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 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.