EB Research: Exposome of Normal Pregnancy

Christopher Wild published a landmark paper in 2005 that introduced the concept of the exposome, which he defined as the "totality of environmental exposures from conception onward." Successful human reproduction and development involves completion of a series of highly integrated and timed events during sensitive windows such as folliculogenesis, spermatogenesis, fertilization, implantation, and pregnancy.

Building upon the division's expertise in the modeling of environmental exposures, including lifestyle, and leveraging existing cohort studies and their repositories, we designed this proof-of-concept study as our initial foray into the exposome research. This work has two research aims:

  • Characterize and quantify the "normal" pregnancy exposome using an existing pregnancy cohort study (Trial of Calcium for Preeclampsia Prevention)
  • Determine its utility and feasibility for design and implementation on a larger scale

Laboratory analyses have recently been completed for a mixture of persistent (i.e., metals and trace elements, organo chlorophosphates, organo polypropylenes, polybrominated biphenyls, polybrominated diphenyl ethers, polychlorinated biphenyls, perfluorinated compound) and non-persistent chemicals (e.g., pesticides, parabens, phenols, phthalates) that are being quantified in blood and urine, respectively, during each trimester of pregnancy. Both non-targeted proteomic and metabolomics analyses and targeted analysis of other biomarkers (e.g., angiogenesis, glucose homeostasis, hormones, inflammation, oxidative stress) have been completed as well. Data analysis is currently underway.

Investigators

Selected Publications

  • Buck Louis, G. M., Yeung, E., Sundaram, R., Laughon, S. K., & Zhang, C. (2013). The exposome--exciting opportunities for discoveries in reproductive and perinatal epidemiology. Paediatric and Perinatal Epidemiology, 27(3), 229–236. PMID: 23574410
  • Buck Louis, G. M., & Sundaram, R. (2012). Exposome: Time for transformative research. Statistics in Medicine, 31(22), 2569–2575. PMID: 22969025
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