Peak Tables and the analysis script of Clinical Breathomics Database

We have performed the GC‒MS analysis for detecting breath molecules in 233 patient samples to create the clinical breathomics dataset. Breath molecules can reflect various conditions, including human psychological and pathological states as well as the microbiome. The noninvasive nature of detecting breath molecules has significant advantages in terms of diagnostic and monitoring capabilities. This dataset contains VOCs present in breath of asthma, bronchiectasis and chronic obstructive pulmonary disease. This dataset is an extensive human clinical breath molecule collection for 3 diseases and has been gathered using consistent sample collection protocols. We believe this clinical breathomics dataset will be a valuable resource for researchers and clinicians as they seek to identify and further study potential biomarkers in patient breath.

本研究通过气相色谱-质谱联用（Gas Chromatography-Mass Spectrometry，GC-MS）分析，对233例患者样本中的呼出气分子进行检测，构建了临床呼吸组学数据集（clinical breathomics dataset）。呼出气分子可反映多种人体状态，包括心理状态、病理状态以及微生物组（microbiome）。呼出气分子检测的无创特性，在疾病诊断与病情监测领域具备显著优势。本数据集涵盖哮喘（asthma）、支气管扩张症（bronchiectasis）及慢性阻塞性肺疾病（chronic obstructive pulmonary disease）患者呼出气中的挥发性有机化合物（Volatile Organic Compounds，VOCs）。本数据集针对上述3种疾病收录了大规模的人体临床呼出气分子数据，所有样本均采用统一的采集规范完成获取。我们相信，这款临床呼吸组学数据集将为研究人员与临床医师识别、深入探究患者呼出气中的潜在生物标志物提供极具价值的研究资源。