In the present study, we conducted transcriptome analysis of B cell subpopulations. First, we found that expression of LINC00487 was upregulated in B cell subsets derived from patients with pSS. Further, LINC00487 expression significantly correlated with disease activity and was induced by IFNα stimulation. Next, using WGCNA, we identified several key networks and hub genes in the B cells of patients with pSS. Our findings deepen our understanding about the mechanism of pathogenesis of aberrant B cells in pSS.
IFN signalling is a central component of the pathogenesis of pSS [27]. While we found significant upregulation of IFN signalling in B cells of patients with pSS, to our knowledge, such differences among subsets have not been reported. Type 1 IFN signalling plays a crucial role in the development of autoreactive B cells in a mouse model of autoimmune disease [5]. Further, more immunological GO terms including type 1 IFN response were enriched in earlier maturation stages of B cells. Moreover, primary component analysis using gene sets of WGCNA and GC-B cells-related genes revealed that Bm1/naïve B cells of pSS were clearly distinguished from those of HC. These results suggest that molecular dysfunction, such as disruption of peripheral tolerance, might start at an early stage in the maturation of B cells. Indeed, the frequencies of naïve B cells expressing autoreactive antibodies are significantly increased in patients with pSS [28].
Interestingly, expression of the HLA class II gene was upregulated. GWAS studies of pSS found associations of HLA-DQA1 and HLA-DQB1 loci [6, 7]. Further, IFNα induces the expression of HLA-DQA1 [29]. In patients with pSS, HLA-DQA1 and HLA-DQB1 alleles are associated with higher concentrations of anti-SSA and SSB antibodies [30]. These findings suggest that aberrant interactions among IFN signalling and HLA class II genes may trigger the breakdown of B cell tolerance, leading to the development of pSS.
LINC00487 was upregulated in all B cell subsets of pSS and its expression significantly correlated with the disease activity scores of pSS and ISGs. Moreover, we found that IFNα was an upstream regulator of LINC00487 in B cells. The sequence of LINC00487, which belongs to the class of long intergenic non-coding RNAs and resides on human chromosome 2, is atypically long (> 40,000 bases). Although LINC00487 is one of the hub genes in the normal development of human B cells [31], many of its properties, including its function, are unexplained. Further, there is no ortholog or paralog of this gene in species other than humans that may provide clues to its function in human cells. However, according to AceView, one of three transcriptional variants derived from LINC00487 has high potential to encode a protein [32].
Four genomic locations are considered candidate enhancers of LINC00487 transcription. The targets of the regulators of LINC00487 overlap with those of other ISGs [33]. Moreover, referring to the public transcriptome database of microarray analyses of healthy humans, expression of LINC00487 is higher specifically in centroblasts and centrocytes of the germinal centre [34]. IFNα promotes the autoreactivity of B cells via germinal centre pathways [5]. Further, LINC00487 expression is upregulated in the subgroup of diffuse large B-cell lymphoma with molecular characteristics of germinal centre B cells, compared with other subgroups, and is associated with the efficacy of B cell depletion therapy [35]. Therefore, our study suggests that upregulation of LINC00487 expression in all B cell subsets may reflect or regulate the enrichment of a germinal centre-like reaction by IFNα from an early stage of B cell development, leading to B cell autoreactivity in patients with pSS. Thus, LINC00487 may serve as a predictive biomarker for B cell target therapy in autoimmune diseases. Indeed, we show here that the expression of LINC00487 was associated with higher IgG levels.
Gene co-expression analysis revealed an aberrant network in B cell subpopulations. The top significant upstream regulator of the grey module of pSS, which was associated with clinical disease activity score and enriched in the early stage of B cell development in pSS, was the gene encoding T-cell acute lymphocytic leukemia protein 1 (TAL1). B cell development is stringently controlled by stage-specific transcription factors. The transcription factor TAL1 regulates genes such as IKAROS family zinc finger 3 (IKZF3), which is one of hub genes in the grey module of pSS (Fig. 5C). IKZF3 is a lineage-specific transcription factor that is important in the regulation of B cell proliferation and development [36].
