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Arvidsson G, Czarnewski P, Johansson A, Raine A, Imgenberg-Kreuz J, Nordlund J, Nordmark G, Syvänen A
Arthritis & rheumatology (Hoboken, N.J.) - (-) - [2023-08-23; online 2023-08-23]
B cells are important in the pathogenesis of primary Sjögren's syndrome (pSS). Patients positive for SSA/SSB autoantibodies are more prone to systemic disease manifestations and adverse outcomes. We aimed to determine the role of B cell composition, gene expression and B cell receptor (BCR) usage in pSS subgroups stratified for SSA/SSB antibodies. Over 230 000 B cells were isolated from peripheral blood of pSS patients (n = 6 SSA-, n = 8 SSA+ single positive and n = 10 SSA/SSB+ double positive) and four healthy controls, and processed for single cell RNA and VDJ sequencing. We show that SSA/SSB+ patients present the highest and lowest proportion of naïve and memory B cells respectively, and the highest upregulation of interferon-induced genes across all B cell subtypes. Differential usage of IGHV showed that IGHV1-69 and IGHV4-30-4 were more often used in all pSS subgroups compared with controls. Memory B cells from SSA/SSB+ patients displayed a higher proportion of cells with unmutated VDJ transcripts compared to other pSS patient groups and controls, indicating altered somatic hypermutation processes. Comparison with previous studies revealed heterogeneous clonotype pools, with little overlap in CDR3 sequences. Joint analysis using scRNA-seq and scVDJ-seq data allowed unsupervised stratification pSS patients, and identified novel parameters that correlated to disease manifestations and antibody status. We describe heterogeneity and molecular characteristics in B cells from pSS patients, providing clues to intrinsic differences in B cells that affect the phenotype and outcome, allowing stratification of pSS patients at improved resolution. This article is protected by copyright. All rights reserved.
Bioinformatics Long-term Support WABI [Collaborative]
Bioinformatics Support, Infrastructure and Training [Collaborative]
NGI Uppsala (SNP&SEQ Technology Platform)
National Genomics Infrastructure
PubMed 37610265
DOI 10.1002/art.42683
Crossref 10.1002/art.42683