Use of Exposomic Methods Incorporating Sensors in Environmental Epidemiology

Purpose of Review The exposome is a recently coined concept that comprises the totality of nongenetic factors that affect human health. It is recognized as a major conceptual advancement in environmental epidemiology, and there is increased demand for technologies that capture the spatial, temporal, and chemical variability of exposures across individuals (i.e., exposomic sensors). We review a selection of these tools, highlighting their strengths and limitations with regard to epidemiological research. Recent Findings Wearable passive samplers are emerging as promising exposomic sensors for individuals. In conjunction with targeted and untargeted assays, these sensors enable the measurement of complex multipollutant mixtures, which can include both known and previously unknown environmental contaminants. Because of their minimally burdensome and noninvasive nature, they are deployable among sensitive populations, such as seniors, pregnant women, and children. The integration of exposomic data captured by these sensors with other omic data (e.g., transcriptomic and metabolomic) presents exciting opportunities for investigating disease risk factors. For example, the linkage of exposomic sensor data with other omic data may indicate perturbation by multipollutant mixtures at multiple physiological levels, which would strengthen evidence of their effects and potentially indicate targets for interventions. However, there remain considerable theoretical and methodological challenges that must be overcome to realize the potential promise of omic integration. Through continued investment and improvement in exposomic sensor technologies, it may be possible to refine their application and reduce their outstanding limitations to advance the fields of exposure science and epidemiology.

Automated summary

The exposome encompasses all non-genetic factors that affect human health, and technologies like wearable passive samplers are emerging as promising tools for measuring complex multipollutant mixtures in individuals. Integrating exposomic data with other omic data presents exciting opportunities for investigating disease risk factors, but overcoming theoretical and methodological challenges is necessary to realize the potential promise of omic integration. Continued investment and improvement in exposomic sensor technologies may help refine their application and reduce outstanding limitations to advance the fields of exposure science and epidemiology.