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

Authors :
Manrai, Arjun K.
Cui, Yuxia
Bushel, Pierre R.
Hall, Molly
Karakitsios, Spyros
Mattingly, Carolyn J.
Ritchie, Marylyn
Schmitt, Charles
Sarigiannis, Denis A.
Thomas, Duncan C.
Wishart, David
Balshaw, David M.
Patel, Chirag J.
Source :
Annual Review of Public Health. 3/20/2017, Vol. 38, p279-294. 12p.
Publication Year :
2017

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01637525
Volume :
38
Database :
Academic Search Index
Journal :
Annual Review of Public Health
Publication Type :
Academic Journal
Accession number :
122335440
Full Text :
https://doi.org/10.1146/annurev-publhealth-082516-012737