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Assessment of pre- and postnatal exposure to polychlorinated biphenyls: lessons from the Inuit Cohort Study
Pierre Ayotte1, Gina Muckle, Joseph L Jacobson
1Department of Social and Preventive Medicine, Laval University and Public Health Research Unit, CHUQ-Laval University Medical Centre, Québec, Québec, Canada. pierre.ayotte@inspq.qc.ca
Insights
Prenatal exposure to polychlorinated biphenyls (PCBs) can be accurately measured using maternal plasma, cord plasma, or breast milk. A predictive model incorporating maternal PCB levels and infant body fat effectively estimated infant PCB concentrations at six months.
Area of Science:
- Environmental Health
- Toxicology
- Human Development
Background:
- Polychlorinated biphenyls (PCBs) are persistent environmental contaminants known to cause developmental issues.
- The Inuit population in northern Québec (Nunavik) is exposed to PCBs through their diet.
- Neurodevelopmental deficits in infants due to environmental PCB exposure require investigation.
Purpose of the Study:
- To compare biomarkers for prenatal polychlorinated biphenyl (PCB) exposure.
- To develop models predicting infant PCB plasma concentration at six months postpartum.
- To assess the effectiveness of different exposure indices in predicting infant PCB levels.
Main Methods:
- Measured 14 PCB congeners in maternal plasma, cord plasma, breast milk, and infant plasma using gas chromatography.
- Analyzed PCB congener profiles and correlations across different biological matrices.
- Developed and compared multivariate models to predict infant PCB-153 plasma concentration at six months postpartum.
Main Results:
- PCB congener profiles were similar across all biological samples.
- Maternal plasma, cord plasma, and milk PCB concentrations were strongly intercorrelated, indicating good prenatal exposure indicators.
- A multivariate model explained 72% of infant PCB-153 variance at six months, significantly outperforming a postnatal exposure index (36% explained variance).
Conclusions:
- Maternal plasma, cord plasma, and breast milk are reliable indicators of prenatal polychlorinated biphenyl (PCB) exposure.
- A predictive model integrating maternal PCB levels, breastfeeding duration, and infant body fat mass accurately estimates infant PCB concentrations.
- This model offers a more robust method for assessing long-term PCB exposure in infants compared to traditional postnatal indices.
Abstract:
Polychlorinated biphenyls (PCBs) are food-chain contaminants that have been shown to induce adverse developmental effects in humans. In the course of an epidemiologic study established to investigate neurodevelopmental deficits induced by environmental PCB exposure in the Inuit population of northern Québec (Nunavik, Canada), we compared three biomarkers of prenatal exposure and models to predict PCB plasma concentration at 6 months postpartum. Concentrations of 14 PCB congeners were measured by high-resolution gas chromatography with electron capture detection in lipids extracted from maternal plasma, cord plasma, breast milk (collected at approximately 1 month postpartum), and 6-month-old infant plasma samples. Similar congener profiles were observed in all biologic samples, and PCB-153, the most abundant and persistent PCB congener, was strongly correlated with other frequently detected PCB congeners in all biologic media. When expressed on a lipid basis, maternal plasma, cord plasma, and milk concentrations of this congener were strongly intercorrelated, indicating that PCB concentration in any of these biologic media is a good indicator of prenatal exposure to PCBs. A multivariate model that included maternal PCB-153 plasma lipid concentration, breast-feeding duration, and the sum of two skin-fold thicknesses (an index of infant body fat mass) explained 72% of PCB-153 plasma concentration variance at 6 months postpartum (p < 0.001). By contrast, based on the product of breast-feeding duration times the concentration of PCBs in plasma lipids, which was used as an index of postnatal PCB exposure in several studies, only 36% of infant plasma concentration was explained.
