免疫系统
免疫学
人口
医学
疾病
抗体
免疫失调
效应器
生物
同型
等离子体电池
美罗华
T细胞
促炎细胞因子
电池类型
蛋白质组学
抗原
基因表达谱
B细胞
CD8型
B细胞激活因子
生物标志物
细胞
自身免疫
受体
作者
Hyo Jae Kim,Min-Gang Kim,Seongryong Kim,Mi Hyeon Kim,Seon Uk Kim,Hee Sung Kwon,Ban S,Hae Rim Kang,Su Young Heo,Sung Ik Cho,Jeong Seok Lee,Jong-Eun Park,Eun Young Lee
标识
DOI:10.1016/j.ard.2026.05.024
摘要
Objectives IgG4-related disease (IgG4-RD) is a systemic fibroinflammatory disorder characterised by tissue infiltration of IgG4 + plasma cells, yet the precise roles of B cells remain unclear. This study aimed to characterise the longitudinal immune dynamics in IgG4-RD during B-cell depletion therapy to identify pathogenic cell subsets and specific biomarkers associated with relapse. Methods We performed a longitudinal multiomics analysis on 119 peripheral blood samples from patients with IgG4-RD undergoing rituximab treatment, spanning active, remission, and relapse phases. Integrated single-cell transcriptomics, B-cell receptor (BCR) sequencing, and serum proteomics were performed on matched blood and tissue samples from submandibular gland and lymph nodes, with Sjögren's syndrome and healthy individuals as controls. Results We identified a previously unrecognised, disease-specific IgG4 + plasma cell subset characterised by aberrant expression of the neuropeptide NMU and highly skewed IGHV1-69 usage. Circulating follicular helper T cells (CD4 + Tfh) displayed signatures consistent with chronic antigen stimulation and type 2 immunity. Furthermore, markedly expanded double-negative T cells (dnT) highly expressed IL10 , suggesting their involvement in immune regulation and isotype class switching. Longitudinal analysis following B-cell depletion emphasised the reconstitution dynamics of pathogenic plasma cells, furthermore highlighting the concurrent shifts in CD4 + Tfh and dnT that mirrored disease remission and relapse, and underscored the amelioration of proinflammatory immune profiles. Conclusions NMU -expressing IGHV1-69 + plasma cells represent a pathogenic effector population driving IgG4-RD recurrence. These findings establish a mechanistic framework for B-cell depletion and identify specific cellular and molecular biomarkers to improve disease monitoring and relapse prediction in clinical practice.
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