AI Article Synopsis

  • The study focuses on improving analytical methods for detecting chemicals in blood, particularly using gas chromatography-high-resolution mass spectrometry (GC-HRMS), by reducing lipid contamination in samples.
  • A new extraction method was developed for small plasma volumes that enhances sensitivity and increases the ability to discover non-target compounds by allowing larger injection volumes without interference from lipids.
  • Testing the method on plasma samples showed it could reliably quantify a wide range of target analytes, detect structural variations, and could be scaled up for larger studies, making it useful for exposomics research.

Article Abstract

For comprehensive chemical exposomics in blood, analytical workflows are evolving through advances in sample preparation and instrumental methods. We hypothesized that gas chromatography-high-resolution mass spectrometry (GC-HRMS) workflows could be enhanced by minimizing lipid coextractives, thereby enabling larger injection volumes and lower matrix interference for improved target sensitivity and nontarget molecular discovery. A simple protocol was developed for small plasma volumes (100-200 μL) by using isohexane (H) to extract supernatants of acetonitrile-plasma (A-P). The HA-P method was quantitative for a wide range of hydrophobic multiclass target analytes (i.e., log > 3.0), and the extracts were free of major lipids, thereby enabling robust large-volume injections (LVIs; 25 μL) in long sequences (60-70 h, 70-80 injections) to a GC-Orbitrap HRMS. Without lipid removal, LVI was counterproductive because method sensitivity suffered from the abundant matrix signal, resulting in low ion injection times to the Orbitrap. The median method quantification limit was 0.09 ng/mL (range 0.005-4.83 ng/mL), and good accuracy was shown for a certified reference serum. Applying the method to plasma from a Swedish cohort ( = 32; 100 μL), 51 of 103 target analytes were detected. Simultaneous nontarget analysis resulted in 112 structural annotations (12.8% annotation rate), and Level 1 identification was achieved for 7 of 8 substances in follow-up confirmations. The HA-P method is potentially scalable for application in cohort studies and is also compatible with many liquid-chromatography-based exposomics workflows.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11465644PMC
http://dx.doi.org/10.1021/acs.est.4c05942DOI Listing

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