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Objective: Human Leukocyte Antigen (HLA) alleles regulate susceptibility to rheumatoid arthritis (RA) and immune-mediated diseases. This study aims to elucidate the impact of HLA alleles to T cell subsets., Methods: We performed genome-wide and HLA allele association analysis for T cell receptor (TCR) beta chain repertoire in 13 purified T cell subsets from the ImmuNexUT database, consisting of 407 donors with ten immune-mediated diseases and healthy controls., Results: HLA class II alleles were associated with TRBV gene usage and the public clones of CD4 T cells, while HLA class I alleles were associated with CD8 T cells. RA-risk and immune-mediated diseases-risk HLA alleles were associated with TRBV gene usage of naive and effector CD4 T cell subsets and public clones accumulating in Th17. Clonal diversity was independent of HLA alleles and was correlated with transcriptome changes that reflect TCR signaling., Conclusion: This study revealed in vivo evidence that both HLA alleles and environmental factors shape naive and effector TCR repertoires in RA and immune-mediated diseases patients., Competing Interests: Declaration of competing interest Y.N., M. Ota, and T.O. belong to the Social Cooperation Program, Department of Functional Genomics and Immunological Diseases, supported by Chugai Pharmaceutical. K.F.s receives consulting honoraria and research support from Chugai Pharmaceutical. All the other authors declared no conflicts of interest., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objective: Previous gene expression analyses seeking genes specific to antineutrophil cytoplasmic antibody-associated vasculitis (AAV) have been limited due to crude cell separation and the use of microarrays. This study aims to identify AAV-specific gene expression profiles in a way that overcomes those limitations., Methods: Blood samples were collected from 26 AAV patients and 28 healthy controls (HCs). Neutrophils were isolated by negative selection, whereas 19 subsets of peripheral blood mononuclear cells were sorted by fluorescence assisted cell sorting. RNA-sequencing was then conducted for each sample, and iterative weighted gene correlation network analysis (iterativeWGCNA) and random forest were consecutively applied to identify the most influential gene module in distinguishing AAV from HCs. Correlations of the identified module with clinical parameters were evaluated, and the biological role was assessed with hub gene identification and pathway analysis. Particularly, the module's association with neutrophil extracellular trap formation, NETosis, was analyzed. Finally, the module's overlap with GWAS-identified autoimmune disease genes (GADGs) was assessed for validation., Results: A neutrophil module (Neu_M20) was ranked top in the random forest analysis among 255 modules created by iterativeWGCNA. Neu_M20 correlated with disease activity and neutrophil counts but not with the presence of antineutrophil cytoplasmic antibody. The module comprised pro-inflammatory genes, including those related to NETosis, supported by experimental evidence. The genes in the module significantly overlapped GADGs., Conclusion: We identified the distinct group of pro-inflammatory genes in neutrophils, which characterize AAV. Further investigations are warranted to confirm our findings as they could serve as novel therapeutic targets., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: Immunological disturbances have been reported in systemic sclerosis (SSc). This study assessed the transcriptome disturbances in immune cell subsets in SSc and characterized a disease-related gene network module and immune cell cluster at single cell resolution., Methods: Twenty-one Japanese SSc patients were enrolled and compared with 13 age- and sex-matched healthy controls (HC). Nineteen peripheral blood immune cell subsets were sorted by flow cytometry and bulk RNA-seq analysis was performed for each. Differential expression and pathway analyses were conducted. Iterative weighted gene correlation network analysis (iWGCNA) of each subset revealed clustered co-expressed gene network modules. Random forest analysis prioritized a disease-related gene module. Single cell RNA-seq analysis of 878 monocytes was integrated with bulk RNA-seq analysis and with a public database for single cell RNA-seq analysis of SSc patients., Results: Inflammatory pathway genes were differentially expressed in widespread immune cell subsets of SSc. An inflammatory gene module from CD16 + monocytes, which included KLF10, PLAUR, JUNB and JUND, showed the greatest discrimination between SSc and HC. One of the clusters of SSc monocytes identified by single-cell RNA-seq analysis characteristically expressed these inflammatory co-expressed genes and was similar to lung infiltrating FCN1 hi monocytes expressing IL1B., Conclusions: Our integrated analysis of bulk and single cell RNA-seq analysis identified an inflammatory gene module and a cluster of monocytes that are relevant to SSc pathophysiology. They could serve as candidate novel therapeutic targets in SSc., (Copyright © 2020 Elsevier Ltd. All rights reserved.)