Xuanmiao Liu , Junchi Xu , Yanjun Feng , Meiying Wu , Hui Chen , Yiyan Song , Huafeng Song , Yanzheng Gu , Ping Xu
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Flow cytometry was used to measure the expression levels of γδ T cells, Vδ1 T-cell subsets/Vδ2 T-cell subsets, naive (CD45RA + CD27<sup>+</sup>) cells, central memory (CD45RA-CD27<sup>+</sup>) cells, effector memory (CD45RA-CD27<sup>−</sup>) cells, and terminally differentiated (CD45RA + CD27<sup>−</sup>) cells in the peripheral blood. The expression levels at different stages of TB infection were compared.</div></div><div><h3>Results</h3><div>There were no significant differences in peripheral blood γδ T cells or Vδ1 T cells among the HC, LTBI and TB groups. The proportion of CD45RA-CD27+Vδ2 T cells in TB patients was significantly lower than that in HCs and LTBI patients, but the proportion of CD45RA + CD27-Vδ2 T cells was greater. ROC curve analysis revealed that CD45RA-CD27+Vδ2 T cells (AUC), CD45RA + CD27-Vδ2 T cells (AUC), and the combination of both (AUC) were effective in differentiating TB patients from LTBI patients.</div></div><div><h3>Conclusion</h3><div>The proportions of CD45RA-CD27+Vδ2 T cells and CD45RA + CD27-Vδ2 T cells are potential biomarkers for the diagnosis of active TB infection and are helpful for distinguishing active TB infection from LTBI.</div></div>","PeriodicalId":18599,"journal":{"name":"Microbial pathogenesis","volume":"198 ","pages":"Article 107032"},"PeriodicalIF":3.3000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of γδ T cells with different memory phenotypes in clinical diagnosis of active pulmonary tuberculosis\",\"authors\":\"Xuanmiao Liu , Junchi Xu , Yanjun Feng , Meiying Wu , Hui Chen , Yiyan Song , Huafeng Song , Yanzheng Gu , Ping Xu\",\"doi\":\"10.1016/j.micpath.2024.107032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>To investigate the application and clinical significance of different memory phenotypes of γδ T-cell subsets in the clinical diagnosis of pulmonary tuberculosis.</div></div><div><h3>Methods</h3><div>In total, 42 patients with tuberculosis (TB) according to the diagnostic criteria for tuberculosis (WS288-2017) who were treated at the Infectious Diseases Hospital affiliated with Soochow University from February 2023 to July 2023 were enrolled. Additionally, 16 patients with latent TB infection (LTBI) and 20 healthy controls (HCs) were included. Flow cytometry was used to measure the expression levels of γδ T cells, Vδ1 T-cell subsets/Vδ2 T-cell subsets, naive (CD45RA + CD27<sup>+</sup>) cells, central memory (CD45RA-CD27<sup>+</sup>) cells, effector memory (CD45RA-CD27<sup>−</sup>) cells, and terminally differentiated (CD45RA + CD27<sup>−</sup>) cells in the peripheral blood. The expression levels at different stages of TB infection were compared.</div></div><div><h3>Results</h3><div>There were no significant differences in peripheral blood γδ T cells or Vδ1 T cells among the HC, LTBI and TB groups. The proportion of CD45RA-CD27+Vδ2 T cells in TB patients was significantly lower than that in HCs and LTBI patients, but the proportion of CD45RA + CD27-Vδ2 T cells was greater. 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引用次数: 0
摘要
目的探讨不同记忆表型的γδT细胞亚群在肺结核临床诊断中的应用及临床意义:方法:选取2023年2月至2023年7月在苏州大学附属传染病医院接受治疗的符合肺结核诊断标准(WS288-2017)的42例肺结核患者为研究对象。此外,还纳入了 16 名潜伏肺结核感染(LTBI)患者和 20 名健康对照(HCs)。流式细胞术用于测量外周血中 γδ T 细胞、Vδ1 T 细胞亚群/Vδ2 T 细胞亚群、幼稚细胞(CD45RA+CD27+)、中心记忆细胞(CD45RA-CD27+)、效应记忆细胞(CD45RA-CD27-)和终末分化细胞(CD45RA+CD27-)的表达水平。比较了结核病感染不同阶段的表达水平:结果:HC 组、LTBI 组和 TB 组的外周血 γδ T 细胞和 Vδ1 T 细胞无明显差异。肺结核患者 CD45RA-CD27+Vδ2 T 细胞的比例明显低于 HC 和 LTBI 患者,但 CD45RA+CD27-Vδ2 T 细胞的比例更高。ROC曲线分析显示,CD45RA-CD27+Vδ2 T细胞(AUC)、CD45RA+CD27-Vδ2 T细胞(AUC)以及两者的组合(AUC)能有效区分肺结核患者和LTBI患者:结论:CD45RA-CD27+Vδ2 T细胞和CD45RA+CD27-Vδ2 T细胞的比例是诊断活动性肺结核感染的潜在生物标志物,有助于区分活动性肺结核感染和LTBI。
Application of γδ T cells with different memory phenotypes in clinical diagnosis of active pulmonary tuberculosis
Objective
To investigate the application and clinical significance of different memory phenotypes of γδ T-cell subsets in the clinical diagnosis of pulmonary tuberculosis.
Methods
In total, 42 patients with tuberculosis (TB) according to the diagnostic criteria for tuberculosis (WS288-2017) who were treated at the Infectious Diseases Hospital affiliated with Soochow University from February 2023 to July 2023 were enrolled. Additionally, 16 patients with latent TB infection (LTBI) and 20 healthy controls (HCs) were included. Flow cytometry was used to measure the expression levels of γδ T cells, Vδ1 T-cell subsets/Vδ2 T-cell subsets, naive (CD45RA + CD27+) cells, central memory (CD45RA-CD27+) cells, effector memory (CD45RA-CD27−) cells, and terminally differentiated (CD45RA + CD27−) cells in the peripheral blood. The expression levels at different stages of TB infection were compared.
Results
There were no significant differences in peripheral blood γδ T cells or Vδ1 T cells among the HC, LTBI and TB groups. The proportion of CD45RA-CD27+Vδ2 T cells in TB patients was significantly lower than that in HCs and LTBI patients, but the proportion of CD45RA + CD27-Vδ2 T cells was greater. ROC curve analysis revealed that CD45RA-CD27+Vδ2 T cells (AUC), CD45RA + CD27-Vδ2 T cells (AUC), and the combination of both (AUC) were effective in differentiating TB patients from LTBI patients.
Conclusion
The proportions of CD45RA-CD27+Vδ2 T cells and CD45RA + CD27-Vδ2 T cells are potential biomarkers for the diagnosis of active TB infection and are helpful for distinguishing active TB infection from LTBI.
期刊介绍:
Microbial Pathogenesis publishes original contributions and reviews about the molecular and cellular mechanisms of infectious diseases. It covers microbiology, host-pathogen interaction and immunology related to infectious agents, including bacteria, fungi, viruses and protozoa. It also accepts papers in the field of clinical microbiology, with the exception of case reports.
Research Areas Include:
-Pathogenesis
-Virulence factors
-Host susceptibility or resistance
-Immune mechanisms
-Identification, cloning and sequencing of relevant genes
-Genetic studies
-Viruses, prokaryotic organisms and protozoa
-Microbiota
-Systems biology related to infectious diseases
-Targets for vaccine design (pre-clinical studies)