Chirag J. Patel, Jacqueline Kerr, Duncan C. Thomas, Bhramar Mukherjee, Beate Ritz, Nilanjan Chatterjee, Marta Jankowska, Juliette Madan, Margaret R. Karagas, Kimberly A. McAllister, Leah E. Mechanic, M. Daniele Fallin, Christine Ladd-Acosta, Ian A. Blair, Susan L. Teitelbaum, Christopher I. Amos

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. We evaluate 1) designs to investigate diseases that consider heterogeneous and multi-dimensional 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. Case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective designs are required but must balance extended data collection with follow-up of study participants. Two phase designs are described. 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. The availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. New exposure assessments offer many new opportunities for environmental assessment in cancer development. We describe and evaluate the state of the art for evaluating high dimensional environmental studies.