Contributions
Abstract: EP1607
Type: ePoster
Abstract Category: Pathology and pathogenesis of MS - 25 Biomarkers
Increasing reports link recent ZIKV infections to various forms of neuropathology, including microcephaly and Guillain-Barré syndrome (GBS). The pathogenesis viral infections and the development of autoimmune diseases may have viral trigger and are linked to disturbances in immune response. Here we compared upregulated transcript profile of multiple scleroses (MS) patients and infection by ZIKV (human neural progenitor cells, human maternal decidual tissues and human fetal brain neural stem cells, all exposed to ZIKV) using bioinformatics tools. In lists available in online databases, we found a total of 593 genes upregulated in MS and 534 in ZIKV infection, 36 genes were shared between them. To further understand the impact of MS and ZIKV infections on the biological processes, we used Gene ontology (GO). Several biological processes were similarly significantly enriched for both MS and ZIKV transcriptomes, these terms include mainly the cell proliferation, response to stress and immune response. In comparative analyses of protein-protein interactions (PPI) network design we observed network with 289-261 nodes and 878-778 connectors in ZIKV and MS network, respectively. Centrality parameters (Node degree and Betweenness) of each node were analyzed. These pathways obtained statistical significance (p < 0.05). STAT1, ISG15, HERC5, OAS1, IFIT3, IRF7, IFIT1, MX1, IFI35 and IFIT2 were the 10 top hub genes in ZIKV network. In MS network, JUN was the gene capable of making the largest numbers of connections with other genes and joining several subnetworks, thus being considered the hub-bottleneck, which controls the most of the information of a network. The 10 top hub in this network were JUN, CDC20, FOS, TOP2A, AURKB, KIF2C, RRM2, CREBBP, IL8 and CDC45. We also did an analysis of the two networks together to identify molecular signatures similar in MS and ZIKV infection. The main functional enrichment categories in this analysis were regulation of apoptosis, chemotaxis, regulation of JAK-STAT cascade, immune response, positive regulation of cell proliferation and signal transmission. The approaches employed in this study enabled us to report sets of genes that according to their physical interactions are predicted to be molecular signatures similar in MS and ZIKV infection, improving the understanding of this new outbreak and, in the future, may support a new proposal of prognostic and treatments.
Disclosure: The authors declare that they have no competing interests.
Abstract: EP1607
Type: ePoster
Abstract Category: Pathology and pathogenesis of MS - 25 Biomarkers
Increasing reports link recent ZIKV infections to various forms of neuropathology, including microcephaly and Guillain-Barré syndrome (GBS). The pathogenesis viral infections and the development of autoimmune diseases may have viral trigger and are linked to disturbances in immune response. Here we compared upregulated transcript profile of multiple scleroses (MS) patients and infection by ZIKV (human neural progenitor cells, human maternal decidual tissues and human fetal brain neural stem cells, all exposed to ZIKV) using bioinformatics tools. In lists available in online databases, we found a total of 593 genes upregulated in MS and 534 in ZIKV infection, 36 genes were shared between them. To further understand the impact of MS and ZIKV infections on the biological processes, we used Gene ontology (GO). Several biological processes were similarly significantly enriched for both MS and ZIKV transcriptomes, these terms include mainly the cell proliferation, response to stress and immune response. In comparative analyses of protein-protein interactions (PPI) network design we observed network with 289-261 nodes and 878-778 connectors in ZIKV and MS network, respectively. Centrality parameters (Node degree and Betweenness) of each node were analyzed. These pathways obtained statistical significance (p < 0.05). STAT1, ISG15, HERC5, OAS1, IFIT3, IRF7, IFIT1, MX1, IFI35 and IFIT2 were the 10 top hub genes in ZIKV network. In MS network, JUN was the gene capable of making the largest numbers of connections with other genes and joining several subnetworks, thus being considered the hub-bottleneck, which controls the most of the information of a network. The 10 top hub in this network were JUN, CDC20, FOS, TOP2A, AURKB, KIF2C, RRM2, CREBBP, IL8 and CDC45. We also did an analysis of the two networks together to identify molecular signatures similar in MS and ZIKV infection. The main functional enrichment categories in this analysis were regulation of apoptosis, chemotaxis, regulation of JAK-STAT cascade, immune response, positive regulation of cell proliferation and signal transmission. The approaches employed in this study enabled us to report sets of genes that according to their physical interactions are predicted to be molecular signatures similar in MS and ZIKV infection, improving the understanding of this new outbreak and, in the future, may support a new proposal of prognostic and treatments.
Disclosure: The authors declare that they have no competing interests.