TY - JOUR
T1 - Opportunities and challenges for environmental exposure assessment in population-based studies
AU - Patel, Chirag J.
AU - Kerr, Jacqueline
AU - Thomas, Duncan C.
AU - Mukherjee, Bhramar
AU - Ritz, Beate
AU - Chatterjee, Nilanjan
AU - Jankowska, Marta
AU - Madan, Juliette
AU - Karagas, Margaret R.
AU - Mcallister, Kimberly A.
AU - Mechanic, Leah E.
AU - Fallin, M. Daniele
AU - Ladd-Acosta, Christine
AU - Blair, Ian A.
AU - Teitelbaum, Susan L.
AU - Amos, Christopher I.
N1 - Funding Information:
This work was supported by the following NIH grants: R00ES023504 and R21ES025052 (to C.J. Patel); R01CA17997 (to J. Kerr and M. Jankowska); P01CA1956569 (to D.C. Thomas); R01ES023541 and R21ES025573 (to B. Ritz); P30CA023108 (to M.R. Karagas, J. Madden, and C.I. Amos); P20GM104416 and P01ES022832 (to M.R. Karagas and J. Madden); U01DD00046, R01ES025216, and R01ES025531 (to M.D. Fallin); P30ES013508 and P42ES023720 (to I. Blair); U2CES026555 (to S. Teitel-baum); and U01CA196386, R21CA191651, R01CA186566, and GM103534 (to C.I. Amos).
Funding Information:
Some investigators have called for a single conceptual definition of heterogeneous measurements of exposure called the "exposome" (2, 31). The exposome considers multiple exposures humans encounter from conception to death (33) simultaneously. Wild has divided the exposome into three domains, including the "general external," the "specific external," and the "internal" (34). The general external exposome includes indicators of socio-economic status, financial status, and stress. The specific external includes factors such as radiation, infectious agents, pollutants, diet, lifestyle factors, and medical interventions. The internal exposome consists of internally measured exposure and phenotypic factors, such as indicators of metabolism, microflora, and inflammatory markers. If the concept is to be successful as a tool for discovery of exposures in disease, the heterogeneity of data measures seen in Table 1 must be addressed in appropriate study designs (see above) and in analyses (see below). A few exposome research efforts are now underway. For example, the Children's Health Exposure Analysis Resource (CHEAR) is a program funded by the National Institute of Environmental Health Sciences (NIEHS) to advance understanding about how environmental exposures impact children's health (35). CHEAR is designed to
Publisher Copyright:
© 2017 American Association for Cancer Research.
PY - 2017/9/1
Y1 - 2017/9/1
N2 - A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development.
AB - A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development.
UR - http://www.scopus.com/inward/record.url?scp=85028938576&partnerID=8YFLogxK
U2 - 10.1158/1055-9965.EPI-17-0459
DO - 10.1158/1055-9965.EPI-17-0459
M3 - Review article
C2 - 28710076
AN - SCOPUS:85028938576
SN - 1055-9965
VL - 26
SP - 1370
EP - 1380
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 9
ER -