A (Non)Targeted Method for Analysis of the Serum Exposome Using Atmospheric Pressure Gas Chromatography-Mass Spectrometry

Academic Research Topics in Environmental Measurement and Monitoring
Oral Presentation

Prepared by K. Jobst1, R. Di Lorenzo2, E. Reiner3, J. Sled4, A. Mell1
1 - McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S4M1, Canada
2 - The Hospital for Sick Children, Mouse Imaging Centre, 25 Orde Street, Toronto, Ontario, M5T 3H7, Canada
3 - University of Toronto, , Toronto, Ontario, Canada
4 - The Hospital for Sick Children, Mouse Imaging Centre, , Toronto, Ontario, Canada


Contact Information: karlj@mcmaster.ca; 416-235-5893


ABSTRACT

Environmental risk factors, such as diet, obesity, smoking and exposure to environmental toxicants, may contribute more than genetic factors to the risks of cancer and other non-communicable diseases. The exposome represents all environmental exposures during the course of a lifetime. Persistent organic pollutants (POPs) represent an important subset of environmental toxicants that exhibit common characteristics, such as persistence, toxicity and a tendency to (bio)accumulate in wildlife and humans.
This contribution reports on a sensitive, quantitative and high-throughput method for the analysis of a signature list of legacy and emerging halogenated POPs in 200uL of serum. The method employs stir-bar sorptive extraction (SBSE), which enables preparation of >20 samples in four hours. Detection is achieved using thermal desorption gas chromatography (GC) coupled to a quadrupole time-of-flight mass spectrometer (qTOF-MS). Sensitivity is enhanced by atmospheric pressure chemical ionization (APCI), a soft ionization technique that minimizes fragmentation and maximizes the yield of target molecular ions. Experiments performed with standard reference materials (SRM 1957, non-fortified serum) showed good agreement with certified values. Method detection limits were constrained by background levels, in line with traditional methods.
The identities of most environmental toxicants and their roles in causing chronic diseases are not known. The full scan data acquired using the qTOF represents a trove of data that can be retrospectively searched for as yet unidentified toxicants. A semi-automated approach will be described that highlights unknown POPs on the basis of their position in compositional space, as defined by accurate mass and isotope ratio measurements.