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López-González JA, Martínez-Soto JM, Avila-Cervantes C, Mata-Pineda AL, Álvarez-Hernández G, Álvarez-Meza JB, Bolado-Martínez E, Candia-Plata MDC. Evaluation of Systemic Inflammation Before and After Standard Anti-tuberculosis Treatment in Patients With Active Pulmonary Tuberculosis and Diabetes Mellitus. Cureus 2024; 16:e55391. [PMID: 38562330 PMCID: PMC10984244 DOI: 10.7759/cureus.55391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/29/2024] [Indexed: 04/04/2024] Open
Abstract
Background Diabetes mellitus (DM) is a common comorbidity of active pulmonary tuberculosis (APTB) that increases the risk of treatment failure during anti-tuberculosis chemotherapy. Evaluating systemic inflammatory response could help determine differences in response to treatment between APTB patients and those with APTB and DM. Methodology To explore changes in systemic inflammation, measured by a set of inflammatory mediators in subjects with APTB and TBDM before and after six months of anti-tuberculosis chemotherapy, 30 APTB and nine TBDM subjects underwent cytokine testing, including interleukin (IL)-6, IL-8, IL-10, interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and transforming growth factor-beta 1 (TGF-β1) by enzyme-linked immunosorbent assay, C-reactive protein by nephelometry, and sialic acid by colorimetric assay at baseline and following six months of standard anti-tuberculosis treatment. Sputum smear microscopy or molecular biology (Xpert MTB/RIF) was used for diagnosis, and sputum smear microscopy was performed monthly during the treatment of the patient with pulmonary tuberculosis to evaluate his evolution. Principal component analysis examined changes in the inflammatory status. Results Both groups showed negative sputum smear microscopy in the sixth month after starting anti-tuberculosis chemotherapy. TGF-β1 was found to be significantly higher in subjects with TBDM before treatment compared to APTB patients (p<0.001), and systemic inflammation continued only in TBDM subjects after treatment (accumulation and persistence of inflammatory mediators like IL-6, IL-8, IL-10, IFN-γ, TNF-α, TGF-β1, C-reactive protein, and sialic acid in blood). On the other hand, the mediators IFN-γ, C-reactive protein, and total sialic acid were found to be most influential in distinguishing pre- and post-treatment inflammatory response in subjects with APTB without DM. Conclusions Inflammatory mediators analyzed in combination, including IFN-γ, CRP, and total sialic acid, may be useful in evaluating the systemic inflammatory response in subjects with APTB and TBDM before and after anti-tuberculosis treatment. Determining these mediators revealed persistent systemic inflammation in TBDM subjects after six months of standard tuberculosis treatment, despite negative sputum smear microscopy results and good glycemic control. This suggests a need for inflammation-modulating therapies during tuberculosis control. Finally, monitoring sputum smear microscopy results alongside the determination of proposed inflammatory mediators (IFN-γ, CRP, and total sialic acid) are effective in evaluating the response to anti-tuberculosis treatment in APTB subjects without DM, warranting further investigation.
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Chen L, Liu C, Liang T, Ye Z, Huang S, Chen J, Sun X, Yi M, Zhou C, Jiang J, Chen T, Li H, Chen W, Guo H, Chen W, Yao Y, Liao S, Yu C, Wu S, Fan B, Gan Z, Zhan X. Mechanism of COVID-19-Related Proteins in Spinal Tuberculosis: Immune Dysregulation. Front Immunol 2022; 13:882651. [PMID: 35720320 PMCID: PMC9202521 DOI: 10.3389/fimmu.2022.882651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose The purpose of this article was to investigate the mechanism of immune dysregulation of COVID-19-related proteins in spinal tuberculosis (STB). Methods Clinical data were collected to construct a nomogram model. C-index, calibration curve, ROC curve, and DCA curve were used to assess the predictive ability and accuracy of the model. Additionally, 10 intervertebral disc samples were collected for protein identification. Bioinformatics was used to analyze differentially expressed proteins (DEPs), including immune cells analysis, Gene Ontology (GO) and KEGG pathway enrichment analysis, and protein-protein interaction networks (PPI). Results The nomogram predicted risk of STB ranging from 0.01 to 0.994. The C-index and AUC in the training set were 0.872 and 0.862, respectively. The results in the external validation set were consistent with the training set. Immune cells scores indicated that B cells naive in STB tissues were significantly lower than non-TB spinal tissues. Hub proteins were calculated by Degree, Closeness, and MCC methods. The main KEGG pathway included Coronavirus disease-COVID-19. There were 9 key proteins in the intersection of COVID-19-related proteins and hub proteins. There was a negative correlation between B cells naive and RPL19. COVID-19-related proteins were associated with immune genes. Conclusion Lymphocytes were predictive factors for the diagnosis of STB. Immune cells showed low expression in STB. Nine COVID-19-related proteins were involved in STB mechanisms. These nine key proteins may suppress the immune mechanism of STB by regulating the expression of immune genes.
