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

Authors: Li, Shuzhao; Cirillo, Piera; Hu, Xin; Tran, ViLinh; Krigbaum, Nickilou; Yu, Shaojun; Jones, Dean P; Cohn, Barbara

Published In Reprod Toxicol, (2020 03)

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.

PubMed ID: 31299210 Exiting the NIEHS site

MeSH Terms: California/epidemiology; Cohort Studies; Exposome*; Female; Humans; Metabolome*; Metabolomics; Neural Networks, Computer*

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