4.7 Review

Recent advances in non-targeted screening analysis using liquid chromatography - high resolution mass spectrometry to explore new biomarkers for human exposure

Journal

TALANTA
Volume 219, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.talanta.2020.121339

Keywords

Non-targeted screening analysis; LC-HRMS; Unknown xenobiotics; Human biomonitoring; Exposure biomarkers

Funding

  1. Canadian Federal Government under the Chemicals Management Plan (CMP)

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Over the last decade, advances related to high-resolution mass spectrometry (HRMS) have led to improved capabilities for non-targeted chemical analyses. Important applications for these capabilities include identifying unknown xenobiotics and discovering emerging contaminants in human samples as exposure biomarkers. Despite technological advances, identifying unknown compounds by non-targeted analyses remains challenging due in part to the lack of MS spectral libraries and inherent sample complexity resulting in the generation of large amounts of MS data. While high resolution can separate nominally isobaric compounds in a mass spectrum, isomers cannot be distinguished. Much work also remains to develop models to predict both mass spectra and retention times for the unexplored regions of chemical space. In this review, we focus on recent advances and applications of non-targeted analyses using liquid chromatography - high-resolution mass spectrometry (LC-HRMS) in human biomonitoring, including sample preparation, molecular formula assignments, and prediction models for retention times and mass fragmentations, to enable and improve identifications of unknown chem-icals. The purpose of this review is to improve our understanding of the applicability and limitations in both the analytical methods and data analysis aspects of non-targeted analysis in human exposure studies. We also discuss the challenges and prospects in this field for future research on sample preparation, identification confidence and accuracy, data processing tools, MS spectra comparability, liquid chromatographic retention time (RT) prediction algorithms, and quantitative capabilities.

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