Deciphering the Role of CircRNA-miRNA Networks in Multiple Sclerosis Pathogenesis through Minimal Cut-Set Analysis

Multiple sclerosis (MS) is a chronic autoimmune neurodegenerative disorder with a complex,yet poorly understood, pathophysiology. Recent studies have highlighted the role of non-coding RNAs,especially circular RNAs (circRNAs), in the regulation of gene expression and their impact on MSprogression. Notably, circRELL۱, circRPPH۱, and circGSDMB have been identified as significantlyupregulated in MS patients. This study aims to elucidate the competing endogenous RNA (ceRNA)network of these circRNAs using minimal cut-set methodology.We employed the CircInteractome web tool and miRTarBase database to analyze the microRNAs andtheir associated mRNA targets for circRELL۱, circRPPH۱, and circGSDMB. The protein-proteininteraction (PPI) network of these mRNAs was reconstructed, and the minimal cut-set was identifiedusing Gephi network analysis tool. The key driver nodes were determined using the CytoCtrlAnalyserplugin in Cytoscape ۳.۹. The present analysis revealed that circRELL۱, circRPPH۱, and circGSDMBtarget ۱۵, ۱۴, and ۶ miRNAs, respectively, with significant interactions observed in the PPI network.Specifically, we identified five proteins - AKT۱, CCND۲, BAX, CRKL, and EGFL۷—as enricheddriver nodes in the PPI network. Notably, at least five circRNA/miRNA/mRNA axes, includingcirc_۰۰۰۱۴۰۰/ miR-۶۳۷/AKT۱, circ_۰۰۰۱۴۰۰/ miR-۱۲۶/ EGFL۷, and circ_۰۰۰۱۴۰۰/ miR-۱۲۶/ CRKL,circ RPPH۱/miR-۶۶۳b/CCND۲, circ_۰۱۰۶۸۰۳/ miR-۷-۵p and miR-۷۶۶-۳p/BAX, were identified as keycontributors to MS pathogenesis, influencing critical processes such as T cell proliferation, blood-brainbarrier integrity, and oligodendrocyte apoptosis.These findings enhance our understanding of the molecular underpinnings of MS and suggest newavenues for targeted therapeutic strategies by modulating these ceRNA networks. Importantly, theidentification of driver nodes within these networks highlights the potential of network analysis indeciphering complex disease mechanisms and guiding the development of effective treatments forneurodegenerative disorders like MS.

کلیدواژه ها:

Splicing detection ، ResNet-۳۲ architecture ، Imbalanced datasets ، DNA sequence analysis