ARID5B is a negative modulator of IL-6 production in rheumatoid arthritis synovial fibroblasts.

Recent single-cell RNA-sequencing analysis of rheumatoid arthritis (RA) synovial tissues revealed the heterogeneity of RA synovial fibroblasts (SFs) with distinct functions such as high IL-6 production. The molecular mechanisms responsible for high IL-6 production will become a promising drug target of RASFs to treat RA. In this study, we performed siRNA screening of 65 transcription factors (TFs) differentially expressed among RASF subsets to identify TFs involved in IL-6 production. The siRNA screening identified 7 TFs including ARID5B, a RA risk gene, that affected IL-6 production. Both long and short isoforms of ARID5B were expressed and negatively regulated by TNF-α in RASFs. The siRNA knockdown and lentiviral overexpression of long and short isoforms of ARID5B revealed that the long isoform suppressed IL-6 production stimulated with TNF-α. eQTL analysis using 58 SFs demonstrated that RA risk allele, rs10821944, in intron 4 of the ARID5B gene had a trend of eQTL effects to the expression of long isoform of ARID5B in SFs treated with TNF-α. ARID5B was found to be a negative modulator of IL-6 production in RASFs. The RA risk allele of ARID5B intron may cause high IL-6 production, suggesting that ARID5B will become a promising drug target to treat RA.

Machine learning-driven immunophenotypic stratification of mixed connective tissue disease corroborating the clinical heterogeneity.

OBJECTIVES: To stratify patients with mixed connective tissue disease (MCTD) based on their immunophenotype. METHODS: We analyzed the immunophenotype and transcriptome of 24 immune cell subsets from patients with MCTD, systemic lupus erythematosus (SLE), idiopathic inflammatory myopathy (IIM), and systemic sclerosis (SSc) from our functional genome database, ImmuNexUT (https://www.immunexut.org/). MCTD patients were stratified by employing machine learning models including Random Forest, trained by immunophenotyping data from SLE, IIM, and SSc patients. Transcriptomes were analyzed with gene set variation analysis (GSVA) and clinical features of MCTD subgroups were compared. RESULTS: This study included 215 patients, including 22 patients with MCTD. Machine learning models, constructed to classify SLE, IIM, and SSc patients based on immunophenotyping, were applied to MCTD patients, resulting in 16 classified as SLE-immunophenotype and 6 as non-SLE-immunophenotype. Among MCTD patients, patients with the SLE-immunophenotype had higher proportions of Th1 cells [2.85% (interquartile range (IQR) 1.54-3.91) vs 1.33% (IQR 0.99-1.74) p= 0.027] and plasmablasts [6.35% (IQR 4.17-17.49) vs 2.00% (IQR 1.20-2.80) p= 0.010]. Notably, the number of SLE-related symptoms was higher in patients with the SLE-immunophenotype [2.0 (IQR 1.0-2.0) vs 1.0 (IQR1.0-1.0) p= 0.038]. Moreover, GSVA scores of interferon-α and -γ responses were significantly higher in patients with the SLE-immunophenotype in central memory CD8+ T cells, while hedgehog signalling was higher in non-SLE-immunophenotype patients in 5 cell subsets. CONCLUSION: This study describes the stratification of MCTD patients based on immunophenotyping, suggesting the presence of distinct immunological processes behind the clinical subtypes of MCTD.

B cell receptor repertoire abnormalities in autoimmune disease.

