Abstract

Alterations to the gut microbiome and exposure to metals during pregnancy have been suggested to impact inflammatory bowel disease. Nonetheless, how prenatal exposure to metals eventually results in long-term effects on the gut microbiome, leading to subclinical intestinal inflammation, particularly during late childhood, has not been studied. It is also unknown whether such an interactive effect drives a specific subgroup of children toward elevated susceptibility to intestinal inflammation. We used an amalgamation of machine-learning techniques with a regression-based framework to explore if children with distinct sets of gut microbes and certain patterns of exposure to metals during pregnancy (metal-microbial clique signature) had a higher likelihood of intestinal inflammation, measured based on fecal calprotectin (FC) in late childhood. We obtained samples from a well-characterized longitudinal birth cohort from Mexico City (n = 108), Mexico. In the second and third trimesters of pregnancy, 11 metals were measured in whole blood. Gut microbial abundances and FC were measured in stool samples from children 9-11 years of age. Elevated FC was defined as having FC above 100 μg/g of stool. We identified subgroups of children in whom microbial and metal-microbial clique signatures were associated with elevated FC (false discovery rate (FDR) < 0.05). In particular, we found two metal-microbial clique signatures significantly associated with elevated FC: (1) low cesium (Cs) and copper (Cu) in the third trimester and low relative abundance of Eubacterium ventriosum (OR [95%CI]: 10.27 [3.57,29.52], FDR < 0.001) and (2) low Cu in the third trimester and high relative abundances of Roseburia inulinivorans and Ruminococcus torques (OR [95%CI]: 7.21 [1.81,28.77], FDR < 0.05). This exploratory study demonstrates that children with specific gut microbes and specific exposure patterns to metals during pregnancy may have higher fecal calprotectin levels in late childhood, denoting an elevated risk of intestinal inflammation.

Original languageEnglish
JournalEnvironment and Health
DOIs
StateAccepted/In press - 2024

Keywords

  • environmental epidemiology
  • exposome
  • intestinal inflammation
  • machine learning
  • metals
  • microbiome

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