Systems toxicology meta-analysis – from aerosol exposure to nanotoxicology

Abstract
Systems toxicology marks an important stage in the evolution of toxicology. It combines the insights from traditional toxicology endpoints, high-throughput data, and quantitative analysis of large cause-and-effect molecular network models that provide the most mechanistic information in the interpretation of high-throughput data. Here, we show an example how pulmonary causal biological network models can be used in a meta-analysis of independent studies on engineered nanomaterials (ENM) to gain mechanistic insight into the similarities and differences of the ways the ENMs impact biological processes in the mouse lung. Meta-analyses using the lung network models could be used in various toxicological applications to find underlying trends in response to exposures, derive compound-specific mechanistic signatures, and translate between species.