Eun-Jeong Won1, Jung-Ho Choi1, Young-Nan Cho2, Hye-Mi Jin2, Hae Jin Kee3, Yong-Wook Park3, Yong-Soo Kwon4, Seung-Jung Kee5. 1. Department of Laboratory Medicine, Chonnam National University Medical School and Hospital, Gwangju, Republic of Korea. 2. Department of Rheumatology, Chonnam National University Medical School and Hospital, Gwangju, Republic of Korea. 3. Heart Research Center, Chonnam National University Hospital, Gwangju, Republic of Korea. 4. Department of Pulmonary and Critical Care Medicine, Chonnam National University Medical School and Hospital, Gwangju, Republic of Korea. Electronic address: yskwon@jnu.ac.kr. 5. Department of Laboratory Medicine, Chonnam National University Medical School and Hospital, Gwangju, Republic of Korea. Electronic address: sjkee@jnu.ac.kr.
Abstract
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.
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 TBpatients (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.
Authors: Christian Lundtoft; Anthony Afum-Adjei Awuah; Norman Nausch; Anthony Enimil; Ertan Mayatepek; Ellis Owusu-Dabo; Marc Jacobsen Journal: Med Microbiol Immunol Date: 2017-03-15 Impact factor: 3.402
Authors: Portia M Manngo; Andrea Gutschmidt; Candice I Snyders; Hygon Mutavhatsindi; Charles M Manyelo; Nonjabulo S Makhoba; Petri Ahlers; Andriette Hiemstra; Kim Stanley; Shirley McAnda; Martin Kidd; Stephanus T Malherbe; Gerhard Walzl; Novel N Chegou Journal: J Infect Date: 2019-07-15 Impact factor: 6.072