Exhaled human breath analysis in active pulmonary tuberculosis diagnostics by comprehensive gas chromatography-mass spectrometry and chemometric techniques
Exhaled human breath analysis in active pulmonary tuberculosis diagnostics by comprehensive gas chromatography-mass spectrometry and chemometric techniques
复制标题
DOI：
10.1088/1752-7163/aae80e
复制
发表时间：
2019-01-01
影响因子：
3.8
通讯作者：
Hill, Jane E.
中科院分区：
文献类型：
--
作者：
Beccaria, Marco;Bobak, Carly;Hill, Jane E.
结核病(TB)是最致命的传染病，但对许多亚群来说，无法对这种疾病进行准确的诊断。在这项研究中，我们还考虑了吸烟者和人类免疫缺陷病毒(HIV)携带者患结核病的几个危险因素，探讨了利用人类呼吸诊断结核病可疑患者的可能性。呼气分析作为痰依赖测试的替代方法，有可能提供一种简单、快速、非侵入性和随时可用的诊断服务，从而积极改变结核病的检测。来自南非一家诊所的50人参加了这项初步研究。利用热解吸-全面的二维气相色谱-飞行时间质谱学方法和化学计量学技术，对活动性结核病患者的人体呼吸进行了研究。从呼吸中挥发性代谢物的整个光谱中，采用了三种机器学习算法(支持向量机、偏最小二乘判别分析和随机森林)来选择可能对活动性结核病诊断有用的区别性挥发性分子。随机林表现最好，训练和测试数据的敏感度分别为0.82和1.00，特异度分别为0.92和0.60。对这些算法所涉及的化合物的非监督分析表明，它们为从其他患者那里聚类活动性结核病提供了重要信息。这些结果表明，开发一种利用患者呼吸对活动性结核病进行非侵入性诊断的方法是一种潜在的丰富的研究途径，包括在合并艾滋病毒的患者中。
Tuberculosis (TB) is the deadliest infectious disease, and yet accurate diagnostics for the disease are unavailable for many subpopulations. In this study, we investigate the possibility of using human breath for the diagnosis of active TB among TB suspect patients, considering also several risk factors for TB for smokers and those with human immunodeficiency virus (HIV). The analysis of exhaled breath, as an alternative to sputum-dependent tests, has the potential to provide a simple, fast, non-invasive, and readily available diagnostic service that could positively change TB detection. A total of 50 individuals from a clinic in South Africa were included in this pilot study. Human breath has been investigated in the setting of active TB using the thermal desorption-comprehensive two-dimensional gas chromatography-time of flight mass spectrometry methodology and chemometric techniques. From the entire spectrum of volatile metabolites in breath, three machine learning algorithms (support vector machines, partial least squares discriminant analysis, and random forest) to select discriminatory volatile molecules that could potentially be useful for active TB diagnosis were employed. Random forest showed the best overall performance, with sensitivities of 0.82 and 1.00 and specificities of 0.92 and 0.60 in the training and test data respectively. Unsupervised analysis of the compounds implicated by these algorithms suggests that they provide important information to cluster active TB from other patients. These results suggest that developing a non-invasive diagnostic for active TB using patient breath is a potentially rich avenue of research, including among patients with HIV comorbidities.