B cells play a crucial role in the immune response and contribute to various autoimmune diseases. Recent studies have revealed abnormalities in the B cell receptor (BCR) repertoire of patients with autoimmune diseases, with distinct features observed among different diseases and B cell subsets. Classically, BCR repertoire was used as an identifier of distinct antigen-specific clonotypes, but the recent advancement of analyzing large-scale repertoire has enabled us to use it as a tool for characterizing cellular biology. In this review, we provide an overview of the BCR repertoire in autoimmune diseases incorporating insights from our latest research findings. In systemic lupus erythematosus (SLE), we observed a significant skew in the usage of VDJ genes, particularly in CD27+IgD+ unswitched memory B cells and plasmablasts. Notably, autoreactive clones within unswitched memory B cells were found to be increased and strongly associated with disease activity, underscoring the clinical significance of this subset. Similarly, various abnormalities in the BCR repertoire have been reported in other autoimmune diseases such as rheumatoid arthritis. Thus, BCR repertoire analysis holds potential for enhancing our understanding of the underlying mechanisms involved in autoimmune diseases. Moreover, it has the potential to predict treatment effects and identify therapeutic targets in autoimmune diseases.

Age-associated CD4+ T cells with B cell-promoting functions are regulated by ZEB2 in autoimmunity.

Aging is a significant risk factor for autoimmunity, and many autoimmune diseases tend to onset during adulthood. We conducted an extensive analysis of CD4+ T cell subsets from 354 patients with autoimmune disease and healthy controls via flow cytometry and bulk RNA sequencing. As a result, we identified a distinct CXCR3midCD4+ effector memory T cell subset that expands with age, which we designated "age-associated T helper (THA) cells." THA cells exhibited both a cytotoxic phenotype and B cell helper functions, and these features were regulated by the transcription factor ZEB2. Consistent with the highly skewed T cell receptor usage of THA cells, gene expression in THA cells from patients with systemic lupus erythematosus reflected disease activity and was affected by treatment with a calcineurin inhibitor. Moreover, analysis of single-cell RNA sequencing data revealed that THA cells infiltrate damaged organs in patients with autoimmune diseases. Together, our characterization of THA cells may facilitate improved understanding of the relationship between aging and autoimmune diseases.

Base-editing mutagenesis maps alleles to tune human T cell functions.

CRISPR-enabled screening is a powerful tool for the discovery of genes that control T cell function and has nominated candidate targets for immunotherapies1-6. However, new approaches are required to probe specific nucleotide sequences within key genes. Systematic mutagenesis in primary human T cells could reveal alleles that tune specific phenotypes. DNA base editors are powerful tools for introducing targeted mutations with high efficiency7,8. Here we develop a large-scale base-editing mutagenesis platform with the goal of pinpointing nucleotides that encode amino acid residues that tune primary human T cell activation responses. We generated a library of around 117,000 single guide RNA molecules targeting base editors to protein-coding sites across 385 genes implicated in T cell function and systematically identified protein domains and specific amino acid residues that regulate T cell activation and cytokine production. We found a broad spectrum of alleles with variants encoding critical residues in proteins including PIK3CD, VAV1, LCP2, PLCG1 and DGKZ, including both gain-of-function and loss-of-function mutations. We validated the functional effects of many alleles and further demonstrated that base-editing hits could positively and negatively tune T cell cytotoxic function. Finally, higher-resolution screening using a base editor with relaxed protospacer-adjacent motif requirements9 (NG versus NGG) revealed specific structural domains and protein-protein interaction sites that can be targeted to tune T cell functions. Base-editing screens in primary immune cells thus provide biochemical insights with the potential to accelerate immunotherapy design.

Gene regulatory network inference from CRISPR perturbations in primary CD4+ T cells elucidates the genomic basis of immune disease.