In the pre-GC B cells-associated module of pSS, SOX4 was identified as an upstream regulator and a hub gene. In mice, SOX4 regulates the differentiation of early-stage B cells by activating the expression of Rag1 and Rag2 [37]. Further, SOX4 contributes to the formation of ectopic lymphoid-like structures via promoting CXCL13, which is ligand of CXCR5 on naïve B cells and critical for migration into light zone of germinal centre undergoing somatic hypermutation, production from PD-1hiCXCR5−CD4+ T cells [38]. Additionally, in proteome analysis, CXCL13 positively correlates with the disease activity score and serum IgG levels of patients with pSS [16]. However, the role of SOX4 in mature B cells is unclear. Our data showed that the expression of SOX4 was significantly associated with AURKA and NFKB1 in B cell subpopulations of patients with pSS, and CD40 and MYC in those of HC, respectively. In the initiation of GC reaction, naïve B cells are activated by antigen within follicles. Then, activated B cells migrate to interfollicular region, where they interact with follicular helper T cells (Tfh) via CD40. After fully activation by Tfh, selected B cells enter the GC pathway to expand and accumulate mutations [39]. A mature GC is composed by two compartments, a dark zone (DZ) and a light zone (LZ) [40]. DZ B cells undergo rapid proliferation and affinity maturation. LZ B cells undergo class switch recombination, and selected B-cells in LZ can recirculate to the DZ for further rounds of division and affinity maturation, or differentiate into memory B-cells or plasma cells and exit the GC. AURKA is serine/threonine kinase which plays an essential role in mitosis [41], and its expression is highly increased in DZ B cells [40]. Additionally, in vivo study, AURKA inhibitor triggers mitotic arrest and apoptosis of B cell lymphoma, indicating AURKA has critical role in GC homeostasis [42]. In cancer-focused protein-protein interaction screens, AURKA and SOX4 are identified as partners [43], although further study is needed to explore the significant function in autoimmune diseases. NFKB signalling is activated by CD40-stimulation in LZ, and aberrant activation of NFKB signalling contributes to the GC lymphogenesis [44]. Previous silico analysis of human breast cancer also identified SOX4 as a activator of Phosphatidyl Inositol-3 kinases/Akt signalling, which is upstream of NFKB [45], supporting our results about association between SOX4 and NFKB1. Regarding CD40 and MYC, their expressions are upregulated in LZ B cells [40]. MYC regulates the expression of key regulators of cell cycle transit to coordinate cell growth and metabolism with cell division, including AURKA [42]. In addition, MYC+-B cells is required for GC formation and maintenance [46, 47]. Given that several studies have suggested that SOX4 function is context-dependent [48], SOX4 may be involved in GC response as important regulator in a complexed gene network of mature B cells, not only T cells.
Further, we identified miR-21 as an upstream regulator of the yellow module of pSS. Although miR-21 is upregulated in peripheral blood mononuclear cells of pSS [49], the present study is the first to indicate its involvement in pSS via B cell dysregulation. miR-21 regulates the immune response of memory T cells via induction of transcription networks, such as SOX4 [50], supporting our hypothesis that interactions between miR-21 and SOX4 play a critical role in B cell dysfunction in pSS.
The current study suffers from several limitations. First, patients in our cohort have low disease activity/severity. Because there were few patients with high disease activity before immunosuppressive treatment, it was difficult to include such patients in this study. Second, sample size was limited. To overcome limitation about small sample size, we validated by qPCR using another cohort, supporting results derived from microarray analysis. Nevertheless, our focus on B cell subpopulation using a multi-level approach employing analysis of DEGs and WGCNA identified significant genes and networks as novel players in the pathogenesis of pSS. To confirm our results, functional studies are required.