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. 2022 Dec;215(Pt 2):114319.
doi: 10.1016/j.envres.2022.114319. Epub 2022 Sep 12.

Metabolome-wide association study of the relationship between chlorpyrifos exposure and first trimester serum metabolite levels in pregnant Thai farmworkers

Collaborators, Affiliations

Metabolome-wide association study of the relationship between chlorpyrifos exposure and first trimester serum metabolite levels in pregnant Thai farmworkers

Donghai Liang et al. Environ Res. 2022 Dec.

Abstract

Introduction: Organophosphate (OP) insecticides, including chlorpyrifos, have been linked with numerous harmful health effects on maternal and child health. Limited data are available on the biological mechanisms and endogenous pathways underlying the toxicity of chlorpyrifos exposures on pregnancy and birth outcomes. In this study, we measured a urinary chlorpyrifos metabolite and used high-resolution metabolomics (HRM) to identify biological perturbations associated with chlorpyrifos exposure among pregnant women in Thailand, who are disparately exposed to high levels of OP insecticides.

Methods: This study included 50 participants from the Study of Asian Women and their Offspring's Development and Environmental Exposures (SAWASDEE). We used liquid chromatography-high resolution mass spectrometry to conduct metabolic profiling on first trimester serum samples collected from participants to evaluate metabolic perturbations in relation to chlorpyrifos exposures. We measured 3,5,6-trichloro-2-pyridinol (TCPy), a specific metabolite of chlorpyrifos and chlorpyrifos-methyl, in first trimester urine samples to assess the levels of exposures. Following an untargeted metabolome-wide association study workflow, we used generalized linear models, pathway enrichment analyses, and chemical annotation to identify significant metabolites and pathways associated with urinary TCPy levels.

Results: In the 50 SAWASDEE participants, the median urinary TCPy level was 4.36 μg TCPy/g creatinine. In total, 691 unique metabolic features were found significantly associated with TCPy levels (p < 0.05) after controlling for confounding factors. Pathway analysis of metabolic features associated with TCPy indicated perturbations in 24 metabolic pathways, most closely linked to the production of reactive oxygen species and cellular damage. These pathways include tryptophan metabolism, fatty acid oxidation and peroxisome metabolism, cytochromes P450 metabolism, glutathione metabolism, and vitamin B3 metabolism. We confirmed the chemical identities of 25 metabolites associated with TCPy levels, including glutathione, cystine, arachidic acid, itaconate, and nicotinamide adenine dinucleotide.

Discussion: The metabolic perturbations associated with TCPy levels were related to oxidative stress, cellular damage and repair, and systemic inflammation, which could ultimately contribute to health outcomes, including neurodevelopmental deficits in the child. These findings support the future development of sensitive biomarkers to investigate the metabolic underpinnings related to pesticide exposure during pregnancy and to understand its link to adverse outcomes in children.

Keywords: Biomarkers; Birth cohort; Farmworker; Metabolomics; Organophosphate; Thailand.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1.
Fig. 1.. Manhattan Plots of four TCPy Models in HILIC and C18 columns.
Top left is the TCPy model in HILIC column; top right is the TCPy model in C18 column; bottom left is the TCPy + Creatinine covariate model in HILIC column; and bottom right is the TCPy + Creatinine covariate model in C18 column. . X-axis denotes the retention time (in seconds), Y-axis denotes the negative log10 of the p-values calculated from the MWAS models. The threshold lines in colors represent the different cut-off value of FDR corrected P-value: red = 0.05, blue = 0.1, and black = 0.2. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2.
Fig. 2.. Significant metabolic pathways in TCPy models in HILIC and C18 columns.
Top left is the TCPy model in HILIC column; top right is the TCPy model in C18 column; bottom left is the TCPy + Creatinine covariate model in HILIC column; and bottom right is the TCPy + Creatinine covariate model in C18 column.
Fig. 3.
Fig. 3.. Heat Map of Significant Pathways Across All TCPy Models.
Cells are shaded according to the magnitude of p-values generated by mummichog for each pathway. Pathways significantly associated with more than two TCPy models were presented. The pathways were ordered according to the total number of the significant associations (p-value<0.05). Abbreviations: TCPy: 3,5,6-trichloro-2-pyridinol.

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