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Updated: May 7, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Integrated Transcriptome Analysis Reveals Molecular Subtypes and ceRNA Networks in Multiple Sclerosis
Caili Ji1, Li Ding1, Fumin Jia2
1Department of Clinical Laboratory, Jingjiang People's Hospital Affiliated to Yangzhou University, Taizhou, Jiangsu, 214504, People's Republic of China.
Aim:
Multiple sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system (CNS). While extensively studied, its molecular subtypes and mechanisms remain poorly understood, hindering the identification of effective therapeutic targets.
Methods:
We used ConsensusClusterPlus to analyze transcriptome data from 215 MS patient samples, identifying distinct molecular subtypes. Differential expression analysis and variability assessments were conducted to further characterize these subtypes. Additionally, circular RNAs (circRNAs) and microRNAs (miRNAs) were screened for potential ceRNA interactions.
Results:
Three molecular subtypes were identified: MS-FCRL1 (C1), MS-BTG1 (C2), and MS-RPL38 (C3). Each subtype was involved in key MS-related pathways (as annotated by KEGG), but the core genes regulating these pathways differed significantly among the subtypes. Subtype C3 exhibited neurodegenerative pathway enrichment, increased immune activity, and immune cell infiltration, suggesting a more severe disease course. Further analysis revealed 18 differentially expressed circRNAs and 22 miRNAs, with EEF1D and TUBA1A as hub targets in C3.
Discussion:
Differential activation of immune pathways across MS subtypes suggests specific gene expression drives disease heterogeneity. We propose a circ_0045537/miR-196a-5p/TUBA1A axis in subtype C3, modulating microtubule dynamics and worsening MS severity.
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