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Target Exposome for Characterizing Early Gestational Exposure to Contaminants of Emerging Concern and Association with Gestational Diabetes Mellitus.
- Source :
-
Environmental science & technology [Environ Sci Technol] 2023 Sep 12; Vol. 57 (36), pp. 13408-13418. Date of Electronic Publication: 2023 Aug 31. - Publication Year :
- 2023
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Abstract
- Characterization of gestational exposure to complex contaminants of emerging concern (CECs) is critical to the identification of environmental risk factors for pregnancy complications. However, determination of various CECs with diverse physicochemical properties in biological fluids is technically challenging. In the present study, we developed a target exposome protocol, consisting of simple liquid-liquid extraction-based sample preparation and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, to determine 325 CECs covering 11 subclasses, including poly- and perfluoroalkyl substances, organophosphate esters, ultraviolet (UV) stabilizers, synthetic antioxidants, phthalate esters, and several others. The protocol exhibits exceptional advantages over traditional approaches in the coverage of chemicals, sample volume demand, and time and financial cost. The protocol was applied in a prospective nested gestational diabetes mellitus (GDM) study including 120 cases and 240 matched healthy controls. Thirty-three CECs were detected in >70% of the samples, with a combined concentration of 17.0-484.7 ng/mL. Bayesian kernel machine regression analysis showed that exposure to the CEC mixture was significantly associated with a higher GDM risk. For example, when increasing all CECs in the mixture from 50th percentile to 75th percentile, the estimated probit of GDM incidence had an increase of 92% (95% CI: 56%, 127%). Meanwhile, perfluorohexanesulfonic acid, 1,3-diphenylguanidine, and dibutyl fumarate were identified as the key CECs driving the joint effect. This work demonstrates great potential of our target exposome protocol for environmental risk factor identification in large-scale epidemiology or biomonitoring studies.
Details
- Language :
- English
- ISSN :
- 1520-5851
- Volume :
- 57
- Issue :
- 36
- Database :
- MEDLINE
- Journal :
- Environmental science & technology
- Publication Type :
- Academic Journal
- Accession number :
- 37651547
- Full Text :
- https://doi.org/10.1021/acs.est.3c04492