Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's

Reprod Toxicol. 2020 Mar:92:57-65. doi: 10.1016/j.reprotox.2019.06.013. Epub 2019 Jul 9.

Abstract

Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many exposures in humans, and the emerging metabolomics technology offers a means to read out both the biological activity and environmental impact in the same dataset. How to integrate exposome and metabolome in data analysis is still challenging. Here, we employ a hierarchical community network to investigate the global associations between the metabolome and mixed exposures including DDTs, PFASs and PCBs, in a women cohort with sera collected in California in the 1960s. Strikingly, this analysis revealed that the metabolite communities associated with the exposures were non-specific and shared among exposures. This suggests that a small number of metabolic phenotypes may account for the response to a large class of environmental chemicals.

Keywords: Breast cancer; DDT; Exposome; Gene environment interaction; Hierarchical community network; MWAS; Metabolic phenotype; Metabolomics; Mixed exposures; Multi-omics integration; PCB; PFAS; Variance analysis.

MeSH terms

  • California / epidemiology
  • Cohort Studies
  • Exposome*
  • Female
  • Humans
  • Metabolome*
  • Metabolomics
  • Neural Networks, Computer*