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实时 PCR 法对潜伏性和活动性结核病差异表达免疫生物标志物的验证。

Validation of Differentially Expressed Immune Biomarkers in Latent and Active Tuberculosis by Real-Time PCR.

机构信息

Public Health England, Porton Down, Salisbury, Wiltshire, United Kingdom.

Centre for Clinical Microbiology, University College London, Royal Free Campus, London, United Kingdom.

出版信息

Front Immunol. 2021 Mar 16;11:612564. doi: 10.3389/fimmu.2020.612564. eCollection 2020.

DOI:10.3389/fimmu.2020.612564
PMID:33841389
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8029985/
Abstract

Tuberculosis (TB) remains a major global threat and diagnosis of active TB ((ATB) both extra-pulmonary (EPTB), pulmonary (PTB)) and latent TB (LTBI) infection remains challenging, particularly in high-burden countries which still rely heavily on conventional methods. Although molecular diagnostic methods are available, e.g., Cepheid GeneXpert, they are not universally available in all high TB burden countries. There is intense focus on immune biomarkers for use in TB diagnosis, which could provide alternative low-cost, rapid diagnostic solutions. In our previous gene expression studies, we identified peripheral blood leukocyte (PBL) mRNA biomarkers in a non-human primate TB aerosol-challenge model. Here, we describe a study to further validate select mRNA biomarkers from this prior study in new cohorts of patients and controls, as a prerequisite for further development. Whole blood mRNA was purified from ATB patients recruited in the UK and India, LTBI and two groups of controls from the UK (i) a low TB incidence region (CNTRLA) and (ii) individuals variably-domiciled in the UK and Asia ((CNTRLB), the latter TB high incidence regions). Seventy-two mRNA biomarker gene targets were analyzed by qPCR using the Roche Lightcycler 480 qPCR platform and data analyzed using GeneSpring™ 14.9 bioinformatics software. Differential expression of fifty-three biomarkers was confirmed between MTB infected, LTBI groups and controls, seventeen of which were significant using analysis of variance (ANOVA): CALCOCO2, CD52, GBP1, GBP2, GBP5, HLA-B, IFIT3, IFITM3, IRF1, LOC400759 (GBP1P1), NCF1C, PF4V1, SAMD9L, S100A11, TAF10, TAPBP, and TRIM25. These were analyzed using receiver operating characteristic (ROC) curve analysis. Single biomarkers and biomarker combinations were further assessed using simple arithmetic algorithms. Minimal combination biomarker panels were delineated for primary diagnosis of ATB (both PTB and EPTB), LTBI and identifying LTBI individuals at high risk of progression which showed good performance characteristics. These were assessed for suitability for progression against the standards for new TB diagnostic tests delineated in the published World Health Organization (WHO) technology product profiles (TPPs).

摘要

结核病(TB)仍然是一个主要的全球威胁,对活动性结核病((ATB),包括肺外(EPTB)和肺(PTB))和潜伏性结核病(LTBI)感染的诊断仍然具有挑战性,特别是在仍然严重依赖传统方法的高负担国家。尽管存在分子诊断方法,例如 Cepheid GeneXpert,但在所有高结核负担国家并非普遍可用。人们强烈关注用于结核病诊断的免疫生物标志物,这可能提供替代的低成本、快速诊断解决方案。在我们之前的基因表达研究中,我们在非人类灵长类动物的结核气溶胶挑战模型中鉴定了外周血白细胞(PBL)mRNA 生物标志物。在这里,我们描述了一项研究,以进一步验证之前研究中来自新患者和对照队列的选定 mRNA 生物标志物,作为进一步开发的前提。从英国和印度招募的 ATB 患者、LTBI 和来自英国的两组对照(i)低结核发病率地区(CNTRLA)和(ii)在英国和亚洲(CNTRLB)居住的个体中,分别从全血中纯化 mRNA ,后者是结核病高发病率地区。使用 Roche Lightcycler 480 qPCR 平台通过 qPCR 分析了 72 个 mRNA 生物标志物基因靶标,并使用 GeneSpring™14.9 生物信息学软件分析数据。使用方差分析(ANOVA)证实了 53 个生物标志物在 MTB 感染、LTBI 组和对照组之间的差异表达,其中 17 个具有统计学意义:CALCOCO2、CD52、GBP1、GBP2、GBP5、HLA-B、IFIT3、IFITM3、IRF1、LOC400759(GBP1P1)、NCF1C、PF4V1、SAMD9L、S100A11、TAF10、TAPBP 和 TRIM25。使用接收器操作特征(ROC)曲线分析对这些标志物进行了分析。使用简单的算术算法进一步分析了单个生物标志物和生物标志物组合。为原发性 ATB(PTB 和 EPTB)、LTBI 诊断和识别 LTBI 个体中的高进展风险,进一步评估了最小组合生物标志物面板,这些面板显示出良好的性能特征。使用新发布的世界卫生组织(WHO)技术产品简介(TPP)中规定的新结核病诊断测试标准评估了它们的适用性。

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