The effects of genetic variation on complex traits act mainly through changes in gene regulation. Although many genetic variants have been linked to target genes in cis, the trans-regulatory cascade mediating their effects remains largely uncharacterized. Mapping trans-regulators based on natural genetic variation, including eQTL mapping, has been challenging due to small effects. Experimental perturbation approaches offer a complementary and powerful approach to mapping trans-regulators. We used CRISPR knockouts of 84 genes in primary CD4+ T cells to perturb an immune cell gene network, targeting both inborn error of immunity (IEI) disease transcription factors (TFs) and background TFs matched in constraint and expression level, but without a known immune disease association. We developed a novel Bayesian structure learning method called Linear Latent Causal Bayes (LLCB) to estimate the gene regulatory network from perturbation data and observed 211 directed edges among the genes which could not be detected in existing CD4+ trans-eQTL data. We used LLCB to characterize the differences between the IEI and background TFs, finding that the gene groups were highly interconnected, but that IEI TFs were much more likely to regulate immune cell specific pathways and immune GWAS genes. We further characterized nine coherent gene programs based on downstream effects of the TFs and linked these modules to regulation of GWAS genes, finding that canonical JAK-STAT family members are regulated by KMT2A, a global epigenetic regulator. These analyses reveal the trans-regulatory cascade from upstream epigenetic regulator to intermediate TFs to downstream effector cytokines and elucidate the logic linking immune GWAS genes to key signaling pathways.

Carriers of HLA-DRB1*04:05 have a better clinical response to abatacept in rheumatoid arthritis.

HLA-DRB1 shared epitope risk alleles are the strongest genetic risk factors for rheumatoid arthritis (RA) and potential biomarkers for treatment response to biological disease-modifying antirheumatic drugs (bDMARDs). This study aimed to investigate the association between treatment response and individual HLA-DRB1 alleles in RA patients receiving different bDMARDs. We recruited 106 patients with active RA who had started abatacept, tocilizumab, or TNF inhibitors as a first-line bDMARDs. We examined the relationship between Simplified Disease Activity Index (SDAI) improvement at 3 months and HLA-DRB1 allele carriage. The results revealed that the HLA-DRB1*04:05 allele, a shared-epitope allele, was significantly associated with better SDAI improvement only after abatacept treatment (SDAI improvement 28.5% without the allele vs 59.8% with allele, p = 0.003). However, no significant association was found with other treatments. Both multivariate linear regression and mediation analysis confirmed that the HLA-DRB1*04:05 allele was independently associated with abatacept treatment response, regardless of anti-CCP antibody titers. The study concluded that in patients with RA receiving their first-line bDMARD treatment, carrying the HLA-DRB1*04:05 allele was associated with better SDAI improvement specifically in abatacept-treated patients. These disease-risk HLA alleles have the potential to serve as genomic biomarkers for predicting treatment response with co-stimulation blockage therapy.

CRISPR screens decode cancer cell pathways that trigger γδ T cell detection.

γδ T cells are potent anticancer effectors with the potential to target tumours broadly, independent of patient-specific neoantigens or human leukocyte antigen background1-5. γδ T cells can sense conserved cell stress signals prevalent in transformed cells2,3, although the mechanisms behind the targeting of stressed target cells remain poorly characterized. Vγ9Vδ2 T cells-the most abundant subset of human γδ T cells4-recognize a protein complex containing butyrophilin 2A1 (BTN2A1) and BTN3A1 (refs. 6-8), a widely expressed cell surface protein that is activated by phosphoantigens abundantly produced by tumour cells. Here we combined genome-wide CRISPR screens in target cancer cells to identify pathways that regulate γδ T cell killing and BTN3A cell surface expression. The screens showed previously unappreciated multilayered regulation of BTN3A abundance on the cell surface and triggering of γδ T cells through transcription, post-translational modifications and membrane trafficking. In addition, diverse genetic perturbations and inhibitors disrupting metabolic pathways in the cancer cells, particularly ATP-producing processes, were found to alter BTN3A levels. This induction of both BTN3A and BTN2A1 during metabolic crises is dependent on AMP-activated protein kinase (AMPK). Finally, small-molecule activation of AMPK in a cell line model and in patient-derived tumour organoids led to increased expression of the BTN2A1-BTN3A complex and increased Vγ9Vδ2 T cell receptor-mediated killing. This AMPK-dependent mechanism of metabolic stress-induced ligand upregulation deepens our understanding of γδ T cell stress surveillance and suggests new avenues available to enhance γδ T cell anticancer activity.

