Abstract：
BACKGROUND: Asthma is characterized by phenotypes of different clinical, demographic, and pathological characteristics. Identifying the profile of exhaled volatile organic compounds (VOCs) in asthma phenotypes may facilitate establishing biomarkers and understanding asthma background pathogenesis. This study aimed to identify exhaled VOCs that characterize severe asthma phenotypes among patients with asthma.
METHODS: This was a multicenter cross-sectional study of patients with severe asthma in Japan. Clinical data were obtained from medical records, and questionnaires were collected. Exhaled breath was sampled and subjected to thermal desorption gas chromatography-mass spectrometry (GC/MS).
RESULTS: Using the decision tree established in the previous nationwide asthma cohort study, 245 patients with asthma were divided into five phenotypes and subjected to exhaled VOC analysis with 50 healthy controls (HCs). GC/MS detected 243 VOCs in exhaled breath samples, and 142 frequently detected VOCs (50% of all samples) were used for statistical analyses. Cluster analysis assigning the groups with similar VOC profile patterns showed the highest similarities between phenotypes 3 and 4 (early-onset asthma phenotypes), followed by the similarities between phenotypes 1 and 2 (late-onset asthma phenotypes). Comparisons between phenotypes 1-5 and HC revealed 19 VOCs, in which only methanesulfonic anhydride showed p < 0.05 adjusted by false discovery rate (FDR). Comparison of these phenotypes yielded several VOCs showing different trends (p < 0.05); however, no VOCs showed p < 0.05 adjusted by FDR.
CONCLUSIONS: Exhaled VOC profiles may be useful for distinguishing asthma and asthma phenotypes; however, these findings need to be validated, and their pathological roles should be clarified.
METHODS: This was a multicenter cross-sectional study of patients with severe asthma in Japan. Clinical data were obtained from medical records, and questionnaires were collected. Exhaled breath was sampled and subjected to thermal desorption gas chromatography-mass spectrometry (GC/MS).
RESULTS: Using the decision tree established in the previous nationwide asthma cohort study, 245 patients with asthma were divided into five phenotypes and subjected to exhaled VOC analysis with 50 healthy controls (HCs). GC/MS detected 243 VOCs in exhaled breath samples, and 142 frequently detected VOCs (50% of all samples) were used for statistical analyses. Cluster analysis assigning the groups with similar VOC profile patterns showed the highest similarities between phenotypes 3 and 4 (early-onset asthma phenotypes), followed by the similarities between phenotypes 1 and 2 (late-onset asthma phenotypes). Comparisons between phenotypes 1-5 and HC revealed 19 VOCs, in which only methanesulfonic anhydride showed p < 0.05 adjusted by false discovery rate (FDR). Comparison of these phenotypes yielded several VOCs showing different trends (p < 0.05); however, no VOCs showed p < 0.05 adjusted by FDR.
CONCLUSIONS: Exhaled VOC profiles may be useful for distinguishing asthma and asthma phenotypes; however, these findings need to be validated, and their pathological roles should be clarified.
摘要：
背景：哮喘的特征是不同的临床表型，人口统计学,和病理特征。识别哮喘表型中呼出的挥发性有机化合物（VOCs）的概况可能有助于建立生物标志物和了解哮喘的背景发病机制。这项研究旨在确定哮喘患者中表征严重哮喘表型的呼出VOC。
方法：这是一项针对日本重度哮喘患者的多中心横断面研究。临床数据来自医疗记录，并收集问卷。对呼气取样并进行热解吸气相色谱法-质谱法(GC/MS)。
结果：使用先前全国哮喘队列研究中建立的决策树，将245名哮喘患者分为5种表型，并与50名健康对照（HCs）进行呼出VOC分析。GC/MS在呼出气样本中检测到243种挥发性有机化合物，142例经常检测到的挥发性有机化合物(占所有样本的50%)被用于统计分析。将具有相似VOC特征模式的组进行聚类分析显示，表型3和4（早发性哮喘表型）之间的相似性最高。其次是表型1和2(晚发性哮喘表型)之间的相似性.表型1-5和HC之间的比较揭示了19种VOC，其中只有甲磺酸酐显示p<0.05，通过错误发现率（FDR）调整。这些表型的比较产生了几种表现出不同趋势的VOCs（p<0.05）；然而，经FDR校正,无VOCs显示p<0.05。
结论：呼出VOC谱可用于区分哮喘和哮喘表型；然而，这些发现需要验证，他们的病理作用应该得到澄清。
方法：这是一项针对日本重度哮喘患者的多中心横断面研究。临床数据来自医疗记录，并收集问卷。对呼气取样并进行热解吸气相色谱法-质谱法(GC/MS)。
结果：使用先前全国哮喘队列研究中建立的决策树，将245名哮喘患者分为5种表型，并与50名健康对照（HCs）进行呼出VOC分析。GC/MS在呼出气样本中检测到243种挥发性有机化合物，142例经常检测到的挥发性有机化合物(占所有样本的50%)被用于统计分析。将具有相似VOC特征模式的组进行聚类分析显示，表型3和4（早发性哮喘表型）之间的相似性最高。其次是表型1和2(晚发性哮喘表型)之间的相似性.表型1-5和HC之间的比较揭示了19种VOC，其中只有甲磺酸酐显示p<0.05，通过错误发现率（FDR）调整。这些表型的比较产生了几种表现出不同趋势的VOCs（p<0.05）；然而，经FDR校正,无VOCs显示p<0.05。
结论：呼出VOC谱可用于区分哮喘和哮喘表型；然而，这些发现需要验证，他们的病理作用应该得到澄清。
