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Yao F, Zhang R, Lin Q, Xu H, Li W, Ou M, Huang Y, Li G, Xu Y, Song J, Zhang G. Plasma immune profiling combined with machine learning contributes to diagnosis and prognosis of active pulmonary tuberculosis. Emerg Microbes Infect 2024; 13:2370399. [PMID: 38888093 PMCID: PMC11225635 DOI: 10.1080/22221751.2024.2370399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 06/16/2024] [Indexed: 06/20/2024]
Abstract
Tuberculosis (TB) remains one of the deadliest chronic infectious diseases globally. Early diagnosis not only prevents the spread of TB but also ensures effective treatment. However, the absence of non-sputum-based diagnostic tests often leads to delayed TB diagnoses. Inflammation is a hallmark of TB, we aimed to identify biomarkers associated with TB based on immune profiling. We collected 222 plasma samples from healthy controls (HCs), disease controls (non-TB pneumonia; PN), patients with TB (TB), and cured TB cases (RxTB). A high-throughput protein detection technology, multiplex proximity extension assays (PEA), was applied to measure the levels of 92 immune proteins. Based on differential analysis and the correlation with TB severity, we selected 9 biomarkers (CXCL9, PDL1, CDCP1, CCL28, CCL23, CCL19, MMP1, IFNγ and TRANCE) and explored their diagnostic capabilities through 7 machine learning methods. We identified combination of these 9 biomarkers that distinguish TB cases from controls with an area under the receiver operating characteristic curve (AUROC) of 0.89-0.99, with a sensitivity of 82-93% at a specificity of 88-92%. Moreover, the model excels in distinguishing severe TB cases, achieving AUROC exceeding 0.95, sensitivities and specificities exceeding 93.3%. In summary, utilizing targeted proteomics and machine learning, we identified a 9 plasma proteins signature that demonstrates significant potential for accurate TB diagnosis and clinical outcome prediction.
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Affiliation(s)
- Fusheng Yao
- National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, People’s Republic of China
| | - Ruiqi Zhang
- National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, People’s Republic of China
| | - Qiao Lin
- The Baoan People's Hospital of Shenzhen, The Second Affiliated Hospital of Shenzhen University, Shenzhen, People’s Republic of China
| | - Hui Xu
- National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, People’s Republic of China
| | - Wei Li
- Zhuhai ICXIVD Biotechnology Co., Ltd, iCarbonX, Zhuhai, People’s Republic of China
| | - Min Ou
- National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, People’s Republic of China
| | - Yiting Huang
- Zhuhai ICXIVD Biotechnology Co., Ltd, iCarbonX, Zhuhai, People’s Republic of China
| | - Guobao Li
- National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, People’s Republic of China
| | - Yuzhong Xu
- The Baoan People's Hospital of Shenzhen, The Second Affiliated Hospital of Shenzhen University, Shenzhen, People’s Republic of China
| | - Jiaping Song
- Zhuhai ICXIVD Biotechnology Co., Ltd, iCarbonX, Zhuhai, People’s Republic of China
| | - Guoliang Zhang
- National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, People’s Republic of China
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Li Z, Hu Y, Wang W, Zou F, Yang J, Gao W, Feng S, Chen G, Shi C, Cai Y, Deng G, Chen X. Integrating pathogen- and host-derived blood biomarkers for enhanced tuberculosis diagnosis: a comprehensive review. Front Immunol 2024; 15:1438989. [PMID: 39185416 PMCID: PMC11341448 DOI: 10.3389/fimmu.2024.1438989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 07/24/2024] [Indexed: 08/27/2024] Open
Abstract
This review explores the evolving landscape of blood biomarkers in the diagnosis of tuberculosis (TB), focusing on biomarkers derived both from the pathogen and the host. These biomarkers provide critical insights that can improve diagnostic accuracy and timeliness, essential for effective TB management. The document highlights recent advancements in molecular techniques that have enhanced the detection and characterization of specific biomarkers. It also discusses the integration of these biomarkers into clinical practice, emphasizing their potential to revolutionize TB diagnostics by enabling more precise detection and monitoring of the disease progression. Challenges such as variability in biomarker expression and the need for standardized validation processes are addressed to ensure reliability across different populations and settings. The review calls for further research to refine these biomarkers and fully harness their potential in the fight against TB, suggesting a multidisciplinary approach to overcome existing barriers and optimize diagnostic strategies. This comprehensive analysis underscores the significance of blood biomarkers as invaluable tools in the global effort to control and eliminate TB.
