Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health

Arjun K. Manrai, Yuxia Cui, Pierre R. Bushel, Molly Hall, Spyros Karakitsios, Carolyn J. Mattingly, Marylyn Ritchie, Charles Schmitt, Denis A. Sarigiannis, Duncan C. Thomas, David Wishart, David M. Balshaw, Chirag J. Patel

Research output: Contribution to journalReview articlepeer-review

64 Scopus citations


The complexity of the human exposome-the totality of environmental exposures encountered from birth to death-motivates systematic, high-throughput approaches to discover new environmental determinants of disease. In this review, we describe the state of science in analyzing the human exposome and provide recommendations for the public health community to consider in dealing with analytic challenges of exposome-based biomedical research. We describe extant and novel analytic methods needed to associate the exposome with critical health outcomes and contextualize the data-centered challenges by drawing parallels to other research endeavors such as human genomics research. We discuss efforts for training scientists who can bridge public health, genomics, and biomedicine in informatics and statistics. If an exposome data ecosystem is brought to fruition, it will likely play a role as central as genomic science has had in molding the current and new generations of biomedical researchers, computational scientists, and public health research programs.

Original languageEnglish (US)
Pages (from-to)279-294
Number of pages16
JournalAnnual Review of Public Health
StatePublished - Mar 20 2017

All Science Journal Classification (ASJC) codes

  • Public Health, Environmental and Occupational Health


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