ObjectiveThis study aimed to explore the shared mechanism and candidate drugs of multiple sclerosis (MS) and Sjögren’s syndrome (SS).MethodsMS- and SS-related susceptibility genes and differentially expressed genes (DEGs) were identified by bioinformatics analysis based on genome-wide association studies (GWAS) and transcriptome data from GWAS catalog and Gene Expression Omnibus (GEO) database. Pathway enrichment, Gene Ontology (GO) analysis, and protein–protein interaction analysis for susceptibility genes and DEGs were performed. The drugs targeting common pathways/genes were obtained through Comparative Toxicogenomics Database (CTD), DrugBank database, and Drug–Gene Interaction (DGI) Database. The target genes of approved/investigational drugs for MS and SS were obtained through DrugBank and compared with the common susceptibility genes.ResultsBased on GWAS data, we found 14 hub common susceptibility genes (HLA-DRB1, HLA-DRA, STAT3, JAK1, HLA-B, HLA-DQA1, HLA-DQA2, HLA-DQB1, HLA-DRB5, HLA-DPA1, HLA-DPB1, TYK2, IL2RA, and MAPK1), with 8 drugs targeting two or more than two genes, and 28 common susceptibility pathways, with 15 drugs targeting three or more than three pathways. Based on transcriptome data, we found 3 hub common DEGs (STAT1, GATA3, PIK3CA) with 3 drugs and 10 common risk pathways with 435 drugs. “JAK-STAT signaling pathway” was included in common susceptibility pathways and common risk pathways at the same time. There were 133 overlaps including JAK-STAT inhibitors between agents from GWAS and transcriptome data. Besides, we found that IL2RA and HLA-DRB1, identified as hub common susceptibility genes, were the targets of daclizumab and glatiramer that were used for MS, indicating that daclizumab and glatiramer may be therapeutic for SS.ConclusionWe observed the shared mechanism of MS and SS, in which JAK-STAT signaling pathway played a vital role, which may be the genetic and molecular bases of comorbidity of MS with SS. Moreover, JAK-STAT inhibitors were potential therapies for MS and SS, especially for their comorbidity.

ObjectiveFinding target genes and target pathways of existing drugs for drug repositioning in multiple sclerosis (MS) based on transcriptomic changes in MS immune cells.Materials and MethodsBased on transcriptome data from Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) in MS patients without treatment were identified by bioinformatics analysis according to the type of immune cells, as well as DEGs in MS patients before and after drug administration. Hub target genes of the drug for MS were analyzed by constructing the protein-protein interaction network, and candidate drugs targeting 2 or more hub target genes were obtained through the connectivity map (CMap) database and Drugbank database. Then, the enriched pathways of MS patients without treatment and the enriched pathways of MS patients before and after drug administration were intersected to obtain the target pathways of the drug for MS, and the candidate drugs targeting 2 or more target pathways were obtained through Kyoto Encyclopedia of Genes and Genomes (KEGG) database.ResultsWe obtained 50 hub target genes for CD4+ T cells in Fingolimod for MS, 15 hub target genes for Plasmacytoid dendritic cells (pDCs) and 7 hub target genes for Peripheral blood mononuclear cells (PBMC) in interferon-β (IFN-β) for MS. 6 candidate drugs targeting two or more hub targets (Fostamatinib, Copper, Artenimol, Phenethyl isothiocyanate, Aspirin and Zinc) were obtained. In addition, we obtained 4 target pathways for CD19+ B cells and 15 target pathways for CD4+ T cells in Fingolimod for MS, 7 target pathways for pDCs and 6 target pathways for PBMC in IFN-β for MS, most of which belong to the immune system and viral infectious disease pathways. We obtained 69 candidate drugs targeting two target pathways.ConclusionWe found that applying candidate drugs that target both the “PI3K-Akt signaling pathway” and “Chemokine signaling pathway” (e.g., Nemiralisib and Umbralisib) or applying tyrosine kinase inhibitors (e.g., Fostamatinib) may be potential therapies for the treatment of MS.

Background: Migraine and multiple sclerosis (MS) are frequent clinical partners, but the mechanisms and treatments of the comorbidity of the two are still unclear. This study aimed to investigate the shared mechanisms and predict potential drugs of migraine and MS with a view to provide new clues and approaches for clinical management. Methods: So firstly, PRJEB40032 (migraine) from ENA and GSE21942 (MS) from GEO were analyzed for differentially expressed genes (DEGs). And then, gene clusters and hub genes for common DEGs were identified, as well as functional annotation and pathway enrichment analysis were performed for exploring the gene signatures and molecular mechanisms of the comorbidity. Further, hub genes and critical pathways were evaluated by the receiver operating characteristic curves (ROC) and previous studies. Finally, the drugs targeting hub genes and critical pathways were predicted, of which drugs targeting both hub genes and critical pathways were further screened. Results: 112 DEGs were identified to be related to the comorbidity of migraine and MS, of which 9 hub genes (IL1B,JUN, CXCL8, FOS, ICAM1, MMP9, EGR1,LCN2, MMP8) were of high diagnostic value for the comorbidity. Functional annotation and pathway enrichment analysis showed that inflammatory response regulation and reactive oxygen species metabolism played a major role, and multiple pathways such as IL17 signaling pathway were involved in the comorbidity. 5 hub genes and 17 critical pathways were further evaluated, with predicted 112 and 535 drugs, respectively, including aspirin (non-steroidal anti-inflammatory drugs (NSAIDs)), baclofen (gamma-aminobutyric acid (GABA) receptor agonist), and melatonin (antioxidant). Ultimately, 10 drugs targeting both hub genes and critical pathways were screened, mainly anti-inflammatory drugs, immunological agents and antineoplastic drugs, in which there were three IL-1β inhibitors with high potential research value for the treatments of the comorbidity. Conclusions: We found that inflammation and oxidative stress were closely related to the comorbidity of migraine and multiple sclerosis. We also predicted some drugs for drawing on from each other and the comorbidity, such as NSAIDs, GABA receptor agonists/analogs andIL-1β inhibitors.