Distinct genetic regions are associated with differential population susceptibility to chemical exposures

Marissa B Kosnik,Stefan Enroth,Oskar Karlsson

doi:10.1016/j.envint.2021.106488

Marissa B Kosnik, Stefan Enroth + Show 1 more

Open Access

https://doi.org/10.1016/j.envint.2021.106488

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Abstract

Interactions between environmental factors and genetics underlie the majority of chronic human diseases. Chemical exposures are likely an underestimated contributor, yet gene-environment (GxE) interaction studies rarely assess their modifying effects. Here, we describe a novel method to profile the human genome and identify regions associated with differential population susceptibility to chemical exposures. Single nucleotide polymorphisms (SNPs) implicated in enriched chemical-disease intersections were identified and validated for three chemical classes with expected GxE interaction potential (neuroactive, hepatoactive, and cardioactive compounds). The same approach was then used to characterize consumer product classes with unknown risk for GxE interactions (washing products, cosmetics, and adhesives). Additionally, high-risk variant sets that may confer differential population susceptibility were identified for these consumer product groups through frequent itemset mining and pathway analysis. A dataset of 2454 consumer product chemical-disease linkages, with risk values, SNPs, and pathways for each association was developed, describing the interplay between environmental factors and genetics in human disease progression. We found that genetic hotspots implicated in GxE interactions differ across chemical classes (e.g., washing products had high-risk SNPs implicated in nervous system disease) and illustrate how this approach can discover new associations (e.g., washing product n-butoxyethanol implicated SNPs in the PI3K-Akt signaling pathway for Alzheimer’s disease). Hence, our approach can predict high-risk genetic regions for differential population susceptibility to chemical exposures and characterize chemical modifying factors in specific diseases. These methods show promise for describing how chemical exposures can lead to varied health outcomes in a population and for incorporating inter-individual variability into chemical risk assessment.

Highlights

Methods to analyze the environmental contributions to human dis ease are often limited to epidemiological analyses
Chemical classes with expected GxE interaction potential are related to consumer product classes with un known risk, and we describe the structure of genetic risk across these classes, assess the combined effect of genetic variants implicated in chemical-disease associations, and demonstrate how GxE interaction potential differs depending on exposure
We aim to demonstrate the utility of this chemical-variant-disease dataset and the disease quotient genetic overview score (DisQGOS) risk value-based approach in describing GxE interaction potential resulting from chemical exposures

Summary

Introduction

Methods to analyze the environmental contributions to human dis ease are often limited to epidemiological analyses. Determining the role that environmental exposures play in differential population suscepti bility is challenged by linking specific exposures to differential out comes, which often depend on a large, highly exposed population for analysis (McAllister et al, 2017) This is not possible for the large number of chemicals in circulation, which is a challenge because the majority of chronic human diseases are not caused by genetic factors alone (Rappaport, 2016). Rare SNPs implicated in diseases can be missed when the small effects of each variant contributing to a disease cannot be statistically detected (Visscher et al, 2017) While approaches such as pathway analysis have assessed the collective effect of multiple variants in disease progression to account for missing heritability (Kao et al, 2017), these methods have rarely been used to characterize gene-environment (GxE)

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