The potential application of transcriptomics and methylomics in environmental epidemiological studies for chemical assessments

Abstract

'Omics technologies can provide comprehensive information on molecular changes in cells and tissues in a cost-effective and efficient manner, and these technologies have the potential to improve chemical assessments through informing hazard identification and informing dose response. There are a growing number of environmental epidemiological studies that have examined chemical exposures and applied ‘omics analyses with the cohort’s biological samples. These environmental epidemiological studies can take the advantage of high-throughput ‘omics technology with classical epidemiology to examine associations with molecular responses. Therefore, this symposium presentation will primarily focus on the broad applications and potential of transcriptomic and methylomic data from environmental epidemiological studies to inform human mechanistic evidence for chemical assessments. This presentation will delve into a novel and complementary case study describing the integration of transcriptomic and methylomic data from environmental epidemiological studies examining chemical exposures. The altered expression of a single gene or methylated region may or may not be biologically relevant, yet a complementary examination of altered genes and regions mapping onto perturbed pathways can contribute to more informed biological plausibility. The presentation will discuss how patterns of DNA methylation and gene expression can complement each other in identifying molecular effects through differential enrichment of biological pathways. Analytical methods will also be discussed on the following: a) identifying differentially-expressed genes; b) using appropriate cellular deconvolution methods to derive differential methylation regions; c) performing gene-set enrichment analysis (GSEA) on the differential genes derived from transcriptomic and methylomic analyses; and d) benchmark dose modeling to characterize the dose ranges responsible for driving the enrichment of biologically-relevant gene expression changes.