Suppr超能文献

用于挥发性有机化合物代谢物交叉验证分析的并行离线呼气采样

Parallel Offline Breath Sampling for Cross-Validated Analysis of Volatile Organic Compound Metabolites.

作者信息

Schulz Eray, Maciel Mariana, Wang Zhige, Heranjal Shivaum, Liu Xiaowen, Cao Sha, Relich Ryan F, Woollam Mark, Agarwal Mangilal

机构信息

Chemistry & Chemical Biology, Indiana University Indianapolis, Indianapolis, IN, USA.

Integrated Nanosystems Development Institute, Indiana University Indianapolis, Indianapolis, IN, USA.

出版信息

Metabolomics. 2025 Sep 17;21(5):138. doi: 10.1007/s11306-025-02340-1.

Abstract

INTRODUCTION

Volatile organic compounds (VOCs) in breath are potential biomarkers for medical conditions that may be used for non-invasive health monitoring. One challenge that still exists is determining the fidelity of reported VOC biomarkers. The lack of universally accepted sampling methods makes it difficult to identify reliable candidates, thus allowing for the potential of false discovery.

OBJECTIVES

The purpose of this study was to robustly profile VOCs in breath samples collected from relatively healthy participants using two offline methods for collection/analysis via solid phase microextraction (SPME) coupled to gas chromatography - mass spectrometry (GC-MS).

METHODS

158 cross-sectional volunteers provided one-time samples using two methods, one which directly sampled breath via SPME and another which collected breath in Tedlar bags. Using both methods, 10 volunteers provided an additional nine longitudinal samples. Ambient air samples were collected routinely, and a robust data processing schematic was used to ensure high quality reporting of on-breath VOCs.

RESULTS

Data screening and processing led to the identification of > 30 unique VOCs in both methods. Hierarchical clustering and correlation analyses demonstrated volatile terpene/-oids showed homologous trends in both data sets. Of the 12 VOCs identified using both methods, 11 analytes displayed statistically significant correlations (p < 0.05) in healthy breath samples. Finally, both methods were benchmarked regarding VOC reproducibility, and analyses showed that longitudinally collected samples were more reproducible compared to cross-sectional.

CONCLUSIONS

The quantitative results from both sampling methods mirrored each other, thus increasing the reliability and fidelity of VOCs reported along with the results from biostatistical analysis.

摘要

引言

呼出气体中的挥发性有机化合物(VOCs)是潜在的疾病生物标志物,可用于非侵入性健康监测。目前仍然存在的一个挑战是确定所报告的VOC生物标志物的准确性。缺乏普遍接受的采样方法使得难以识别可靠的候选物,从而存在假发现的可能性。

目的

本研究的目的是使用两种离线方法,通过固相微萃取(SPME)结合气相色谱-质谱联用(GC-MS),对从相对健康的参与者收集的呼出气体样本中的VOCs进行全面分析。

方法

158名横断面志愿者使用两种方法提供一次性样本,一种是通过SPME直接采集呼出气体,另一种是在 Tedlar 袋中收集呼出气体。使用这两种方法,10名志愿者额外提供了9个纵向样本。定期收集环境空气样本,并使用强大的数据处理示意图来确保对呼出VOCs进行高质量报告。

结果

数据筛选和处理导致在两种方法中均鉴定出超过30种独特的VOCs。层次聚类和相关性分析表明,挥发性萜烯/类萜在两个数据集中均呈现同源趋势。在两种方法鉴定出的12种VOCs中,11种分析物在健康呼出气体样本中显示出统计学上的显著相关性(p < 0.05)。最后,对两种方法在VOC重现性方面进行了基准测试,分析表明纵向收集的样本比横断面样本更具重现性。

结论

两种采样方法的定量结果相互印证,从而提高了所报告的VOCs的可靠性和准确性以及生物统计学分析的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc5/12443928/8a060e12bf18/11306_2025_2340_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验