High-performance quantitative exposomics covering up to >230 toxicants and key biomarkers

01 April 2025, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The exposome encompasses environmental exposures throughout life and significantly impacts health and disease. Exposure chemicals, typically present at trace levels, are mostly quantified using targeted LC-MS/MS. However, many existing methods are limited to a narrow range of analyte classes or lack sufficient sensitivity for exposomic analyses and the applicability to large sample cohorts for exposome-wide association studies (ExWAS) remains to be demonstrated. Here, we present a scala-ble workflow for analyzing >230 biomarkers in urine, plasma, and serum using solid-phase extraction in 96-well plates and LC-MS/MS. Moreover, a new conceptual framework for validation criteria of assays designed to analyze highly diverse com-pounds at trace levels is proposed. Method robustness was evaluated, demonstrating suitable extraction recovery and matrix effects (SSE) within 60-130%, inter-/intra-day precision (RSD) <30%, and exceptional sensitivity (limit of detection, 0.015-50 pg/mL) for 60-80% of the analytes across the investigated matrices. To showcase the method's applicability in epidemio-logical studies, 200 urine samples from pregnant women in a longitudinal cohort were analyzed, with more than 130 bi-omarkers detected in the real-life samples, several for the first time in US urine. With its broad analyte coverage, excellent sensitivity, robustness, and exceptionally high sample throughput, this method offers the necessary performance for large-scale ExWAS studies in the future.

Keywords

Next-generation human biomonitoring
Mass spectrometry
Early-life chemical exposure
Exposome wide association study (ExWAS)
Public and environmental health

Supplementary materials

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Supplementary Information
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Additional information for meterials, experiments, results and discussion, and supplementary figures.
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Supplementary Tables Part 1
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Supplementary Tables Part 1, S1-S12
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Supplementary Tables Part 2
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Supplementary Tables Part 1, S13-S23
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