Unique ability of pandemic influenza to downregulate the genes involved in neuronal disorders Academic Article uri icon


  • Pandemic influenza remains as a substantial threat to humans with a widespread panic worldwide. In contrast, seasonal (non-pandemic) has a mild non-lethal infection each year. The underlying mechanisms governing the detrimental effects of pandemic influenza are yet to be known. Transcriptomic-based network discovery and gene ontology (GO) analysis of host response to pandemic influenza, compared to seasonal influenza, can shed light on the differential mechanisms which pandemic influenza is employed during evolution. Here, using microarray data of infected ferrets with pandemic and seasonal influenza (as a model), we evaluated the possible link between altered genes after pandemic infection with activation of neuronal disorders. To this end, we utilized novel computational biology techniques including differential transcriptome analysis, network construction, GO enrichment, and GO network to investigate the underlying mechanisms of pandemic influenza infection and host interaction. In comparison to seasonal influenza, pandemic influenza differentially altered the expression of 31 genes with direct involvement in activity of central nervous system (CNS). Network topology highlighted the high interactions of IRF1, NKX2-1 and NR5A1 as well as MIR27A, MIR19A, and MIR17. TGFB2, NCOA3 and SP1 were the central transcription factors in the┬ánetworks. Pandemic influenza remarkably downregulated GPM6A and GTPase. GO network demonstrated the key roles of GPM6A and GTPase in regulation of important functions such as synapse assembly and neuron projection. For the first time, we showed that besides interference with cytokine/chemokine storm and neuraminidase enzyme, H1N1 pandemic influenza is able to directly affect neuronal gene networks. The possibility of application of some key regulators such as GPM6A protein, MIR128, and MIR367 as candidate therapeutic agents is discussed. The presented approach established a new way to unravel unknown pathways in virus-associated CNS dysfunction by utilizing global transcriptomic data, network and GO analysis.


publication date

  • 2015