Exposome
Chemical exposures exert a pervasive and profound impact on human health, presenting both individualized and population-wide risks. Historically, a fundamental challenge has been the lack of a unifying mechanistic understanding of how structurally diverse compounds interfere with complex biological processes, thereby contributing to chronic disease risk. To address this gap, we employed a novel network-based systems biology approach, constructing a comprehensive map linking a cohort of 9,887 distinct chemical exposures based on their shared downstream impact at the genetic level.
This investigation reveals that chemical stressors do not act randomly; rather, they target specific, definable modules within the human interactome—the complex network of protein-protein interactions. Our model suggests that exposure hazard is directly correlated with its connectivity within this interactome. Critically, by systematically comparing these targeted exposed modules with modules implicated in various diseases, we established a predictive framework: the proximity of an exposure module to a known disease-associated module within the interactome can predict a potential exposure-disease relationship.
To validate this theoretical construct, we cross-referenced these predicted associations with real-world, national disease prevalence data, correlating elevated levels of specific environmental exposures (e.g., in air or water) with observable increases in specified disease incidences. Collectively, our findings provide a highly systematic blueprint. This platform moves beyond simple lists of correlated exposures, offering a robust methodology for understanding the precise molecular pathways through which environmental chemistry initiates biological disruption, and consequently, linking that molecular impact to quantifiable population health outcomes.
You can find the app at: exposome.westeurope.cloudapp.azure.com
