The purpose of this funding opportunity is to solicit applications that fully integrate recent innovative advances of in vitro functional genomics tools/technologies and approaches for environmental health and toxicology research. The overall goal of this NIEHS led initiative is to generate proof-of-principle studies incorporating these new in vitro approaches, together with well characterized exposures, to further our understanding of gene-environment (G x E) interactions in complex human disorders.
Many complex human diseases are known to involve multiple, potentially interacting genetic and environmental factors. Gene-environment (G x E) interaction or interplay is interchangeably used for the purposes of this FOA. G x E is defined broadly as a varying effect of an environmental exposure(s) depending on genetic background (susceptibility) of an individual or the stimulation of a gene variant(s) to cause disease phenotype or dysfunction only under certain environmental conditions.
Human epidemiology studies that aim to identify any interplay between genetics and environmental factors face many challenges. Foremost is the need for large sample sizes to detect an exclusive G x E association, relative to main effects, and the need for the study population to exhibit a range of both genetic and environmental variation. Consortium approaches to increase power can face difficulties in the harmonization of exposure measures and unevenness in quality of exposure assessments across different study populations. Addressing the temporality of exposures and compound mixtures brings additional complexities. Patterns of linkage disequilibrium and genetic and phenotypic heterogeneity can also reduce power to identify potential causal variants. Finally, the location of most GWAS hits in non-coding regions hinders mechanistic interpretation, and this is even more true for G x E findings with non-coding variants.
Despite these challenges, epidemiology studies supported by NIEHS and other NIH Institutes have revealed a few intriguing G x E interactions associated with several complex diseases. These potential G x E interactions were often identified through unique human population studies (with specific exposures, ethnic backgrounds, or rare disease phenotypes), making it extremely difficult to replicate or validate many of these limited G x E findings in other appropriate human populations. New approaches to therefore both identify and validate gene-environment (G x E) paradigms relevant to human disease are sorely needed.
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