Multimodal repertoire analysis unveils B cell biology in immune-mediated diseases.

OBJECTIVES: Despite the involvement of B cells in the pathogenesis of immune-mediated diseases (IMDs), biological mechanisms underlying their function are scarcely understood. To overcome this gap, here we constructed and investigated a large-scale repertoire catalogue of five B cell subsets of patients with IMDs. METHODS: We mapped B cell receptor regions from RNA sequencing data of sorted B cell subsets. Our dataset consisted of 595 donors under IMDs and health. We characterised the repertoire features from various aspects, including their association with immune cell transcriptomes and clinical features and their response to belimumab treatment. RESULTS: Heavy-chain complementarity-determining region 3 (CDR-H3) length among naïve B cells was shortened among autoimmune diseases. Strong negative correlation between interferon signature strength and CDR-H3 length was observed in naïve B cells and suggested the role for interferon in premature B cell development. VDJ gene usage was skewed especially in plasmablasts and unswitched-memory B cells of patients with systemic lupus erythematosus (SLE). We developed a scoring system to quantify this skewing, and it positively correlated with peripheral helper T cell transcriptomic signatures and negatively correlated with the amount of somatic hyper mutations in plasmablasts, suggesting the association of extrafollicular pathway. Further, this skewing led to high usage of IGHV4-34 gene with 9G4 idiotypes in unswitched-memory B cells, which showed a prominent positive correlation with disease activity in SLE. Gene usage skewing in unswitched-memory B cells was ameliorated after belimumab treatment. CONCLUSIONS: Our multimodal repertoire analysis enabled us the system-level understanding of B cell abnormality in diseases.

Synovial Tissue Heterogeneity in Japanese Patients With Rheumatoid Arthritis Elucidated Using a Cell-Type Deconvolution Approach.

OBJECTIVE: Recent advances in single-cell RNA sequencing technology have improved our understanding of the immunological landscape of rheumatoid arthritis (RA). We aimed to stratify the synovium from East Asian patients with RA by immune cell compositions and gain insight into the inflammatory drivers of each synovial phenotype. METHODS: Synovial tissues were obtained from East Asian patients in Japan with RA (n = 41) undergoing articular surgery. The cellular composition was quantified by a deconvolution approach using a public single-cell-based reference. Inflammatory pathway activity was calculated by gene set variation analysis, and chromatin accessibility was evaluated using assay of transposase accessible chromatin-sequencing. RESULTS: We stratified RA synovium into three distinct subtypes based on the hierarchical clustering of cellular composition data. One subtype was characterized by abundant HLA-DRAhigh synovial fibroblasts, autoimmune-associated B cells, GZMK+ GZMB+ CD8+ T cells, interleukin (IL)1-ß+ monocytes, and plasmablasts. In addition, tumor necrosis factor (TNF)-α, interferons (IFNs), and IL-6 signaling were highly activated in this subtype, and the expression of various chemokines was significantly enhanced. Moreover, we found an open chromatin region overlapping with RA risk locus rs9405192 near the IRF4 gene, suggesting the genetic background influences the development of this inflammatory synovial state. The other two subtypes were characterized by increased IFNs and IL-6 signaling, and expression of molecules associated with degeneration, respectively. CONCLUSION: This study adds insights into the synovial heterogeneity in East Asian patients and shows a promising link with predominant inflammatory signals. Evaluating the site of inflammation has the potential to lead to appropriate drug selection that matches the individual pathology.

Functional evaluation of rare OASL variants by analysis of SLE patient-derived iPSCs.

