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Prenatal metal exposures and childhood gut microbial signatures are associated with depression score in late childhood
Journal article   Open access   Peer reviewed

Prenatal metal exposures and childhood gut microbial signatures are associated with depression score in late childhood

Vishal Midya, Kiran Nagdeo, Jamil M Lane, Libni A Torres-Olascoaga, Mariana Torres-Calapiz, Chris Gennings, Megan K Horton, Martha M Téllez-Rojo, Robert O Wright, Manish Arora, …
The Science of the total environment, Vol.916, 170361
03/2024
DOI: 10.1016/j.scitotenv.2024.170361
PMCID: PMC10922719
PMID: 38278245
url
https://doi.org/10.1016/j.scitotenv.2024.170361View
Published (Version of record) Open Access

Abstract

Childhood depression is a major public health issue worldwide. Previous studies have linked both prenatal metal exposures and the gut microbiome to depression in children. However, few, if any, have studied their interacting effect in specific subgroups of children. Using an interpretable machine-learning method, this study investigates whether children with specific combinations of prenatal metals and childhood microbial signatures (cliques or groups of metals and microbes) were more likely to have higher depression scores at 9-11 years of age. We leveraged data from a well-characterized pediatric longitudinal birth cohort in Mexico City and its microbiome substudy (n = 112). Eleven metal exposures were measured in maternal whole blood samples in the second and third trimesters of pregnancy. The gut microbial abundances were measured at 9-11-year-olds using shotgun metagenomic sequencing. Depression symptoms were assessed using the Child Depression Index (CDI) t-scores at 9-11 years of age. We used Microbial and Chemical Exposure Analysis (MiCxA), which combines interpretable machine-learning into a regression framework to identify and estimate joint associations of metal-microbial cliques in specific subgroups. Analyses were adjusted for relevant covariates. We identified a subgroup of children (11.6 % of the sample) characterized by a four-component metal-microbial clique that had a significantly high depression score (15.4 % higher than the rest) in late childhood. This metal-microbial clique consisted of high Zinc in the second trimester, low Cobalt in the third trimester, a high abundance of Bacteroides fragilis, a high abundance of Faecalibacterium prausnitzii. All combinations of cliques (two-, three-, and four-components) were significantly associated with increased log-transformed t-scored CDI (β = 0.14, 95%CI = [0.05,0.23], P < 0.01 for the four-component clique). This study offers a new approach to chemical-microbial analysis and a novel demonstration that children with specific gut microbiome cliques and metal exposures during pregnancy may have a higher likelihood of elevated depression scores.
 Machine Learning Environmental epidemiology Exposome Child health Microbiome

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