The Exposome: Embracing the Complexity for Discovery in Environmental Health

Abstract

Environmental exposures are ubiquitous and play a fundamental role in the development of complex human diseases. The exposome, which is defined as the totality of environmental exposures over the life course, allows for systematic evaluation of the relationship between exposures and associated biological consequences, and represents a powerful approach for discovery in environmental health research. However, implementing the exposome concept is challenged by the ability to accurately assess multiple exposures and the ability to integrate information across the exposure–disease continuum. On 14–15 January 2015, the National Institute of Environmental Health Sciences (NIEHS) held the Exposome Workshop where a group of international and U.S. scientists from different disciplines gathered to review the state of the science in research areas related to the exposome and to provide recommendations for incorporating the exposome concept into each research area. To move the field forward, the NIEHS is establishing a Children’s Health Exposure Analysis Resource (CHEAR) to provide infrastructure support for access to laboratory and statistical analyses to children’s health studies. It is recognized that incorporating the exposome concept into exposure and environmental health research will be a long journey and will require significant collaborative efforts from different scientific disciplines, nations, and stakeholders.

Figure 1

A person’s health and disease status is determined by the combined effects of complex environmental exposures, associated biological responses, and individual susceptibility over time. While individual genomic composition is stable, environmental exposures vary over the time course of an individual’s life as will the way they respond to those exposures or how those responses ultimately manifest themselves as health effects. Adopting the exposome approach is to collect relevant information across all variables, anchor it in meaningful biological consequences and use this for systems analysis and data-driven discovery.