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结核和晚期 HIV 感染者外周血中的免疫生物标志物。

Immunologic Biomarkers in Peripheral Blood of Persons With Tuberculosis and Advanced HIV.

机构信息

Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil.

Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative, Salvador, Brazil.

出版信息

Front Immunol. 2022 Jun 10;13:890003. doi: 10.3389/fimmu.2022.890003. eCollection 2022.


DOI:10.3389/fimmu.2022.890003
PMID:35757685
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9226490/
Abstract

INTRODUCTION: Tuberculosis (TB) is a common opportunistic infection among people living with HIV. Diagnostic tests such as culture, Xpert-MTB-RIF, and ULTRA have low sensitivity in paucibacillary TB disease; a blood biomarker could improve TB diagnostic capabilities. We assessed soluble factors to identify biomarkers associated with TB among persons with advanced HIV. METHODS: A case-control (1:1) study was conducted, with participants from Rio de Janeiro and Manaus, Brazil. People living with HIV presenting with CD4 count ≤100 cells/mm3 were eligible to participate. Cases had culture-confirmed TB (N=15) (positive for [Mtb]); controls had HIV-infection only (N=15). Study visits included baseline, month 2 and end of TB therapy, during which samples of peripheral blood were obtained. A panel containing 29 biomarkers including cytokines, chemokines and growth factors was utilized to assess candidate biomarkers using Luminex technology in cryopreserved EDTA plasma samples. We used neural network analysis, based on machine learning, to identify biomarkers (single or in combination) that best distinguished cases from controls. Additional multi-dimensional analyses provided detailed profiling of the systemic inflammatory environment in cases and controls. RESULTS: Median CD4 count and HIV-1 RNA load values were similar between groups at all timepoints. Persons with TB had lower body mass index (BMI) (median=19.6, Interquartile Range [IQR]=18.6-22.3) than controls (23.7; IQR: 21.8 = 25.5, p=0.004). TB coinfection was also associated with increased frequency of other comorbidities. The overall profile of plasma cytokines, chemokines and growth factors were distinct between the study groups at all timepoints. Plasma concentrations of IL-15 and IL-10 were on average lower in TB cases than in controls. When used in combination, such markers were able to discriminate between TB cases and controls with the highest degree of accuracy at each study timepoint. CONCLUSION: Among persons with advanced HIV, plasma concentrations of IL-15 and IL-10 can be used in combination to identify TB disease regardless of time on anti-TB treatment.

摘要

简介:结核病(TB)是艾滋病毒感染者中常见的机会性感染。培养、Xpert-MTB-RIF 和 ULTRA 等诊断检测方法在少量结核疾病中的敏感性较低;血液生物标志物可以提高结核病诊断能力。我们评估了可溶性因素,以确定与晚期 HIV 人群中结核病相关的生物标志物。 方法:进行了病例对照(1:1)研究,参与者来自巴西的里约热内卢和马瑙斯。符合条件的参与者为 CD4 计数≤100 个细胞/mm3 的艾滋病毒感染者。病例组有培养确诊的结核病(TB)(阳性 [Mtb])(N=15);对照组仅为 HIV 感染(N=15)。研究访视包括基线、第 2 个月和结束结核病治疗期间,在此期间获得外周血样本。使用包含 29 种生物标志物(包括细胞因子、趋化因子和生长因子)的面板,利用 Luminex 技术在冷冻 EDTA 血浆样本中评估候选生物标志物。我们使用基于机器学习的神经网络分析来识别最佳区分病例和对照的生物标志物(单个或组合)。额外的多维分析提供了病例和对照人群系统炎症环境的详细分析。 结果:在所有时间点,TB 组和对照组的 CD4 计数和 HIV-1 RNA 载量中位数均相似。TB 患者的体重指数(BMI)(中位数=19.6,四分位距 [IQR]=18.6-22.3)低于对照组(23.7;IQR:21.8=25.5,p=0.004)。TB 合并感染也与其他合并症的频率增加有关。在所有时间点,研究组之间的血浆细胞因子、趋化因子和生长因子的总体特征均不同。TB 病例的 IL-15 和 IL-10 血浆浓度平均低于对照组。当联合使用时,这些标志物能够在每个研究时间点以最高的准确度区分 TB 病例和对照。 结论:在晚期 HIV 人群中,无论抗结核治疗时间如何,IL-15 和 IL-10 的血浆浓度均可组合使用来识别结核病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/3e0cf9a23cd8/fimmu-13-890003-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/4c8e6f7e0c3b/fimmu-13-890003-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/703af447cd54/fimmu-13-890003-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/fee2c0fe52cd/fimmu-13-890003-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/84bfc0a8923e/fimmu-13-890003-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/697f8e147151/fimmu-13-890003-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/887120963121/fimmu-13-890003-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/3e0cf9a23cd8/fimmu-13-890003-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/4c8e6f7e0c3b/fimmu-13-890003-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/703af447cd54/fimmu-13-890003-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/88fbae9fe7ae/fimmu-13-890003-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/fee2c0fe52cd/fimmu-13-890003-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/84bfc0a8923e/fimmu-13-890003-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/697f8e147151/fimmu-13-890003-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/887120963121/fimmu-13-890003-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a4/9226490/3e0cf9a23cd8/fimmu-13-890003-g008.jpg

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本文引用的文献

[1]
Inflammatory profile of patients with tuberculosis with or without HIV-1 co-infection: a prospective cohort study and immunological network analysis.

Lancet Microbe. 2021-8

[2]
Validation and Optimization of Host Immunological Bio-Signatures for a Point-of-Care Test for TB Disease.

Front Immunol. 2021

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