samples obtained from unstimulated and or antigen specific stimulated cells with the objective to discriminate active TB cases from latently infected contacts, or if the combination of different biomarkers could be useful as biosignature of disease/infection
Baseline level of IFNα2 was slightly increased over the maximum normal range value (1,14-fold) in patients with active TB, but this was only detected in approximately one third of the patients, while the baseline of GM-CSF was increased in LTBI compared to active TB (1,20-fold) in the 50% of LTBI subjects

Summary

Introduction

Tuberculosis (TB) continues to be the cause of death of 4000 people per day [1], and the World Health Organization (WHO) and all the people that are involved in the field are still searching solutions able to control and prevent the socio-economic and medical problems caused by this pathology. In order to bypass 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 [8,9,10,11,12]. These cytokines/chemokines were analyzed as a single biomarker or in combination, in order to find a tool to discriminate, in an unequivocal way, subjects with latent infection from that with active disease. Some biomarkers were found at the high significant difference between patients with active disease and LTBI subjects; while in other studies other cytokines have been indicated in order to discriminate the infection from disease, demonstrating that several factors, other than the pathogen, could influence the cytokines/chemokines levels [13,14,15]

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