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Objective.To delineate clinical characteristics of patients with spondyloarthritis (SpA) in Japan in comparison to other areas of the world.Methods.Using the ASAS-COMOSPA (Assessment of Spondyloarthritis international Society–COMOrbidities in SPondyloArthritis) data, an international cross-sectional observational study of patients with SpA, we analyzed information on demographics, disease characteristics, comorbidities, and risk factors. Patients were classified by region: Japan, other Asian countries (China, Singapore, South Korea, Taiwan), and non-Asian countries (Europe, the Americas, Africa). Patient characteristics, including diagnosis and treatment, were compared.Results.Among 3984 patients included in the study, 161 were from centers in Japan, 933 from other Asian countries, and 2890 from other regions. Of patients with SpA in Japan, 42 (26.1%) had peripheral SpA, substantially more than in other countries. This trend was explained by the predominance of psoriatic arthritis (PsA) among Japanese patients with SpA. In contrast to the relatively low number in Japan, 54% of patients from other Asian countries had pure axial SpA (axSpA) without peripheral features. HLA-B27 testing, considered an integral part of the classification of axSpA, was performed in only 63.6% of Japanese patients with axSpA. More than half of Japanese patients with axSpA were classified using imaging criteria.Conclusion.In our study, there was a more substantial number of peripheral SpA cases observed in Japan compared to other parts of Asia and other regions of the world. Aside from ethnic differences, increasing recognition of PsA in Japan, as well as a potential underdiagnosis of axSpA due to the insufficient use of HLA-B27 testing, may partly explain regional discrepancies.

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Background Behçet’s syndrome (BS) is an immune-mediated disease characterized by recurrent oral ulcers, genital ulcers, uveitis, and skin symptoms. HLA-B51, as well as other genetic polymorphisms, has been reported to be associated with BS; however, the pathogenesis of BS and its relationship to genetic risk factors still remain unclear. To address these points, we performed immunophenotyping and transcriptome analysis of immune cells from BS patients and healthy donors. Methods ImmuNexUT is a comprehensive database consisting of RNA sequencing data and eQTL database of immune cell subsets from patients with immune-mediated diseases and healthy donors, and flow cytometry data and transcriptome data from 23 BS patients and 28 healthy donors from the ImmuNexUT study were utilized for this study. Differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify genes associated with BS and clinical features of BS. eQTL database was used to assess the relationship between genetic risk factors of BS with those genes. Results The frequency of Th17 cells was increased in BS patients, and transcriptome analysis of Th17 cells suggested the activation of the NFκB pathway in Th17 cells of BS patients. Next, WGCNA was used to group genes into modules with similar expression patterns in each subset. Modules of antigen-presenting cells were associated with BS, and pathway analysis suggested the activation of antigen-presenting cells of BS patients. Further examination of genes in BS-associated modules indicated that the expression of YBX3, a member of a plasmacytoid dendritic cell (pDC) gene module associated with BS, is influenced by a BS risk polymorphism, rs2617170, in pDCs, suggesting that YBX3 may be a key molecule connecting genetic risk factors of BS with disease pathogenesis. Furthermore, pathway analysis of modules associated with HLA-B51 indicated that the association of IL-17-associated pathways in memory CD8+ T cells with HLA-B51; therefore, IL-17-producing CD8+ T cells, Tc17 cells, may play a critical role in BS. Conclusions Various cells including CD4+ T cells, CD8+ T cells, and antigen-presenting cells are important in the pathogenesis of BS. Tc17 cells and YBX3 may be potential therapeutic targets in BS.

Various immune cell types, including monocytes, macrophages, and adaptive immune T and B cells, play major roles in inflammation in systemic autoimmune diseases. However, the precise contribution of these cells to autoimmunity remains elusive. Transcriptome analysis has added a new dimension to biology and medicine. It enables us to observe the dynamics of gene expression in different cell types in patients with diverse diseases as well as in healthy individuals, which cannot be achieved with genomic information alone. In this review, we summarize how transcriptome analysis has improved our understanding of the pathological roles of immune cells in autoimmune diseases with a focus on the ImmuNexUT database we reported. We will also discuss the common experimental and analytical design of transcriptome analyses. Recently, single-cell RNA-seq analysis has provided atlases of infiltrating immune cells, such as pro-inflammatory monocytes and macrophages, peripheral helper T cells, and age or autoimmune-associated B cells in various autoimmune disease lesions. With the integration of genomic data, expression quantitative trait locus (eQTL) analysis can help identify candidate causal genes and immune cells. Finally, we also mention how the information obtained from these analyses can be used practically to predict patient prognosis.

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