TY - JOUR
T1 - Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health
AU - Manrai, Arjun K.
AU - Cui, Yuxia
AU - Bushel, Pierre R.
AU - Hall, Molly
AU - Karakitsios, Spyros
AU - Mattingly, Carolyn J.
AU - Ritchie, Marylyn
AU - Schmitt, Charles
AU - Sarigiannis, Denis A.
AU - Thomas, Duncan C.
AU - Wishart, David
AU - Balshaw, David M.
AU - Patel, Chirag J.
PY - 2017/3/20
Y1 - 2017/3/20
N2 - 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.
AB - 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.
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U2 - 10.1146/annurev-publhealth-082516-012737
DO - 10.1146/annurev-publhealth-082516-012737
M3 - Review article
C2 - 28068484
AN - SCOPUS:85017186712
VL - 38
SP - 279
EP - 294
JO - Annual Review of Public Health
JF - Annual Review of Public Health
SN - 0163-7525
ER -