Accumulation of Black Carbon Particles in Placenta, Cord Blood, and Childhood Urine in Association with the Intestinal Microbiome Diversity and Composition in Four- to Six-Year-Old Children in the ENVIR <i>ON</i> AGE Birth Cohort
Bibliographic record
Abstract
Background: The gut microbiome plays an essential role in human health. Despite the link between air pollution exposure and various diseases, its association with the gut microbiome during susceptible life periods remains scarce. Objectives: In this study, we examined the association between black carbon particles quantified in prenatal and postnatal biological matrices and bacterial richness and diversity measures, and bacterial families. Methods: A total of 85 stool samples were collected from 4- to 6-y-old children enrolled in the ENVIRonmental influence ON early AGEing birth cohort. We performed 16S rRNA gene sequencing to calculate bacterial richness and diversity indices (Chao1 richness, Shannon diversity, and Simpson diversity) and the relative abundance of bacterial families. Black carbon particles were quantified via white light generation under femtosecond pulsed laser illumination in placental tissue and cord blood, employed as prenatal exposure biomarkers, and in urine, used as a post-natal exposure biomarker. We used robust multivariable-adjusted linear models to examine the associations between quantified black carbon loads and measures of richness (Chao1 index) and diversity (Shannon and Simpson indices), adjusting for parity, season of delivery, sequencing batch, age, sex, weight and height of the child, and maternal education. Additionally, we performed a differential relative abundance analysis of bacterial families with a correction for sampling fraction bias. Results are expressed as percentage difference for a doubling in black carbon loads with 95% confidence interval (CI). Results: Two diversity indices were negatively associated with placental black carbon [Shannon: −4.38% (95% CI: −8.31%, −0.28%); Simpson: −0.90% (95% CI: −1.76%, −0.04%)], cord blood black carbon [Shannon: −3.38% (95% CI: −5.66%, −0.84%); Simpson: −0.91 (95% CI: −1.66%, −0.16%)], and urinary black carbon [Shannon: −3.39% (95% CI: −5.77%, −0.94%); Simpson: −0.89% (95% CI: −1.37%, −0.40%)]. The explained variance of black carbon on the above indices varied from 6.1% to 16.6%. No statistically significant associations were found between black carbon load and the Chao1 richness index. After multiple testing correction, placental black carbon was negatively associated with relative abundance of the bacterial families Defluviitaleaceae and Marinifilaceae, and urinary black carbon with Christensenellaceae and Coriobacteriaceae; associations with cord blood black carbon were not statistically significant after correction. Conclusion: Black carbon particles quantified in prenatal and postnatal biological matrices were associated with the composition and diversity of the childhood intestinal microbiome. These findings address the influential role of exposure to air pollution during pregnancy and early life in human health. https://doi.org/10.1289/EHP11257
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".