Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, P. R. China.
Institute of Eco-Chongming (IEC), Shanghai 200062, P. R. China.
Environ Sci Technol. 2024 Oct 22;58(42):18541-18553. doi: 10.1021/acs.est.4c04575. Epub 2024 Sep 28.
Breathomics, a growing field in exposure monitoring and clinical diagnostics, has faced accuracy challenges due to unclear contributing factors. This study aims to enhance the potential of breathomics in various frontiers by categorizing exhaled volatile organic compounds (VOCs) as endogenous or exogenous. Analyzing ambient air and breath samples from 271 volunteers via TD-GC × GC-TOF MS/FID, we identify and quantify 50 common VOCs in exhaled breath. Advanced quantitative structure-property relationships and compartment models are employed to obtain VOCs kinetic parameters. This in-depth approach allows us to accurately determine the alveolar concentration of VOCs and further discern their origins, facilitating personalized application of breathomics in exposure assessment and disease diagnosis. Our findings demonstrate that prolonged external exposure turns humans into secondary pollutant sources. Analysis of endogenous VOCs reveals that internal exposure poses more significant health risks than external. Moreover, by correcting environmental backgrounds, we improve the accuracy of gastrointestinal disease diagnostic models by 15-25%. This advancement in identifying VOC origins via compartmental models promises to elevate the clinical relevance of breathomics, marking a leap forward in exposure assessment and precision medicine.
呼吸组学作为暴露监测和临床诊断领域的一个新兴分支,由于其影响因素不明确,一直面临着准确性挑战。本研究旨在通过将呼气挥发性有机化合物(VOC)分类为内源性或外源性,从而提高呼吸组学在各个领域的应用潜力。通过 TD-GC×GC-TOF MS/FID 对 271 名志愿者的环境空气和呼吸样本进行分析,我们在呼出的呼吸样本中识别并定量了 50 种常见的 VOC。采用先进的定量构效关系和隔室模型来获取 VOC 的动力学参数。这种深入的方法可以准确地确定 VOC 的肺泡浓度,并进一步区分它们的来源,从而促进呼吸组学在暴露评估和疾病诊断中的个性化应用。我们的研究结果表明,长期的外部暴露会使人类成为二次污染物的来源。对内源性 VOC 的分析表明,内部暴露比外部暴露对健康的威胁更大。此外,通过校正环境背景,我们将胃肠道疾病诊断模型的准确性提高了 15%至 25%。通过隔室模型识别 VOC 来源的这一进展有望提高呼吸组学的临床相关性,标志着在暴露评估和精准医学方面迈出了重要一步。