Understanding and Reporting PFAS Exposure: Wide-Scope Retrospective Suspect Screening of High-Resolution Mass Spectrometry Data from Exposomics Studies
Jul 2026· Environmental Science and Technology· Vol 60, pp. 20790 - 20800· 0 citations· 47 references
Medicine
Abstract
Per- and polyfluoroalkyl substances (PFAS) comprise thousands of persistent and structurally diverse chemicals that contribute to chronic human exposure. Yet, routine biomonitoring targets only a limited set of regulated legacy compounds, underestimating overall exposure. We present a retrospective, wide-scope suspect screening analysis framework to extract PFAS information from archived LC–HRMS exposomics datasets. A curated list of 1,666 PFAS, filtered for reversed-phase LC compatibility and enriched with structural descriptors, predicted retention indices, and MS2 fragments, was used to reprocess two human biomonitoring studies involving firefighter serum pools and population-based plasma samples. Candidate features were prioritized using precursor accuracy, isotopic patterns, and MS2 similarity, followed by spectral quality filtering and retention time-index regression models based on isotopically labeled standards, reinforcing identification confidence. The reanalysis recovered up to 80% of previously reported PFAS while revealing overlooked high-confidence carboxylic, sulfonic, and sulfonamidoacetic acid homologues, and >30 tentative PFAS series, encompassing isomeric clusters (alcohols and ethers) and structurally distinct subclasses (alkylpyrimidine PFAS). The reanalysis framework also revealed shared homologue patterns across exposure contexts. By framing PFAS chemical space and providing a reusable repository of confirmed and tentative structures, this framework reinterprets HRMS biobanked data, improving PFAS pattern assessment.
Per- and polyfluoroalkyl substances (PFASs) are synthetic chemicals of considerable epidemiological concern. While targeted liquid chromatography (LC)–tandem mass spectrometry (MS/MS) methods are established for legacy PFAS, emerging replacement compounds require nontargeted analysis (NTA) for comprehensive characterization. However, NTA of complex biological matrices like human serum is analytically challenging because of the presence of many endogenous interferences and unknown PFAS molecules. To address this, ion mobility spectrometry has been coupled with LC and MS (LC-IMS-MS). This approach provides orthogonal separation via collision cross section to resolve isobars and filter noise. Despite its utility, current software lacks efficient PFAS feature prioritization, requiring extensive manual curation. We developed the PFAS IMplementer for Mass Spectrometry (PIMMS), a vendor-neutral, open-source tool that uses advanced filtering and scoring algorithms for rapid LC-IMS-MS data analysis. The potential utility of PIMMS was demonstrated using serum from bovine and human populations. PIMMS could identify both legacy and novel PFAS in addition to eight halogenoalkane xenobiotics (containing bromine, chlorine, and iodine). Of note, these halogenoalkane species were often only singly or doubly halogenated and were still effectively prioritized by PIMMS demonstrating the potential to identify a potentially growing number of novel compounds with only a single degree of halogenation.
Gregory P Kudzin, J. Dodds, E. Baker· Science Advances· 0 citations
Reliable screening of per- and polyfluoroalkyl substances (PFASs) in complex environmental matrices remains challenging due to severe spectral congestion and matrix-derived interferences under nontargeted conditions. Accurate-mass criteria from high-resolution mass spectrometry (HRMS) alone are often insufficient to suppress putative PFAS candidates arising from natural organic matter (NOM), leading to elevated false-positive rates. Here, we develop a mobility-resolved PFAS screening strategy by integrating direct-infusion gated trapped ion mobility spectrometry with Fourier transform ion cyclotron resonance mass spectrometry (gTIMS FTICR MS). By defining the mobility-resolved chemical space and characteristic mobility behavior of PFAS reference standards, ion mobility is implemented as a physically based decision constraint rather than a supplementary descriptor. Evaluation across chemically diverse NOM systems and environmental samples (e.g., landfill leachate and wastewater) demonstrates that enforcing mobility-m/z consistency reduces the space of putative PFAS candidates by more than 90% relative to mass-only screening. The mobility constraint further enables discrimination of near-isobaric interferences differing by only a few millidaltons (e.g., 2.54 mDa) and supports higher-confidence prioritization of PFAS candidates through agreement with homologous mobility trends. Rather than aiming for definitive structural identification, this work establishes a transferable mobility-constrained screening framework that improves the reliability of nontargeted PFAS detection in complex environmental matrices.