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Affiliation(s)
- Liyi Chen
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Chong Liu
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Tuo Liang
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Zhen Ye
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Shengsheng Huang
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Jiarui Chen
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Xuhua Sun
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Ming Yi
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Chenxing Zhou
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Jie Jiang
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Tianyou Chen
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Hao Li
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Wuhua Chen
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Hao Guo
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Wenkang Chen
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Yuanlin Yao
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Shian Liao
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Chaojie Yu
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Shaofeng Wu
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Binguang Fan
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Zhaoping Gan
- Department of Hematology, Guangxi Medical University First Affiliated Hospital, Nanning, China
| | - Xinli Zhan
- Spine and Osteopathy Ward, Guangxi Medical University First Affiliated Hospital, Nanning, China
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Kathamuthu GR, Moideen K, Sridhar R, Baskaran D, Babu S. Reduced neutrophil granular proteins and post-treatment modulation in tuberculous lymphadenitis. PLoS One 2021; 16:e0253534. [PMID: 34153068 PMCID: PMC8216526 DOI: 10.1371/journal.pone.0253534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/07/2021] [Indexed: 11/29/2022] Open
Abstract
Background Neutrophils are important for host innate immune defense and mediate inflammatory responses. Pulmonary tuberculosis (PTB) is associated with increased neutrophil granular protein (NGP) levels in the circulation. However, the systemic levels of neutrophil granular proteins were not examined in tuberculous lymphadenitis (TBL) disease. Methods We measured the systemic levels of NGP (myeloperoxidase [MPO], elastase and proteinase 3 [PRTN3]) in TBL and compared them to latent tuberculosis (LTB) and healthy control (HC) individuals. We also measured the pre-treatment (Pre-T) and post-treatment (Post-T) systemic levels of neutrophil granular proteins in TBL individuals upon anti-tuberculosis treatment (ATT) completion. In addition, we studied the correlation and discriminatory ability of NGPs using receiver operating characteristic (ROC) analysis. Results Our data suggests that systemic levels of NGPs (MPO, PRTN3, elastase) were significantly reduced in TBL individuals compared to LTB and HC individuals. Similarly, after ATT, the plasma levels of MPO and elastase but not PRTN3 were significantly elevated compared to pre-treatment levels. NGPs (except PRTN3) were positively correlated with absolute neutrophil count of TBL, LTB and HC individuals. Further, NGPs were able to significantly discriminate TBL from LTB and HC individuals. Conclusion Hence, we conclude reduced neutrophil granular protein levels might be associated with disease pathogenesis in TBL.
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Affiliation(s)
- Gokul Raj Kathamuthu
- National Institutes of Health-NIRT-International Center for Excellence in Research, Chennai, India
- National Institute for Research in Tuberculosis (NIRT), Chennai, India
- * E-mail:
| | - Kadar Moideen
- National Institutes of Health-NIRT-International Center for Excellence in Research, Chennai, India
| | | | - Dhanaraj Baskaran
- National Institute for Research in Tuberculosis (NIRT), Chennai, India
| | - Subash Babu
- National Institutes of Health-NIRT-International Center for Excellence in Research, Chennai, India
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
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FasL regulatory B-cells during Mycobacterium tuberculosis infection and TB disease. J Mol Biol 2021; 433:166984. [PMID: 33845087 DOI: 10.1016/j.jmb.2021.166984] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 03/29/2021] [Accepted: 03/30/2021] [Indexed: 11/20/2022]
Abstract
Tuberculosis (TB) disease remains a major health crisis. Infection with Mycobacterium tuberculosis (M.tb) cause a range of diseases ranging from latent infection to active TB disease. This active state of the disease is characterised by the formation of granulomas (a physical barrier in the lung), a structure thought to protect the host by controlling the infection through preventing the growth of the bacilli. Subsequently, the surviving bacteria become inactive and in most cases, TB reactivation is prevented by the immune response of the host. B-cells perform numerous immunological functions beyond antibody production to positively regulate the response to pathogenic assault. A subgroup of B-cells with regulatory functions express death-inducing ligands, such as Fas ligand (FasL). Expression and interaction of the Fas receptor-ligand promotes the induction of apoptosis and the induction of T-cell tolerance. Here, we focus on the significance of B-cells by addressing their FasL phenotype and regulatory functions during TB, with reference to disease in humans, non-human primates and mice.
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