Comput Biol Med. 2021 Apr;131:104243. doi: 10.1016/j.compbiomed.2021.104243. Epub 2021 Jan 27.
Computers in biology and medicine
Athina I Amanatidou, George V Dedoussis
PMID: 33550014 DOI: 10.1016/j.compbiomed.2021.104243
Non-alcoholic fatty liver disease (NAFLD) is a disease with multidimensional complexities. Many attempts have been made over the years to treat this disease but its incidence is rising. For this reason, the need to identify and study new candidate proteins that may be associated with NAFLD is of utmost importance. Systems-based approaches such as the analysis of protein-protein interaction (PPI) network could lead to the discovery of new proteins associated with a disease that can then be translated into clinical practice. The aim of this study is to analyze the interaction network of human proteins associated with NAFLD as well as their experimentally verified interactors and to identify novel associations with other human proteins that may be involved in this disease. Computational analysis made it feasible to detect 77 candidate proteins associated with NAFLD, having high network scores. Furthermore, clustering analysis was performed to identify densely connected regions with biological significance in this network. Additionally, gene expression analysis was conducted to validate part of the findings of this research work. We believe that our research will be helpful in extending experimental efforts to address the pathogenesis and progression of NAFLD.
Copyright © 2021 Elsevier Ltd. All rights reserved.
Keywords: Bioinformatics; Non-alcoholic fatty liver disease; Nonalcoholic steatohepatitis; Protein-disease association; Protein-protein interaction (PPI) network
