Quantitative Exposomics Targeting over 200 Toxicants and Key Biomarkers at the Picomolar Level

定量暴露组学可检测超过200种毒物和关键生物标志物,检测精度达皮摩尔级。

阅读:1

Abstract

The exposome encompasses environmental exposures throughout life and significantly impacts health and disease. Exposure chemicals, present at trace levels, are frequently quantified using targeted LC-MS/MS. Many existing methods are limited to a narrow range of analyte classes or lack sufficient sensitivity for exposomic analyses, and applicability to large sample cohorts for exposome-wide association studies (ExWAS) remains to be demonstrated. Here, we present a scalable, fit-for-purpose next-generation human biomonitoring (HBM) workflow for analyzing >230 biomarkers in urine, plasma, and serum using solid-phase extraction in 96-well plates and LC-MS/MS. Moreover, a complementary conceptual framework for validation criteria of assays designed to analyze large panels of highly diverse compounds at trace levels is proposed. Method robustness was evaluated, demonstrating extraction recovery (60-130%), matrix effects (SSE, 60-130%), inter-/intraday precision (RSD <30%), and high sensitivity (limit of detection <0.1 ng/mL) for 59-80% of the analytes across the investigated biological matrices. To showcase the method's applicability in epidemiological studies, 200 urine samples from pregnant women in a longitudinal pregnancy cohort were analyzed. More than 100 analytes including PFAS, drugs, air pollutants, pesticides, flame retardants, mycotoxins, industrial products, food processing contaminants, plastics-related chemicals, and phytotoxins, were detected, several for the first time in a U.S. urinary biomonitoring study. With its broad analyte coverage, ultimate sensitivity, robustness, and high sample throughput, this method meets the performance requirements for future large-scale ExWAS applications in public and personalized prevention research.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。