Prenatal exposure to rare earth elements (REEs) has been linked to impaired neurodevelopment in children; however, the underlying biological mechanisms remain insufficiently characterized. In the Wuhan Healthy Baby Cohort ( N = 1,045), we quantified thirteen REEs in first-trimester maternal urine and conducted metabolomic profiling of cord blood. Cognitive neurodevelopment was assessed by the Bayley Scales of Infant Development at 2 years of age. Overall mixture effects of REEs were evaluated using quantile g-computation (qgcomp) and weighted quantile sum (WQS) regression. Weighted gene co-expression network analysis (WGCNA) was used to identify key metabolic modules and further examine their mediating role in the associations between REE exposure and neurodevelopmental outcomes. After covariate adjustment, each one-unit increase in natural log-transformed maternal urinary concentrations of seven REEs (neodymium, samarium, gadolinium, holmium, erbium, thulium and ytterbium) was significantly associated with higher odds of cognitive developmental delays (CDD), with adjusted ORs ranging from 1.13 to 1.25 ( P < 0.05). WQS regression revealed positive mixture effects of REEs on both CDD and psychomotor developmental delays, identifying ytterbium and cerium as the primary contributors to each outcome, respectively. We applied WGCNA to cord blood metabolomic data using a soft-thresholding power of 5 (scale-free R 2 = 0.87) and identified 13 color-coded metabolic modules. Prenatal REE exposure was associated with perturbations in modules enriched in lysophospholipids and phosphatidylethanolamines, and mediation analyses further demonstrated that these two modules partially mediated the associations between REE exposure and increased risk of neurodevelopmental delay. Prenatal REE exposure is associated with neurodevelopmental delay in children, partly through disruption of phospholipid metabolism. These findings highlight the need for health risk assessment of REE exposure during pregnancy and provide clues for potential intervention targets.
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Xie et al. (2026) studied this question.
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