Construction and analysis of protein-protein interaction network of non-alcoholic fatty liver disease

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.

Automated summary

Non-alcoholic fatty liver disease (NAFLD) is a complex disease that requires identification and study of new candidate proteins. This study analyzed the interaction network of human proteins associated with NAFLD to identify novel associations with other proteins involved in the disease. The computational analysis detected 77 candidate proteins with high network scores, and clustering analysis identified densely connected regions with biological significance. Additionally, gene expression analysis was conducted to validate some of the research findings, aiming to provide insights for addressing the pathogenesis and progression of NAFLD.