Abstract：
Endocrine disrupting chemicals are of concern because of possible human health effects, thus they are frequently included in biomonitoring studies. Current analytical methods are focused on known chemicals and are incapable of identifying or quantifying other unknown chemicals and their metabolites. Non-targeted analysis (NTA) methods are advantageous since they allow for broad chemical screening, which provides a more comprehensive characterization of human chemical exposure, and can allow elucidation of metabolic pathways for unknown chemicals. There are still many challenges associated with NTA, which can impact the results obtained. The chemical space, i.e., the group of known and possible compounds within the scope of the method, must clearly be defined based on the sample preparation, as this is critical in identifying chemicals with confidence. Data acquisition modes and mobile phase additives used with liquid chromatography coupled to high-resolution mass-spectrometry can affect the chemicals ionized and structural identification based on the spectral quality. In this study, a sample preparation method was developed using a novel clean-up approach with CarbonS cartridges, for endocrine-disrupting chemicals in urine, including new bisphenol A analogues and benzophenone-based UV filters, like methyl bis (4-hydroxyphenyl acetate). The study showed that data dependent acquisition (DDA) had a lower identification rate (40%) at low spiking levels, i.e., 1 ng/mL, compared to data independent acquisition (DIA) (57%), when Compound Discoverer was used. In DDA, more compounds were identified using Compound Discoverer, with an identification rate of 95% when ammonium acetate was compared to acetic acid (82%) as a mobile phase additive. TraceFinder software had an identification rate of 53% at 1 ng/mL spiking level using the DDA data, compared to 40% using the DIA data. Using the developed method, 2,4 bisphenol F was identified for the first time in urine samples. The results show how NTA can provide human exposure information for risk assessment and regulatory action but standardized reporting of procedures is needed to ensure study results are reproducible and accurate. His Majesty the King in Right of Canada, as represented by the Minister of Health, 2024.
摘要：
内分泌干扰化学物质由于可能对人类健康造成影响而令人担忧，因此，它们经常被包括在生物监测研究中。目前的分析方法集中在已知的化学物质上，无法识别或定量其他未知的化学物质及其代谢物。非目标分析（NTA）方法是有利的，因为它们允许广泛的化学筛选，这提供了更全面的人体化学暴露的特征，并且可以阐明未知化学物质的代谢途径。还有许多与NTA相关的挑战，这可能会影响获得的结果。化学空间，即，方法范围内的一组已知和可能的化合物，必须根据样品制备清楚地定义，因为这对于自信地识别化学品至关重要。数据采集模式和液相色谱与高分辨率质谱联用的流动相添加剂会影响基于光谱质量的化学物质电离和结构识别。在这项研究中,使用一种新型的CarbonS墨盒清理方法开发了一种样品制备方法，尿液中的内分泌干扰化学物质，包括新的双酚A类似物和二苯甲酮紫外线过滤剂，如双(4-羟基苯基乙酸甲酯)。研究表明，在低尖峰水平下，数据相关采集(DDA)的识别率较低(40%)，即，1ng/mL,与数据独立采集(DIA)(57%)相比，当使用复合发现者时。在DDA，使用CompoundDiscoverer鉴定出更多化合物，当将乙酸铵与乙酸（82％）作为流动相添加剂进行比较时，识别率为95％。使用DDA数据，TraceFinder软件在1ng/mL加标水平下的识别率为53％，与使用DIA数据的40%相比。使用开发的方法，首次在尿液样品中鉴定出2,4双酚F。结果表明，NTA如何为风险评估和监管行动提供人体暴露信息，但需要标准化程序报告，以确保研究结果的可重复性和准确性。