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Affiliation(s)
- Zhaodong Li
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, China
| | - Yunlong Hu
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - Wenfei Wang
- National Clinical Research Center for Infectious Disease, The Third People's Hospital of Shenzhen, Southern University of Science and Technology, Shenzhen, China
| | - Fa Zou
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - Jing Yang
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - Wei Gao
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - SiWan Feng
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - Guanghuan Chen
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - Chenyan Shi
- Department of Preventive Medicine, School of Public Health, Shenzhen University, Shenzhen, China
| | - Yi Cai
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - Guofang Deng
- Guangdong Key Lab for Diagnosis & Treatment of Emerging Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, China
| | - Xinchun Chen
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
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Mahmoudi S, García MJ, Drain PK. Current approaches for diagnosis of subclinical pulmonary tuberculosis, clinical implications and future perspectives: a scoping review. Expert Rev Clin Immunol 2024; 20:715-726. [PMID: 38879875 DOI: 10.1080/1744666x.2024.2326032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 02/28/2024] [Indexed: 06/18/2024]
Abstract
INTRODUCTION Subclinical tuberculosis (TB) is the presence of TB disease among people who are either asymptomatic or have minimal symptoms. AREAS COVERED Currently, there are no accurate diagnostic tools and clear treatment approaches for subclinical TB. In this study, a comprehensive literature search was conducted across major databases. This review aimed to uncover the latest advancements in diagnostic approaches, explore their clinical implications, and outline potential future perspectives. While innovative technologies are in development to enable sputum-free TB tests, there remains a critical need for precise diagnostic tools tailored to the unique characteristics of subclinical TB. Given the complexity of subclinical TB, a multidisciplinary approach involving clinicians, microbiologists, epidemiologists, and public health experts is essential. Further research is needed to establish standardized diagnostic criteria and treatment guidelines specifically tailored for subclinical TB, acknowledging the unique challenges posed by this elusive stage of the disease. EXPERT OPINION Efforts are needed for the detection, diagnosis, and treatment of subclinical TB. In this review, we describe the importance of subclinical TB, both from a clinical and public health perspective and highlight the diagnostic and treatment gaps of this stage.
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Affiliation(s)
- Shima Mahmoudi
- Biotechnology Centre, Silesian University of Technology, Gliwice, Poland
| | - Maria J García
- Department of Preventive Medicine and Public Health and Microbiology, Autonoma University of Madrid, Madrid, Spain
| | - Paul K Drain
- International Clinical Research Center, Department of Global Health, Schools of Medicine and Public Health, University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
- Division of Allergy and Infectious Diseases, Department of Medicine, School of Medicine, University of Washington, Seattle, WA, USA
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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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Ren W, Ma Z, Li Q, Liu R, Ma L, Yao C, Shang Y, Zhang X, Gao M, Li S, Pang Y. Antigen-specific chemokine profiles as biomarkers for detecting Mycobacterium tuberculosis infection. Front Immunol 2024; 15:1359555. [PMID: 38510248 PMCID: PMC10950995 DOI: 10.3389/fimmu.2024.1359555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/23/2024] [Indexed: 03/22/2024] Open
Abstract
