Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated disease
Objective To elucidate crucial immune cell subsets and associated immunological pathways by stratifying patients with immune-mediated diseases (IMDs) using immunophenotyping and transcriptomic approaches.Methods We conducted flow cytometric and transcriptomic analyses in 23 immune cell subsets deriv...
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BMJ Publishing Group
2025-04-01
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| Series: | RMD Open |
| Online Access: | https://rmdopen.bmj.com/content/11/2/e005310.full |
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| author | Kazuhiko Yamamoto Mineto Ota Keishi Fujio Yasuo Nagafuchi Tomohisa Okamura Saeko Yamada Hirofumi Shoda Takahiro Itamiya Toshihiko Komai Shinji Izuka Kosuke Matsuki |
| author_facet | Kazuhiko Yamamoto Mineto Ota Keishi Fujio Yasuo Nagafuchi Tomohisa Okamura Saeko Yamada Hirofumi Shoda Takahiro Itamiya Toshihiko Komai Shinji Izuka Kosuke Matsuki |
| author_sort | Kazuhiko Yamamoto |
| collection | DOAJ |
| description | Objective To elucidate crucial immune cell subsets and associated immunological pathways by stratifying patients with immune-mediated diseases (IMDs) using immunophenotyping and transcriptomic approaches.Methods We conducted flow cytometric and transcriptomic analyses in 23 immune cell subsets derived from 235 patients with six IMDs, using our database, utilizing our database, ImmuNexUT. Patients were stratified based on immunophenotyping data. Subsequently, we examined clinical and transcriptomic differences among these stratified clusters.Results Patients with IMDs were stratified into two clusters based on their immunophenotypes. Cluster 1 was enriched with differentiated B cells, including unswitched memory B cells (USM B), switched memory B cells, double-negative B cells and plasmablasts, while cluster 2 was enriched with naïve B cells. Higher disease activity in rheumatoid arthritis and decreased respiratory functions in systemic sclerosis were observed in cluster 1, whereas the disease activity of systemic lupus erythematosus was higher in cluster 2. Numerous differentially expressed genes were detected in USM B. Cluster 1 was associated with glycosylation processes in USM B and elevated B cell-activating factor signalling from myeloid cells in B cells, while cluster 2 exhibited higher B-cell receptor signalling in USM B. Patients in cluster 2, which had an elevated age-associated B-cell signature, exhibited more frequent flares, suggesting that an increased proportion of naïve B cells with this signature is associated with poor prognosis.Conclusion Immunophenotyping-based clusters and transcriptome-based states revealed quantitative and qualitative differences in B cells. To predict IMD prognosis, assessing both the quantity and quality of naïve B cells may be crucial. |
| format | Article |
| id | doaj-art-9cfccf4c02044c15b0ddddb5679c920b |
| institution | OA Journals |
| issn | 2056-5933 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | RMD Open |
| spelling | doaj-art-9cfccf4c02044c15b0ddddb5679c920b2025-08-20T02:16:29ZengBMJ Publishing GroupRMD Open2056-59332025-04-0111210.1136/rmdopen-2024-005310Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated diseaseKazuhiko Yamamoto0Mineto Ota1Keishi Fujio2Yasuo Nagafuchi3Tomohisa Okamura4Saeko Yamada5Hirofumi Shoda6Takahiro Itamiya7Toshihiko Komai8Shinji Izuka9Kosuke Matsuki10Center for Integrative Medical Sciences, the Institute of Physical and Chemical Research (RIKEN), Yokohama, Kanagawa, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanResearch Division, Chugai Pharmaceutical Co., Ltd, Yokohama, Kanagawa, JapanObjective To elucidate crucial immune cell subsets and associated immunological pathways by stratifying patients with immune-mediated diseases (IMDs) using immunophenotyping and transcriptomic approaches.Methods We conducted flow cytometric and transcriptomic analyses in 23 immune cell subsets derived from 235 patients with six IMDs, using our database, utilizing our database, ImmuNexUT. Patients were stratified based on immunophenotyping data. Subsequently, we examined clinical and transcriptomic differences among these stratified clusters.Results Patients with IMDs were stratified into two clusters based on their immunophenotypes. Cluster 1 was enriched with differentiated B cells, including unswitched memory B cells (USM B), switched memory B cells, double-negative B cells and plasmablasts, while cluster 2 was enriched with naïve B cells. Higher disease activity in rheumatoid arthritis and decreased respiratory functions in systemic sclerosis were observed in cluster 1, whereas the disease activity of systemic lupus erythematosus was higher in cluster 2. Numerous differentially expressed genes were detected in USM B. Cluster 1 was associated with glycosylation processes in USM B and elevated B cell-activating factor signalling from myeloid cells in B cells, while cluster 2 exhibited higher B-cell receptor signalling in USM B. Patients in cluster 2, which had an elevated age-associated B-cell signature, exhibited more frequent flares, suggesting that an increased proportion of naïve B cells with this signature is associated with poor prognosis.Conclusion Immunophenotyping-based clusters and transcriptome-based states revealed quantitative and qualitative differences in B cells. To predict IMD prognosis, assessing both the quantity and quality of naïve B cells may be crucial.https://rmdopen.bmj.com/content/11/2/e005310.full |
| spellingShingle | Kazuhiko Yamamoto Mineto Ota Keishi Fujio Yasuo Nagafuchi Tomohisa Okamura Saeko Yamada Hirofumi Shoda Takahiro Itamiya Toshihiko Komai Shinji Izuka Kosuke Matsuki Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated disease RMD Open |
| title | Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated disease |
| title_full | Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated disease |
| title_fullStr | Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated disease |
| title_full_unstemmed | Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated disease |
| title_short | Integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of B cells across immune-mediated disease |
| title_sort | integration of transcriptome and immunophenotyping data highlights differences in the pathogenetic kinetics of b cells across immune mediated disease |
| url | https://rmdopen.bmj.com/content/11/2/e005310.full |
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