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Using immune clusters for classifying Mycobacterium tuberculosis infection

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收录情况： ◇ SCIE

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单位： [1]Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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关键词： ATB LTBI Subtypes Prediction model

摘要：

The differential diagnosis between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) is still a challenge worldwide.Immune indicators involved in innate, humoral, and cellular immune cells, as well as antigen-specific cells were simultaneously assessed in patients with ATB and LTBI.Of 54 immune indicators, no indicator could distinguish ATB from LTBI, likely due to an obvious heterogeneity of immune indicators noticed in ATB patients. Cluster analysis of ATB patients identified three immune clusters with different severity. Cluster 1 (42.1 %) was a ''Treg/Th1/Tfh unbalance type" cluster, whereas cluster 2 (42.1 %) was an "effector type'' cluster, and cluster 3 was a ''inhibition type'' cluster (15.8 %) which showed the highest severity. A prediction model based on immune indicators was established and showed potential in classifying Mycobacterium tuberculosis infection.We depicted the immune landscape of patients with ATB and LTBI. Three immune subtypes were identified in ATB patients with different severity.Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

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出版当年[2023]版：

大类 | 2 区

医学

小类 | 2 区免疫学 2 区药学

最新[2025]版：

大类 | 2 区医学

小类 | 2 区药学 3 区免疫学

JCR分区：

出版当年[2022]版：

Q1 PHARMACOLOGY & PHARMACY Q2 IMMUNOLOGY

最新[2023]版：

Q1 PHARMACOLOGY & PHARMACY Q2 IMMUNOLOGY

影响因子： 4.8 最新[2023版] 5 最新五年平均 5.6 出版当年[2022版] 5.6 出版当年五年平均 5.714 出版前一年[2021版] 4.8 出版后一年[2023版]

第一作者：

第一作者单位： [1]Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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