Gene network and proteomic analyses of cardiac responses to pathological and physiological stress

Ignat Drozdov, Athanasios Didangelos, Xiaoke Yin, Anna Zampetaki, Mélanie Abonnenc, Colin Murdoch, Min Zhang, Christos A. Ouzounis, Manuel Mayr, Sophia Tsoka, Ajay M. Shah

    Research output: Contribution to journalArticlepeer-review

    17 Citations (Scopus)


    Background: The molecular mechanisms underlying similarities and differences between physiological and pathological left ventricular hypertrophy (LVH) are of intense interest. Most previous work involved targeted analysis of individual signaling pathways or screening of transcriptomic profiles. We developed a network biology approach using genomic and proteomic data to study the molecular patterns that distinguish pathological and physiological LVH.
    Methods and Results: A network-based analysis using graph theory methods was undertaken on 127 genome-wide expression arrays of in vivo murine LVH. This revealed phenotype-specific pathological and physiological gene coexpression networks. Despite >1650 common genes in the 2 networks, network structure is significantly different. This is largely because of rewiring of genes that are differentially coexpressed in the 2 networks; this novel concept of differential wiring was further validated experimentally. Functional analysis of the rewired network revealed several distinct cellular pathways and gene sets. Deeper exploration was undertaken by targeted proteomic analysis of mitochondrial, myofilament, and extracellular subproteomes in pathological LVH. A notable finding was that mRNA–protein correlation was greater at the cellular pathway level than for individual loci.
    Conclusions: This first combined gene network and proteomic analysis of LVH reveals novel insights into the integrated pathomechanisms that distinguish pathological versus physiological phenotypes. In particular, we identify differential gene wiring as a major distinguishing feature of these phenotypes. This approach provides a platform for the investigation of potentially novel pathways in LVH and offers a freely accessible protocol ( for similar analyses in other cardiovascular diseases.
    Original languageEnglish
    Pages (from-to)588-597
    Number of pages10
    JournalCirculation: Cardiovascular Genetics
    Issue number6
    Publication statusPublished - Dec 2013


    • computational biology
    • genetics
    • genomics
    • proteomics


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