Computational Identification of Guillain-Barré Syndrome-Related Genes by an mRNA Gene Expression Profile and a Protein–Protein Interaction Network - Wang, Chunyang; Liao, Shiwei; Wang, Yiyi; Hu, Xiaowei; Xu, Jing (Frontiers in Molecular Neuroscience, 2022)
Background: In this study, we used a computational method to identify Guillain–Barré syndrome (GBS) related genes based on (i) a gene expression profile, and (ii) the shortest path analysis in a protein-protein interaction (PPI) network. Results: Totally 30 GBS related genes were screened out, in which 20 were retrieved from PPI analysis of up-regulated expressed genes and 23 were from down-regulated expressed genes (13 overlap genes). GO enrichment and KEGG enrichment analysis were performed respectively. Results showed that there were some overlap GO terms and KEGG pathway terms in both up-regulated and down-regulated analysis, including positive regulation of macromolecule metabolic process, intracellular signaling cascade, cell surface receptor linked signal transduction, intracellular non-membrane-bounded organelle, non-membrane-bounded organelle, plasma membrane, ErbB signaling pathway, focal adhesion, neurotrophin signaling pathway and Wnt signaling pathway, which indicated these terms may play critical role during GBS process Discussion: These results could shed some light on the understanding of the genetic and molecular pathogenesis of GBS disease, providing basis for future experimental biology studies and for the development of effective genetic strategies for GBS clinical therapies.