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Background: The gut microbiome is important in modulating health in childhood. Metal exposures affect multiple health outcomes, but their ability to modify bacterial communities in children is poorly understood. Objectives: We assessed the associations of childhood and perinatal blood metal levels with childhood gut microbiome diversity, structure, species, gene family-inferred species, and potential pathway alterations. Methods: We assessed the gut microbiome using 16S rRNA gene amplicon sequencing and shotgun metagenomic sequencing in stools collected from 6- to 7-year-old children participating in the GESTation and Environment (GESTE) cohort study. We assessed blood metal concentrations [cadmium (Cd), manganese (Mn), mercury (Hg), lead (Pb), selenium (Se)] at two time points, namely, perinatal exposures at delivery ( ) and childhood exposures at the 6- to 7-y follow-up ( ). We used multiple covariate-adjusted statistical models to determine microbiome associations with continuous blood metal levels, including linear regression (Shannon and Pielou alpha diversity indexes), permutational multivariate analysis of variance (adonis; beta diversity distance matrices), and multivariable association model (MaAsLin2; phylum, family, species, gene family-inferred species, and pathways). Results: Children’s blood Mn and Se significantly associated with microbiome phylum [e.g., Verrucomicrobiota ( , ; , , respectively)] and children’s blood Mn significantly associated with family [e.g., Eggerthellaceae ( , )]-level differences. Higher relative abundance of potential pathogens (e.g., Flavonifractor plautii ), beneficial species (e.g., Bifidobacterium longum , Faecalibacterium prausnitzii ), and both potentially pathogenic and beneficial species (e.g., Bacteriodes vulgatus , Eubacterium rectale ) inferred from gene families were associated with higher childhood or perinatal blood Cd, Hg, and Pb ( ). We found significant negative associations between childhood blood Pb and acetylene degradation pathway abundance ( ). Finally, neither perinatal nor childhood metal concentrations were associated with children’s gut microbial inter- and intrasubject diversity. Discussion: Our findings suggest both long- and short-term associations between metal exposure and the childhood gut microbiome, with stronger associations observed with more recent exposure. Future epidemiologic analyses may elucidate whether the observed changes in the microbiome relate to children’s health. https://doi.org/10.1289/EHP9674

Root concentration factor (RCF) is an important characterization parameter to describe accumulation of organic contaminants in plants from soils in life cycle impact assessment (LCIA) and phytoremediation potential assessment. However, building robust predictive models remains challenging due to the complex interactions among chemical–soil–plant root systems. Here we developed end-to-end machine learning models to devolve the complex molecular structure relationship with RCF by training on a unified RCF data set with 341 data points covering 72 chemicals. We demonstrate the efficacy of the proposed gradient boosting regression tree (GBRT) model based on the extended connectivity fingerprints (ECFP) by predicting RCF values and achieved prediction performance with R-squared of 0.77 and mean absolute error (MAE) of 0.22 using 5-fold cross validation. In addition, our results reveal nonlinear relationships among properties of chemical, soil, and plant. Further in-depth analyses identify the key chemical topological substructures (e.g., −O, −Cl, aromatic rings and large conjugated π systems) related to RCF. Stemming from its simplicity and universality, the GBRT-ECFP model provides a valuable tool for LCIA and other environmental assessments to better characterize chemical risks to human health and ecosystems.

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