An integrated bioinformatics analysis of the potential regulatory effects of mir-21 on t-cell related target genes in multiple sclerosis

Background Overexpression of miR-21 is a characteristic feature of patients with Multiple Sclerosis (MS) and is involved in gene regulation and the expression enhance-ment of pro-inflammatory factors including IFN? and TNF-a following stimulation of T-cells via the T Cell Receptor (TCR). In this study, a novel integrated bioinformatics analysis was used to obtain a better understanding of the involvement of miR-21 in the development of MS, its protein biomarker signatures, RNA levels, and drug interactions through existing microarray and RNA-seq datasets of MS. Methods In order to obtain data on the Differentially Expressed Genes (DEGs) in patients with MS and normal controls, the GEO2R web tool was used to analyze the Gene Expression Omnibus (GEO) datasets, and then Protein-Protein Interaction (PPI) networks of co-expressed DEGs were designed using STRING. A molecular network of miRNA-genes and drugs based on differentially expressed genes was created for T-cells of MS patients to identify the targets of miR-21, that may act as important regu-lators and potential biomarkers for early diagnosis, prognosis and, potential therapeutic targets for MS. Results It found that seven genes (NRIP1, ARNT, KDM7A, S100A10, AK2, TGFßR2, and IL-6R) are regulated by drugs used in MS and miR-21. Finally, three overlapping genes (S100A10, NRIP1, KDM7A) were identified between miRNA-gene-drug network and nineteen genes as hub genes which can reflect the pathophysiology of MS. Conclusion Our findings suggest that miR-21 and MS-related drugs can act synergisti-cally to regulate several genes in the existing datasets, and miR-21 inhibitors have the potential to be used in MS treatment.