An Untargeted Exposure Study of Small Isolated Populations Using Atmospheric Gas Chromatography Coupled with High Resolution Mass Spectrometry

Importance of the topic

Understanding the full range of chemical exposures in human populations is critical for assessing environmental health risks. Persistent organic pollutants and related compounds can bioaccumulate and disrupt biological processes over time. An untargeted exposomics strategy that captures both known and unknown contaminants in a single analysis offers a comprehensive view of exposure profiles in small, isolated communities.

Objectives and study overview

This study aimed to compare contaminant patterns among five small isolated coastal communities using an untargeted approach. Pooled plasma samples were analyzed by atmospheric pressure gas chromatography coupled to high resolution mass spectrometry (APGC-HRMS) in data independent acquisition (MSE) mode. Both targeted screening of a custom POP database and untargeted multivariate analysis were performed to detect known pollutants and discover new exposure markers.

Methodology and Instrumentation

• Sample Preparation: Plasma (2 mL) spiked with 13C internal standard, denatured with ethanol and saturated ammonium sulfate, extracted with hexane, cleaned on florisil and concentrated to 20 µL.
• GC Conditions: Restek RTX-5MS column (0.25 µm × 0.25 mm × 30 m), splitless injection, temperature ramp from 80 °C to 340 °C over 37.7 min, constant flow at 2 mL/min.
• MS Conditions: Waters Xevo G2-XS QTof, APGC positive ion mode, MSE acquisition from m/z 50–1000, low collision energy at 6 eV, high energy ramp 30–75 eV, source at 150 °C, corona current 3 µA.
• Data Processing: UNIFI Scientific Information System and Progenesis QI for retention alignment, aggregate peak picking, targeted MetaScope search and untargeted statistical analysis.

Main results and discussion

Targeted analysis against 98 expected POPs identified 24 compounds, including hexachlorobenzene, multiple PCBs, DDT metabolites and PBDE 99. Community 1 showed the highest enrichments, with PCB 118 increasing 2.6-fold. Untargeted PCA and OPLS-DA in Progenesis QI and EZinfo separated Community 1 from the others. S-plot analysis highlighted 17 significant markers. ChemSpider searches and in silico fragmentation attributed two novel markers to tocopherol (vitamin E) and 1,3-benzothiazole derivatives. Authentic standard injections confirmed the 1,3-benzothiazole assignment.

Practical benefits and applications

• Combined APGC soft ionization and MSE fragmentation deliver intact precursor ions and structural information in one run.
• Progenesis QI ensures robust retention alignment, peak matching and zero missing values for reliable multivariate statistics.
• Automated database searching with ChemSpider and in silico fragmentation accelerates identification of unknown environmental markers.

Future trends and potential applications

Extending custom libraries and integrating advanced chemoinformatics and machine learning will enhance exposome characterization. Applying this workflow to larger cohorts and diverse geographical regions can deepen our understanding of exposure–disease relationships and support environmental health policies.

Conclusion

The APGC-HRMS MSE workflow with Progenesis QI processing provides a streamlined platform for simultaneous targeted and untargeted exposomics. It effectively distinguishes contaminant profiles among isolated populations and identifies both expected POPs and novel exposure markers, enabling comprehensive environmental biomonitoring.

Reference

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