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High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

Abstract

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

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References
1.
Thevis M, Thomas A, Pop V, Schanzer W . Ultrahigh pressure liquid chromatography-(tandem) mass spectrometry in human sports drug testing: possibilities and limitations. J Chromatogr A. 2013; 1292:38-50. DOI: 10.1016/j.chroma.2012.12.048. View

2.
Wong J, Wang J, Chow W, Carlson R, Jia Z, Zhang K . Perspectives on Liquid Chromatography-High-Resolution Mass Spectrometry for Pesticide Screening in Foods. J Agric Food Chem. 2018; 66(37):9573-9581. DOI: 10.1021/acs.jafc.8b03468. View

3.
Pejchinovski M, Klein J, Ramirez-Torres A, Bitsika V, Mermelekas G, Vlahou A . Comparison of higher energy collisional dissociation and collision-induced dissociation MS/MS sequencing methods for identification of naturally occurring peptides in human urine. Proteomics Clin Appl. 2015; 9(5-6):531-42. DOI: 10.1002/prca.201400163. View

4.
Blazenovic I, Kind T, Torbasinovic H, Obrenovic S, Mehta S, Tsugawa H . Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy. J Cheminform. 2017; 9(1):32. PMC: 5445034. DOI: 10.1186/s13321-017-0219-x. View

5.
Yu M, Dolios G, Petrick L . Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features. J Cheminform. 2022; 14(1):6. PMC: 8848943. DOI: 10.1186/s13321-022-00586-8. View