• Title of article

    Interaction Network Prediction and Analysis of Anorexia Nervosa

  • Author/Authors

    Rezaei-Tavirani, Majid Faculty of Medicine - Iran University of Medical Sciences, Tehran - Proteomics Research Center - Shahid Beheshti University of Medical Sciences, Tehran , Zamanian-Azodi, Mostafa Proteomics Research Center - Shahid Beheshti University of Medical Sciences, Tehran , Vafaee, Reza Proteomics Research Center - Shahid Beheshti University of Medical Sciences, Tehran

  • Pages
    10
  • From page
    45
  • To page
    54
  • Abstract
    Anorexia Nervosa (AN) as a mental condition is a common eating disorder among young women. We aimed to shed lights on molecular behavior of this serious disorder in terms of protein interacting profile to provide further insight about its complexity. Materials & Methods The AN related genes were extracted from STRING database and included in interactome via Cytoscape software. The central nodes of the network were enriched via gene ontology (GO) by ClueGO+CluePedia and the action relationship between the nodes were determined by CluePedia. Results Six genes including LEP, INS, POMC, GCG, SST, and ALB were introduced as hub-bottlenecks that among them LEP, INS, and POMC were the super hub-bottlenecks based on further analysis. Action map analysis showed prominent role of hubs relative to bottlenecks in the network. Regulation of behavior, regulation of carbohydrate biosynthetic process, and regulation of appetite are the top associated processes for the identified hub genes. Conclusion Topological analysis proposed the five hub-bottlenecks as the most central genes in the network, these genes and their contributing biological terms may suggest additional importance in AN pathogenesis and thereby possible candidates for therapeutic usage. However, further studies are required to justify these findings.
  • Keywords
    Anorexia nervosa , Eating disorder , Protein-protein interaction network analysis , Protein clustering , Gene ontology
  • Journal title
    Astroparticle Physics
  • Serial Year
    2019
  • Record number

    2488224