New models for large prospective studies: is there a better way?

Large prospective cohort studies are critical for identifying etiologic factors for disease, but they require substantial long-term research investment. Such studies can be conducted as multisite consortia of academic medical centers, combinations of smaller ongoing studies, or a single large site such as a dominant regional health-care provider. Still another strategy relies upon centralized conduct of most or all aspects, recruiting through multiple temporary assessment centers. This is the approach used by a large-scale national resource in the United Kingdom known as the "UK Biobank," which completed recruitment/examination of 503,000 participants between 2007 and 2010 within budget and ahead of schedule. A key lesson from UK Biobank and similar studies is that large studies are not simply small studies made large but, rather, require fundamentally different approaches in which "process" expertise is as important as scientific rigor. Embedding recruitment in a structure that facilitates outcome determination, utilizing comprehensive and flexible information technology, automating biospecimen processing, ensuring broad consent, and establishing essentially autonomous leadership with appropriate oversight are all critical to success. Whether and how these approaches may be transportable to the United States remain to be explored, but their success in studies such as UK Biobank makes a compelling case for such explorations to begin.

Multicenter study of acetaminophen hepatotoxicity reveals the importance of biological endpoints in genomic analyses.

Gene expression profiling is a widely used technique with data from the majority of published microarray studies being publicly available. These data are being used for meta-analyses and in silico discovery; however, the comparability of toxicogenomic data generated in multiple laboratories has not been critically evaluated. Using the power of prospective multilaboratory investigations, seven centers individually conducted a common toxicogenomics experiment designed to advance understanding of molecular pathways perturbed in liver by an acute toxic dose of N-acetyl-p-aminophenol (APAP) and to uncover reproducible genomic signatures of APAP-induced toxicity. The nonhepatotoxic APAP isomer N-acetyl-m-aminophenol was used to identify gene expression changes unique to APAP. Our data show that c-Myc is induced by APAP and that c-Myc-centered interactomes are the most significant networks of proteins associated with liver injury. Furthermore, sources of error and data variability among Centers and methods to accommodate this variability were identified by coupling gene expression with extensive toxicological evaluation of the toxic responses. We show that phenotypic anchoring of gene expression data is required for biologically meaningful analysis of toxicogenomic experiments.

Personalized exposure assessment: promising approaches for human environmental health research.

New technologies and methods for assessing human exposure to chemicals, dietary and lifestyle factors, infectious agents, and other stressors provide an opportunity to extend the range of human health investigations and advance our understanding of the relationship between environmental exposure and disease. An ad hoc Committee on Environmental Exposure Technology Development was convened to identify new technologies and methods for deriving personalized exposure measurements for application to environmental health studies. The committee identified a "toolbox" of methods for measuring external (environmental) and internal (biologic) exposure and assessing human behaviors that influence the likelihood of exposure to environmental agents. The methods use environmental sensors, geographic information systems, biologic sensors, toxicogenomics, and body burden (biologic) measurements. We discuss each of the methods in relation to current use in human health research; specific gaps in the development, validation, and application of the methods are highlighted. We also present a conceptual framework for moving these technologies into use and acceptance by the scientific community. The framework focuses on understanding complex human diseases using an integrated approach to exposure assessment to define particular exposure-disease relationships and the interaction of genetic and environmental factors in disease occurrence. Improved methods for exposure assessment will result in better means of monitoring and targeting intervention and prevention programs.