Respiratory Research Group, Faculty of Medical and Human Sciences, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Thorax. 2011 Sep;66(9):804-9. doi: 10.1136/thx.2010.156695. Epub 2011 Jul 11.
Breath volatile organic compounds (VOCs) may be useful for asthma diagnosis and phenotyping, identifying patients who could benefit from personalised therapeutic strategies. The authors aimed to identify specific patterns of breath VOCs in patients with asthma and in clinically relevant disease phenotypes.
Breath samples were analysed by gas chromatography-mass spectrometry. The Asthma Control Questionnaire was completed, together with lung function and induced sputum cell counts. Breath data were reduced to principal components, and these principal components were used in multiple logistic regression to identify discriminatory models for diagnosis, sputum inflammatory cell profile and asthma control.
The authors recruited 35 patients with asthma and 23 matched controls. A model derived from 15 VOCs classified patients with asthma with an accuracy of 86%, and positive and negative predictive values of 0.85 and 0.89, respectively. Models also classified patients with asthma based on the following phenotypes: sputum (obtained in 18 patients with asthma) eosinophilia ≥2% area under the receiver operating characteristics (AUROC) curve 0.98, neutrophilia ≥40% AUROC 0.90 and uncontrolled asthma (Asthma Control Questionnaire ≥1) AUROC 0.96.
Detection of characteristic breath VOC profiles could classify patients with asthma versus controls, and clinically relevant disease phenotypes based on sputum inflammatory profile and asthma control. Prospective validation of these models may lead to clinical application of non-invasive breath profiling in asthma.
呼吸挥发性有机化合物（VOCs）可能有助于哮喘的诊断和表型分析，以确定可能从个体化治疗策略中获益的患者。作者旨在确定哮喘患者和临床相关疾病表型中呼吸 VOCs 的特定模式。
使用气相色谱-质谱法分析呼吸样本。完成哮喘控制问卷，同时进行肺功能和诱导痰细胞计数。将呼吸数据简化为主成分，然后将这些主成分用于多元逻辑回归，以确定用于诊断、痰炎症细胞谱和哮喘控制的判别模型。
作者招募了 35 名哮喘患者和 23 名匹配的对照者。由 15 种 VOC 组成的模型将哮喘患者分类的准确率为 86%，阳性和阴性预测值分别为 0.85 和 0.89。该模型还根据以下表型对哮喘患者进行分类：痰（18 名哮喘患者中获得）嗜酸性粒细胞≥2% 受试者工作特征（ROC）曲线下面积（AUROC）为 0.98，中性粒细胞≥40% AUROC 为 0.90，未控制的哮喘（哮喘控制问卷≥1）AUROC 为 0.96。
检测特征性呼吸 VOC 谱可将哮喘患者与对照者以及基于痰炎症谱和哮喘控制的临床相关疾病表型进行分类。对这些模型进行前瞻性验证可能会导致非侵入性呼吸分析在哮喘中的临床应用。
