In-silico Analyses for Finding Potential Key Genes and Pathways Associated with Guillain-Barré Syndrome Using Computational Tools

Guillain-Barré syndrome (GBS) is an immune-mediated neuropathy associated with infection and vaccination. Although numerous genes and proteins are linked to GBS, the pathogenesis of GBS remains poorly understood. This study aims to elucidate the underlying pathomechanisms of GBS using bioinformatic tools. We sourced GBS-related genes from NLP databases, literature, and datasets of previous studies. A protein-protein interaction (PPI) network using these genes was constructed, and hub genes were identified through centrality parameters. Additionally, we created a pathway-pathway interaction network through enrichment analysis to decipher GBS complexity and associated pathways. A gene-disease network was also developed to explore the molecular connection between GBS and other diseases. The study identified ۶۱۱ unique genes and proteins associated with GBS. Key hub proteins in the PPI network included AKT serine/threonine kinase ۱ (AKT۱), tumor necrosis factor-α (TNF-α), CD۴, albumin (ALB), and JUN. The pathway-pathway interaction network highlighted significantly enriched pathways like allograft rejection, graft versus host disease, inflammatory bowel disease (IBD), coronavirus disease, and necroptosis signaling. Shared genes and proteins with GBS were found in autoimmune, viral, and infectious diseases, including multiple sclerosis, IBD, and tuberculosis. Common biological pathways between GBS and other diseases involved cellular response to lipopolysaccharides and cytokines, and regulation of inflammatory response. Our findings reveal molecular links between GBS and various pathways and diseases, including SARS-CoV-۲, that could be used for novel preventative and therapeutic strategies and highlighting a new frontier in GBS research and treatment.

Keywords:

Guillain-Barré syndrome , GBS , Pathogenesis , In-silico analysis , Gene-Disease network