Unveiling the Molecular Landscape: Network Analysis of Genes, Proteins, and Transcription Factors in Primary Progressive and Secondary Progressive Multiple Sclerosis for Unraveling Disease Progression and Prognostic Factors

Abstract

Abstract Multiple sclerosis (MS) is a chronic autoimmune disease characterized by the destruction of the myelin sheath in the central nervous system (CNS), leading to various neurological symptoms. The disease has different types, including relapsing-remitting MS (RRMS), secondary progressive MS (SPMS), primary progressive MS (PPMS), and progressive-relapsing MS (PRMS), each with its own clinical characteristics and prognosis. The exact cause of MS is not known, but it is believed to result from a complex interaction between genetic and environmental factors. This study offers a comprehensive analysis of individuals with varying disease durations in multiple sclerosis, comparing those who experienced earlier mortality with those who lived longer. By elucidating the factors influencing disease progression and severity, we anticipate that our findings will contribute to the advancement of knowledge in the field, with the potential to inform future research and clinical practices aimed at improving patient outcomes in MS. In this study, we used microarray data from postmortem brain tissue samples available from NCBI and used a system biology approach to identify differentially expressed genes (DEGs) associated with PPMS and SPMS. We performed protein-protein interaction (PPI) network analysis to identify common proteins and modules involved in the pathogenesis of the two diseases. Additionally, we analyzed the interaction between transcription factors (TFs) and DEGs to identify potential regulatory mechanisms. Furthermore, gene ontology analysis was conducted to investigate the biological processes and pathways affected by the DEGs. Our analysis identified a total of 153 common DEGs between PPMS and SPMS. These DEGs were involved in various biological processes such as cell adhesion, regulation of apoptotic process, inflammatory response, and protein phosphorylation. The PPI network analysis revealed key proteins, including MSN, ROS1, CD4, and NR4A1, which may play important roles in the pathogenesis of both diseases. We also identified TFs that interacted with the DEGs, highlighting their potential regulatory roles. Our study provides insights into the molecular mechanisms underlying PPMS and SPMS. By identifying common DEGs, PPIs, and TFs, we contribute to the understanding of shared pathways and potential therapeutic targets for these neurodegenerative disorders. Further research is warranted to validate and explore the functional significance of these findings.