Pesticide residues and polyphenols in urine – A combined LC-HRMS screening to reveal intake patterns

• Published in: Environment international Vol. 191; p. 108981
• Main Authors: Huber, Carolin, Brack, Werner, Röder, Stefan, von Bergen, Martin, Rolle-Kampczyk, Ulrike, Zenclussen, Ana Claudia, Krauss, Martin, Herberth, Gunda
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.09.2024; Elsevier
• Subjects: Adult; Chromatography, Liquid - methods; Diet; Exposomics; Female; Fruit - chemistry; Human biomonitoring; Humans; LC-HRMS; Mass Spectrometry - methods; Pesticide; Pesticide Residues - analysis; Pesticide Residues - urine; Polyphenols; Polyphenols - urine; Pregnancy; Prospective Studies; Pyrimidines; Polyphenols; Human biomonitoring; Exposomics; Pesticide; LC-HRMS
• ISSN: 0160-4120; 1873-6750; 1873-6750
• DOI: 10.1016/j.envint.2024.108981

[Display omitted] •Urine samples from 587 women in the 34th week of pregnancy were analyzed by LC-HRMS.•Pesticide residues and polyphenols were annotated in the same data set.•40 pesticide residues associated with exposure to 27 pesticides were reported.•46 polyphenols were identified and used for a cluster analysis.•Citrus fruit consumption might associate with pyrimethanil metabolites. Human exposure to pesticides in the general population occurs mainly through food consumption. However, specific dietary habits or food products that contribute to pesticide exposure are often unknown. In this study, we propose a combined screening for polyphenols and pesticide residues by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to assess the diet and the associated pesticide exposure. We measured 587 urine samples from women around the 34th week of pregnancy of a prospective mother–child cohort. A non-targeted screening for flavonoid-like compounds related to fruit and vegetable consumption was performed, prioritizing 164 features and identifying a total of 46 features by spectral library search. Based on a subset of markers, k-means clustering was performed, leading to four clusters with presumably similar dietary habits. The clusters were compared against food questionnaire data collected within the period of sample collection. Suspect screening of more than 500 pesticide residues including metabolites was performed, with a total of 40 residues being reported for 27 different pesticides. The detection of pesticide residues was compared across the different clusters of dietary habits. Indications were found that pyrimethanil metabolites might be associated with the consumption of citrus fruits or derivate products. We demonstrate that the method used has the potential to reveal patterns of pesticide intake from specific food commodities.