Department of Electrical Electronic Engineering and Automation, Universitat Rovira I Virgili (URV), 43003, Tarragona, Spain; Department of Nutrition and Metabolism, Institut D'Investigació Sanitària Pere Virgili (IISPV), CERCA, 43204, Spain.
Department of Electrical Electronic Engineering and Automation, Universitat Rovira I Virgili (URV), 43003, Tarragona, Spain; Department of Nutrition and Metabolism, Institut D'Investigació Sanitària Pere Virgili (IISPV), CERCA, 43204, Spain; Centre for Biomedical Research in Diabetes and Associated Metabolic Diseases (CIBERDEM), Av. Monforte de Lemos, 3-5, Pabellón 11, Planta 0, 28029, Madrid, Spain.
Anal Chim Acta. 2024 Nov 15;1329:343261. doi: 10.1016/j.aca.2024.343261. Epub 2024 Sep 18.
Volatile organic compounds (VOCs) present in human urine are promising biomarkers for various health conditions and environmental exposures. However, their reliable detection is challenging due to the complexity of urinary matrices and the low concentrations of VOCs. Moreover, untargeted approaches present considerable challenges in terms of data interpretation, increasing the complexity of method development. Here we address these challenges by developing a new method that combines solid-phase microextraction (SPME) Arrow with gas chromatography-high resolution mass spectrometry (GC-HRMS), using a design of experiments (DOE) approach for targeted and untargeted compounds. This methodology, specifically tailored for SPME Arrow, represents a significant advancement in untargeted urinary analysis.
The method was developed based on targeted and untargeted outcomes, were ranking results focus on the highest response area of 11 spiked target VOCs representative of urinary volatilomics, and on identifying the maximum untargeted number of VOCs. The method was developed focusing on the highest response area of 11 spiked target VOCs representative of urinary volatilomics and identifying the maximum number of VOCs. A univariate method determined the optimal coating type, urine volume, and salt addition. Subsequently, a central composite design (CCD) DOE was used to determine ideal temperature, extraction, and incubation times. The best method obtained has an extraction time of 60 min at a temperature of 53 °C, with an SPME Arrow CAR/PDMS using 2 mL of urine, with 0.25 % w/v of NaCl and a pH of 2. Compared to conventional SPME fibers, the SPME Arrow showed improved extraction efficiency, detecting more VOCs. Finally, the enhanced method was successfully applied to urine samples from children exposed and non-exposed to tobacco smoke, identifying specific VOCs, like p-cymene and p-isopropenyl toluene related to tobacco exposure.
By integrating both targeted and untargeted approaches, the developed method comprehensively captures the complexity of urinary metabolomics. This dual strategy ensures the precise identification of known compounds and the discovery of novel biomarkers, thereby providing a more complete metabolic profile. Such an approach is crucial for advancing in non-invasive diagnostics and environmental health studies, as it offers deeper insights into the intricate relationships between metabolic processes and various health conditions.
人体尿液中存在的挥发性有机化合物（VOCs）是各种健康状况和环境暴露的有前途的生物标志物。然而，由于尿液基质的复杂性和 VOCs 的低浓度，它们的可靠检测具有挑战性。此外，非靶向方法在数据解释方面存在相当大的挑战，增加了方法开发的复杂性。在这里，我们通过开发一种新的方法来解决这些挑战，该方法将固相微萃取（SPME）Arrow 与气相色谱-高分辨率质谱（GC-HRMS）相结合，使用实验设计（DoE）方法来针对和非靶向化合物。这种专门为 SPME Arrow 量身定制的方法代表了非靶向尿液分析的重大进展。
该方法是基于靶向和非靶向结果开发的，排名结果侧重于 11 种代表尿液挥发组学的靶向 VOCs 的最高响应区域，以及确定最大数量的非靶向 VOCs。该方法的开发侧重于代表尿液挥发组学的 11 种靶向 VOCs 的最高响应区域，并确定 VOCs 的最大数量。单变量方法确定了最佳涂层类型、尿液量和盐添加量。随后，使用中心复合设计（CCD）DoE 确定理想的温度、提取和孵育时间。获得的最佳方法具有 60 分钟的提取时间，温度为 53°C，使用 2mL 尿液，0.25%w/v NaCl 和 pH 值为 2。与传统的 SPME 纤维相比，SPME Arrow 显示出改进的提取效率，检测到更多的 VOCs。最后，该增强方法成功应用于接触和不接触烟草烟雾的儿童尿液样本，鉴定出特定的 VOC，如与烟草暴露相关的 p-枯茗和 p-异丙基甲苯。
通过整合靶向和非靶向方法，开发的方法全面捕捉了尿液代谢组学的复杂性。这种双重策略确保了已知化合物的精确识别和新生物标志物的发现，从而提供了更完整的代谢谱。这种方法对于推进非侵入性诊断和环境健康研究至关重要，因为它提供了对代谢过程与各种健康状况之间复杂关系的更深入了解。
