Department of Respiratory Medicine, AO Monaldi, Faculty of Medicine, University of Naples Federico II, Naples, Italy.
J Proteome Res. 2013 Mar 1;12(3):1502-11. doi: 10.1021/pr301171p. Epub 2013 Feb 12.
Nuclear magnetic resonance (NMR)-based metabolomics separates exhaled breath condensate (EBC) profiles of patients affected by pulmonary disease from those of healthy subjects. Here we show the discriminatory ability of NMR-based metabolomics in separating patients exposed to the same risk factor, namely, smoking habit in smoking-related diseases. Fifty duplicated EBC samples from a cohort of current smokers without chronic obstructive pulmonary disease (COPD, henceforth HS), COPD smokers, and subjects with established pulmonary Langerhans cell histiocytosis (PLCH) were analyzed by means of NMR spectroscopy followed by principal component analysis (PCA) and projection to latent structures discriminant analysis (PLS-DA). Clusterization of EBC spectra was disease-specific. COPD and PLCH samples present a profile different from that of HS, showing acetate increase and 1-methylimidazole reduction. An inverse behavior of 2-propanol and isobutyrate characterized COPD with respect to PLCH (high/low in COPD, low/high in PLCH). Both the 2-component and the 3-component PLS-DA models showed a 96% cross-validated accuracy, presenting R(2) and Q(2) values in the ranges of 0.97-0.87 and 0.91-0.78, respectively, and R(2) = 0.87 and Q(2) = 0.78, indicating that data variation is well explained by each model (R(2)), with a good predictivity (Q(2)). NMR spectra of EBC discriminate COPD and PLCH patients from HS and between them, with well-defined metabolic profiles for each class. The specificity of EBC profiles suggests that disease itself drives metabolic separation overwhelming the "common background" due to smoking habit. EBC-NMR investigation offers a powerful tool for assessing the evolution of airway diseases even in the presence of a strong common factor.
基于核磁共振（NMR）的代谢组学可以将患有肺部疾病的患者的呼气冷凝物（EBC）谱与健康受试者的 EBC 谱区分开来。在这里，我们展示了基于 NMR 的代谢组学在区分暴露于相同危险因素（即吸烟习惯）的患者方面的区分能力，这些患者患有与吸烟有关的疾病。对来自一组无慢性阻塞性肺疾病（COPD，下文简称 HS）的当前吸烟者、COPD 吸烟者和已确诊的肺朗格汉斯细胞组织细胞增生症（PLCH）患者的 50 个重复 EBC 样本进行了 NMR 光谱分析，然后进行主成分分析（PCA）和偏最小二乘判别分析（PLS-DA）。EBC 光谱的聚类是特定于疾病的。COPD 和 PLCH 样本的谱与 HS 不同，表现为乙酸盐增加和 1-甲基咪唑减少。与 PLCH 相比，COPD 的 2-丙醇和异丁酸的反向行为（COPD 中高/低，PLCH 中低/高）。双组分和三组分 PLS-DA 模型的交叉验证准确率均为 96%，R(2)和 Q(2)值分别在 0.97-0.87 和 0.91-0.78 之间，R(2)=0.87 和 Q(2)=0.78，表明数据变化由每个模型（R(2)）很好地解释，具有良好的预测能力（Q(2)）。EBC 的 NMR 谱可以将 COPD 和 PLCH 患者与 HS 患者以及他们之间区分开来，每个类别都有明确的代谢谱。EBC 谱的特异性表明，疾病本身驱动代谢分离，超过了由于吸烟习惯导致的“共同背景”。EBC-NMR 研究为评估气道疾病的演变提供了有力工具，即使存在强烈的共同因素也是如此。
