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使用便携式气相色谱法进行成人哮喘表型的实时呼吸分析

Real Time Breath Analysis Using Portable Gas Chromatography for Adult Asthma Phenotypes.

作者信息

Sharma Ruchi, Zang Wenzhe, Zhou Menglian, Schafer Nicole, Begley Lesa A, Huang Yvonne J, Fan Xudong

机构信息

Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.

Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.

出版信息

Metabolites. 2021 Apr 23;11(5):265. doi: 10.3390/metabo11050265.

Abstract

Asthma is heterogeneous but accessible biomarkers to distinguish relevant phenotypes remain lacking, particularly in non-Type 2 (T2)-high asthma. Moreover, common clinical characteristics in both T2-high and T2-low asthma (e.g., atopy, obesity, inhaled steroid use) may confound interpretation of putative biomarkers and of underlying biology. This study aimed to identify volatile organic compounds (VOCs) in exhaled breath that distinguish not only asthmatic and non-asthmatic subjects, but also atopic non-asthmatic controls and also by variables that reflect clinical differences among asthmatic adults. A total of 73 participants (30 asthma, eight atopic non-asthma, and 35 non-asthma/non-atopic subjects) were recruited for this pilot study. A total of 79 breath samples were analyzed in real-time using an automated portable gas chromatography (GC) device developed in-house. GC-mass spectrometry was also used to identify the VOCs in breath. Machine learning, linear discriminant analysis, and principal component analysis were used to identify the biomarkers. Our results show that the portable GC was able to complete breath analysis in 30 min. A set of nine biomarkers distinguished asthma and non-asthma/non-atopic subjects, while sets of two and of four biomarkers, respectively, further distinguished asthmatic from atopic controls, and between atopic and non-atopic controls. Additional unique biomarkers were identified that discriminate subjects by blood eosinophil levels, obese status, inhaled corticosteroid treatment, and also acute upper respiratory illnesses within asthmatic groups. Our work demonstrates that breath VOC profiling can be a clinically accessible tool for asthma diagnosis and phenotyping. A portable GC system is a viable option for rapid assessment in asthma.

摘要

哮喘具有异质性,但仍缺乏可用于区分相关表型的生物标志物,尤其是在非2型(T2)高哮喘中。此外,T2高哮喘和T2低哮喘的常见临床特征(如特应性、肥胖、吸入性类固醇使用)可能会混淆对假定生物标志物及其潜在生物学机制的解释。本研究旨在识别呼出气中的挥发性有机化合物(VOC),这些化合物不仅能区分哮喘患者和非哮喘患者,还能区分特应性非哮喘对照者,以及反映哮喘成年患者临床差异的变量。本试点研究共招募了73名参与者(30名哮喘患者、8名特应性非哮喘患者和35名非哮喘/非特应性受试者)。使用内部开发的自动化便携式气相色谱(GC)设备对总共79份呼出气样本进行了实时分析。还使用GC-质谱法识别呼出气中的VOC。机器学习、线性判别分析和主成分分析被用于识别生物标志物。我们的结果表明,便携式GC能够在30分钟内完成呼出气分析。一组9种生物标志物可区分哮喘患者和非哮喘/非特应性受试者,而分别由2种和4种生物标志物组成的集合进一步区分了哮喘患者和特应性对照者,以及特应性和非特应性对照者。还识别出了其他独特的生物标志物,可根据血液嗜酸性粒细胞水平、肥胖状态、吸入性糖皮质激素治疗情况以及哮喘组内的急性上呼吸道疾病对受试者进行区分。我们的工作表明,呼出气VOC分析可成为一种临床上易于使用的哮喘诊断和表型分析工具。便携式GC系统是哮喘快速评估的可行选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0937/8145057/d05d61217e46/metabolites-11-00265-g001.jpg

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