Background Latent tuberculosis (TB) infection can progress to active TB, which perpetuates community transmission that undermines global TB control efforts. Clinically, interferon-γ release assays (IGRAs) are commonly used for active TB case detection. However, low IGRA sensitivity rates lead to false-negative results for a high proportion of active TB cases, thus highlighting IGRA ineffectiveness in differentiating MTB-infected individuals from healthy individuals. Methods Participants enrolled at Beijing Chest Hospital from May 2020-April 2022 were assigned to healthy control (HC), LTBI, IGRA-positive TB, and IGRA-negative TB groups. Screening cohort MTB antigen-specific blood plasma chemokine concentrations were measured using Luminex xMAP assays then were verified via testing of validation cohort samples. Results A total of 302 individuals meeting study inclusion criteria were assigned to screening and validation cohorts. Testing revealed significant differences in blood plasma levels of CXCL9, CXCL10, CXCL16, CXCL21, CCL1, CCL19, CCL27, TNF-α, and IL-4 between IGRA-negative TB and HC groups. Levels of CXCL9, CXCL10, IL-2, and CCL8 biomarkers were predictive for active TB, as reflected by AUC values of ≥0.9. CXCL9-based enzyme-linked immunosorbent assay sensitivity and specificity rates were 95.9% (95%CI: 91.7-98.3) and 100.0% (92.7-100.0), respectively. Statistically similar AUC values were obtained for CXCL9 and CXCL9-CXCL10 assays, thus demonstrating that combined analysis of CXCL10 and CXCL9 levels did not improve active TB diagnostic performance. Conclusion The MTB antigen stimulation-based CXCL9 assay may compensate for low IGRA diagnostic accuracy when used to diagnose IGRA-negative active TB cases and thus is an accurate and sensitive alternative to IGRAs for detecting MTB infection.
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Affiliation(s)
- Weicong Ren
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Zichun Ma
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Qiang Li
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Rongmei Liu
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Liping Ma
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Cong Yao
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Yuanyuan Shang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Xuxia Zhang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Mengqiu Gao
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Shanshan Li
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Yu Pang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
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Li H, Ren W, Liang Q, Zhang X, Li Q, Shang Y, Ma L, Li S, Pang Y. A novel chemokine biomarker to distinguish active tuberculosis from latent tuberculosis: a cohort study. QJM 2023; 116:1002-1009. [PMID: 37740371 PMCID: PMC10753411 DOI: 10.1093/qjmed/hcad214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/12/2023] [Indexed: 09/24/2023] Open
Abstract
BACKGROUND Interferon-γ release assays (IGRAs), which are widely used to diagnose tuberculosis (TB), cannot effectively discriminate latent TB infection (LTBI) from active TB (ATB). This study aimed to identify potential antigen-specific biomarkers for differentiating LTBI cases from ATB cases. METHODS Ongoing recruitment was conducted of individuals meeting study inclusion criteria at Beijing Chest Hospital from May 2020 to April 2022; 208 participants were enrolled and assigned to three groups: HC (60 healthy controls), LTBI (52 subjects with LTBI) and ATB (96 ATB patients). After participants were assigned to the discovery cohort (20 or 21 subjects/group), all others were assigned to the verification cohort. Discovery cohort blood levels of 40 chemokines were measured using Luminex assays to identify chemokines that could be used to discriminate LTBI cases from ATB cases; candidate biomarkers were verified using enzyme-linked immunosorbent assay-based testing of validation cohort samples. RESULTS Luminex results revealed highest ATB group levels of numerous cytokines, growth factors and chemokines. Receiving operating characteristic curve-based analysis of 40 biomarkers revealed CCL8 (AUC = 0.890) and CXCL9 (AUC = 0.883) effectively discriminated between LTBI and TB cases; greatest diagnostic efficiency was obtained using both markers together (AUC = 0.929). Interpretation of CCL8 and CXCL9 levels for validation cohort IGRA-positive subjects (based on a 0.658-ng/ml cutoff) revealed ATB group CCL8-based sensitivity and specificity rates approaching 90.79% and 100.00%, respectively. CONCLUSION TB-specific chemokines hold promise as ATB diagnostic biomarkers. Additional laboratory confirmation is needed to establish whether CCL8-based assays can differentiate between ATB and LTBI cases, especially for bacteriologically unconfirmed TB cases.
