Integrated analysis of differentially expressed genes and a ceRNA network to identify hub lncRNAs and potential drugs for multiple sclerosis.

Objective: Multiple sclerosis (MS) is an autoimmune neuroinflammatory disease of the nervous system. However, the precise molecular mechanisms underlying MS have yet to be fully elucidated. In this study, our aim was to provide novel insight into the pathogenesis of MS and provide a resource for identifying new biomarkers and therapeutics for MS.

Methods: In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs). Next, we constructed a protein-protein interaction (PPI) network and a MS-specific ceRNA network (MCEN) by integrating expression profiles, interaction pairs of mRNA-miRNAs and lncRNA-miRNAs. Then, according to the modular structure of the PPI network, we identified hub DEmRNAs and generated a ceRNA subnetwork so that we could analyze the key lncRNAs that were associated with MS.

Results: We first identified 4 modules by constructing a PPI network using DEmRNAs. Functional enrichment analysis showed these modules were enriched in immune-related pathways. Then, we constructed the MCEN and the hub gene-associated ceRNA subnetwork using a comprehensive computational approach. We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork. Finally, by analyzing LINC00649-miR-1275-CD20, we identified 6 drugs that may represent novel drugs for MS.

Conclusion: Collectively, our results provide novel insight for the discovery of biomarkers and therapeutics for MS and provide a suitable foundation from which to design future investigations of the pathogenic mechanisms associated with MS.