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic systemic autoimmune disease characterized by genetic heterogeneity and an interferon (IFN) signature. The overall landscapes of the heritability of SLE remains unclear. OBJECTIVES: To identify and elucidate the biological functions of rare variants underlying SLE, we conducted analyses of patient-derived induced pluripotent stem cells (iPSCs) in combination with genetic analysis. METHODS: Two familial SLE patient- and two healthy donor (HD)-derived iPSCs were established. Type 1 IFN-secreting dendritic cells (DCs) were differentiated from iPSCs. Genetic analyses of SLE-iPSCs, and 117 SLE patients and 107 HDs in the ImmuNexUT database were performed independently. Genome editing of the variants on iPSCs was performed with the CRISPR/Cas9 system. RESULTS: Type 1 IFN secretion was significantly increased in DCs differentiated from SLE-iPSCs compared to HD-iPSCs. Genetic analyses revealed a rare variant in the 2'-5'-Oligoadenylate Synthetase Like (OASL) shared between SLE-iPSCs and another independent SLE patient, and significant accumulation of OASL variants among SLE patients (HD 0.93%, SLE 6.84%, OR 8.387) in the database. Genome editing of mutated OASL 202Q to wild-type 202 R or wild-type OASL 202 R to mutated 202Q resulted in reduced or enhanced Type 1 IFN secretion of DCs. Three other OASL variants (R60W, T261S and A447V) accumulated in SLE patients had also capacities to enhance Type 1 IFN secretion in response to dsRNA. CONCLUSIONS: We established a patient-derived iPSC-based strategy to investigate the linkage of genotype and phenotype in autoimmune diseases. Detailed case-based investigations using patient-derived iPSCs provide information to unveil the heritability of the pathogenesis of autoimmune diseases.

Immunomics analysis of rheumatoid arthritis identified precursor dendritic cells as a key cell subset of treatment resistance.

OBJECTIVES: Little is known about the immunology underlying variable treatment response in rheumatoid arthritis (RA). We performed large-scale transcriptome analyses of peripheral blood immune cell subsets to identify immune cells that predict treatment resistance. METHODS: We isolated 18 peripheral blood immune cell subsets of 55 patients with RA requiring addition of new treatment and 39 healthy controls, and performed RNA sequencing. Transcriptome changes in RA and treatment effects were systematically characterised. Association between immune cell gene modules and treatment resistance was evaluated. We validated predictive value of identified parameters for treatment resistance using quantitative PCR (qPCR) and mass cytometric analysis cohorts. We also characterised the identified population by synovial single cell RNA-sequencing analysis. RESULTS: Immune cells of patients with RA were characterised by enhanced interferon and IL6-JAK-STAT3 signalling that demonstrate partial normalisation after treatment. A gene expression module of plasmacytoid dendritic cells (pDC) reflecting the expansion of dendritic cell precursors (pre-DC) exhibited strongest association with treatment resistance. Type I interferon signalling was negatively correlated to pre-DC gene expression. qPCR and mass cytometric analysis in independent cohorts validated that the pre-DC associated gene expression and the proportion of pre-DC were significantly higher before treatment in treatment-resistant patients. A cluster of synovial DCs showed both features of pre-DC and pro-inflammatory conventional DC2s. CONCLUSIONS: An increase in pre-DC in peripheral blood predicted RA treatment resistance. Pre-DC could have pathophysiological relevance to RA treatment response.

Transcriptome Profiling of Immune Cell Types in Peripheral Blood Reveals Common and Specific Pathways Involved in the Pathogenesis of Myositis-Specific Antibody-Positive Inflammatory Myopathies.

