Abstract
Major technological advancements in the last decade have resulted in extensive new insights in the role of genomics in health. However, in addition to and in interaction with genetics, the environment has a crucial, potentially modifiable impact on health. For common disorders with a huge public health impact in modern societies the environment constitutes a major risk factor.
Environmental exposures are ubiquitous and arise from a variety of sources and include external chemicals (e.g. air pollution, smoking), physical (e.g. traffic noise) and biological (e.g. zoonosis) factors, and lifestyle (diet, physical activity). Social factors, from the household and family environment, to neighborhoods, work, school and social networks are also included. These external stressors influence the internal human environment (via for example gene-signaling, host metabolism, RNA and protein expression, microbiome composition) putting people at risk for adverse health effects. Although information on both environmental and genomic causes of disease is growing as a result of large-scale epidemiological research, environmental exposure data is often static, fragmentary, non-standardized, at crude resolution, and generally does not include estimates at the individual level. As a result, spatio-temporal patterns in exposures can go undetected limiting the identification of important risk factors, collective public health measures and effective personalized intervention strategies. This limitation has recently been conceptualized as the exposome; the environmental complement of the genome.
Recently, several large scale projects have been initiated on the exposome. This presentation will highlight the opportunities and practical and statistical challenges encountered when implementing the exposome in epidemiological research.
