Identification of a core set of genes that signifies pathways underlying cardiac hypertrophy

C.C. Strom, M. Kruhoffer, Steen Knudsen, F. Stensgaard-Hansen, T.E.N. Jonassen, T.F. Omtoft, S. Haunso, S.P. Sheikh

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    Although the molecular signals underlying cardiac hypertrophy have been the subject of intense investigation, the extent of common and distinct gene regulation between different forms of cardiac hypertrophy remains unclear. We hypothesized that a general and comparative analysis of hypertrophic gene expression, using microarray technology in multiple models of cardiac hypertrophy, including aortic banding, myocardial infarction, an arteriovenous shunt and pharmacologically induced hypertrophy, would uncover networks of conserved hypertrophy-specific genes and identify novel genes involved in hypertrophic signalling. From gene expression analyses (8740 probe sets, n = 46) of rat ventricular RNA, we identified a core set of 139 genes with consistent differential expression in all hypertrophy models as compared to their controls, including 78 genes not previously associated with hypertrophy and 61 genes whose altered expression had previously been reported. We identified a single common gene program underlying hypertrophic remodelling, regardless of how the hypertrophy was induced. These genes constitute the molecular basis for the existence of one main form of cardiac hypertrophy and may be useful for prediction of a common therapeutic approach. Supplementary material for this article can be found at:
    Original languageEnglish
    JournalComparative and Functional Genomics
    Issue number6-7
    Pages (from-to)459-470
    Publication statusPublished - 2004


    • remodelling
    • cardiac hypertrophy
    • gene expression
    • DNA microarrays

    Cite this

    Strom, C. C., Kruhoffer, M., Knudsen, S., Stensgaard-Hansen, F., Jonassen, T. E. N., Omtoft, T. F., Haunso, S., & Sheikh, S. P. (2004). Identification of a core set of genes that signifies pathways underlying cardiac hypertrophy. Comparative and Functional Genomics, 5(6-7), 459-470.