Meng Jiao, S. Ollivier, M. Hubert-Roux et al.· Analytical Chemistry· 0 citations
Biomonitoring of commercial endocrine-disrupting chemicals (EDCs) increasingly underpins exposure assessment and risk evaluation, yet most large-scale studies still rely on indirect, enzymatic hydrolysis–based methods whose quantitative performance has not been systematically verified. Here, we describe the development and rigorous validation of a direct liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay using validated standards to simultaneously quantify bisphenol S (BPS), propylparaben (PrP), monobutyl phthalate (MBP), and their major urinary glucuronide and sulfate conjugates in human urine.
A direct LC–MS/MS assay was developed for the simultaneous quantification of BPS, PrP, MBP and their major urinary metabolites. The method was validated in accordance with U.S. Food and Drug Administration bioanalytical guidelines, including assessments of linearity, accuracy, precision, selectivity, specificity, matrix effects, recovery, and carryover. The validated assay was then used to evaluate the accuracy of a conventional β‐glucuronidase–based hydrolysis workflow across a wide concentration range in spiked synthetic urine by comparing indirect measurements with direct totals for each analyte. Method utility in human biomonitoring was demonstrated by analysis of urine samples from 30 pregnant women in their second trimester.
Using isotope-dilution calibration, solid-phase extraction, and negative-ion electrospray multiple reaction monitoring, the method achieved sub‐ng/mL limits of detection for all analytes, linear response over 3-4 orders of magnitude, and intra‐ and inter‐day precision and accuracy within contemporary bioanalytical criteria, confirming fitness for trace-level biomonitoring. Indirect, hydrolysis-based measurements closely tracked direct totals for BPS and PrP, but systematically underestimated MBP, with a concentration-dependent negative bias that increased at higher levels, demonstrating that hydrolysis efficiency is analyte-specific and cannot be inferred from surrogate substrates alone. Application of the direct method to archived urine samples from 30 pregnant individuals enabled the first simultaneous resolution of the free and conjugated forms of these three EDCs in a maternal cohort and revealed that glucuronides accounted for the majority of the total urinary burden, with total concentrations exceeding contemporary NHANES estimates.
Collectively, these findings show that indirect methods can introduce substantial, analyte-dependent underestimation of internal dose, with implications for exposure misclassification, attenuation of epidemiologic effect estimates, and underestimation of population risk. The data support the position that direct LC–MS/MS quantification of parent and conjugated species, coupled with analyte-resolved assessment of hydrolysis efficiency, should become standard practice in method validation and national biomonitoring programs to ensure accurate exposure assessment for non‐persistent EDCs.
Unknown authors· Frontiers in Chemistry· 0 citations
Broad coverage exposome- and metabolome-wide association studies rely on advanced instrumentation, typically anchored in liquid chromatography-high-resolution mass spectrometry (LC-HRMS) to investigate exposure-effect associations. Sample preparation for biological fluids is a delicate matter, as it is essential to strike a pragmatic balance between sensitivity, chemical coverage, robustness, and time efficiency to meet the requirements of large-scale epidemiological studies. Here, we established a protein precipitation workflow in a scalable, high-throughput format for human plasma and urine. Different protocols were evaluated utilizing a xenobiotic mixture containing >200 exposure compounds based on extraction recovery, repeatability, and applicability for nontargeted analysis (NTA) and suspect screening. The tested high-throughput options included a protein precipitation workflow in 96-well plates and a phospholipid removal plate. For urine, a dilute-and-shoot approach was additionally tested. The plate-based protein precipitation resulted in superior performance with acceptable extraction recoveries (RE, 60-140%) for >70% of the highly diverse analyte panel in plasma and >80% in urine, and acceptable repeatability with relative standard deviations of <30% for more than 95% of analytes in plasma and 80% in urine. NTA results exhibited only a small number of altered annotated features compared to a tube-based protocol used for benchmarking, while increasing the overall time efficiency by a factor of five. To further test the protocol, it was applied to the NIST plasma standard reference material SRM1950. A total of 22 toxicants were identified and (semi-)quantified, with most concentrations comparable to available reference values. The results demonstrate the suitability of the established protocol for combined MWAS/ExWAS.
