ArticleFrontiers in immunology2021
Peripheral B-Cell Immunophenotyping Identifies Heterogeneity in IgG4-Related Disease.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Pathogenesis exploration of lgG4-related disease: From the traditional central dogma and its remodeling perspective.Chinese medical journal · 2026Review
- New Developments in the Treatment of IgG4-Related Disease: A Comprehensive Clinical Approach.Journal of clinical medicine · 2025Review
- Expression of USP25 associates with fibrosis, inflammation and metabolism changes in IgG4-related disease.Nature communications · 2024Article
- IgG4 autoantibodies and autoantigens in the context of IgG4-autoimmune disease and IgG4-related disease.Frontiers in immunology · 2024Review
- Immune phenotype changes in IgG4-related disease: CD161 + Treg and Foxp3 + Treg.Clinical rheumatology · 2023Article
- The spectrum of B cells in the pathogenesis, diagnosis and therapeutic applications of immunoglobulin G4-related disease.Clinical & translational immunology · 2023Review
- Dawn of Precision Medicine in Psoriatic Arthritis.Frontiers in medicine · 2022Review
- Single-Cell Sequencing of Immune Cell Heterogeneity in IgG4-Related Disease.Frontiers in immunology · 2022Article
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Authors and funding
18 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To elucidate heterogeneity of IgG4-related disease (IgG4-RD) based on B cell immunophenotyping. Methods: Immunophenotyping of 4 B-cell subsets in peripheral blood from patients with active IgG4-RD (aIgG4-RD, n=105) was performed using flow cytometry to get preliminary B-cell heterogeneity spectrum. Then 10 B-cell subsets were characterized in aIgG4-RD (n = 49), remissive IgG4-RD (rIgG4-RD, n = 49), and healthy controls (HCs, n = 47), followed by principal components analysis (PCA) and cluster analysis to distinguish B-cell immunophenotypes and classify IgG4-RD patients into subgroups. Results: Cluster analysis identified two endotypes in 105 aIgG4-RD patients based on 4 B-cell subsets: Group1 with higher Breg and naive B cells (n = 48), and Group2 with higher plasmablasts and memory B cells (MBCs) (n = 57). PCA indicated that aIgG4-RD consisted of plasmablast-naive B cell and MBCs-Breg axes abnormalities. There was a negative relationship between naive B cells and disease activity. Both plasmablasts and MBCs were positively associated with serological biomarkers. Cluster analysis stratified aIgG4-RD patients into 3 subgroups based on 10 B-cell subsets: subgroup1 with low MBCs and normal Breg, subgroup2 with high MBCs and low Breg, and subgroup3 with high plasmablasts and low naive B cells. Patients in subroup2 and subgroup3 were more likely to be resistant to treatment. Conclusion: Patients with aIgG4-RD can be divided into 3 subgroups based on B cell heterogeneity. The B cell immunophenotyping could help elucidate the pathogenesis of IgG4-RD, identify patients with potential refractory IgG4-RD, and provide important information for the development of new therapies.
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