Human Genomics (Dec 2017)

Yale school of public health symposium on lifetime exposures and human health: the exposome; summary and future reflections

  • Caroline H. Johnson,
  • Toby J. Athersuch,
  • Gwen W. Collman,
  • Suraj Dhungana,
  • David F. Grant,
  • Dean P. Jones,
  • Chirag J. Patel,
  • Vasilis Vasiliou

DOI
https://doi.org/10.1186/s40246-017-0128-0
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 8

Abstract

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Abstract The exposome is defined as “the totality of environmental exposures encountered from birth to death” and was developed to address the need for comprehensive environmental exposure assessment to better understand disease etiology. Due to the complexity of the exposome, significant efforts have been made to develop technologies for longitudinal, internal and external exposure monitoring, and bioinformatics to integrate and analyze datasets generated. Our objectives were to bring together leaders in the field of exposomics, at a recent Symposium on “Lifetime Exposures and Human Health: The Exposome,” held at Yale School of Public Health. Our aim was to highlight the most recent technological advancements for measurement of the exposome, bioinformatics development, current limitations, and future needs in environmental health. In the discussions, an emphasis was placed on moving away from a one-chemical one-health outcome model toward a new paradigm of monitoring the totality of exposures that individuals may experience over their lifetime. This is critical to better understand the underlying biological impact on human health, particularly during windows of susceptibility. Recent advancements in metabolomics and bioinformatics are driving the field forward in biomonitoring and understanding the biological impact, and the technological and logistical challenges involved in the analyses were highlighted. In conclusion, further developments and support are needed for large-scale biomonitoring and management of big data, standardization for exposure and data analyses, bioinformatics tools for co-exposure or mixture analyses, and methods for data sharing.