Protein-Protein Interaction Network Analysis Revealed a New Prospective of Posttraumatic Stress Disorder

Abstract

Background: Posttraumatic stress disorder (PTSD) is known by a number of mental disorders, including recurring memories of trauma, mental appalling, and escaping of sign that make them recall the trauma in question. Clinical interviews serve as the main diagnostic tool for PTSD. With respect to treatment, either pharmacotherapy or psychotherapy or a combination of both is used as a therapeutic method for PTSD. In this study, a number of crucial genes related to PTSD, which can be considered as biomarker candidates, were represented. Materials and Methods: The genes related to PTSD were extracted from the STRING database and organized in a protein-protein interaction network with the help of Cytoscape software version 3.6.0. The network was analyzed, and the important genes were introduced based on central indices. The biological processes related to the crucial genes were enriched via gene ontology using ClueGO. Results: From a total of 100 genes, 63 genes were extracted that formed the main connected component, and of these, 12 crucial genes¾POMC, BDNF, FOS, NR3C1, CRH, IL6, NPS, HTR1A, NPY, CREB1, CRHR1, and TAC1¾were introduced. Biological processes were classified into the regulation of corticosterone, regulation of behavior, response to fungus, multicellular organism response to stress, and associative learning. Conclusion: The introduced 12 crucial genes can be used as a biomarker panel related to PTSD and can be considered as a diagnostic reagent or drug target; however, more investigations are needed to use these genes as biomarkers.[GMJ.2018;7:e1137]

Comparative Bioinformatics Characteristic of Bladder Cancer Stage 2 from Stage 4 Expression Profile: A Network-Based Study

“…We used the Cytoscape version 3.6.1. application for the network data visualization and analysis. Network centrality is one of the fundamental concepts for the network [15]. After network data integration via the STRING database plug-in in Cytoscape, essential centrality parameters including degree and betweenness were explored by the use of Genetic Network Analyzer [18,19].…”

“…Network analysis, therefore, could present multiple powerful therapeutic targets [14]. In this study, we aimed to examine DEG via protein interaction maps to find better biomarkers for stages 2 and 4 of BC, as bioinformatics can analyze and screen the genes related to various diseases to select the more important ones [15].…”