Combining genome-wide data from humans and animal models of dyslipidemia and atherosclerosis.

Abstract

Comparative genomics allows researchers to combine genome-wide association data from humans with studies in animal models in order to assist in the identification of the genes and the genetic variants that modify susceptibility to dyslipidemia and atherosclerosis. Association and linkage studies in human and rodent species have been successful in identifying genetic loci associated with complex traits, but have been less robust in identifying and validating the responsible gene and/or genetic variants. Recent technological advancements have assisted in the development of comparative genomic approaches, which rely on the combination of human and rodent datasets and bioinformatics tools, followed by the narrowing of concordant loci and improved identification of candidate genes and genetic variants. Additionally, candidate genes and genetic variants identified by these methods have been further validated and functionally investigated in animal models, a process that is not feasible in humans. Comparative genomic approaches have led to the identification and validation of several new genes, including a few not previously implicated, as modifiers of plasma lipid levels and atherosclerosis, yielding new insights into the biological mechanisms of these complex traits.