Julia Füreder, Amira Müller, Giulia Guerra et al.· Analytical Chemistry· 0 citations
Endocrine-disrupting chemicals (EDCs), including bisphenols, phthalates, and parabens, are widely used in plastics, personal care, and household products and are linked to adverse health outcomes such as cancer, metabolic disease, and infertility. Although product labels disclose ingredients, they often fail to capture the full range of consumer chemical exposures. Building on prior evidence that participants in the Million Marker (MM) biomonitoring program reduced some (but not all) EDC metabolites, we hypothesized that undisclosed ingredients, mislabeling, and contamination contribute to persistent exposures. We conducted nontargeted chemical analyses of 113 personal care and cleaning products across 12 categories, spanning a range of label-based hazard ratings, using high-resolution GC × GC-MS with machine-learning–assisted identification. We detected 3,141 unique chemicals, including 303 with confirmed, probable, or tentative identification. Nearly all products (98%) contained at least one unlabeled chemical, and 85% contained at least one with known or suspected health hazards, with products averaging more than three times as many chemicals as listed on labels. Over half of the products (57.5%) failed testing based on undisclosed contaminants, including many marketed as “natural,” “non-toxic,” or “fragrance-free,” and 26% contained chemicals that directly contradicted label claims. These findings reveal substantial gaps in product transparency and demonstrate that ingredient labels alone cannot reliably convey product safety, underscoring the need for nontargeted testing of finished products to reduce harmful chemical exposures.
Kim Schultz, J. Rochester, Michael Kupec Lathrop et al.· Environment & Health· 1 citation
Targeted analytical methods are widely used to quantify per- and polyfluoroalkyl substances (PFAS) in combustion flue-gas. However, interpretation of PFAS emission data is challenged by high shares of non-detects (NDs), heterogeneous limits of quantification (LoQs), and extensive target analyte lists. This study evaluates the influence of ND-treatment, target-list composition and LoQ distributions on PFAS-derived fluorine metrics using two pilot-scale incineration datasets. Both datasets exhibit high ND-shares and analyte-specific LoQs spanning several orders of magnitude. Current analytical target lists appear highly sensitive to the ND-substitution approach. However, sensitivity analyses demonstrated that this apparent sensitivity was governed by a small number of analytes exhibiting elevated LoQs. Excluding these analytes reduced variability among ND-substitution approaches by approximately 95 % in one dataset and by more than 99.9 % in the other, largely independent of the selected descriptive statistical parameter. Target-list reduction also decreased variability but provided little additional improvement. Consequently, the apparent influence of target-list composition was found to be largely attributable to the inclusion of a small number of analytes with exceptionally high LoQs. The findings indicate that apparent sensitivities to ND-treatment are governed primarily by analyte-specific LoQ distributions, and, to a lesser extent, by target-list composition. Robust assessment of PFAS-derived metrics therefore primarily requires critical evaluation of analytes exhibiting elevated LoQs, transparent handling of NDs and the application of lower- and upper-bound estimates. Future method development should prioritize harmonized LoQs, refinement of target lists, and inclusion of volatile PFAS and non-target analysis to improve PFAS emission assessment.
Unknown authors· Waste Management· 0 citations
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