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Razbek J, Daken M, Chen Y, Ma L, Zhang Y, Xu W, Wen B, Wang J, Wang X, Cao M. Association Studies of Serum Levels of TNF- α, IL-10, IFN-γ and CXCL 5 with Latent Tuberculosis Infection in Close Contacts. Infect Drug Resist 2024; 17:899-910. [PMID: 38468847 PMCID: PMC10926862 DOI: 10.2147/idr.s442682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 02/22/2024] [Indexed: 03/13/2024] Open
Abstract
Purpose Early recognition and treatment of latent tuberculosis infection(LTBI) is key to tuberculosis(TB) prevention. However, the emergence of LTBI is influenced by a combination of factors, of which the role of individual immune cytokines remains controversial. The aim of this study is to explore the influencing factors of LTBI and their effects with cytokines on LTBI. Patients and Methods Close contacts of tuberculosis in Urumqi City from 2021 to 2022 were selected for the study to conduct a field survey. It used logistic regression model to analyse the influencing factors of LTBI, principal component analysis to extract a composite indicators of cytokines, and structural equation modelling to explore the direct and indirect effects of cytokines and influencing factors on LTBI. Results LTBI infection rate of 33.3% among 288 TB close contacts. A multifactorial Logistic model showed that factors influencing LTBI included education, daily contact hours, eating animal liver, and drinking coffee (P<0.05); After controlling for confounding factors and extracting composite indicators of cytokines using principal component analysis, CXCL5 and IFN-γ is a protective factor for LTBI(OR=0.572, P=0.047), IL-10 and TNF-α is a risk factor for LTBI(OR=2.119, P=0.010); Structural equation modelling shows drinking coffee, eating animal liver, daily contact hours, and IL-10 and TNF-α had direct effects on LTBI and educations had indirect effects on LTBI(P<0.05). Conclusion IL-10 and TNF-α are involved in the immune response and are directly related to LTBI. By monitoring the cytokine levels of TB close contacts and paying attention to their dietary habits and exposure, we can detect and intervene in LTBI at an early stage and control their progression to TB.
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Affiliation(s)
- Jaina Razbek
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Mayisha Daken
- Department of Epidemic Prevention, Karamay Centre for Disease Control and Prevention, Karamay, 834000, People’s Republic of China
| | - Yanggui Chen
- Department of Prevention and Control of Tuberculosis, Urumqi Centre for Disease Control and Prevention, Urumqi, 830011, People’s Republic of China
| | - Li Ma
- Department of Prevention and Control of Tuberculosis, Urumqi Centre for Disease Control and Prevention, Urumqi, 830011, People’s Republic of China
| | - Yan Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Wanting Xu
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Baofeng Wen
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Junan Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Xiaomin Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Mingqin Cao
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
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Zhang L, Yang Z, Wu F, Ge Q, Zhang Y, Li D, Gao M, Liu X. Multiple cytokine analysis based on QuantiFERON-TB gold plus in different tuberculosis infection status: an exploratory study. BMC Infect Dis 2024; 24:28. [PMID: 38166667 PMCID: PMC10762904 DOI: 10.1186/s12879-023-08943-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND More efficient and convenient diagnostic method is a desperate need to reduce the burden of tuberculosis (TB). This study explores the multiple cytokines secretion based on QuantiFERON-TB Gold Plus (QFT-Plus), and screens for optimal cytokines with diagnostic potential to differentiate TB infection status. METHODS Twenty active tuberculosis (ATB) patients, fifteen patients with latent TB infection (LTBI), ten patients with previous TB and ten healthy controls (HC) were enrolled. Whole blood samples were collected and stimulated by QFT-Plus TB1 and TB2 antigens. The levels of IFN-γ, TNF-α, IL-2, IL-6, IL-5, IL-10, IP-10, IL-1Ra, CXCL-1 and MCP-1 in supernatant were measured by Luminex bead-based multiplex assays. The receiver operating characteristic curve was used to evaluate the diagnostic accuracy of cytokine for distinguishing different TB infection status. RESULTS After stimulation with QFT-Plus TB1 and TB2 antigens, the levels of all cytokines, except IL-5 in TB2 tube, in ATB group were significantly higher than that in HC group. The levels of IL-1Ra concurrently showed the equally highest AUC for distinguishing TB infection from HC, followed by the levels of IP-10 in both TB1 tube and TB2 tube. Moreover, IP-10 levels displayed the largest AUC for distinguishing ATB patients from non-ATB patients. Meanwhile, the levels of IP-10 also demonstrated the largest AUC in both TB1 tube and TB2 tube for distinguishing ATB patients from LTBI. CONCLUSIONS In addition to conventional detection of IFN-γ, measuring IP-10 and IL-1Ra based on QFT-Plus may have the more tremendous potential to discriminate different TB infection status.
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Affiliation(s)
- Lifan Zhang
- Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Clinical Epidemiology Unit, Peking Union Medical College, International Clinical Epidemiology Network, Beijing, China
- Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhengrong Yang
- Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fengying Wu
- Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qiping Ge
- Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Yueqiu Zhang
- Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongyu Li
- Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mengqiu Gao
- Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Xiaoqing Liu
- Division of Infectious Diseases, Department of Internal medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
- Clinical Epidemiology Unit, Peking Union Medical College, International Clinical Epidemiology Network, Beijing, China.
- Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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