OBJECTIVE: Idiopathic inflammatory myopathies (IIM) demonstrate characteristic clinical phenotypes depending on the myositis-specific antibody (MSAs) present. We aimed to identify common or MSA-specific immunological pathways in different immune cell types from peripheral blood by transcriptome analysis. METHODS: We recruited 33 patients with IIM who were separated into the following groups: 15 patients with active disease at onset and 18 with inactive disease under treatment. All patients were positive for MSAs: anti-melanoma differentiation-associated gene 5 (MDA5) antibody (Ab) in 10 patients, anti-Mi-2 Ab in 7, and anti-aminoacyl-transfer RNA synthetase (ARS) Ab in 16. The patients were compared with 33 healthy controls. Twenty-four immune cell types sorted from peripheral blood were analyzed by flow cytometry, RNA sequencing, and differentially expressed gene analysis combined with pathway analysis. RESULTS: The frequencies of memory B cell types were significantly decreased in active patients, and the frequency of plasmablasts was prominently increased in active patients with anti-MDA5 Ab in comparison with healthy controls. The expression of type I interferon (IFN)-stimulated genes of all immune cell types was increased in the active, but not inactive, patients. Endoplasmic reticulum stress-related genes in all IIM memory B cells and oxidative phosphorylation-related genes in inactive IIM double negative B cells were also increased, suggesting prominent B cell activation in IIM. Furthermore, active patients with anti-MDA5 Ab, anti-Mi-2 Ab, or anti-ARS Ab were distinguished by IFN-stimulated and oxidative phosphorylation-related gene expression in plasmablasts. CONCLUSION: Unique gene expression patterns in patients with IIM with different disease activity levels and MSA types suggest different pathophysiologies. Especially, B cells may contribute to common and MSA-specific immunological pathways in IIM.

Combined plasma metabolomic and transcriptomic analysis identify histidine as a biomarker and potential contributor in SLE pathogenesis.

OBJECTIVES: To investigate metabolite alterations in the plasma of SLE patients to identify novel biomarkers and provide insight into SLE pathogenesis. METHODS: Patients with SLE (n = 41, discovery cohort and n = 37, replication cohort), healthy controls (n = 30 and n = 29) and patients with RA (n = 19, disease control) were recruited. Metabolic profiles of the plasma samples were analysed using liquid chromatography-time-of-flight mass spectrometry and capillary electrophoresis-time-of-flight mass spectrometry. Transcriptome data was analysed using RNA-sequencing for 18 immune cell subsets. The importance of histidine (His) in plasmablast differentiation was investigated by using mouse splenic B cells. RESULTS: We demonstrate that a specific amino acid combination including His can effectively distinguish between SLE patients and healthy controls. Random forest and partial least squares-discriminant analysis identified His as an effective classifier for SLE patients. A decrease in His plasma levels correlated with damage accrual independent of prednisolone dosage and type I IFN signature. The oxidative phosphorylation signature in plasmablasts negatively correlated with His levels. We also showed that plasmablast differentiation induced by innate immune signals was dependent on His. CONCLUSIONS: Plasma His levels are a potential biomarker for SLE patients and are associated with damage accrual. Our data suggest the importance of His as a pathogenic metabolite in SLE pathogenesis.

Serum extracellular traps associate with the activation of myeloid cells in SLE patients with the low level of anti-DNA antibodies.

Neutrophil extracellular traps (NETs) are involved in systemic lupus erythematosus (SLE). We sought to cluster SLE patients based on serum NET levels. Serum NET levels were higher in SLE patients than healthy controls. Frequencies of pleuritis and myositis were increased in patients with high serum NET levels. Serum NET levels negatively correlated with anti-double stranded DNA (anti-dsDNA) antibody titers and C1q-binding immune complexes, but positively correlated with C-reactive protein (CRP) and monocyte counts. Neutrophil transcriptome analysis demonstrated no difference in NET-associated signatures, irrespective of serum NET levels, suggesting anti-dsDNA antibody-mediated clearance of NETs. In serum, NET levels were significantly correlated with myeloid cell-derived inflammatory molecules. Serum NET-based cluster analysis revealed 3 groups of patients based on serum NET and CRP levels, anti-dsDNA antibody titers, and monocyte count. Monocytes were consistently activated following NET-containing immune complex (NET-IC) stimulation. In conclusion, SLE patients with high serum NET levels had lower anti-dsDNA antibody titers and higher inflammatory responses. NET-IC-stimulated monocytes might associate with an inflammatory response characterized by elevated CRP levels. These findings can apply to precision medicine, as inflammatory processes, rather than antibody-dependent processes, can be targeted in specific subpopulations of SLE patients.

