Physiological genomics of cardiac disease: quantitative relationships between gene expression and left ventricular hypertrophy

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Abstract
The pathogenesis of cardiac left ventricular hypertrophy and failure is poorly defined due to the complexity of the disease phenotype. To gain a better understanding of the relationship between gene expression and left ventricular hypertrophy, we employed a quantitative approach to identify genes with expression patterns that correlate in a numerically continuous manner with parameters of cardiac structure and function in a mouse model of left ventricular hypertrophy due to transverse aortic constriction. Several genes showed expression patterns that were significantly correlated (Pearson's correlation coefficient) with measurements of left ventricular weight, left ventricular wall thickness, and diastolic dimension. We validated our findings in two independent data sets and in a small subset of genes by real-time RT-PCR. Of genes with significant correlations to numerically continuous measurements of hypertrophy, we found enrichment for genes encoding extracellular matrix, growth-related and secreted proteins in the directly correlated subset, and for genes encoding mitochondria and metabolic/fatty acid oxidation proteins in the inversely correlated subset. The results of this filtering strategy suggest that this subset of transcripts with quantitative relationships between gene expression and left ventricular hypertrophy represents potentially important pathways that contribute to the progression to heart failure and are thus candidates for follow-up and functional analysis.