These findings suggest that MR16-1 can decrease mechanical allodynia in EAE mice through inhibition of microglial activation and proliferation in the spinal cord.

Objectives. Large vessel vasculitis (LVV) is characterised by a high relapse rate. Because accurate assessment of the LVV disease status can be difficult, an accurate prognostic marker for initial risk stratification is required. We conducted a comprehensive longitudinal investigation of next-generation RNA-sequencing data for patients with LVV to explore useful biomarkers associated with clinical characteristics. Methods. Key molecular pathways relevant to LVV pathogenesis were identified by examining the whole blood RNA from patients with LVV and healthy controls (HCs). The data were examined by pathway analysis and weighted gene correlation network analysis (WGCNA) to identify functional gene sets that were differentially expressed between LVV patients and HCs, and associated with clinical features. We then compared the expression of the selected genes during week 0, week 6, remission and relapse. Results. The whole-transcriptome gene expression data for 108 samples obtained from LVV patients (n = 27) and HCs (n = 12) were compared. The pathway analysis and WGCNA revealed that molecular pathway related to interleukin (IL)-1 was significantly upregulated in LVV patients compared with HCs, which correlated with the positron emission tomography vascular activity score, a disease-extent score based on the distribution of affected arteries. Further analysis revealed that the expression levels of genes in the IL-1 signalling pathway remained high after conventional treatment and were associated with disease relapse. Conclusion. Upregulation of the IL-1 signalling pathway was a characteristic of LVV patients and was associated with the extent of disease and a poor prognosis.

No abstract

No abstract

Background Giant cell arteritis (GCA) is a primary large-vessel vasculitis (LVV) of unknown origin. Its management is a challenge due to the late onset of disease symptoms and frequent relapse; therefore, clarifying the pathophysiology of GCA is essential to improving treatment. This study aimed to identify the transition of molecular signatures in immune cells relevant to GCA pathogenesis by analyzing longitudinal transcriptome data in patients. Methods We analyzed the whole blood transcriptome of treatment-naive patients with GCA, patients with Takayasu arteritis (TAK), age-matched, old healthy controls (HCs), and young HCs. Characteristic genes for GCA were identified, and the longitudinal transition of those genes was analyzed using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). Results Repeated measures analysis of variance revealed 739 differentially expressed genes among all patients and HCs. Of the 739 genes, 15 were characteristically upregulated and 36 were downregulated in patients with GCA compared to those with TAK and HCs. Pathway enrichment analysis showed that downregulated genes in GCA were associated with B cell activation. CIBERSORT analysis revealed that upregulation of “M0-macrophages” and downregulation of B cells were characteristic of GCA. Upregulation of “M0-macrophages” reflects the activation of monocytes in GCA toward M0-like phenotypes, which persisted under 6 weeks of treatment. Combined treatment with prednisolone and an interleukin-6 receptor antagonist normalized molecular profiles more efficiently than prednisolone monotherapy. Conclusions Gene signatures of monocyte activation and B cell inactivation were characteristic of GCA and associated with treatment response.