Gene Coexpression Network Topology of Cardiac Development, Hypertrophy, and Failure CIRCULATION-CARDIOVASCULAR GENETICS Dewey, F. E., Perez, M. V., Wheeler, M. T., Watt, C., Spin, J., Langfelder, P., Horvath, S., Hannenhalli, S., Cappola, T. P., Ashley, E. A. 2011; 4 (1): 26-U129


Network analysis techniques allow a more accurate reflection of underlying systems biology to be realized than traditional unidimensional molecular biology approaches. Using gene coexpression network analysis, we define the gene expression network topology of cardiac hypertrophy and failure and the extent of recapitulation of fetal gene expression programs in failing and hypertrophied adult myocardium.We assembled all myocardial transcript data in the Gene Expression Omnibus (n=1617). Because hierarchical analysis revealed species had primacy over disease clustering, we focused this analysis on the most complete (murine) dataset (n=478). Using gene coexpression network analysis, we derived functional modules, regulatory mediators, and higher-order topological relationships between genes and identified 50 gene coexpression modules in developing myocardium that were not present in normal adult tissue. We found that known gene expression markers of myocardial adaptation were members of upregulated modules but not hub genes. We identified ZIC2 as a novel transcription factor associated with coexpression modules common to developing and failing myocardium. Of 50 fetal gene coexpression modules, 3 (6%) were reproduced in hypertrophied myocardium and 7 (14%) were reproduced in failing myocardium. One fetal module was common to both failing and hypertrophied myocardium.Network modeling allows systems analysis of cardiovascular development and disease. Although we did not find evidence for a global coordinated program of fetal gene expression in adult myocardial adaptation, our analysis revealed specific gene expression modules active during both development and disease and specific candidates for their regulation.

View details for DOI 10.1161/CIRCGENETICS.110.941757

View details for PubMedID 21127201