Autotaxin is a potential link between genetic risk factors and immunological disturbances of plasmacytoid dendritic cells in systematic lupus erythematosus.

BACKGROUND: The importance of autotaxin, an enzyme that catalyzes lysophospholipid production, has recently been recognized in various diseases, including cancer and autoimmune diseases. Herein, we examined the role of autotaxin in systemic lupus erythematosus (SLE), utilizing data from ImmuNexUT, a comprehensive database consisting of transcriptome data and expression quantitative trait locus (eQTL) data of immune cells from patients with immune-mediated disorders. METHODS: Serum autotaxin concentrations in patients with SLE and healthy controls (HCs) were compared. The transcriptome data of patients with SLE and age- and sex-matched HCs were obtained from ImmuNexUT. The expression of ENPP2, the gene encoding autotaxin, was examined in peripheral blood immune cells. Next, weighted gene correlation network analysis (WGCNA) was performed to identify genes with expression patterns similar to ENPP2. The ImmuNexUT eQTL database and public epigenomic databases were used to infer the relationship between autotaxin and pathogenesis of SLE. RESULTS: Autotaxin levels were elevated in the serum of patients with SLE compared to HCs. Furthermore, the expression of ENPP2 was higher in plasmacytoid dendritic cells (pDCs) than in other immune cell subsets, and its expression was elevated in pDCs of patients with SLE compared to HCs. In WGCNA, ENPP2 belonged to a module that correlated with disease activity. This module was enriched in interferon-associated genes and included genes whose expression was influenced by single-nucleotide polymorphisms associated with SLE, suggesting that it is a key module connecting genetic risk factors of SLE with disease pathogenesis. Analysis utilizing the ImmuNexUT eQTL database and public epigenomic databases suggested that the increased expression of ENPP2 in pDCs from patients with SLE may be caused by increased expression of interferon-associated genes and increased binding of STAT3 complexes to the regulatory region of ENPP2. CONCLUSIONS: Autotaxin may play a critical role in connecting genetic risk factors of SLE to disease pathogenesis in pDCs.

Control of naive and effector CD4 T cell receptor repertoires by rheumatoid-arthritis-risk HLA alleles.

OBJECTIVE: Human Leukocyte Antigen (HLA) alleles regulate susceptibility to rheumatoid arthritis (RA) and immune-mediated diseases. This study aims to elucidate the impact of HLA alleles to T cell subsets. METHODS: We performed genome-wide and HLA allele association analysis for T cell receptor (TCR) beta chain repertoire in 13 purified T cell subsets from the ImmuNexUT database, consisting of 407 donors with ten immune-mediated diseases and healthy controls. RESULTS: HLA class II alleles were associated with TRBV gene usage and the public clones of CD4 T cells, while HLA class I alleles were associated with CD8 T cells. RA-risk and immune-mediated diseases-risk HLA alleles were associated with TRBV gene usage of naive and effector CD4 T cell subsets and public clones accumulating in Th17. Clonal diversity was independent of HLA alleles and was correlated with transcriptome changes that reflect TCR signaling. CONCLUSION: This study revealed in vivo evidence that both HLA alleles and environmental factors shape naive and effector TCR repertoires in RA and immune-mediated diseases patients.

