Non-Target PFAS Analysis in Dried Blood Spots Using the Agilent 6546 LC/Q-TOF with Profinder and FluoroMatch

Significance of the Topic

Per- and polyfluoroalkyl substances are potent environmental pollutants with thousands of unknown homologues. High-resolution non-targeted analysis is essential to characterize human exposure and assess health risks. Dried blood spots offer a minimally invasive sample format that can leverage existing newborn screening collections for large-scale monitoring.

Objectives and Overview

This study evaluates two complementary workflows for identifying unknown PFAS in dried blood spots using Agilent 6546 LC/Q-TOF with iterative exclusion MS/MS. Workflow one combines Agilent MassHunter Profinder peak picking with FluoroMatch Modular annotation. Workflow two uses the open-source FluoroMatch Flow suite as an all-in-one solution. Performance is benchmarked by discovery coverage, false positive and false negative rates for 21 spiked standards.

Methodology

Blank human whole blood spiked with native PFAS standards and 13C-labeled internal standards was applied to filter cards and air dried. Samples were extracted by alkaline methanol, sonication, centrifugation, lipid removal, and reconstitution. Iterative exclusion MS/MS acquisition across m/z 40–1000 in negative mode at 10 and 40 eV collision energies over five injections maximized fragmentation of low-abundance PFAS.

Used Instrumentation

• Agilent 1290 Infinity II LC with high-speed pump, cooled multisampler, and PFC-free conversion kit
• Agilent InfinityLab Poroshell 120 EC-C18 column (2.1×100 mm, 2.7 μm) at 40 °C
• Mobile phases: 2 mM ammonium acetate in water and 95:5 acetonitrile:water; 12 min gradient at 0.4 mL/min
• Agilent 6546 LC/Q-TOF with Jet Stream source (gas temp 120 °C, sheath gas 390 °C, capillary 2000 V) acquiring m/z 40–1000

Major Findings and Discussion

A total of 29 PFAS across five homologous series were annotated with high confidence. Among these, 21 matched spiked standards, four were contaminants from standards, and four were likely endogenous. Iterative exclusion increased MS/MS coverage by 14% over single-run acquisition. The Profinder plus FluoroMatch Modular workflow achieved 0% false negatives and ~4% false positives prior to manual validation. FluoroMatch Flow attained 95% detection of spiked PFAS but had ~30% false positives due to in-source artifacts. Profinder algorithms effectively filtered adducts, dimers, and fragments, simplifying datasets and improving annotation accuracy.

Benefits and Practical Applications

This integrated approach enables reliable discovery of known and novel PFAS in dried blood spots, supporting QA/QC, epidemiological studies, and exposure monitoring. The Profinder plus FluoroMatch Modular workflow balances comprehensive coverage with minimal artifacts. FluoroMatch Flow provides an accessible drag-and-drop interface for non-targeted PFAS screening without specialized software installation.

Future Trends and Possibilities

• Incorporation of machine learning for enhanced fragmentation assignment and homologous series detection
• Expansion of PFAS reference libraries to cover emerging and transformation products
• Standardization of data formats and reporting for interoperable non-target workflows
• Extension of workflows to additional biological and environmental matrices for exposome-wide studies

Conclusion

Combining iterative exclusion acquisition with Agilent Profinder peak picking and FluoroMatch software delivers a robust non-targeted PFAS analysis platform in dried blood spots. The optimized workflows yield high-confidence annotations with minimal false positives and negatives, facilitating large-scale human exposure assessment.

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