Gene-by-environment interactions that affect exposure-mediated congenital heart disease

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Project Summary/Abstract We propose to exploit unique features of the Atlantic killifish model system to elucidate the interaction of genetic variation and environmental exposures in the etiology of congenital heart disease (CHD). This complex human disease encompasses a suite of structural and functional deficits and is the most common human congenital malformation worldwide. The etiology of CHD is poorly understood, but appears to involve both genetic and environmental risk factors, including exposure to environmental chemicals. The Atlantic killifish (Fundulus heteroclitus) is a novel population-based model system that harbors substantial genetic diversity and exhibits chemical-induced cardiovascular disease states that mimic substantial aspects of CHD in humans. Killifish inhabit urbanized environments that are polluted by mixtures of chemicals including polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs). Urban and non-urban populations vary profoundly in their sensitivity to CHD caused by exposure to these compounds. We propose to use this unique and powerful system to explore gene-environment interactions associated with CHD, expanding on our successful use of the Quantitative Trait Loci (QTL) approach in this species. A particularly compelling feature of this model is that natural selection has increased the frequency of otherwise rare variants that influence sensitivity to these (and potentially other) important classes of pollutants. Our previous data reveal some regions of the genome that affect fitness in polluted environments, and contribute to variation in sensitivity to CHD. The overall objective of the proposed research is to determine the genes and pathways harboring genetic variation that controls sensitivity to PCB- and PAH-induced CHD. We will test for genetic associations through genome-wide genotyping of phenotyped animals in replicate families bred using QTL strategies and exposed to PCB and PAHs. Experiments will test for genetic association with multiple specific structural and functional deficits that define the suite of CHD phenotypes. This QTL mapping will include 1) multiple genetic backgrounds, 2) multiple CHD-associated chemicals, each with different hypothesized mechanisms of action, and 3) multiple exposure levels. We will test whether the different CHD features are associated with unique or shared variants in different genetic backgrounds, and whether disease-associated variants are unique or shared among structurally diverse classes of chemicals that may cause CHD by different mechanisms. We will evaluate the relevance of CHD-associated variants by testing whether they are associated with variable fitness between polluted and clean environments, focus inference of candidate genes using eQTL mapping, and test hypothesized associations using genome editing by CRISPR-Cas9 technology. This research in a population-based vertebrate model will reveal mechanisms underlying gene- environment interactions involved in determining susceptibility to CHD, a common congenital condition.