Distinct transcriptome architectures underlying lupus establishment and exacerbation.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease involving multiple immune cells. To elucidate SLE pathogenesis, it is essential to understand the dysregulated gene expression pattern linked to various clinical statuses with a high cellular resolution. Here, we conducted a large-scale transcriptome study with 6,386 RNA sequencing data covering 27 immune cell types from 136 SLE and 89 healthy donors. We profiled two distinct cell-type-specific transcriptomic signatures: disease-state and disease-activity signatures, reflecting disease establishment and exacerbation, respectively. We then identified candidate biological processes unique to each signature. This study suggested the clinical value of disease-activity signatures, which were associated with organ involvement and therapeutic responses. However, disease-activity signatures were less enriched around SLE risk variants than disease-state signatures, suggesting that current genetic studies may not well capture clinically vital biology. Together, we identified comprehensive gene signatures of SLE, which will provide essential foundations for future genomic and genetic studies.

Transcriptome analysis of immune cells from Behçet's syndrome patients: the importance of IL-17-producing cells and antigen-presenting cells in the pathogenesis of Behçet's syndrome.

BACKGROUND: Behçet's syndrome (BS) is an immune-mediated disease characterized by recurrent oral ulcers, genital ulcers, uveitis, and skin symptoms. HLA-B51, as well as other genetic polymorphisms, has been reported to be associated with BS; however, the pathogenesis of BS and its relationship to genetic risk factors still remain unclear. To address these points, we performed immunophenotyping and transcriptome analysis of immune cells from BS patients and healthy donors. METHODS: ImmuNexUT is a comprehensive database consisting of RNA sequencing data and eQTL database of immune cell subsets from patients with immune-mediated diseases and healthy donors, and flow cytometry data and transcriptome data from 23 BS patients and 28 healthy donors from the ImmuNexUT study were utilized for this study. Differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify genes associated with BS and clinical features of BS. eQTL database was used to assess the relationship between genetic risk factors of BS with those genes. RESULTS: The frequency of Th17 cells was increased in BS patients, and transcriptome analysis of Th17 cells suggested the activation of the NFκB pathway in Th17 cells of BS patients. Next, WGCNA was used to group genes into modules with similar expression patterns in each subset. Modules of antigen-presenting cells were associated with BS, and pathway analysis suggested the activation of antigen-presenting cells of BS patients. Further examination of genes in BS-associated modules indicated that the expression of YBX3, a member of a plasmacytoid dendritic cell (pDC) gene module associated with BS, is influenced by a BS risk polymorphism, rs2617170, in pDCs, suggesting that YBX3 may be a key molecule connecting genetic risk factors of BS with disease pathogenesis. Furthermore, pathway analysis of modules associated with HLA-B51 indicated that the association of IL-17-associated pathways in memory CD8+ T cells with HLA-B51; therefore, IL-17-producing CD8+ T cells, Tc17 cells, may play a critical role in BS. CONCLUSIONS: Various cells including CD4+ T cells, CD8+ T cells, and antigen-presenting cells are important in the pathogenesis of BS. Tc17 cells and YBX3 may be potential therapeutic targets in BS.

AFF3, a susceptibility factor for autoimmune diseases, is a molecular facilitator of immunoglobulin class switch recombination.

Immunoglobulin class switch recombination (CSR) plays critical roles in controlling infections and inflammatory tissue injuries. Here, we show that AFF3, a candidate gene for both rheumatoid arthritis and type 1 diabetes, is a molecular facilitator of CSR with an isotype preference. Aff3-deficient mice exhibit low serum levels of immunoglobulins, predominantly immunoglobulin G2c (IgG2c) followed by IgG1 and IgG3 but not IgM. Furthermore, Aff3-deficient mice show weak resistance to Plasmodium yoelii infection, confirming that Aff3 modulates immunity to this pathogen. Mechanistically, the AFF3 protein binds to the IgM and IgG1 switch regions via a C-terminal domain, and Aff3 deficiency reduces the binding of AID to the switch regions less efficiently. One AFF3 risk allele for rheumatoid arthritis is associated with high mRNA expression of AFF3, IGHG2, and IGHA2 in human B cells. These findings demonstrate that AFF3 directly regulates CSR by facilitating the recruitment of AID to the switch regions.