much an evolving topic in statistical research [77]. In summary, the present study suggests ERS is a promising tool for integrating disease risks from multi-pollutant mixture exposures. The ERS is a simplest form of data reduction, characterizing the summary exposure burden like a polygenic risk score in genetics [27]. This new approach supports the need for moving from a single-pollutant to a multi-pollutant framework for new discoveries and better risk stratification. Combining information from ERS along with known predictors can improve disease prediction. Also, the ERS along with genetic risk score can potentially provide a way to reduce dimension and increase the power in studies of gene-environment interaction. More generally, ERS can be taken as a measure of summary/background burden of environmental exposure and it will be interesting to explore whether the effect of a certain gene, behavioral factors (diet, physical activity, smoking) or another pollutant is larger if individuals are in the highest quartile of ERS. The contribution of ERS to risk prediction and classification warrants further studies.
