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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.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with heterogeneous clinical manifestations and the pathogenesis of SLE is still unclear. Various omics results have been reported for SLE, but the molecular hallmarks of SLE, especially in patients with different disease activity, using an integrated multi-omics approach have not been fully investigated. Here, we collected blood samples from 10 healthy controls (HCs) and 40 SLE patients with different clinical activity including inactive (IA), low activity (LA), and high activity (HA). Using an integrative analysis of proteomic, metabolomic and lipidomic profiles, we report the multi-omics landscape for SLE. The molecular changes suggest that both the complement system and the inflammatory response were activated in SLEs and were associated with disease activity. Additionally, activation of the immunoglobulin mediated immune response were observed in the LA stage of the disease, however this immune response was suppressed slightly in the HA stage. Finally, an imbalance in lipid metabolism, especially in sphingolipid metabolism, accompanied with dysregulated apolipoproteins were observed to contribute to the disease activity of SLE. The multi-omics data presented in this study and the characterization of peripheral blood from SLE patients may thus help provide important clues regarding the pathogenesis of SLE.

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.

The incidence of Aspergillus fumigatus infection and the rate of resistance to antifungal drugs have sharply increased in recent years. LL37 has been reported as a host defense peptide with broad-spectrum antibacterial activities. However, the role of LL37 during A. fumigatus infection remains unclear. Here, we examined the interaction between LL37 and A. fumigatus and found that synthetic LL37 could directly bind to the surface of A. fumigatus, disrupting the integrity of the cell wall in vitro. LL37 inhibited mycelial growth in a concentration-dependent manner, rather than fungicidal effect even at high concentration (e.g., 20 μM). Interestingly, low concentrations of LL37 (e.g., 4 μM) significantly attenuated mycelial adhesion and prevented the invasion and destruction of epithelial cells. Following LL37 treatment, the levels of proinflammatory cytokines released by A. fumigatus-stimulated macrophages decreased significantly, accompanied by downregulation of M1 type markers. In a mouse model of pulmonary A. fumigatus infection, LL37-treated mice showed lower amounts of fungi load, moderate pathological damage, and reduced proinflammatory cytokines. Further, LL37 transgenic mice (LL37+/+) were examined to investigate the effects of endogenous LL37 in an A. fumigatus infection model and showed lower susceptibility to A. fumigatus infection in comparison with wild-type mice. In addition, LL37 also played a protective role in an immunosuppressed mouse model of A. fumigatus infection. Thus, LL37 inhibits A. fumigatus infection via directly binding to mycelia and reducing excessive inflammation. LL37 or its analogs may therefore constitute potential drug components for A. fumigatus infection.