Temporal analysis of mRNA and miRNA expression in transgenic mice overexpressing Arg- and Gly389 polymorphic variants of the β1-adrenergic receptor.

Several studies in humans or transgenic animals have reported that the 389 Arg or Gly polymorphic variation of the β1-adrenergic receptor (AR) is associated with differential responses to beta-blocker therapy and/or myocardial disease progression. Analysis of changes in gene expression is an important means of defining molecular differences associated with structural or functional phenotypic variations. To determine if structural and functional myocardial phenotypic differences between β1389 Arg vs. Gly transgenic overexpressors are associated with qualitative and/or quantitative differences in gene expression, a comprehensive analysis of mRNAs and miRNAs expressed in the hearts of 3 and 6-8 mo old β1-Arg389 and β1-Gly389 overexpressor transgenic mice was performed. Changes in mRNA and miRNA expression were analyzed by arrays and partially confirmed by RT-qPCR. Bioinformatic analysis demonstrated that several genes, including those involved in PKA and CaMK signaling pathways, are regulated in a temporal- or phenotype-specific manner. Furthermore, expression signature analyses indicated that miRNAs have the potential to target expression of a number of genes involved in multiple cardiomyopathy-related pathways, and changes in miRNA expression can precede the onset of disease. Differences in gene expression between β1-Arg389 and β1-Gly389 transgenic mice are largely quantitative rather than qualitative and are associated with the development of cardiomyopathy in a time-dependent manner. Chronic β1-AR overdrive results in increased expression of components of the CaMK pathway, with correspondingly decreased levels of components of the PKA pathway. Based on the temporal and genotype-specific pattern of miRNA expression, miRNAs are likely to be important predictors of disease states, especially when miRNA expression is paired with mRNA expression, and that miRNA/mRNA expression signatures have the potential to be useful in determining the underlying risk associated with cardiac disease progression.