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Affiliation(s)
- H Li
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Postal No. 9, Beiguan Street, Tongzhou District, Beijing 101149, People’s Republic of China
| | - W Ren
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Postal No. 9, Beiguan Street, Tongzhou District, Beijing 101149, People’s Republic of China
| | - Q Liang
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People’s Republic of China
| | - X Zhang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Postal No. 9, Beiguan Street, Tongzhou District, Beijing 101149, People’s Republic of China
| | - Q Li
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People’s Republic of China
| | - Y Shang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Postal No. 9, Beiguan Street, Tongzhou District, Beijing 101149, People’s Republic of China
| | - L Ma
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People’s Republic of China
| | - S Li
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Postal No. 9, Beiguan Street, Tongzhou District, Beijing 101149, People’s Republic of China
| | - Y Pang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Postal No. 9, Beiguan Street, Tongzhou District, Beijing 101149, People’s Republic of China
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Wang R, Fan X, Xu D, Li M, Zhao X, Cao B, Qian C, Yu J, Fang D, Gu Y, Wan K, Liu H. Comparison of the Immunogenicity and Efficacy of rBCG-EPCP009, BCG Prime-EPCP009 Booster, and EPCP009 Protein Regimens as Tuberculosis Vaccine Candidates. Vaccines (Basel) 2023; 11:1738. [PMID: 38140143 PMCID: PMC10747267 DOI: 10.3390/vaccines11121738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/04/2023] [Accepted: 11/15/2023] [Indexed: 12/24/2023] Open
Abstract
Bacillus Calmette-Guérin (BCG) is the only widely used prophylactic tuberculosis (TB) vaccine that can prevent severe TB in infants. However, it provides poor protection in adults, and therefore, there is ongoing research into new TB vaccines and immunization strategies with more durable immune effects. The recombinant BCG and BCG prime-protein booster are two important vaccine strategies that have recently been developed based on BCG and could improve immune responses. In this study, three immune strategies based on four protective antigens, namely, ESAT-6, CFP-10, nPPE18, and nPstS1, were applied to construct recombinant rBCG-EPCP009, EPCP009 subunit protein, and BCG prime-EPCP009 booster vaccine candidates. The short- and long-term immune effects after vaccination in Balb/c mice were evaluated based on humoral immunity, cellular immunity, and the ability of spleen cells to inhibit in vitro mycobacterial growth. At 8 and 12 weeks after the initial immunization, splenocytes from mice inoculated with the BCG prime-EPCP009 protein booster secreted higher levels of PPD- and EPCP009-specific IFN-γ, IL-2, TNF-α, IL-17, GM-CSF, and IL-12 and had a higher IFN-γ+CD4+ TEM:IL-2+CD8+ TCM cell ratio than splenocytes from mice inoculated with the rBCG-EPCP009 and EPCP009 proteins. In addition, the EPCPE009-specific IgG2a/IgG1 ratio was slightly higher in the BCG prime-EPCP009 protein booster group than in the other two groups. The in vitro mycobacterial inhibition assay showed that the splenocytes of mice from the BCG prime-EPCP009 protein booster group exhibited stronger inhibition of Mycobacterium tuberculosis (M. tuberculosis) growth than the splenocytes of mice from the other two groups. These results indicate that the BCG prime-EPCP009 protein booster exhibited superior immunogenicity and M. tuberculosis growth inhibition to the parental BCG, rBCG-EPCP009, and EPCP009 proteins under in vitro conditions. Thus, the BCG prime-EPCP009 protein booster may be important for the development of a more effective adult TB vaccine.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Kanglin Wan
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (X.F.); (D.X.); (M.L.); (X.Z.); (B.C.); (C.Q.); (J.Y.); (D.F.); (Y.G.)
| | - Haican Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (X.F.); (D.X.); (M.L.); (X.Z.); (B.C.); (C.Q.); (J.Y.); (D.F.); (Y.G.)
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